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ASSESSING THE ROLE OF ATTENTIONAL ENGAGEMENT
AND ATTENTIONAL DISENGAGEMENT
IN ANXIETY-LINKED ATTENTIONAL BIAS
Patrick Clarke
BSc. (Hons)
MA
This thesis is presented for the degree of Doctor of Philosophy
School of Psychology
The University of Western Australia
2009
ii
ABSTRACT
It has consistently been found that individuals who are more highly vulnerable to
anxious mood selectively attend to emotionally negative stimuli as compared to those
lower in anxiety vulnerability, suggesting that such anxiety-prone individuals possess an
attentional bias favouring negative information. Two of the most consistent tasks used to
reveal this bias have been the attentional probe and emotional Stroop tasks. It has been
noted, however, that these tasks have not been capable of differentiating the relative role of
attentional engagement with, and attentional disengagement from emotionally valenced
stimuli, suggesting that either of these attentional processes could account for the
attentional bias observed in individuals with high levels of anxiety vulnerability on the
attentional probe and emotional Stroop tasks. A number of resent studies have claimed
support for the operation of biased attentional disengagement in anxiety using a modified
attentional cueing paradigm, concluding that individuals more vulnerable to anxious mood
have a selective difficulty disengaging attention from emotionally negative stimuli. The
current thesis highlights the possibility, however, that the structure of the modified cueing
paradigm could allow individual differences in initial attentional engagement with
differentially valenced stimuli to be interpreted as a selective disengagement bias. The goal
of research reported in this dissertation was to develop modified variants of attentional
probe and emotional Stroop tasks which would discriminate the role of biased attentional
engagement with and biased attentional disengagement from emotionally valenced stimuli
for individuals who differ in vulnerability to anxious mood. Results of experiments
employing modified variants of the attentional probe task did not reveal anxiety-linked
differences in spatially orienting attention to engage with the locus of differentially
valenced stimuli, or, anxiety-linked differences in spatially orienting attention to disengage
iii
attention from the locus of differentially valenced stimuli. These studies therefore provided
no evidence to support either the presence of an anxiety-linked bias in attentional
engagement or attentional disengagement. The modified emotional Stroop task employed
in the current research measured participant‟s ability to engage with the emotional content
of differentially valenced stimuli having initially processed non-emotional information
(stimulus colour), and measured their relative ability to disengage attention from such
emotional content to process non-emotional stimulus information. Results using this
modified Stroop task suggested that those with high vulnerability to anxious mood were
disproportionately fast to engage with the content of negative as compared to non-negative
stimuli whereas those with low vulnerability to anxious mood did not display this pattern.
The results provided no support for presence of an anxiety-linked bias in attentional
disengagement from the content of differentially valenced stimuli. Results derived from the
modified emotional Stroop task therefore provided support for the presence of an anxiety-
linked bias in attentional engagement with the content of emotionally negative stimuli, but
no support for a bias in attentional disengagement from the content of such material. The
final study in the present series of experiments was designed to address the novel
possibility that a bias in attentional disengagement could result in ongoing semantic
activation of negatively valenced stimuli which would not necessarily be indexed by
previous tasks assessing biased attentional disengagement. The results of this final study,
however, provided no evidence to suggest the presence of anxiety-linked differences in
ongoing semantic activation of differentially valenced stimuli. The present series of studies
therefore provide support for the presence of an anxiety-linked bias in attentional
engagement with the content of emotionally negative stimuli, while providing no support
iv
for the presence of an anxiety-linked bias in attentional disengagement from negative
stimuli.
v
ACKNOWLEDGEMENTS
I am deeply grateful to my supervisor Colin MacLeod for his perpetual, infectious,
and seemingly boundless enthusiasm which has sustained my motivation over these years.
For his patience and helpful guidance in developing my capabilities as a researcher, and
honing my skills in communication, I am eternally indebted and without this support I
would have struggled to reach this point.
My sincere thanks to Mike Anderson who was kind enough to read a draft of this
document and provide valuable feedback prior to its submission.
My gratitude goes to my office mates both past and present, Shane, Stewart, Dave
and Johnson, for providing the distraction and humor when it was necessary and being the
sounding board and filter for many ideas, with varying degrees of rationality, that occurred
during the completion of this dissertation.
To all the members of the Cognition and Emotion Lab that have come and gone
over the years, Russsel, Sian, David, Nicole, Helen and particularly Ed Wilson, for the
support they provided and the comfort gained from sharing this ride, and observing that
some do come out the other end.
I am eternally grateful to both my parents, Nigel and Sue Clarke, who have
nurtured my enquiry into the workings of the world from an early age and have always
encouraged me in my pursuit of education. I thank you both for you contribution to this.
And finally, to my partner, and soon to be wife, Kim Shirras, for her gentle
tolerance of my constant enquiry into the workings of the world, for her strength,
emotional support and encouragement in times of need, and for her patience over this long
journey, I am forever grateful.
vi
TABLE OF CONTENTS
ABSTRACT ....................................................................................................................... ii
ACKNOWLEDGEMENTS .............................................................................................. v
CHAPTER 1
INTRODUCTION .............................................................................................................. 1
Overview ..................................................................................................................... 1
Individual Differences in Anxiety Vulnerability ........................................................ 1
Cognitive Models of Anxiety Vulnerability ............................................................... 5
Experimental Support of the Association Between Attentional Bias to Negative
Stimuli and Anxiety Vulnerability ............................................................................ 10
Emotional Stroop Task and Attentional Bias ........................................................... 10
Attentional Probe Task and Attentional Bias ........................................................... 16
Does Biased Attentional Engagement or Biased Attentional Disengagement
Underpin Attentional Bias in Anxiety? ..................................................................... 21
Overview of Current Research Program ................................................................... 30
Summary ................................................................................................................... 32
CHAPTER 2
EXPERIMENT 1 ............................................................................................................. 34
Method ...................................................................................................................... 37
Overview .................................................................................................................. 37
Participants .............................................................................................................. 39
Materials .................................................................................................................. 40
Procedure ................................................................................................................. 44
Results ....................................................................................................................... 46
vii
Discussion ................................................................................................................. 53
CHAPTER 3
EXPERIMENT 2 ............................................................................................................. 65
Method ...................................................................................................................... 69
Overview .................................................................................................................. 69
Participants .............................................................................................................. 70
Materials .................................................................................................................. 71
Emotional Assessment Measure ............................................................................... 71
Procedure ................................................................................................................. 74
Results ....................................................................................................................... 75
Discussion ................................................................................................................. 79
CHAPTER 4
EXPERIMENT 3 ............................................................................................................. 84
Method ...................................................................................................................... 86
Overview .................................................................................................................. 86
Participants .............................................................................................................. 88
Materials .................................................................................................................. 89
Procedure ................................................................................................................. 92
Results ....................................................................................................................... 93
Discussion ............................................................................................................... 100
CHAPTER 5
EXPERIMENT 4 ........................................................................................................... 112
Method .................................................................................................................... 117
Overview ................................................................................................................ 117
viii
Participants ............................................................................................................ 119
Materials ................................................................................................................ 120
Procedure ............................................................................................................... 124
Results ..................................................................................................................... 124
Assessment of Biased Attentional Disengagement from Semantic Content ........... 126
Assessment of Biased Attentional Engagement with Emotional Content ............... 129
Discussion ............................................................................................................... 131
CHAPTER 6
EXPERIMENT 5 ........................................................................................................... 135
Method .................................................................................................................... 138
Overview ................................................................................................................ 138
Participants ............................................................................................................ 139
Materials ................................................................................................................ 140
Procedure ............................................................................................................... 143
Results ..................................................................................................................... 144
Assessment of Biased Attentional Disengagement from Semantic Content ........... 146
Assessment of Biased Attentional Engagement with Semantic Content ................. 148
Discussion ............................................................................................................... 152
CHAPTER 7
EXPERIMENT 6 ........................................................................................................... 162
Method .................................................................................................................... 168
Overview ................................................................................................................ 168
Participants ............................................................................................................ 169
Materials ................................................................................................................ 170
ix
Procedure ............................................................................................................... 173
Results ..................................................................................................................... 174
Analysis of Lexical Decision Latency Data ........................................................... 175
Analysis of Word-Naming Latency Data ................................................................ 177
Discussion ............................................................................................................... 181
CHAPTER 8
GENERAL DISCUSSION ............................................................................................. 189
Review of Research Findings .................................................................................. 189
Evidence for the Biased Attentional Disengagement account of anxiety-linked
attentional bias ....................................................................................................... 190
Evidence for the Biased Attentional Engagement account of anxiety-linked
attentional bias ....................................................................................................... 194
Theoretical Implications and Future Theoretical Research Directions ................... 196
Applied Implications and Future Applied Research Directions ............................. 211
Limitations of Present Research and Future Research Directions to Overcome
These ....................................................................................................................... 213
Concluding Comments ............................................................................................ 223
REFERENCES ............................................................................................................... 225
APPENDIX A ................................................................................................................ 240
APPENDIX B ................................................................................................................ 244
APPENDIX C ................................................................................................................ 246
APPENDIX D ................................................................................................................ 248
1
CHAPTER 1
INTRODUCTION
Overview
In this chapter the constructs of anxiety and anxiety vulnerability are first defined.
Recent causal theories of individual differences in anxiety vulnerability next are
discussed, with specific attention devoted to models implicating cognitive processing
biases in the development and maintenance of anxiety vulnerability. Research findings
from studies which have identified a link between vulnerability to anxious mood and an
attentional bias favoring the processing of negatively valenced material are then
reviewed, along with common methodological approaches used to assess this attentional
bias. The relatively new theoretical question which forms the basis of this thesis is then
considered: whether the observed attentional bias favouring negative stimuli reflects
biased attentional engagement with or biased attentional disengagement from negatively
valenced stimuli. Recent studies attempting to address this question are reviewed, along
with discussion of the methodological flaws inherent in the majority of these
experiments. Finally, an overview of the current research program is described.
Individual Differences in Anxiety Vulnerability
At any given moment we are likely to experience different levels of anxious mood
state depending on the situation we find ourselves in. It is also readily observable,
however, that some people display a more intense anxiety response to the same stressful
situation than do others. The level of anxious mood at any one time, and the propensity to
become anxious in response to a given situation, form the basis of a key distinction made
in anxiety research between state anxiety and trait anxiety (Endler, Edwards, Vitelli, &
2
Parker, 1989). State anxiety describes an individual‟s immediate level of anxious mood,
which can fluctuate from moment to moment in response to environmental stressors
(Spielberger, 1985). Trait anxiety on the other hand refers to a more stable dispositional
characteristic reflecting the degree to which an individual will elevate anxious mood in
response to environmental stressors (Endler, 1997; Jorm, 1989). Anxiety vulnerability
therefore corresponds to individual differences in trait anxiety while anxious mood refers
to an individual‟s current state anxiety. As the construct of trait anxiety is said to be
predictive of the frequency and intensity of an individual‟s state anxiety response to
stressful events, a strong association should exist between these two dimensions. Indeed,
research has consistently demonstrated that measures of state and trait anxiety are
commonly quite highly correlated (Bleiker, Pouwer, van der Ploeg, Leer, & Ader, 2000;
Czarnocka & Slade, 2000; Giacobbi & Weinberg, 2000). In examining long and short-
term factors associated with anxiety vulnerability, research has estimated that around
44% of the variance in state anxiety symptoms over the period of a year can be accounted
for by a measure of trait anxiety (Duncan-Jones, 1987).
Individuals with high trait anxiety are distinguished from those with lower trait
anxiety by the frequency and intensity with which they experience elevations in state
anxiety. Symptoms of state anxiety are commonly grouped according to their affective,
somatic and cognitive features. Affective characteristics of state anxiety commonly
include irritability and apprehension. Somatic features of state anxiety can include
general physiological arousal (increased heart rate and respiration), muscle tension,
exaggerated startle response and motor restlessness (Barlow, 2002). At its most extreme,
as in a panic response, individuals can experience nausea, chest pain, the sensation of
choking, sweating and trembling (American Psychiatric Association, 1994). Chronic
3
elevation of state anxiety, as observed in some anxiety disorders, can be associated with
symptoms such as sleep disturbance and tiring easily (Resick & Calhoun, 2001). The
cognitive features of state anxiety may consist of difficulty concentrating and biases in
cognitive processing such as selective attention favouring more negative/threatening
information. Cognitive characteristics associated with more extreme state anxiety
responses can include derealisation (feelings of unreality) and/or depersonalisation (being
detached from oneself; Resick & Calhoun, 2001).
The adaptive value of state anxiety responses to stress could broadly be
considered to reflect enhanced successful avoidance of potential dangers (Barlow, 2002).
Increasing state anxiety in response to an imminent threat is likely to motivate a
behavioural response that will eliminate or reduce the prospect of the threat negatively
affecting an individual. Adaptive anxiety could therefore be considered to serve an
anticipatory function in identifying and reducing the occurrence or impact of potentially
adverse events. Alternatively, maladaptive anxiety occurs when the anxiety response is
disproportionately high in relation to the potential threat, or when it is based on
misappraisal of the potential danger posed by a situation or stimulus. When these
distortions of anxious reactivity and/or perceived danger significantly impair an
individuals everyday functioning, such a condition will often attract diagnosis of a
clinical anxiety disorder.
Individuals who are higher in trait anxiety by definition experience more intense
and frequent elevations in anxious mood than do their low trait anxious counterparts. It is
unsurprising therefore that individuals with greater vulnerability to anxious mood have a
substantially increased risk of developing a clinical anxiety disorder (Eysenck, 1992).
Indeed elevated trait anxiety is a common feature of many anxiety disorders including
4
Generalised Anxiety Disorder (MacLeod & Mathews, 1991; Rapee, 1991), Panic
Disorder (Borden & Turner, 1989), Social Phobia (Chambers, Power, & Durham, 2004),
Post Traumatic Stress Disorder (Shalev, Freedman, Peri, Brandes, & Sahar, 1997; Sutker,
Bugg, & Allain, 1991), and Obsessive Compulsive Disorder (Apter, et al., 2003;
Scarrabelotti, Duck, & Dickerson, 1995). Long-term follow up of anxiety disorder
patients has also demonstrated that those individuals with higher levels of trait anxiety
pre-treatment have a poorer prognosis of recovery from such conditions (Chambers, et
al., 2004). While higher trait anxiety clearly acts as a risk factor for the development of
anxiety disorders, is has also been demonstrated that successful treatment of anxiety
disorders is associated with a decline in measures of trait anxiety (Chambers, et al., 2004;
Fisher & Durham, 1999).
While considerable differences exist between the presentation of various anxiety
disorders, the strong association between vulnerability to anxious mood and anxiety
pathology suggest that those who develop anxiety disorders commonly lie at the upper
end of the trait anxiety continuum. Research on the contribution of genetics to the
development of anxiety disorders provides further support for this assertion. Studies
examining the concordance rates of anxiety disorders and symptoms among first degree
relatives have consistently demonstrated that variance in the distinctive symptoms of
anxiety pathology is not strongly related to genetic factors (Tambs, 1991). What does
appear to be inherited, however, is a general vulnerability to anxious mood rather than a
specific susceptibility to developing a particular anxiety disorder (Kendler, Kessler,
Walters, MacLean, & et al., 1995). Therefore, despite variation in their symptomatology,
it is reasonable to suggest that a common variable in the development of anxiety
disorders is the dispositional characteristic of high trait anxiety. Therefore, a sound
5
understanding of factors associated with the maintenance of high trait anxiety is likely to
improve knowledge regarding appropriate preventative and treatment strategies, both for
individuals who suffer from anxiety disorders and those at risk of developing them.
Cognitive Models of Anxiety Vulnerability
Conceptions of anxiety vulnerability have evolved considerably in the last
century. Past theories often have strongly reflected the dominant explanatory models of
the time. In the late 19th
and early 20th
century, for example, Freudian theories were
commonly embraced as ways of understanding anxiety vulnerability. Freud proposed that
anxiety is the product of conflict between impulses arising from urges to satisfy physical
drives, and the desire to conform to internally embraced social expectation. These
theories were largely based on Freud‟s interpretations of clinical observations
(Rachmann, 1998). Later researchers criticised such psychodynamic accounts for their
lack of empirical basis, their loose evidence and their lack of methodological rigor
(Wolpe & Rachman, 1960). These theories gave way to behavioural models of human
functioning, which emphasised the role of learning experiences in the acquisition of
anxiety symptoms (e.g. Estes & Skinner, 1941; Pavlov, 1934; Wolpe, 1958). The
exclusive focus on observable behaviour became a point of criticism for behavioural
accounts of anxiety by the 1970‟s, with researchers challenging the capacity of
behavioural models to completely account for the range of anxiety symptoms and their
modes of acquisition (e.g. Ohman, 1979; Rachman, 1977). A number of influential
cognitive models of anxiety have since been proposed to account for the range of
symptoms observed in normal and pathological anxiety. These models emphasise the role
of information processing systems in the development and maintenance of anxiety
6
vulnerability. Three influential cognitive models of anxiety vulnerability are reviewed
below.
One cognitive account that has guided theoretical investigation into anxiety and
other dysphoric mood states is Bower‟s associative network model (Bower, 1981; Bower,
1987; Bower, et al., 1994). Bower‟s model conceptualises emotions such as anxiety as
being represented as „nodes‟ that are embedded within a cluster of related concepts
within long-term memory. Any particular emotion node is said to be connected to
emotionally congruent semantic information within this memory system via an
associative network. When an emotion is aroused, its node becomes activated; this
activation spreads from the emotion node to associated cognitive structures making
information contained in these structures more accessible to current cognitive operations.
Experiencing a particular emotional state will therefore partially activate, or prime,
emotion-congruent information in the cognitive system. This means that such information
will be more accessible for subsequent cognitive operations due to this sub-threshold
excitation.
While Bower‟s model focuses principally on the cognitive characteristics of state
anxiety, individual differences in trait anxiety can also be represented within this model.
The nature of the information connected to the anxiety node within the memory system,
and the relative strength of the connections between the anxiety node and this anxiety-
congruent information in the cognitive system will be dependent on the frequency and
intensity with which anxiety is experienced, and so the anxiety node is activated. More
frequent state anxiety responses will result in stronger connections between the anxiety
node and other anxiety-congruent information. This in turn will render those individuals
more prone to display anxiety-congruent biases in information processing when state
7
anxiety is elevated. One specific characteristic of elevated anxiety vulnerability that this
model predicts is a bias in attention, whereby a mild increase in state anxiety will cause
anxiety-prone individuals to disproportionately favour attending to anxiety-congruent
(negative/ threatening) information.
Another highly influential cognitive model of anxiety vulnerability is that of Beck
(1976; Beck & Clark, 1988; Beck, Emery, & Greenberg, 1985). While Beck‟s model was
constructed to specifically account for anxiety pathology, this theory is also readily
applicable to general anxiety vulnerability. Beck suggests that information processing in
anxiety is affected by schemata. Schemata are hypothetical cognitive structures that
represent exemplars of early life events stored in long-term memory. When in a given
situation, the particular schema relevant to the characteristics of that event is activated.
This schema is then used to interpret, classify and assign meaning to the event. Beck
suggests that individuals vulnerable to anxious mood possess maladaptive „danger
schemata‟, which developed during the processing of past events involving high levels of
personal danger. When activated, these schemata act to bias information processing in a
threat-congruent manner and will directly influence the content of an individual‟s
perceptions, interpretations, and associations in a ways that favour the processing of
negative stimuli and so exacerbate anxiety responses to stressful events or stimuli.
Therefore, according to this account, anxiety vulnerability is associated with
idiosyncrasies in high level cognitive structures that influence lower level cognitive
processes, such as attention. Like Bower‟s model, however, Beck‟s schema model also
predicts that individuals vulnerable to anxious mood will display a selective attentional
bias favouring the processing of emotionally negative stimuli.
8
A more recent cognitive model of emotional vulnerability which specifically
focuses on information processing has been proposed by Williams, Watts, MacLeod, &
Mathews (1988; 1997). This model makes a key distinction between the processes of
integration and elaboration, which operate on mental representations. Integration is said
to occur automatically and acts to strengthen the internal structure of a representation
such that the elements of that structure become more closely associated with one another.
Activation of any feature within a highly integrated structure will therefore result in
activation of the entire representation due to the close association between the features.
Highly integrated representations will therefore be more accessible to cognitive
processes. Being more accessible in this respect refers to mental representations coming
to mind more readily. Highly integrated representations will therefore be accessed more
rapidly and will have a lower threshold for activation because stronger internal
representation will lead to partial matches in the environment activating the entire
representation. Alternatively, elaborative processing is said to strengthen the associative
connections between different representations in memory. Increased strength in the
connections between distinct structures will increase the likelihood that activation of one
structure will also prime the recall of a linked structure making this information more
retrievable. Being more retrievable in this sense therefore refers to the relative ability to
recall information from long-term memory. As such recall is believed to occur through
associative pathways, highly elaborated representations will be more retrievable.
Williams et al. (1988; 1997) propose that anxiety vulnerability reflects the
increased integrative but not elaborative processing of anxiety-related representations.
Thus, high trait anxiety will be associated with enhanced accessibility, but not
retrievability, of anxiety-related representations, given that individuals more vulnerable
9
to anxious mood have more highly integrated representations for anxiety-related
information. The model predicts that the highly integrated representations of anxiety-
related stimuli for high trait anxious individuals will result in these individuals displaying
an attentional bias favouring the processing of more negative stimuli.
Despite differences in the mechanisms they implicate, each cognitive model
reviewed above makes the common prediction that vulnerability to anxious mood will be
associated with a bias in attention selectively favouring the processing of negative as
compared to non-negative stimuli. There now exists a considerable body of literature to
support the existence of an association between anxiety vulnerability and an attentional
bias favouring negative material, and this will be reviewed in detail below. Recently,
experimental investigations have questioned whether the attentional bias associated with
heightened anxiety vulnerability is characterised by enhanced engagement of attention
with negative stimuli, or, by impaired disengagement of attention from negative stimuli.
These alternative hypotheses will be referred to as the Biased Attentional Engagement
account, and the Biased Attentional Disengagement account respectively. The question of
which account best explains the pattern of attentional bias associated with elevated trait
anxiety forms the basis the current thesis. The following review of research that has
demonstrated a relationship between attentional bias to negative stimuli and elevated trait
anxiety highlights how these presently available findings are equally amenable to either
the Biased Attentional Engagement account, or Biased Attentional Disengagement
account, of anxiety-linked attentional bias.
10
Experimental Support of the Association Between Attentional Bias to Negative Stimuli
and Anxiety Vulnerability
A number of experimental approaches have been employed in research examining
the link between attentional bias to negative stimuli and anxiety vulnerability. Two of the
most common tasks employed in such research, which have consistently revealed an
association between attentional bias and anxiety vulnerability, have been emotional
Stroop task and attentional probe task. The majority of research using such tasks has
contrasted patterns of attention for high trait anxious or clinically anxious individuals,
with low trait anxious controls, to reveal differences in the degree of attention paid to
stimuli which vary in emotional tone. In addition to these group comparison studies,
research has also examined the capacity of attentional bias measures to predict
subsequent emotional reactions to stressful life events and, has explored the causal nature
of the relationship between attentional bias and anxiety vulnerability by investigating
whether the direct manipulation of attentional bias can serve to modify emotional
reactivity to stressful events. These experimental approaches, which have employed both
the emotional Stroop and the attentional probe task, will be reviewed in turn below.
Emotional Stroop Task and Attentional Bias
The emotional Stroop task is a widely used method of examining attentional
responses to negative stimuli in anxiety. This task is based on the original Stroop colour-
naming task (Stroop, 1935; 1938) in which the colour names were printed in different ink
colours. In this original task, participants were required to name the ink colour of words
while ignoring the word meanings. Stroop revealed that participants were consistently
slower to colour-name the ink of colour words when the word itself spelled a different
colour name than when the word spelled the same colour name, or than they were to
11
colour-name the same colours printed in squares. This effect was attributed to the
interference produced from having read the incongruous colour words in text. In a simple
adaptation of this task, Mathews and MacLeod (1985) replaced the colour words with
words that were negative or non-negative in emotional tone. As with the original task,
participants were required to name the ink colour on each trial while ignoring word
content. The relative colour-naming interference for negative as compared to non-
negative words was taken as a measure of the degree to which participants differentially
processed the semantic content of these stimulus words. Slowing to colour-name words
of a particular emotional valence would therefore suggest selective attention favouring
the content of these stimuli.
Using this emotional Stroop task, Mathews and MacLeod (1985) compared the
performance of individuals with a clinical anxiety disorder (Generalised Anxiety
Disorder - GAD) to that of non-anxious controls. They found that the GAD patients,
unlike control participants, were disproportionately slow to colour-name negative as
compared to non-negative stimulus words, suggesting that these individuals preferentially
attended to the content of the more negative stimuli. Subsequent research has produced
support for these findings, consistently demonstrating that patients with GAD are
disproportionately slow to colour-name negative words as compared to controls (Martin,
Williams, & Clark, 1991; Mogg, Mathews, & Weinman, 1989).
Experimental findings using the emotional Stroop task have not been limited to
populations with generalised anxiety disorder. A considerable body of literature has
amassed to indicate that clinically anxious individuals are disproportionately slow to
colour-name emotionally negative words, especially when relevant to their specific
domains of concern, as compared to non-anxious individuals. For example, individuals
12
who suffer from Panic Disorder show significantly longer latencies to colour-name
negative words concerning separation, physical harm or social embarrassment, relative to
normal controls (Ehlers, Margraf, Davies, & Roth, 1988). A similar effect has also been
observed for those who suffer from Post-traumatic Stress Disorder (PTSD). For example,
in a study comparing groups of individuals who were involved in a motor vehicle
accident (MVA) and either had, or had not developed PTSD, Bryant and Harvey (1995)
found that those who had developed PTSD demonstrated greater colour-naming
interference for strongly negative MVA related words as compared to those who had not
developed PTSD.
Patients who suffer from specific phobias also display greater colour-naming
interference on negative words relating to their feared situation or object. When
compared to controls, individuals with Social Phobia have been found to display greater
colour-naming interference on socially negative words (e.g. criticise) and negative words
describing physical responses to embarrassment (e.g. blushing; Spector, Pecknold, &
Libman, 2003). Those who suffer specific object-related phobias also show
disproportionately slow colour-naming for words relating to these stimuli. For example,
Watts, McKenna, Sharrock and Treize (1986) found spider phobics to be specifically
slowed to colour-name spider-related words relative to non-negative words. Furthermore,
their study also revealed that, following a desensitisation procedure, spider phobics
showed a marked selective decrease in colour-naming latencies for spider-related words,
suggesting that this bias is attenuated with successful treatment of the anxiety disorder.
The anxiety-linked interference effect observed on the emotional Stroop task is
not limited to clinical populations. Research using this same task confirms the presence
of biased attention favouring negative stimuli among high trait anxious members of the
13
general population. For example, MacLeod and Rutherford, (1992) demonstrated that
high relative to low trait anxious students displayed greater slowing to colour-name
exam-related negative words. Subsequent research using the emotional Stroop has
consistently produced support for an attentional bias which favors the selective
processing of emotionally negative material in high trait anxious individuals (e.g.
Eysenck & Byrne, 1992; Mogg, Kentish, & Bradley, 1993; Richards, French, Johnson,
Naparstek, & Williams, 1992; Rutherford, MacLeod, & Campbell, 2004).
Therefore results obtained from studies using the emotional Stroop task have
consistently supported the hypothesis that selective attention to negative stimuli is a
cognitive characteristic of high trait anxiety. There also is evidence to suggest that this
bias may mediate anxiety reactivity to stressful events. In a study designed to assess
whether this attentional bias is predictive of dysphoric responses to a subsequent stressful
life event, MacLeod and Hagen (1992) first assessed patients awaiting investigation for
potential cervical pathology using a number of traditional questionnaire measures and the
emotional Stroop task. They then assessed emotional reactions to a subsequent diagnosis
of such cervical pathology in those participants who later received such a diagnosis. They
found that the best predictor of the intensity of emotional distress elicited by this negative
life event was the degree of attentional selectivity to negative stimuli previously
evidenced by the emotional Stroop task. This was taken to suggest that the attentional
processing bias observed on this task may moderate emotional reactions to stressful
events.
As outlined above, there exists considerable empirical support for an anxiety-
linked attentional bias favouring the processing of negative material, as indexed by
slowing to colour name negative stimuli on the emotional Stroop task. It is unknown,
14
however, whether this bias reflects biased attentional engagement with the content of
negative stimuli or, biased attentional disengagement from the content of such stimuli. A
bias in either of these attentional processes can provide an equally plausible account of
the findings observed using this task. The attentional processes involved in performing
the emotional Stroop task could be considered in terms of distinct phases which allow for
individual differences in attentional engagement and disengagement to emerge at
different times. When a coloured word is first presented it is assumed that there is an
initial phase where some degree of stimulus processing occurs prior to any differential
processing of the stimulus content or colour. The second phase could then be considered
the point at which an individual has the opportunity to increase processing of the
emotional content of the stimulus by engaging attention with this stimulus dimension.
According to the Biased Attentional Engagement account, it is at this point that high trait
anxious individuals will demonstrate enhanced engagement with the content of negative
stimuli and the resulting increase in engagement will contribute to longer latencies to
colour-name negatively valenced words. The Biased Attentional Disengagement account,
however, suggests that high trait anxious individuals will not necessarily demonstrate
such preferential engagement at this point. Rather, this account predicts that it is after this
second phase, when an individual then has the opportunity to disengage from processing
the stimulus content to process stimulus colour that anxiety related differences will
emerge. The Biased Attentional Disengagement account suggests that during this third
phase high trait anxious individuals will have disproportionate difficulty disengage
attention from the emotional content of negative stimuli, resulting in slower colour-
naming latencies. The biased attentional engagement account, however, suggests that
there would be no anxiety-linked differences during this phase. Figure 1.1 summarises
15
the proposed amount of attention devoted to processing the content of negative and non-
negative words (indicated by the thickness of the line) implicated by the Biased
Attentional Engagement and Biased Attentional Disengagement accounts of anxiety-
linked attentional bias for high trait anxious individuals the at different stages of the
emotional Stroop task.
As can be observed, both accounts suggest equivalent low level initial processing
of negative and non-negative stimuli during the first phase. It is during the second phase
that the Biased Attentional Engagement account predicts differences will emerge with
high trait anxious individuals selectively engaging with the content of negative material
Biased
Attentional
Engagement
Account
Negative
Word
Non-negative
Word
1. Initial stimulus
processing
2. Opportunity to
engage
3. Requirement to
disengage
Negative
Word Biased
Attentional
Disengagement
Account Non-negative
Word
Figure 1.1. Pattern of attention implicated by the Biased Attentional Engagement and Biased Attentional
Disengagement accounts for high trait anxious individuals completing the emotional Stroop task. Line
thickness represents the amount of attention devoted to processing the stimulus at a given point.
16
while the Biased Attentional Engagement account predicts no differential engagement
during this phase. During the third phase the Biased Attentional Engagement account
predicts high trait anxious individuals will show equivalent disengagement from
processing negative and non-negative stimuli while the Biased Attentional
Disengagement account predicts that these individuals will have difficulty disengaging
attention from negative words in particular. It is evident therefore that results obtained for
the emotional Stroop task are amenable to either enhanced attentional engagement with
stimulus content or impaired disengagement from such stimuli for high trait anxious
individuals.
Attentional Probe Task and Attentional Bias
In the attentional probe task, developed by MacLeod Mathews & Tata (1986),
negative and non-negative words are presented simultaneously on a computer screen for a
short duration. On critical trials, a small probe is presented in one of the two locations
vacated by the previously presented words, and participants are required to process the
probe as quickly as possible. The latency to identify probes appearing in the vicinity of
negative or non-negative words provides an indication of attentional distribution in
relation to these stimuli. MacLeod et al. (1986) used this task to examine attentional
distribution in a group of GAD patients and matched normal controls. They found that
the GAD patients were significantly faster to discriminate probes presented in the vicinity
of negative words as compared to neutral words, while control participants showed the
reverse pattern, being slower to discriminate probes in the vicinity of negative words as
compared to neutral words. Subsequent findings consistent with this result have served to
substantiate the conclusions drawn by MacLeod et al. (1986), that clinically anxious
17
individuals selectively attend to the spatial locus of anxiety-related stimuli (Mogg,
Bradley, & Williams, 1995; Mogg, Mathews, & Eysenck, 1992).
Researchers employing this probe task methodology have revealed findings
consistent with an attentional bias favouring negative stimuli in other clinically anxious
groups. In a study examining patterns of attention on this task shown by patients with
social phobia and non-anxious controls, Musa, Lepine, Clark, Mansell, & Ehlers (2003)
found results consistent with the hypothesis that patients with social phobia selectively
attend to socially-negative words while controls attend away from such words. Research
using the probe methodology have also revealed patterns of probe discrimination
latencies suggesting an attentional bias for negative stimuli for individuals with PTSD (R.
A. Bryant & Harvey, 1997), Panic Disorder (Kroeze & van den Hout, 2000), and
Obsessive-Compulsive disorder (Tata, Leibowitz, Prunty, Cameron, & Pickering, 1996).
Attentional probe task support for an anxiety-linked attentional bias favouring
negative stimuli have not been restricted to individuals with clinical anxiety disorders and
studies consistently have revealed similar results for high trait anxious members of the
normal population. MacLeod & Mathews (1988) administered the attentional probe task
to a group of first year medical students selected on the basis that their trait anxiety scores
were either high or low. They revealed that individuals high in trait anxiety displayed a
heightened tendency to attend to negative material, while low trait anxious individuals
showed attentional avoidance of this material. Such findings have been well replicated,
with other investigations confirming on probe task variants, that high relative to low trait
anxious individuals selectively attend to the locus of emotionally negative as compared to
non-negative stimuli (Broadbent & Broadbent, 1988; Fox, 1993; Mogg, Bradley, &
Hallowell, 1994).
18
Recent research using a modified version of the attentional probe task has
provided direct evidence that attentional bias may causally contribute to trait anxiety
vulnerability. MacLeod, Rutherford, Campbell, Ebsworthy, and Holker (2002) were able
to demonstrate this by showing that the direct manipulation of attentional bias, achieved
using a training variant of the attentional probe task, served to modify the intensity of
anxiety reactions to a subsequent stressful event. This training variant of the probe task
was designed to encourage an attentional bias favouring either negative or non-negative
stimuli, by establishing a contingency between the position of the negative word and the
position of the probe. To train attention to negative stimuli, the contingency was such
that, across many trials, the probe always appeared in the vicinity of the negative word.
Conversely, to train attention to non-negative stimuli, the probe always appeared in the
vicinity of a non-negative word. After extended exposure to these training contingencies,
MacLeod et al. (2002) found that participants‟ came to consistently shift attention in the
direction encouraged by the training contingency. Furthermore, participants‟ affective
response to a subsequent stressor task revealed that the induction of these different
attentional biases served to modify the intensity of the emotional reaction, such that those
participants trained to attend to negative stimuli experienced a more intense emotional
reaction to the stressor than did those trained to attend to non-negative stimuli. The
observation that the manipulation of attentional bias using the probe task methodology
resulted in the modification of emotional reactivity to a stressful event provides
compelling support for the causal role of attentional bias in mediating anxiety
vulnerability.
The association between anxiety vulnerability and the allocation of spatial
attention observed in studies using the attentional probe task clearly supports the notion
19
that high trait anxious and clinically anxious individuals selectively attend to negatively
valenced stimuli. The observation that manipulation of attentional bias can causally
modify anxiety response to a stressful event further suggests that this attentional bias may
functionally mediate anxiety vulnerability. Nevertheless, despite this consistency of
findings using the probe task, the precise attentional process which gives rise to the
attentional bias favouring negative stimuli remains unknown. It is plausible that findings
using the attentional probe task can be accommodated either by the Biased Attentional
Disengagement account or the Biased Attentional Engagement account of anxiety-linked
attentional bias.
As with the emotional Stroop task, the dot probe task could be considered to
involve distinct phases where individual differences in attentional engagement and
disengagement can potentially emerge. When negative and non-negative words are
initially displayed in the dot probe task it is assumed that there is some initial degree of
equivalent pre-attentive processing of both stimuli. Following this, an individual may
then deploy attentional resources to one of the two stimulus words and therefore increase
attentional engagement with this attended stimulus. The Biased attentional engagement
account suggests that high trait anxious individuals will preferentially engage with
negative as compared to non-negative stimuli during this phase, thus decreasing the
latencies to identify probes appearing in this location and increasing latencies to identify
probes in the opposite location. The Biased Attentional Disengagement account predicts
that high trait anxious individuals will not preferentially attend to either negative or non-
negative material during this phase. This account instead suggests that it is during the
third phase, when the presence of the dot probe requires attentional disengagement from
the attended stimuli, that differences will emerge for high trait anxious individuals. It
20
should be noted that the need to disengage will only occur on half the trials. The Biased
Attentional Engagement account predicts that on those trials where the probe appears
opposite an attended negative word, high trait anxious individuals will be
disproportionately slow to respond due to their difficulty disengaging from this material,
while they will be faster to identify probes in the locus of negative material, due to the
absence of the requirement to disengage.
The predictions of the Biased Attentional Engagement and Biased Attentional
Disengagement accounts regarding the allocation of attention on the dot probe task also
map onto the pattern of attention depicted for high trait anxious individuals in Figure 1.1.
Thus, during initial processing in the first phase neither accounts predict differences in
allocation of attention across negative and non-negative material. When the opportunity
to selectively engage occurs in the second phase however, the Biased Attentional
Engagement account predicts enhanced engagement with negative stimuli while the
Biased Attentional Disengagement account predicts no difference in the allocation of
attention. When probe stimuli require attentional disengagement in the third phase, the
Biased Attentional Engagement account predicts equivalent disengagement for negative
and non-negative stimuli while the Biased Attentional Disengagement account predicts
greater ongoing processing of negative stimuli for high trait anxious individuals. The
observation that high trait anxious individuals are faster to identify probes appearing in
the locus of negative relative to non-negative words on the dot probe task could therefore
be either due to these individuals‟ tendency to rapidly orient attention to preferentially
engage with such stimuli, or, disproportionate difficulty disengaging from such stimuli.
The results of studies reviewed above demonstrating an anxiety-linked attentional bias on
21
the dot probe task can therefore be readily explained by either the Biased Attentional
Engagement or Biased Attentional Disengagement accounts.
Thus, while the emotional Stroop and attentional probe tasks have produced
considerable evidence for an attentional bias in anxiety, neither task is capable of
revealing whether this bias is associated with enhanced engagement with, or, impaired
disengagement from negative stimuli. The following section considers this relatively new
question regarding the role of attentional engagement and disengagement in anxiety-
linked attentional bias, and critically evaluates attempts to empirically resolve this issue.
Does Biased Attentional Engagement or Biased Attentional Disengagement
Underpin Attentional Bias in Anxiety?
Posner (1980; Posner, Inhoff, Friedrich, & Cohen, 1987) proposed that visual
attention can be decomposed into a number of critical component processes. Whenever a
shift in attention occurs, the first action is to disengage from the current focus of
attention. It has been suggested that degree of difficulty in performing this operation
relates to the processing demands occurring at the time of attentional disengagement
(Kerr, 1973; LaBerge, 1973). The second and third actions involve movement of
attention, before finally engaging with a new target respectively. Posner developed a
paradigm to assess these components of visual attention. In this task, attention was
initially directed to a locus by the presentation of a cue, such as the brightening of one
area of a screen. On the majority of trials (80%) the cue would accurately predict the
location of a to-be-identified target (valid trials) while on the remaining trials the target
would appear in the location opposite the initial cue (invalid trials). Posner et al. (1987)
found that targets were detected faster on valid trials as compared to invalid trials.
22
Slowing on invalid trials was attributed to costs of having to disengage from the cued
location, and engage with the target appearing in the opposite location.
In considering the discrete components which contribute to a shift in attention as
described by Posner, it is readily apparent that biased attention to negative material could
readily be affected by selectivity operating within either the engagement or
disengagement process. It is curious therefore, that relatively little research to date has
been devoted to determining which component of attention is implicated in the
processing of negative stimuli. An appreciation for the precise contributions of
engagement and disengagement in attentional bias could be considered fundamental to
understanding the nature of this bias and hence clearly identifying the crucial target of
curative change for interventions designed to remediate dysfunctional anxiety through the
manipulation of attentional bias. Thus, there are both theoretical and applied reasons for
investigating whether attentional bias in anxiety is characterised by enhanced engagement
with or impaired disengagement from negative stimuli.
In considering the theoretical implications of Biased Attentional Engagement and
Biased Attentional Disengagement accounts of anxiety-linked attentional bias, it worth
reflecting on the cognitive models of anxiety vulnerability previously outlined. Both
Beck‟s (1976) schema model and Bower‟s (1981) associative network model predict that
a number of processing biases will be associated with anxiety, including selective
attention to negative stimuli. While these models do not explicitly differentiate between
attentional engagement and disengagement in their predictions, the generality with which
they predict anxiety-congruent processing of negative information by high trait anxious
individuals suggests that they would anticipate both anxiety-linked enhancement of
attentional engagement with, and anxiety-linked impaired disengagement from, negative
23
stimuli. Williams et al.‟s (1988) integrative processing model, however, more specifically
predicts the enhanced detection of potentially negative information in high trait anxious
individuals. This model therefore implicates biased attentional engagement with negative
stimuli as underlying the pattern of attentional selectivity displayed by high trait anxious
individuals.
Identifying the specific attentional process which underpins anxiety-linked
attentional bias also has number of potential applied implications. As reviewed earlier,
research has demonstrated that measures of selective attention to negative stimuli have
proven to be the most accurate predictors of emotional reactions to later stressful life
events (MacLeod & Hagen, 1992). By resolving whether such anxiety-linked selective
attention reflects biased attentional engagement with or biased attentional disengagement
from negative stimuli, it would become possible to improve their assessment by
developing tasks specifically sensitive to that particular dimension of attentional
selectivity, thereby enhancing prediction of anxiety reactivity in ways that lead to
improved methods of preempting distress to adverse events by providing appropriate
support based on the accurate prediction of needs.
A thorough understanding of the processes which underlie attentional bias in
anxiety could also lead to the development of improved methods for therapeutically
modifying such attentional biases in individuals with anxiety pathology. Recent success
in experimentally modifying attentional bias, and consequently influencing anxiety
responses to a stressor (MacLeod et al., 2002), suggests that developing means to directly
alter attentional bias may have direct therapeutic implications in reducing anxiety
vulnerability. It could be anticipated that a task which acts to specifically modify the
precise attentional mechanism that directly underpins the attentional bias associated with
24
anxiety vulnerability would be most effective in reducing such anxiety vulnerability.
Clearly, therefore, revealing whether anxiety-linked attentional bias is characterised by
selective attentional engagement with or disengagement from negative stimuli is likely to
maximise the effectiveness of interventions designed to modify anxiety vulnerability
through the manipulation of attentional bias.
Despite the importance of this issue, few empirical studies have been devoted to
differentiating the roles of attentional engagement with and disengagement from
differentially valenced stimuli in the pattern of attentional selectivity evidenced by
anxious individuals. Furthermore, the limited existing work has been compromised by
methodological flaws in the tasks employed which raise concerns about their ability
employ the resulting findings to resolve the matter. One such study, which has attempted
to identify whether anxiety-linked attentional bias is characterised by biased attentional
engagement with, or biased attentional disengagement from, negative information, was
conducted by Fox, Russo, Bowles, and Dutton (2001). These researchers adopted a
modified version of Posner et al.‟s (1987) cueing paradigm to assess these processes. The
structure of this modified task was such that, on each trial, a negative or non-negative
word, acting as a directional cue, was presented to the right or left of a central fixation
point for a brief duration. The display was then cleared for a brief period and a target
probe was presented to the right or left of the fixation point for a brief duration. On the
majority of trials (75%) the word cue predicted the location of the target probe while on
the remainder, the target appeared in the opposite location to the word stimuli.
Participants were required to identify whether the target probe appeared in the right or
left screen location. On trials where the target appeared opposite the negative or non-
negative stimulus, participants who were higher in anxiety were slower to identify targets
25
when the cue was negatively valenced. The authors drew the conclusion that that the
presence of negative information influences the disengage process in anxious individuals.
A subsequent study using the same cueing paradigm also revealed a similar effect, in
another sample of high trait anxious participants (Fox, Russo, & Dutton, 2002). Based on
the results of these tasks Fox et al. (2001, 2002) have suggested that past research which
has demonstrated anxiety-linked attentional bias may have wrongly attributed this bias to
differential engagement and these past findings may instead be due to biased attentional
disengagement from negative stimuli.
When considering the results of this research it is worth pausing to reflect on the
structure of the task as employed in its original form, and how this was modified for use
in the studies described above. In adapting Posner et al‟s (1987) cueing task, Fox et al.
(2001, 2002) replaced a neutral cue, designed to direct attention to a particular locus, with
an emotionally valenced cue. In doing this, however, they potentially compromised
Posner‟s experimental manipulation designed to secure initial attention to this locus, as
the emotional valence of the stimuli could differentially influence the degree of initial
attention to this locus across individuals. The key problem is that the task is insensitive to
the possibility that the securing of initial attention varied across participants as a function
of the emotional valence of a cue. It is known that anxious individuals will exhibit
selective processing of negative stimuli, even when such stimuli are presented in a
manner that precludes conscious awareness (MacLeod & Rutherford, 1992). Therefore,
employing a stimulus known to elicit differences in attentional processing in a task
format where this cue is supposed to equivalently orient initial attention could be
considered incompatible.
26
While Fox et al.‟s modification of Posner‟s cueing task would seem a logical
means of assessing individual differences in attentional disengagement from valenced
stimuli, the problem with replacing Posner‟s neutral cue with an emotionally valenced
stimulus becomes evident when considering the possibility that an attentional bias may be
characterised by individual differences in attentional engagement with negative stimuli.
As discussed by Posner et al. (1987), any shift in attention involves disengagement from
the attended stimulus and engagement with a subsequent stimulus. In Fox et al.‟s
modified version of the cueing task, speed to respond to a target appearing in the uncued
location will be affected by individual differences in initial attentional engagement with
the cue, subsequent disengagement from the cue, and engagement with the probe target.
The measure of speed to process uncued targets will therefore be influenced by individual
differences in each of these stages. It is plausible that the degree to which participants
initially engaged with the cue stimuli, or indeed the probability that they engaged at all,
may depend on differences in anxiety vulnerability. As a result, it is possible that high
trait anxious participants‟ slowing to detect probes in the opposite location to negative
stimuli, which has been construed as evidence for an anxiety-linked impairment in
attentional disengagement from negative information, instead could have reflected
increased initial attentional engagement with the negative information by these
participants. The valenced cue in the modified version of Posner‟s task is therefore
performing the two incompatible functions of securing attention and differentiating
attentional response to an emotional stimulus. Thus, a key problem with using emotional
material to secure initial attention is that it compromises the conclusions that can be
drawn about attentional disengagement from emotionally valenced material.
27
Another problem with the modified Posner task becomes evident if you consider
the possibility that individuals who differ in vulnerability to anxious mood may also
differ in response times when negative and non-negative stimuli are present. It is entirely
plausible that anxious individuals may be slower to respond when negative as compared
to non-negative stimuli are presented. The emotional Stroop task is also susceptible to the
effect of general slowing in the presence of threat. MacLeod et al., (1986) highlighted
that the different pattern of responses observed across high and low trait anxious
individuals on the emotional Stroop task could simply reflect individual differences in
slowing in the presence of negative stimuli. The attentional probe task developed by
MacLeod et al., (1986) was designed to overcome this problem by always having both
negative and non-negative stimuli on the screen at the same time, thus controlling for any
general slowing in the presence of negative stimuli. By presenting only a single stimulus
at any one time, the modified version of the Posner task has reintroduced a potential
confound that had been overcome by the dot probe task.
In considering the pattern of effects observed using the modified attentional
cueing paradigm (Fox et al. 2001, 2002), it is quite possible that, when the potential
influence of slowing in the presence of negative stimuli is taken into consideration, the
pattern of effects could be due to differences in attentional engagement rather than
attentional disengagement. If anxious individuals do selectively engage with negative
stimuli on valid trials (where the negative cue appears in the same location as the
subsequent probe), the relative speeding to attend to such stimuli could be offset by
slowing to respond in the presence of negative stimuli, thereby negating any relative
differences in relative speeding to attend to these versus non-negative stimuli. Slowing in
the presence of threat for anxious individuals could also account for longer response
28
times of these individuals on invalid trials (where the negative cue appears in the opposite
location to the subsequent probe). Anxious individuals may be slower to respond to
probes in the opposite screen position, not because of a difficulty disengaging from
negative words but from a slowing to respond when such words are present. Indeed, a
recent study by Mogg, Holmes, Gardiner and Bradley (2008) directly assessed this
possibility. They employed a similar task design to Fox et al. (2001, 2002) but included a
baseline condition where participants did not relocate attention from an initial central
fixation where a negative or non-negative stimulus was presented prior to a probe being
presented in the same location. This condition was designed to measure any differences
in slowing in the presence of emotional stimuli in the absence of any shift in attention.
They found that when the relative slowing on these control trials was accounted for, high
trait anxious individuals were observed to be relatively faster to discriminate probes
appearing in the position of negative as compared to non-negative words. This study
clearly highlights that measures of both attentional engagement and disengagement on
the modified Posner task may be compromised by general effects of slowing in the
presence of threat.
A number of studies have been conducted using the same attentional cueing
paradigm employed by Fox et al (2001, 2002) and have consistently revealed that high
trait anxious individuals are slower to respond to probes appearing in the screen position
opposite negative as compared to non-negative words (Koster, Crombez, Verschuere,
Van Damme, & Wiersema, 2006; Yiend & Mathews, 2001). This effect has also been
observed for individuals with social phobia who are disproportionately slow to respond to
probes that appear opposite initially exposed socially negative words as compared to non-
negative words (Amir, Elias, Klumpp, & Przeworski, 2003). All these studies, however,
29
are compromised in the same way, by employing emotionally valenced stimuli as the
stimuli supposed to secure initial attentional engagement and by not controlling for
individual differences in slowing in the presence of differentially valenced stimuli. The
results of all of these therefore remain amenable to either the Biased Attentional
Engagement account or the Biased Attentional Disengagement account of anxiety-linked
attentional bias.
One study has used an alternative probe task variant to draw the same conclusion
as researchers using variants of the Posner task. Koster, Crombez, Verschuere, and De
Houwer (2004) presented participants with a number of trials each containing pairs of
words that could both be non-negative or comprised of negative and non-negative
members. On trials containing negative and non-negative words probes could appear with
equal frequency in the location of either the negative or the non-negative word. The study
found that on trials containing negative and non-negative words, participants were faster
to identify probes in the vicinity of negative words and slower to identify probes in the
vicinity of non-negative words. It was also observed that on trials containing both
negative and non-negative words, responding to probes in the vicinity of neutral words
was slower overall than when compared to response times to probes on trials containing
both neutral words. The authors attributed this effect to difficulty disengaging attention
from negative words on negative/non-negative word trials where probes appear in the
vicinity of non-negative words. The problem with this claim however is that it assumes
that, on trials containing negative and non-negative words, slowing to identify probes in
the vicinity of non-negative words is directly attributable to difficulty disengaging from
negative material. A number of equally plausible possibilities could also account for this
pattern of findings. For example, it is possible that this pattern of slowing to respond to
30
probes in the vicinity of non-negative words on trials also containing negative words,
may be due to selective attentional engagement with negative stimuli, resulting in slower
responses to process probes in the locus of neutral material, not because of a greater
difficulty disengaging attention from the negative information, but because of the
necessity to disengage more often as a result of their engagement bias favouring such
information. Therefore, as with prior attentional probe tasks, the results of this study are
amenable to either the Biased Attentional Engagement or Biased Attentional
Disengagement accounts of this attentional bias.
The existing research designed to differentiate the role of attentional engagement
and disengagement in anxiety-linked attentional bias has been compromised by a number
of methodological flaws. As has been highlighted, studies claiming to reveal biased
attentional disengagement from negative stimuli in anxious participants have employed
experimental tasks which permit the observed effects to be readily attributed to enhanced
attentional engagement with negative stimuli. Thus, the effects observed in past research
using attentional probe and emotional Stroop methodologies, and in more recent studies
seeking to specifically examine attentional engagement and disengagement, remain
equally amenable to either the Biased Attentional Engagement or Biased Attentional
Disengagement accounts of attentional bias in anxiety.
Overview of Current Research Program
The principal goal of the present research program was to employ experimental
tasks that will overcome the limitations of past approaches, in order to successfully
differentiate the contribution of attentional engagement and disengagement processes to
anxiety-linked attentional bias. As has been argued, to date no strong empirical evidence
31
has been presented to clearly favour one of these hypothetical accounts of selective
attention in anxiety over the other. The aim of the present series of experiments was to
investigate the Biased Attentional Engagement and Biased Attentional Disengagement
accounts of attentional bias in anxiety, using modified versions of tasks which have
consistently been successful in revealing attentional biases in anxiety in the past.
In order to accurately measure attentional engagement and disengagement, a
number of critical criteria must be fulfilled by an experimental task. First, it is necessary
for a task to provide a means of securing initial attention to an emotionally neutral cue.
Ideally, a measure of whether attention has been secured would also be included to verify
that attention was indeed directed towards this emotionally neutral cue at the start of each
trial. Secondly, the task must require participants to then shift their attention in relation to
emotionally valenced stimuli, and must provide a means of assessing the relative ease
with which these shifts occur. To reliably index attentional engagement, a task should
therefore secure initial attention with a consistently non-emotional stimulus, before
requiring an attentional shift to engage with a negative or non-negative stimulus,
providing a measure of the speed with which this shift occurs. Baseline trials where
negative or non-negative stimuli are presented with no requirement to shift attention
should also be included to control for any possible influence of general slowing in the
presence of differentially valenced stimuli. According to the Biased Attentional
Engagement account of anxiety-linked attentional bias, high trait anxious individuals will
be disproportionately fast as compared to low trait anxious individuals to shift attention
to negative stimuli, having initially been engaged with a non-emotional stimulus. In
contrast, to reliably index attentional disengagement, a task should equivalently secure
initial attention with negative or non-negative stimuli and then require attentional
32
disengagement from this stimulus to an alternative non-emotional stimulus. Again,
baseline trials where negative or non-negative stimuli are presented in the attended
location and no shift in attention is required will control for any general slowing in the
presence of differentially valenced stimuli. According to the Biased Attentional
Disengagement account of anxiety-linked attentional bias, high trait anxious individuals
will be disproportionately slow to shift attention to the non-emotional stimulus having
been initially engaged with a negative, as compared to non-negative stimulus.
The present series of studies fulfill these criteria, by developing novel variants of
both the dot probe and emotional Stroop tasks, and so meet the requirements necessary to
differentiate and accurately measure anxiety-linked biases in attentional engagement
with, and disengagement from, emotionally negative and non-negative stimuli.
Experiments 1, 2 and 3 were devoted to examining Biased Attentional Engagement and
Biased Attentional Disengagement accounts of anxiety-linked attentional bias in spatial
attention, using attentional probe task variants. Experiments 4 and 5 then proceed to do
the same with respect to non spatial aspects of attention by employing modified variants
of the emotional Stroop task to examine these engagement and disengagement processes.
The final experiment was designed to answer remaining questions regarding the nature of
attentional disengagement, arising from consideration of preceding task structure and
results of Experiment 5.
Summary
Cognitive models of anxiety have proposed that vulnerability anxiety is
characterised by a number of processing biases, including an attentional bias that favors
anxiety-related stimuli. A considerably body of literature has amassed to support the
33
presence of such an attentional bias in clinically anxious and high trait anxious
individuals. Resent research also indicates that this attentional bias may predict, and
make a causal contribution to, anxiety vulnerability. However, the tasks commonly used
to demonstrate anxiety-linked attentional bias have not been able to differentiate whether
this bias is characterised by enhanced engagement with, or impaired disengagement from,
negative stimuli. Recent research attempting to differentiate these alternative accounts of
anxiety-linked attentional bias has claimed support for the Biased Attentional
Disengagement account over the Biased Attentional Engagement account. However,
these studies have consistently employed assessment tasks that preclude the differential
assessment of these two hypothetical classes of attentional bias, and their findings can be
equally well accommodated by either the Biased Attentional Engagement or Biased
Attentional Disengagement hypotheses. The aim of the current series of studies was
therefore to overcome the methodological flaws present in past research, and to
discriminate the validity of the Biased Attentional Engagement and Biased Attentional
Disengagement accounts of anxiety-linked attentional bias using modified variants of
tasks which have successfully revealed an attentional bias in past research.
34
CHAPTER 2
EXPERIMENT 1
Both engagement and disengagement process are constantly in operation in day-
to-day attentional functioning. Therefore, the question posed by the current research is
not whether individuals who differ in anxiety vulnerability can engage with or disengage
from the locus of negatively valenced material, it is whether the attentional bias in
anxiety selectively affects the engage or disengage component of attention when
processing differentially valenced stimuli. The principal purpose of the first experiment
was therefore to determine whether anxiety vulnerability is characterised by enhanced
attentional engagement with or impaired attentional disengagement from differentially
valenced stimuli. These attentional processes were examined using an attentional probe
task variant.
As outlined in the general introduction, previous attempts to measure attentional
engagement and disengagement processes have used cueing paradigms supposed to direct
initial attention to negative and non-negative stimuli and have then measured the relative
ease with which participants can relocate their attention to a different spatial locus (e.g.
Fox et al., 2001; Fox et al., 2002; Yiend & Mathews, 2001). As previously highlighted, a
limitation associated with these tasks is that they have been premised on the assumption
that differentially valenced material would initially secure attention in a given locus to
the same degree for both high and low trait anxious participants. If we entertain the
possibility that individuals who differ in anxiety vulnerability also vary in their tendency
to initially engage with negative material, then the ability of these task to measure and
isolate attentional engagement and attentional disengagement processes is seriously
compromised.
35
In order to eliminate the reliance on this assumption of equivalent engagement
with differentially valenced stimuli that has formed the basis of previous tasks, two key
requirements were considered crucial in developing a probe task capable of measuring
attentional engagement and disengagement. The first was that the task should require all
participants to attend equally to the locus of differentially valenced stimuli, thus
controlling for potential individual differences in the tendency to spatially attend to such
stimuli on subsequent measures of engagement and disengagement. The second
requirement was that the task should include a performance measure capable of
confirming that attention indeed was secured in the initial location as required. By
including these additional requirements this new task should allow the isolation and
measurement of attentional engagement with and disengagement from negative and non-
negative stimuli.
The probe task variant used in the first experiment was conceptually similar in
format to MacLeod et al.‟s (1986) probe task. A critical difference between this task and
previous modified versions of Posner‟s (1987) cueing task (e.g. Fox et al. 2001, 2002),
was that a neutral cue acted to reliably secure attention to an initial locus. Furthermore,
the task did not rely on the probability of to-be-presented material appearing in a cued
location to secure attention. Initial attention was instead secured by requiring participants
to attend to a particular location in order to obtain information essential to the successful
completion of the task. This was achieved by briefly replacing an initial fixation cross,
indicating the locus that participants must initially attend to, with a stimulus cue that
participants must note the structure of (i.e. noting the structure of one of two different
arrows), and use to make their final decision on the trial. The presentation of this cue was
sufficiently brief to ensure that participants must be attending to the fixation location in
36
order to correctly identify the structure of the stimulus. The cue presentation was then
immediately replaced by a differentially valenced word (either negative or non-negative)
paired with a non-word, one appearing in the location vacated by the briefly exposed cue
and the other appearing in the other half of the screen. This display remained for a brief
duration before one of these letter strings was replaced with a probe stimulus that was
either structurally identical to, or different from, the initial cue stimulus. On half the
trials, the probe required participants to relocate their attention to the opposite screen
position to process its content while in the remainder, the probe was presented in the
initially attended locus. Participants were required to decide whether this probe was a
structural match or mismatch to the initial cue stimulus. Probe response accuracy
therefore provided a measure of whether participants were attending to the locus of the
probe and also confirmed that attention was initially secured in the locus of the stimulus
cue as required.
Critical trials on this task were those where the probe appears in the opposite
screen location to the initial cue requiring participants to relocate attention either toward
differentially valenced material (providing a measure of engagement) or away from such
material (providing a measure of disengagement). Trials on which the cue position and
probe position were the same therefore acted as a baseline measure for the trials where
cue position did not predict probe position. The Biased Attentional Engagement and
Biased Attentional Disengagement accounts both make different predictions about the
likely pattern of results. The Biased Attentional Disengagement account predicts that
high trait anxious participants will evidence greater slowing, as compared to low trait
anxious participants, when they are required to relocate attention away from the locus of
negative as compared to non-negative material to identify probes. Conversely the Biased
37
Attentional Engagement account predicts that high trait anxious participants will be faster
than low trait anxious participants to relocate attention to probes appearing in the vicinity
of negative as compared to non-negative words.
In summary, the aim of the first experiment was to determine whether differences
exist in attentional engagement with, and disengagement from, the locus of negative and
non-negative stimuli, for individuals who differ in vulnerability to anxious mood.
Introducing the requirement that participants must process the structure of the initial cue,
and a means of testing whether this cue has been processed, will allow the task to control
and verify the position of the participant‟s initial attentional fixation. By varying the
position of the initial cue, the subsequent probe, and the intervening lexical stimuli
presented in each location, the task will be able to measure anxiety-linked differences in
attentional engagement with and disengagement from negative and non-negative material
without the confounding influence of an emotionally valenced attentional cue. It was
therefore the goal of this first experiment to employ this new task to determine whether
the attentional bias, favoring the locus of more negative material for high trait anxious
individuals, represents enhanced engagement with, or impaired disengagement from the
locus of such material.
Method
Overview
The principal focus of the current study was to permit the measurement of the
relative speeding or slowing to attentionally engage with and attentionally disengage
from the locus of emotionally valenced words, in high and low trait anxious individuals.
To achieve this, a computer task was developed which required participants sometimes to
38
initially focus attention in the location of a word that varied in emotional valence (a
negative or non-negative word), and then to keep attention in the same locus, or shift
attention to where a non-word had appeared, in order to identify a probe presented in that
locus. At other times the task required participants to initially focus attention in the
location of a non-word and then to keep attention in the same locus or instead to shift
attention to the locus where an emotionally valenced word appeared in order to identify a
probe presented in that locus. The former type or trials yield information about the
relative difficulty disengaging attention from the locus of differentially valenced words
by comparing response latency across trials where participants are required to keep
attention in the same locus as such words, and trials where they instead are required to
move attention away from such words. In contrast the latter type of trials can yield
information about the relative ease with which attention can engage with the locus of
differentially valenced words by comparing response latencies across trials where
participants are required to keep attention in the locus opposite such words, and trials
where they instead are required to move attention toward such words.
The Biased Attentional Engagement hypothesis predicts that when probe
presentation requires that participants relocate attention to the position of these
differentially valenced stimuli, high trait anxious individuals will demonstrate
disproportionate speeding to identify probes appearing in the location of negative stimuli.
Alternatively, the Biased Attentional Disengagement hypothesis predicts that when
differentially valenced stimuli are presented in the initially attended locus, high trait
anxious individuals will show a disproportionately slow response to the probes that then
appear in the opposite location to negative words.
39
Participants
As the present series of studies wished to assess anxiety-linked differences in the
allocation of attention, it was desirable to select participants on the basis of differences in
vulnerability to anxious mood. Many previous studies examining individual differences
in anxiety vulnerability have employed median splits on anxiety measures as a means of
differentiating high and low trait anxious groups for comparison (e.g. Karch et al., 2008;
Rutherford, MacLeod, & Campbell, 2004; Hubert & de Jong-Meyer, 1992). An obvious
problem with using such a criterion, however, is that it involves the classification of
individuals in the mid-range of trait anxiety measures into high or low anxious groups.
Such classification will be dubious, however, due to the considerable role of
measurement error in determining whether an individual is allocated to a high or a low
anxious group. A better criterion, and one employed throughout the current thesis, is to
select individuals whose trait anxiety scores fall within the upper or lower band (e.g.
thirds) of a distribution of scores obtained from individuals belonging to a larger
population screened on measures of trait anxiety. This decreases the possibility of overlap
between groups and increases the likelihood that differences on measures of interest can
be attributed to true differences in anxiety vulnerability between groups. Many studies
which have successfully demonstrated anxiety-linked differences in attention have used
pre-screened distributions of non-disordered populations to guide sample selection of
individuals who differ in emotional vulnerability (e.g. Wilson & MacLeod, 2003; Mogg,
Mathews, Bird, & Macgregor-Morris, 1990). Such sample selection could be considered
more methodologically rigorous due to its reference to a larger screened population and is
the method adopted in the present series of studies.
40
To ensure participants differed in trait anxiety as required in the current study,
selection of participants was guided by the screening of 449 students using the trait
version of the Spielberger State-Trait Anxiety Inventory (STAI-T; Spielberger, Gorsuch,
Luchene, Vagg & Jacobs, 1983) in an earlier session prior to the commencement of the
study. Those individuals whose trait anxiety scores fell in either the upper third (at or
above 43) or lower third (at or below 36) of the distribution were considered eligible to
participate. Of the 48 participants who were recruited for this study, 24 were from the
lower third of the distribution and were designated the low trait anxious group, while the
remaining 24 were from the upper third of the distribution and were designated the high
trait anxious group. Of those in the high trait anxious group, six were male and 18 were
female (mean age 18.79 years) while the low trait anxious group consisted of, 10 males
and 14 females (mean age 19.00 years). The high and low trait anxious groups did not
differ significantly in terms of age, t(46) = 0.20, ns, and chi square analysis revealed that
the two groups did not differ significantly in terms of gender ratio, ²(1,47) = 1.50, ns.
Materials
Emotional Assessment Measure
Anxiety vulnerability was assessed using the trait version of the Spielberger State
Trait Anxiety Inventory (STAI-T), and participants also completed the state version of
this questionnaire (STAI-S; Spielberger et al., 1983) to reveal their level of anxious mood
state. The STAI is considered the most widely used questionnaire assessing trait and state
anxiety in the area of anxiety research (Keedwell & Snaith, 1996; Marteau & Bekker,
1992; Reiss, 1997). It also has well established reliability (Abdel-Khalek, 1989; L. L.
Barnes, Harp, & Jung, 2002) and validity (Dupuis, Perrault, Kennedy, & Lambany, 1991;
Sutker et al., 1991). The state section of the questionnaire is comprised of 20 items
41
designed to measure an individual‟s current anxious mood state (state anxiety). Total
scores on the STAI-S scales can range from 20 through to 80 with norms showing a mean
of around 40 with a standard deviation of 10. The trait section of the questionnaire is also
comprised of 20 items and is designed to measure the frequency and intensity with which
an individual experiences symptoms of anxiety to determine their general vulnerability to
anxious mood (trait anxiety). Total scores on the STAI-T can range from 20 through to
80 with norms similarly showing a mean of around 40 with a standard deviation of 10.
Stimulus Words
The task required differentially valenced stimulus words that would be perceived
by participants as either negative or non-negative in emotional tone. It was believed that
negative words would be considered most salient when of relevance to the type of
worries and concerns experienced by the participant population. To obtain a stimulus
sample, an initial pool of 182 candidate negative and 182 candidate non-negative words
was generated. These 364 words were compiled into a questionnaire to be rated according
to valence and relevance. A group of 14 undergraduates, drawn from the same population
as the experimental population, rated all words on a 7-point scale according to how
positive or negative they thought the word was (ranging from -3 “very negative” to 3
“very positive”) and rated negative words on an 11 point scale as to how relevant the
word was to their worries (ranging from 0 “not relevant at all” to 10 “very relevant”).
Negative words were first selected according to how relevant they were to
participant worries. Candidate words were deemed to be irrelevant if they were not rated
at least 5 on the relevance scale by multiple raters. From the surviving pool of candidate
negative words, the 48 which had the most negative rating were selected for use in the
study. To ensure that the non-negative words were indeed non-negative in tone, those that
42
had a valence rating of less than 0 were omitted. All non-negative words therefore had a
valence rating of equal to, or greater than 0. Such non-negative words were selected for
inclusion in a manner that ensured equivalency with the negative stimuli in terms of letter
length and frequency of usage (according to Kucera & Francis, 1967). The design of the
current study required that each negative and non-negative word be paired with a
stimulus that was structurally similar yet without meaning. A set of 96 length matched
non-words consisting of random letter strings was therefore created to serve this function.
The final stimulus set therefore comprised 96 words (48 negative and 48 non-negative),
each paired with a length-matched non-word (see Appendix A for stimulus words and
mean judge ratings of negativity and relevance). An addition set of 96 pairs of non-words
was also constructed for the exclusive use during practice trials.
Experimental Hardware
An Acorn Archimedes 5000 computer, with two-button response box and high
resolution monitor was used to present stimuli and record participants‟ probe
discrimination responses.
Experimental Task
The basic trial format was consistent across each trial presentation. A fixation cue
was first presented for a total duration of 450ms in either of two possible screen
locations. This cue consisted of a cross presented in either the upper or lower screen
location. This was then replaced for 150ms by the stimulus cue in the same screen
location (a stationary arrow facing either right or left). Immediately after the offset of the
stimulus cue, a word (negative or non-negative) and non-word pair was presented. These
two letter strings were presented vertically aligned in one of two screen locations
separated by 3cm on the vertical axis of the display which, at a viewing distance of
43
approximately 75cm, subtends around 2 of visual angle separation. This is consistent
with spatial parameters utilised in previous attentional probe tasks (e.g. C. MacLeod et
al., 1986). On half the trials the word was presented in the location vacated by the cue
while on the remaining trials the non-word appeared in this location. This verbal stimulus
display remained on the screen for 300ms. Following this, a visual probe (a stationary
arrow facing either right or left) was presented in either screen location, replacing the
letter string that occupied that space. The visual probe remained on the screen until the
participant made a response. The participant was required to determine whether the probe
stimulus exactly matched the cue stimulus in form (i.e. faced in the same direction) or not
(faced in the opposite direction), and their latency to make this response was recorded
together with accuracy. A “match” response required a right mouse click while a
“mismatch” response required a left mouse click. The participants‟ response terminated
the trial and the next trial began 1000ms later.
The entire task consisted of 768 experimental trials. During the task each stimulus
pair was presented once before any were repeated and across the 768 trials each
word/non-word pair appeared once in each of the 8 unique conditions resulting from the
nested combination of the three two-level factors of cue locus (cue word or cue non-
word), word valence (negative or non-negative word) and probe position (probe word or
probe non-word). The order in which the stimuli were presented was randomised within
these constraints. The eight different trial conditions generated by the combination of
these experimental factors are summarized in Figure 2.1. Cue position (top or bottom
screen location), cue stimulus (left or right facing arrow) and probe type (match or
mismatch with cue stimulus) was determined randomly within the constraint that each
occurred an equal number of times across the 768 trials. Three equally spaced, self-paced
44
rest periods were included in the task which occurred after the completion of every 192
trials.
Procedure
All participants were tested individually in a sound-attenuated cubicle. Upon arrival
participants first completed state and trait versions of the STAI questionnaire prior to the
commencement of the computer task. A brief description of the trial presentation was
provided to participants and they were informed that their aim in the task was to discern
as quickly as possible, without inaccuracy, whether the probe stimulus presented at the
end of each trial was a match or mismatch to the initially presented stimulus cue. The
importance of attending to the initial fixation cue was impressed upon participants,
highlighting that it was necessary in order to note the structure of the briefly presented
stimulus cue and therefore, to correctly complete the task of identifying a match or
mismatch between this and the probe stimulus. Prior to beginning the experimental trials,
each participant completed 96 practice trials where the letter strings presented were
comprised of only non-words generated for the use in practice trials alone. On these
practice trials, the fixation cue appeared with equal frequency in the top or bottom screen
location and the probe stimuli appeared in the same and opposite location to the cue with
equal frequency. Once the practice trials were completed and any additional questions
answered participants began the experimental task.
45
asdfasef
Figure 2.1. Eight trial combinations resulting from the experimental variables of word valence (negative or
non-negative) cue locus (word or non-word) and probe position (word or non-word), including stimulus
exposure durations. Initial cue position and match/mismatch between cue and probe shown randomly.
+
+
ONION
XHDVM
XHDVM
+
IVFKLZJID
CRITICISE
CRITICISE
+
EARS
RQBW
EARS
+
RQBW
EARS
EARS
+
LFGPQ
CRUEL
LFGPQ
+
XHDVM
ONION
XHDVM
Cue non-word
Negative word
Probe non-word
Engagement trial baseline
Cue non-word
Negative word
Probe word
Engagement trial
Cue non-word
Non-Negative word
Probe non-word
Engagement trial baseline
Cue non-word
Non-Negative word
Probe word
Engagement trial
+
CRUEL
LFGPQ
CRUEL
IVFKLZJID
CRITICISE
NONWORD
IVFKLZJID
NONWORD
Cue word
Negative word
Probe word locus
Disengagement trial baseline
Cue word
Negative word
Probe non-word locus
Disengagement trial
Cue word
Non-Negative word
Probe word
Disengagement trial baseline
Cue word
Non-Negative word
Probe non-word
Disengagement trial
Fixation Cue Stimulus Cue Word Stimuli Probe
450ms 150ms 300ms Remain until response
46
Results
A summary of participant characteristics taken at the time of testing, including
measures of state anxiety are provided in Table 2.1. In accordance with expected
requirements, the high trait anxious group scored significantly higher than the low trait
anxious group on the STAI-T at the time of testing t(46) = 13.23, p < .01. These scores
ranged between a minimum of 37 and a maximum of 63 with a mean of 50.71 (SD =
6.72) in the high trait anxious group, and from 23 to 38 with a mean of 29.54 (SD = 4.03)
in the low trait anxious group. It was also revealed that high and low trait anxious groups
differed according to state anxiety scores t(46) = 6.77, p < .01. While this is not
unexpected, given the close association between state and trait anxiety, it also means that
any differences observed between these groups could also be due to differences in state
anxiety. Correlational analyses are also conducted with measures derived from the
experimental task to assess the degree of association between these and state and trait
anxiety.
Table 2.1
Characteristics of participants in Experiment 1. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F
High Trait Anxious 50.71 (6.72) 42.54 (9.91) 18.97 (3.16) 6:18
Low Trait Anxious 29.54 (4.03) 27.50 (4.49) 19.00 (4.02) 10:14
All Participants 40.12 (10.02) 35.02 (10.75) 18.90 (3.58) 16:22
Eight different trial types were generated by the combination of the three
experimental factors of word type (negative or non-negative) cue locus (cue word or cue
47
non-word) and probe locus (probe word or probe non-word). Those trials where the initial
cue appeared in the locus of a word provide information regarding participants‟ ability to
disengage attention from differing word types by revealing the extent of slowing to
respond when the subsequent probe appeared in the opposite (non-word) location,
compared to when this subsequent probe appeared in the same (word) location. These
will therefore be referred to as attentional disengagement trials. Trials where the cue
appears in the locus of the non-word will instead yield information regarding speed to
engage attention with differing word types, again by revealing speed to respond when the
subsequent probe appears in the opposite location, which now will be the locus of the
word, compared to when this subsequent probe instead appears in the same (non-word)
location. These trials are therefore referred to as attentional engagement trials.
Overall accuracy on the probe discrimination latencies was high with participants
averaging 93.80% (SD = 6.51) across all trials. To minimise the influence of outlying
data points, median discrimination latencies for correct responses were calculated for
each experimental condition for each participant. As high numbers of incorrect responses
would suggest noncompliance with task instructions, it was inappropriate to include
participants with very low accuracy rates. Therefore, participants who failed to obtain
greater than 80% accuracy were excluded. This resulted in two exclusions, one each from
the high and low trait anxious groups. For the remaining participants, no overall
difference in incorrect responses were observed for the high and low trait anxious
individuals, F(1, 44) = 0.97, ns, and similarly, no group differences in incorrect responses
were observed across different trial types in the interactions described below. The probe
discrimination latencies in each experimental condition across the high and low trait
anxious participants are provided in Table 2.2.
48
Table 2.2
Mean probe discrimination latencies in milliseconds across experimental conditions and trait
anxiety groups. Standard deviations given in parenthesis.
Cue Locus Word Valence Probe Locus High Trait Group Low Trait Group
Word
(Attentional engage
trials)
Negative Word 622.82 (135.88) 661.30 (115.14)
Non-Word 628.70 (106.19) 690.65 (137.93)
Non-negative Word 600.43 (92.66) 659.78 (103.27)
Non-Word 636.30 (123.81) 686.74 (118.79)
Non-Word
(Attentional disengage
trials)
Negative Word 633.48 (109.00) 673.70 (115.19)
Non-Word 597.17 (116.72) 660.43 (107.90)
Non-negative Word 624.56 (109.42) 695.65 (121.56)
Non-Word 605.43 (112.52) 605.65 (119.81)
These data were subjected to a 2 x 2 x 2 x 2 mixed design ANOVA consisting of
one between group factor and three within group factors. The between group factor was
trait anxiety (high or low) and the three within group factors were cue locus (cue word or
cue non-word), word valence (negative or non-negative), and probe locus (probe word or
probe non-word). Both accounts under experimental test predict a significant four-way
interaction, however, each account differs in the predictions it would make about the
pattern of component three-way interactions across trials where the cue acts to secure
initial attention in the locus of words (attentional disengagement trials) versus trials
where the cue acts to secure initial attention in the locus of non-words (attentional
engagement trials) that will give rise to this four-way effect. Specifically, the Biased
Attentional Disengagement account predicts that the simple three-way interaction will be
49
restricted to attentional disengagement trials, where the initial cue acts to secure attention
in the location of words, whereby high trait anxious participants will show
disproportionate slowing to respond to probes in the opposite (non-word) location when
the initially fixated word is negative rather than non-negative in valence. The Biased
Attentional Engagement account, however, predicts that a three-way interaction will be
restricted to attentional engagement trials only, where the initial cue acts to secure
attention in the location of non-words, whereby high trait anxious participants will show
disproportionate speeding to identify probes appearing in the opposite (word) location
when the word appearing in that locus is negative in valence.
The analysis revealed a significant main effect of cue locus, F(1, 44) = 4.88, p
<.05, whereby all participants were faster to identify probes when the cue initially
secured attention in the locus of non-words (M = 642.34, SD = 16.22) and slower to
identify probes when the cue secured attention in the locus of words (M = 648.34, SD =
16.68). A significant 2-way interaction between cue locus and probe locus was also found
F(1, 44) = 46.73, p <.01. This interaction essentially reflects the fact that trials requiring
participants to relocate attention to the opposite screen position from the initially attended
cue locus resulted in longer latencies to identify probes. This was specifically
demonstrated in that all participants were faster to identify probes appearing in the
location of the word rather, than the non-word, if the initial cue had also been in the locus
of the word (M = 636.09, SD = 16.12) than if the initial cue had been the locus of the
non-word (M = 656.85, SD = 16.35); while they were faster to identify a probe in the
locus of the non-word if the initial cue had also been in the locus of the non-word (M =
628.42, SD = 16.32) than if the initial cue had been in the locus of a word (M = 660.60,
SD = 17.55).
50
The only other interaction to emerge from the four-way ANOVA was a
significant three-way between trait anxiety, word valence and probe locus F(1, 44) =
11.47, p <.01. This three-way interaction was observed to be comprised of a simple two-
way interaction for the high trait anxious group, who showed disproportionate speeding1
to process probes on trials where the word valence was negative and probes were
presented in the non-word (M = 612.93, SD = 22.70) as compared to the word locus (M =
628.15, SD = 25.09) while they showed disproportionate slowing on trials where word
valence was non-negative and probes were presented in the non-word (M = 620.87, SD =
23.54) as compared to the word locus (M = 612.50, SD = 20.02), F(1, 22) = 10.71, p
<.01. While this pattern of results was reversed for the equivalent two-way interaction
involving low trait anxious participants, who showed disproportionate slowing on trials
where the word valence was negative and probes were presented in the non-word (M =
675.54, SD = 24.72) as compared to the word locus (M = 660.54, SD = 22.47) while they
showed disproportionate speeding on trials where word valence was non-negative and
probes were presented in the non-word (M = 655.54, SD = 23.05) as compared to the
word locus (M = 684.67, SD = 23.89), this interaction did not reach significance (F(1, 22)
= 3.16, ns). The three-way interaction between trait anxiety, word valence and probe
locus is summarised in Figure 2.2.
The expected four-way interaction between trait anxiety, cue locus, word valence
and probe locus predicted by both the Biased Attentional Disengagement and Biased
Attentional Engagement accounts was not observed to be significant F(1, 44) = 0.11, ns.
Similarly, neither of the simple three-way interactions predicted by the Biased
1 Throughout this thesis focus will be on relative rather than absolute speeding. This is because it is
possible that absolute speeding may be affected by extraneous variables other than attentional bias. For
example, a general slowing for high trait anxious participants may be the result of a factor unrelated to
attentional bias, such as arousal which would not be of focal interest in the current research.
51
Attentional Disengagement and Biased Attentional Engagement accounts between trait
anxiety, word valence and probe locus for either the attentional engage trials (cue word
trials) and attentional disengage trials (cue non-word trials) were observed to be
significant (F(1, 44) = 1.38, ns and F(1, 44) = 3.13, ns respectively).
Figure 2.2. Three-way interaction between trait anxiety group (low or high), word
valence (negative or non-negative) and probe locus (probe word or probe non-word).
Although the expected group differences did not emerge for either the attentional
engage or attentional disengage trials it remains possible that associations may exist
between engagement and/or disengagement measures and state and trait anxiety scores.
Correlational analyses were therefore conducted to determine if such relationships were
present. Two indices were therefore computed, one each for attentional engage trials and
attentional disengage trials. For the attentional engage trials it was necessary to first
compute an index of speeding to process probes in the vicinity of words for negative and
Low Trait Anxious
660
664
668
672
676
680
Negative Non-Negative
Word Valence
Re
sp
on
se
La
ten
cy
(m
s)
High Trait Anxious
610
614
618
622
626
630
Negative Non-Negative
Word Valence
Resp
on
se L
ate
ncy (
ms)
Probe Word
Probe Non-Word
52
non-negative word trials. This was achieved by subtracting latencies to identify probes in
the vicinity of words from latencies to identify probes in the vicinity of non-words for
both negative and non-negative word trials. This resulted in two measures of speeding to
process words, one each for negative and non-negative word trials where higher scores
represent shorter response latencies to process probes in the vicinity of words as
compared to non-words. A single index of enhanced engagement with the locus of
negative relative to non-negative words was then computed by subtracting the measure of
speed to engage with negative words from the measure of speed to engage with non-
negative words. Higher scores on this enhanced engagement index therefore represented
disproportionate speeding to process probes in the vicinity of negative as compared to
non-negative words. The equivalent index was also calculated for attentional disengage
trials. This involved first calculating two measures of speed to disengage from the locus
of words, one each for negative and non-negative word trials. Latencies to identify probes
in the same locus of words were therefore taken from latencies to identify probes in the
opposite locus to words (non-words locus) to yield a measure of relative slowing to
disengage from the locus of words for both negative and non-negative word trials. A
single index of impaired disengagement from the locus of negative words was then
computed by subtracting the measure of slowing to disengage from the locus of non-
negative words, from the measure of slowing to disengage from the locus of non-negative
words. Higher scores on this index of impaired disengagement from negative words
represented disproportionate slowing to identify probes in the vicinity of non-words
having processed negative as compared to non-negative stimuli. Pearson‟s correlations
between the index representing impaired disengagement from negative words was not
observed to be significantly correlated with either state anxiety scores (r(46) = .12, ns), or
53
trait anxiety scores (r(46) = .18, ns). Similarly, correlations between the index of
enhanced engagement with negative words was not significantly correlated with either
state anxiety scores (r(46) = .28, ns), or trait anxiety scores (r(46) = .23, ns).
Discussion
The accuracy data in the current study provide encouragement that participants
were performing the task in accordance to expectations in securing attention in the
initially attended locus. As task performance accuracy could only be attained by noting
the structure of the initially attended stimulus cue, the high level of participant‟s accuracy
in matching cue and probe stimuli allows confidence that the stimulus cue provided an
effective means of securing attention to the initial locus. The main effect of cue position
also highlighted that securing participants‟ attention in the locus of words, as compared to
non-words, resulted in longer response latencies to process subsequent probes appearing
in either the same or opposite screen location. This result suggest that there was some
selective processing of word as compared to non-word stimuli with participants showing
a pattern of slowing to process probes after having attended to the locus of words. The
significant 2-way interaction between cue locus and probe locus, demonstrating that
probe discrimination latencies were slower when participants were required to relocate
attention to the opposite screen location to identify probes, as compared when probes
were presented in the cued location, also suggest that the requirement to process the
stimulus cue was a reliable means of securing initial attention. These results therefore
provide confidence that the task used in the current study reliably secured participants‟
initial attention in the desired location and having done this, should provide a measure of
54
the relative ease or difficulty relocating attention in relation to differentially valenced
stimuli to the locus of a subsequently presented probe.
Despite assurances that the task was functioning according to its designed purpose
of securing attention to an initial location and requiring participants to relocate attention
from or toward the locus of negative or non-negative stimuli, the results of the first study
provide little support for either the Biased Attentional Engagement or Biased Attentional
Disengagement accounts of attentional bias in anxiety. That is, results from the four-way
ANOVA provided no evidence that high trait anxious participants were
disproportionately fast, as compared to low trait anxious participants, to relocate attention
from the cue locus toward negative stimuli or, having been initially secured in the locus
of negative stimuli, being disproportionately slow to relocate attention away from this
spatial locus to identify a probe in the opposite screen location.
The current results would clearly run counter to the Biased Attentional
Disengagement account espoused by the research of Yiend and Mathews (2001) amongst
others (e.g. Fox et al., 2001; 2002). Their findings, demonstrating that anxious
participants were disproportionately slow to identifying probes appearing in the screen
location opposite initially presented negative material, appear inconsistent with the
current study‟s finding, that no significant differences in probe discrimination latencies
emerged across high and low trait anxious participants when relocating attention from the
locus of differentially valenced stimuli. The most direct implication of the current results
for the Biased Attentional Disengagement account therefore is that, when care is taken to
ensure that participants engage attention equally with the locus of an initially exposed
word, high and low trait anxious individuals do not evidence differences in the speed
with which they can relocate attention away from this material. The failure to
55
demonstrate a selective difficulty for high trait anxious individuals to disengage attention
from the locus of negative material under the current task conditions, therefore presents
as inconsistent with the predictions of the Biased Attentional Disengagement account of
anxiety-linked attentional bias. It must, however, be recognised that it is not possible to
dismiss the existence of such a bias based on the absence of findings in favour of this
hypothesis. Thus, while the current results provide no support for the Biased Attentional
Disengagement account it would be premature to rule out the existence of an anxiety-
linked disengagement bias based on the present findings.
Given that the current task allows us to be confident that participants‟ attention is
equivalently secured in an initial locus and, there is no evidence that high and low trait
anxious participants are differentially slow to disengage attention from the spatial locus
of negative or non-negative material, then this absence of a biased attentional
disengagement effect might implicate biased attentional engagement as the likely
mechanism underpinning the anxiety-linked attentional bias favouring negative stimuli.
The results of the current study however, also failed to demonstrate a pattern of biased
attentional engagement with the locus of negative stimuli for high trait anxious
participants. It was predicted that, if the group difference in trait anxiety is characterised
by biased engagement with negative material then, an interaction would emerge on trials
where attention is initially secured in the location of non-words and participants are either
required to remain in that locus or relocate attention to negative or non-negative words
appearing in the opposite screen location. No such interaction was demonstrated
however, suggesting that, having been secured in an initial locus, high and low trait
anxious participants did not significantly differ in the speed with which they then were
able to engage attention with the spatially removed locus of negative or non-negative
56
material. While the absence of support for the Biased Attentional Engagement account
could lead us to question the validity of this hypothesis, the absence of evidence for both
this and the Biased Attentional Disengagement account would suggest the possibility that
the present task may be in fact be insensitive to individual differences in attentional
engagement and disengagement. Therefore, as with the Biased Attentional
Disengagement account, while the present findings provide no support for the Biased
Attentional Engagement account they do not allow us to rule out the possibility that such
a bias exists.
The only higher-order interaction observed in the current study which involved
differences in probe discrimination latencies across trait anxiety groups, was the three-
way interaction between trait anxiety (high or low trait anxious), word valence (negative
or non-negative) and probe locus (word or non-word). While it did not involve cue locus,
and is therefore not informative in relation to attentional engagement and disengagement,
this interaction demonstrated valence-related differences in probe discrimination latencies
between high and low trait anxious participants. When considering that the removal of
the cue locus factor from the current task results in a close resemblance to original
versions of the probe task, with the simple presentation of two stimuli followed by a
probe appearing in the spatial locus of one of these two stimuli, the presence of such a
three-way interaction would seem fairly unsurprising. A three-way interaction between
trait anxiety group, valence and probe locus demonstrating that high trait anxious
individuals more rapidly processed probes appearing in the vicinity of negative as
compared to non-negative words would therefore be very consistent with findings of
previous probe tasks. However, the direction of the three-way interaction observed in the
current study was the opposite of this and runs counter to the expectations of traditional
57
probe tasks. This three-way interaction demonstrated that high trait anxious participants
were disproportionately slow to identify probes in the vicinity of negative as compared to
non-negative words and disproportionately fast to identify probes appearing opposite
negative as compared to non-negative words, while low trait anxious participants showed
the reverse pattern. The simple two-way interaction for the high trait anxious group was
independently significant while the two-way interaction for the low trait anxious group
was not. The most direct implication of this interaction for the high trait anxious group
suggests that these individuals preferentially attended away from the locus of negative
words while being more inclined to attend to the locus of non-negative words.
The three-way interaction observed in the current experiment clearly contradicts
past findings regarding attentional bias and anxiety. Prior research employing probe tasks
has consistently demonstrated that individuals more vulnerable to anxious mood evidence
an attentional bias favouring the locus of negative material as demonstrated by shorter
latencies to identify probes appearing in the locus of negative stimuli as compared to non-
negative stimuli (e.g. Broadbent & Broadbent, 1988; MacLeod et al., 1986; Mogg et al.,
1994). The results of the current study however highlight that high trait anxious
individuals were slower to process probes presented in the vicinity of negative words.
Such a pattern of findings would beg the question as to why the current task produced a
result which so starkly contrasts those obtained in previous probe tasks.
An obvious difference between the current and previous probe tasks is that
original versions of the probe task involved the simultaneous presentation of both a
negative and non-negative word on the screen at the same time. In considering how this
change could potentially affect participant responses, it will be recalled that the purpose
of presenting both negative and non-negative stimuli in the original probe task was to
58
yield a directional measure of attentional bias in relation to differentially valenced
stimuli. One reason for wishing to include both negative and non-negative words
simultaneously was that this that would control for any interference effects potentially
resulting from general slowing in the presence of negative material. While interference
effects have been relied upon to infer selective processing of negative material for high
trait anxious individuals in tasks such as the emotional Stroop (e.g. Mathews &
MacLeod, 1985), the presence of these effects in probe tasks compromise the ability of
such tasks to attribute differences in reaction times to selective attention to a given locus,
as discrimination latencies could also be influenced by general slowing in the presence of
negative words. Traditional probe tasks have been able to control for interference effects
by always presenting negative stimuli. In the current task however, it is possible that the
necessary inclusion of only a single, differentially valenced, stimulus word on each trial
has exposed the task to the potential influence of interference effects in response to the
presence of specific stimulus types.
In considering how the presence of interference effects could account for the
apparently contradictory finding in the current study, which suggest that high trait
anxious individuals selectively attend away from, rather than toward negative stimuli, it
is necessary to distinguish potential differences in types of interference. Interference
paradigms, such as the traditional Stroop and emotional Stroop involve semantic
interference where individuals are distracted by the meaning of the stimulus causing a
slowing in task performance. An alternative type of interference can also arise when the
presence of particular salient stimuli causes an individual to become emotionally aroused
or anxious and this in turn impairs or enhances task performance (depending on the
difficulty of the task and the level of arousal experienced). In considering how
59
interference effects may have influenced the pattern of findings in the current study, it is
possible that the presence of negative words appearing in the same spatial locus as probes
resulted in greater interference for high trait anxious participants in the current study due
to their tendency to selectively process word content rather than probe information, thus
contributing to longer latencies to perform the task of matching probe and cue stimuli.
The possibility that individuals may have been differentially processing material in an
attended locus also highlights an issue salient to the current research that will be returned
to later in the discussion. This interference effect of slowing in the presence of negative
material would not however account for the fact that high trait anxious individuals also
evidenced speeding to process probes appearing in the screen location opposite negative
stimuli. It is possible that an arousal-mediated interference effect could account for such a
pattern of findings if the presence of negative stimuli increased arousal such that the
processing of negative stimuli interfered with performing the task of probe discrimination
in the same spatial as this material however, the heightened arousal resulting from the
presence of negative stimuli resulted in speeded processing of stimuli in the opposite
screen location. While such an arousal-mediated interference would appear possible,
results of past attentional probe studies would tend to refute the presence of a locus-
specific interference effect where the presence of negative material acts to slow
processing of probes in the same spatial locus as negative stimuli while speeding the
processing of probes appearing in the location opposite negative stimuli. Therefore, while
the task structure in the current study would potentially allow interference effects to
emerge, it would appear unlikely that simple interference effects or arousal-mediated
interference effects could account for the pattern of findings observed.
60
An alternative possibility which could go some way to accounting for the pattern
of findings observed in the present study is that the temporal characteristics of the task
allowed for unmeasured shifts in attention. It is possible that the 300ms presentation of
differentially valenced and non-word stimuli, following presentation of the stimulus cue
and prior to the probe being revealed, could have allowed sufficient time for participants
attention to relocate. It is possible therefore that unmeasured shifts in attention occurring
within this window could have contributed to the present unexpected findings. This
underscores the potential problem of assumptions regarding stimulus presentation times.
Specifically, for a task wishing to assess individual differences in the allocation of
attention, fixed intervals of stimulus presentation could allow such individual differences
in attentional deployment during such fixed intervals to go unnoticed, or interact with
task parameters to produce results which are not representative of the true pattern of
attention. This issue is addressed in later studies by including in tasks the requirement
that participants respond to stimuli presented at various stages rather than any
assumptions about attentional deployment within specific exposure durations.
Having earlier highlighted the possibility that individuals may differentially
processing the meaning of valenced material, it is worth pausing and reflecting on the
implication of this for conclusions that can be drawn regarding allocating attention to a
spatial location, as distinct from the issue of attending to the content of stimuli appearing
in that location. In the current study, as with prior probe tasks, we have been primarily
interested in examining the orientation of attention to the spatial locus of negative and
non-negative stimuli. The suggestion that individuals may differ in the degree to which
they process the meaning of a given stimulus highlights the possibility that attending to
the spatial locus of a particular word does not necessarily involve attending to the content
61
of that word. Both the current and previous probe tasks allow conclusions to be drawn
only about the spatial locus of attention, though such conclusions have previously always
been premised on the assumption that attending to a spatial locus implies attending to the
content of the information appearing in that locus. If we entertain the alternative
possibility, that making decisions about probes in a spatial locus may not require
attention to the content of verbal material in that locus, then this carries implications for
both the current and previous probe tasks. In relation to the current study, the task
allowed confidence only that participants were initially attending to specific spatial loci
but still permitted the possibility that participants differentially processed the content of
the stimulus presented in these spatial loci. When processing cues or probes, we can be
certain that participants were attending to their spatial location and to the probe or cue
information in order to correctly discriminate these stimulus types but cannot be certain
they were attending to the content of stimuli occupying these locations.
The main effect of cue locus observed in the current task would, however, suggest
that there may have been some processing of stimulus word content. This main effect
demonstrated that all participants were faster to discriminate probes when the cue secured
initial attention in the locus of words as compared to non-words. The presence of this
effect could counter the suggestion that participants were potentially not processing word
content. It is possible, however, that participants may have engaged in some level of
processing that was sufficient to discriminate between words and non-words but may not
have been sufficiently deep, or consistent, to reliably produce processing of word content.
Participants may therefore have processed some, more salient words during the task but
may not have been reliably processing word content. An alternative possibility is that the
main effect observed in the current study between words and non-words was not due to
62
differences in processing meaning but instead because word stimuli formed
graphemically legitimate letter strings while non-words did not. Indeed it is possible that
that participants could discriminate words form non-words on the basis of graphemic
legitimacy without having to process word meaning at all. For example, people presented
with an unfamiliar word, such as „vellum‟, and a graphemically illegitimate letter string,
such as „uxhdvm‟, are likely to perform well above chance in deciding which of these
two strings are real words despite the fact that few would be readily able to identify the
meaning of the former word (being a parchment written on animal skin). It is therefore
possible that participants may not have been processing word content in the current study
but instead responding to the difference in graphemic legitimacy between words and non-
words.
Based on the rationale outlined above, the results of the present study allow us to
conclude that, when attention is initially secured in the spatial location of differentially
valenced stimuli, high and low trait anxious individuals do not differ in the speed with
which they can relocate attention to a spatially removed location. Similarly, we can
conclude that, when attention is initially secured in the spatial locus of non-words, high
and low trait anxious participants do not evidence differences in the speed with which
they can relocate attention to the spatial loci of negative and non-negative words. Based
on the distinction identified between attending to a given locus and processing the
content of material presented in that locus however, the current task does not allow us to
draw conclusions about attentional disengagement from the locus of semantically
processed negative and non-negative words, or attentional engagement with the semantic
content of spatially removed negative and non-negative words. In the current task, the
method of ensuring equivalent processing of initially attended material in order to assess
63
biased attentional disengagement or, of requiring subsequent engagement with word
content to examine differences in attentional engagement with such material may not
have met the objective of ensuring equivalent processing of stimulus content.
This raises the possibility that the current task may be insensitive to individual
differences in disengagement due the fact that, having been secured in the same spatial
locus, high and low trait anxious individuals either did not process the semantic content
of the differentially valenced stimulus in that location, or differences in the degree of
initial engagement with the stimulus content negate differences in the speed to identify
spatially removed probes such that no overall differences in probe discrimination
latencies emerge. Similarly, with attentional engagement, it is possible that relocating
attention to the locus of negative and non-negative stimuli did not involve the processing
of these stimuli, or, that differences across high and low trait anxious individuals in
speeding to the locus of differentially valenced stimuli is negated by differences in
processing the content of these stimuli.
To provide greater assurance that individuals are equivalently processing the
content of an initially presented stimulus, or are relocating attention and processing the
meaning of a stimulus in a spatially removed locus, a refinement of the current
methodology is required. In order to measure the ease with which individuals can
spatially disengage from attending to differentially valenced semantic information, it
would be necessary to provide them with an initial task which provides assurance that
they are indeed attending to the semantic content of the word stimuli presented.
Similarly, in order to measure the speed with which individuals engage attention with
differentially valenced semantic information, it is necessary to employ a task that
measures the speed of moving to process the semantic content of the word stimuli. These
64
requirements will be met across the next two experiments, of which the first (Experiment
2) examines relative speed to disengage attention from the locus of material that
participants are processing the semantic content of, while the second study (Experiment
3) examines speed to engage attention with the semantic content of material presented in
a locus participants are not initially attending to.
In summary, while the task employed in the current study demonstrated its
capacity to secure attention in an initial locus and measure the speed of shifts in spatial
attention toward or away from the locus of differentially valenced stimuli, it has revealed
no evidence of anxiety-linked differences in biased attentional engagement or biased
attentional disengagement from the content of differentially valenced stimuli. A potential
reason for this has been identified in the limitations of using a probe methodology to
secure engagement with the semantic content of initially presented stimuli or to measure
the speed with which attention can move to engage with the semantic content of spatially
removed stimuli. The possibility that participants may differentially process the content
of stimuli in an equally attended locus highlights the need to ensure equivalent processing
of such information when measuring biased attentional engagement with and
disengagement from negative and non-negative words. Studies two and three therefore
include these necessary task requirements to measure biased attentional disengagement
from the locus of semantically processed stimuli and biased attentional engagement with
the locus of semantically processed stimuli respectively.
65
CHAPTER 3
EXPERIMENT 2
Traditionally, research into attentional bias in anxiety using probe task
methodologies has not drawn the distinction between attending to a specific locus and
processing the content of information in that locus, tending to assume equivalence
between these two factors. Such a distinction becomes important however when
attempting to isolate and measure engagement and disengagement components of
attention. In relation to the measurement of disengagement, differences in, or the
potential lack of, processing of information in an attended locus can compromise
conclusions about the relative difficulty with which individuals can subsequently
disengage their attention from such information. In principal, it is possible that
differential processing, or a lack of processing, material presented in an initially attended
spatial locus could give rise to apparent disengagement effects when none in fact exist or,
alternatively, could obscure disengagement effects that do actually exist.
If individuals were to differentially engage with the semantic content of material
in an attended spatial locus, it is possible that measures of speed to disengage from such
material would reveal the cumulative effects of slowing resulting from variations in
initial engagement with the content of the material. Any subsequent slowing resulting
from selective difficulty disengaging attention from that stimulus to a spatially removed
locus would therefore also be influenced by individual differences in greater levels of
initial engagement with the content of the stimulus. Alternatively, it is possible that an
individual may possess a selective difficulty disengaging attention from stimuli of a
particular valence, but such a bias does not manifest when performing a task where there
is no advantage to initially process such material. A selective difficulty to spatially
66
disengage attention may therefore not manifest if a task does not require participants to
process the content of information presented in an initially attended locus. Conceptually,
the same issues arise in the measurement of biased attentional engagement when
considering potential discordance between engaging with a spatial locus and engaging
with the content of the material presented in that locus. This issue will be returned to in
Experiment 3.
The task employed in Experiment 1 provided a means of ensuring that
participants were equivalently attending to an initial locus and demonstrated that when
this is controlled, no anxiety-linked differences in attentional disengagement are
apparent. This result would suggest that past findings which have demonstrated
disproportionate slowing of high anxious individuals to relocate attention away from the
locus of negative stimuli (e.g. Fox et al., 2001; 2002; Yiend & Mathews, 2001), may not
be due to impaired disengagement from such stimuli. While the results of the first study
demonstrated that controlling the initially attended locus eliminates biased attentional
disengagement effects, the possibility remains however, that differences in attentional
disengagement could emerge when a task involves equivalent semantic processing of
negative and non-negative information before requiring participants to relocate attention
to a spatially removed locus. The key aim of the present study was therefore to examine
whether anxiety-linked differences in biased attentional disengagement from the locus of
negative and non-negative stimuli will emerge when equivalent processing of the
semantic content of such stimuli is ensured.
While the task used in the first study was able to provide certainty only that
participants were initially attending to a predetermined spatial locus, the aim of the
current study required that the task ensure participants equivalently engage with the
67
semantic content of the stimuli in the predetermined initial spatial locus. Ideally, the task
would require that individuals engage with the word‟s meaning and having done so,
provide a measure to verify that this has occurred. A number of methods have been used
in the past to ensure individuals process the semantic content of stimulus words including
word-naming, lexical classification (classifying a target letter string as a word or non-
word) or grammatical judgment (classifying a word according to its part of speech). It has
been demonstrated however that word-naming does not necessarily require an individual
to process the meaning of named words and this can occur through the execution of
simple grapheme to phoneme conversions (Joubert & Lecours, 2000). Word-naming
would not therefore be considered an appropriate means of ensuring participants attempt
to access the meaning of a stimulus. While the process of grammatically judging a word
necessarily involves first identifying its semantic meaning, the process of classifying the
word according to its part of speech (e.g. verb, noun, adjective) may involve post-lexical
processing beyond simply accessing meaning. Alternatively, a lexical decision task can
be performed more easily. However, past theories have suggested that identifying the
lexical status of a word may not necessarily require that an individual access its meaning
(Meyer & Schvaneveldt, 1971). It has subsequently been argued however that a lexical
decision task can only be performed by accessing the representation of a word, which in
turn includes its associated semantic meaning (James, 1975; Schvaneveldt, Meyer, &
Becker, 1976). The current task therefore employed a lexical decision component to
ensure participants accessed the semantic meaning of word stimuli.
A lexical decision task will only ensure that participants attempt to access the
semantic meaning of words when the difference between these word stimuli and non-
word foils is limited to the meaningfulness of the word stimuli. That is, participants may
68
not attempt to access the semantic representation to decide if a particular stimulus is a
word if they are able to make such a decision based on another difference between the
stimuli, such as graphemic legitimacy. It is necessary therefore for non-word stimuli to
also be graphemically legitimate, thus eliminating this as criteria on which to base lexical
decisions. The current study therefore included a lexical decision component to ensure
equivalent semantic processing of target stimuli across participants. Including the
requirement that participants initially determine the lexical status of word stimuli ensures
that they must attend to the word or letter string, access the semantic representation
attached to it, and respond accordingly. Performance of the task thus ensures that a string
has been processed for meaning, while accuracy provides reassurance that an individual
has successfully attempted this.
A modified version of the task used in the first study was therefore constructed
with the added inclusion of an initial lexical decision component. The current task
therefore directed attention to the locus of one of two letter strings by presenting a cue (a
small cross) in one of two locations. The cue was then replaced by a valenced word
(negative and non-negative word) paired with a non-word, one appearing in the location
previously occupied by the cue and the other appearing in the other screen location.
Participants were required to determine the lexical status of the string appearing in the
same locus as the initial cue. Immediately following this response participants were then
required to determine the identity of a simple probe stimulus, which appeared with equal
frequency in either the same or opposite location to the lexical decision string. Critical
trials on the current task were those where the lexical decision target was a negative or
non-negative word and probes were presented in the opposite screen position to the initial
fixation. These trials therefore required participants to process the semantic content of a
69
negative or non-negative word before then being required to spatially relocate attention
away from this stimulus in order to identify the probe. Trials on which the lexical
decision target was a negative or non-negative word and participants remained in the
initially attended locus therefore acted as a baseline for these trials. If attentional bias in
anxiety is characterised by impaired disengagement from the locus of semantically
processed negative stimuli, then it follows that high trait anxious participants should be
disproportionately slow to relocate attention away from the locus of negative, as
compared to non-negative stimuli, to identify probes appearing in the opposite screen
location.
Method
Overview
To meet the additional requirements of the second experiment, a modified version
of the probe task used in the first study was employed. This modified task again directed
attention to an initial locus with a briefly presented cue. The function of this cue,
however, was slightly different from the first study, as it instead signaled the location of
the subsequently presented letter string that participants were required to determine the
lexical status of. As with the first study, a differentially valenced word (negative or non-
negative) paired with a non-word was always presented simultaneously, one appearing in
the location of the cue and one in the opposite screen location. Participants were required
to make a lexical decision about the letter string appearing in the location of the cue,
classifying it as either a word or non-word, and were then required to identify a probe
that subsequently appeared either in the same locus, or in the alternative locus. Critical
trials were those on which participants were first required to determine the lexical status
70
of negative or non-negative words. On half of these trials participants were then required
to relocate attention to the opposite screen position (move locus trials), providing a
measure of difficulty disengaging attention from the locus of such stimuli, while the trials
where they processed words and remained in the same screen locus (stay locus trials)
acted as a baseline for these trials. Trials where participants initially determined the
lexical status of non-words were a necessary feature of the current task in order to
maintain the expectation that a word or non-word could be presented with equal
probability on each trial. The trials of focal interest were therefore those where
participants initially processed the content of words before either remaining in the same
locus or relocating attention away from the locus of the initially processed word. The
Biased Attentional Disengagement hypothesis predicts that when individuals have been
required to determine the lexical status of differentially valenced words in the initially
attended locus, high trait anxious individuals will be disproportionately slow to then
spatially shift attention to identify probes appearing in the opposite location, when this
initially processed word was negative as compared to non-negative.
Participants
Participant selection was again guided by the screening of undergraduate students
on the trait version of the Spielberger State-Trait Anxiety Inventory (STAI-T;
Spielberger, et al., 1983) in an earlier session prior to the commencement of the study.
From a pool of 509 individuals, potential participants were those whose STAI-T score
fell within the upper third (at or above 45) or lower third (at or below 37) of the
distribution. Of those who were recruited for the study, 24 were from the lower third of
the distribution (low trait anxious group) and 24 were from the upper third of the
distribution (high trait anxious group). The low trait anxious group was comprised of 9
71
male and 16 female participants with a mean age of 18.75 years (SD = 1.39) while the
high trait anxious group consisted of 4 male and 20 female participants with a mean age
of 20.96 years (SD = 6.59). The high and low trait anxious groups did not differ
significantly in terms of age, t(47) = 1.67, ns, or gender ratio gender ratio, ²(1,47) =
1.77, ns.
Materials
Emotional Assessment Measure
The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger, et al., 1983)
was again employed as the emotional assessment measure in the current study.
Stimulus Words
The same 48 negative and 48 non-negative words used in the first study were
employed in the Experiment 2. As previously highlighted in Chapter 2, the possibility
that participants could differentiate stimulus words and non-words based on graphemic
legitimacy alone was identified as an issue of potential concern in Experiment 1. The
inclusion of lexical decisions in the current task also means that it is critical for all non-
words to be graphemically legitimate to ensure that participants attempt semantic access
for all stimuli, rather than being able to determine lexical status based on graphemically
legitimacy alone. All non-words used in the study were therefore constructed to be
graphemically legitimate, thus requiring participants to process the stimuli for potential
meaning. A new set of length-matched, graphemically legitimate non-words was
therefore created and paired with negative and non-negative words (see Appendix B). As
the current study involved lexical decisions, it was also necessary to use both word and
non-word stimuli in practice trials, as compared to non-word stimuli alone, as in
72
Experiment 1. A set of 96 non-negative words, paired with length matched non-words,
was therefore created for use in the practice trials alone.
Experimental Hardware
Delivery of the experimental task was managed by an Acorn Archimedes 5000
computer, with stimuli presented on a high resolution monitor.
Experimental Task
Each trial began with the words “next trial” appearing in the centre of the screen
for 500ms to signal the beginning of the trial. A small cue consisting of a cross was then
presented for 200ms in either the upper or lower screen location. The purpose of this was
to indicate to participants the location of the letter string they were required to determine
the lexical status of. Following the cue presentation, two vertically aligned letter strings
were presented, one in the location vacated by the cue and one in the opposite screen
location. The spatial parameters of the stimulus display were identical to the first study
with letter strings presented vertically aligned in one of two screen locations separated by
3cm. Participants were required to determine the lexical status of the letter string
appearing in the locus of the initially presented cue by pressing a key labeled “non-word”
if the string was a non-word, and pressing a key labeled “word” if the string was a word,
using their left hand. Immediately following this response, a probe was presented either
in the same locus as the lexical decision string or the opposite location. Probes were
presented superimposed on the letter string, thus leaving both stimuli present on the
screen until participants responded. The probe again consisted of an arrow facing either
left or right and participants were asked to indicate the direction of the arrow by pressing
the left mouse key for a left facing arrow, and pressing a right mouse key for a right
73
facing arrow, using their right hand. Latencies to correctly identify the probe were taken
as the dependent measure.
Inter-trial interval Cue Lexical Decision Probe Discrimination
500ms 200ms Remain Until Response Remain Until Response
Figure 3.1. Four possible trial types resulting from the task factors of word valence (negative or
non-negative) and probe position (word or non-word), including exposure durations. Initial cue
position and probe type are shown randomly.
The entire task consisted of 768 trials with each of the 96 word/non-word
stimulus pairs being presented once before being repeated again. Across the 768 trials,
each stimulus pair was presented once in each of the four trial types where the initial
lexical decision was performed on a negative or non-negative word, resulting from the
combination of the two, two-level factors of word valence (negative or non-negative) and
probe position (stay locus or move locus). Stimulus presentation order was randomised
+
CRUEL
ERLUC
NONWORD
CRUEL
ERLUC
NONWORD
NEXT TRIAL
Negative Stimulus
Stay locus
Disengage from
negative baseline
+
AGULEE
LEAGUE
AGULEE
LEAGUE
TAFLA
FATAL
TAFLA
FATAL
CAMPUS
PUCSAM
CAMPUS
PUCSAM
+
+
NEXT TRIAL
NEXT TRIAL
NEXT TRIAL
Negative Stimulus
Move locus
Disengage from
negative
Non-Negative Stimulus
Stay locus
Disengage from
non-negative baseline
Non-Negative Stimulus
Move locus
Disengage from
non-negative
74
within these constraints. The four conditions generated by the combination of the two
task variables are provided in Figure 3.1. As the probe position factor determines whether
attention is required to shift from the initially attended locus or not, trials where the probe
appears in the same position as the initial word will be referred to as „stay locus trials‟
while trials where probes appear opposite the initial word will be referred to as „move
locus trials‟. Cue position (upper or lower screen location) and probe type (left or right
arrow) were determined randomly on each trial with the restriction that each was
presented an equal number of times across the 768 trials. Participants were given the
opportunity to have two brief, self-paced rest periods after the completion of every 256
trials.
Procedure
Participants were first administered the Spielberger State-Trait Anxiety Inventory
(STAI; Spielberger et al., 1983) questionnaire upon arrival before completing the
computer task individually in a sound attenuated cubicle. A brief description of the task
presentation structure was provided and participants were informed that they were
required to make two responses, the first being the decision regarding the lexical status of
a letter string, and the second to determine the orientation of the probe stimulus by
pressing the corresponding mouse key. Participants were instructed to attend to the locus
of the initial cue as this signaled the location of the to-be-decided letter string.
Participants were directed to be as fast as possible in their responses without
compromising accuracy. Before commencing the experimental trials participants
completed 96 practice trials consisting of the 96 non-negative words with their non-word
partners.
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Results
A summary of participant characteristics taken at the time of testing, including
measures of state anxiety are provided in Table 3.1. STAI-T scores taken at the time of
experimental testing confirmed that the high trait anxious participants (M = 48.12, SD =
7.14) continued to score significantly higher than the low trait anxious group (M = 29.95
(SD = 5.17) as required, t(47) = 10.09, p < .01. The high and low trait anxious groups
also differed according to state anxiety scores, t(47) = 4.41, p < .01. As any differences
across trait anxiety groups may also be attributed to this difference in state anxiety,
correlational analyses are conducted to determine the relative association of experimental
measures with state and trait anxiety.
Table 3.1
Characteristics of participants in Experiment 2. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (Years) Gender Ratio M:F
High Trait Anxious 48.12 (7.14) 39.78 (8.42) 18.75 (1.39) 4:20
Low Trait Anxious 29.95 (5.17) 29.95 (6.77) 21.08 (6.70) 8:16
Total 38.80 (11.80) 34.60 (9.00) 19.88 (4.89) 12:36
The dependent measure of interest for examining biased attentional
disengagement from the locus of semantically processed negative and non-negative
material was derived from trials where the initial lexical decision target was a word. This
is because it was these trials that provide information about participants‟ relative ability
to disengage from the locus of semantically processed information, by revealing the
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extent of slowing across trials where the probe appears in the opposite location to the
initially processed word (move locus trials) location as compared to trials where the
probe appears in the same location as the initially processed word (stay locus trials).
There were four such trial types given by the combination of the two two-level factors of
word valence (negative or non-negative) and probe locus (move locus or stay locus).
Overall accuracy was high for both the lexical decision and probe discrimination
responses with participants averaging 93.28% (SD = 8.21) and 92.05% (SD = 7.25) for
these two measures respectively. Median discrimination latencies were again used as a
means of minimising the influence of outlying data points. As incorrect responses in the
lexical decision component of the task would suggest insufficient processing of word
content, while incorrect probe discrimination responses would suggest insufficient
engagement with the probe locus, it was inappropriate to include participants with very
low accuracy rates. Therefore, participants who failed to obtain greater than 80%
accuracy on either lexical decision, or probe discrimination components of the task, were
excluded from the final analysis. This resulted in five exclusions, three from the high trait
anxious group and two from the low trait anxious group. As the current task was designed
to ensure that participants were equivalently engaging with the semantic content of the
presented material, it was necessary to verify that the trait anxious groups did not differ in
their rates of accuracy in correctly identifying the lexical status of negative and non
negative words. In accordance with this, it was demonstrated that high and low trait
anxious groups did not differ in terms of accuracy rates for identifying negative, F(1, 42)
= 0.57, ns, or non-negative words, F(1, 42) = 0.78, ns, and the interaction between
valence of lexical decision targets (negative and non-negative words) and trait anxiety
group (high and low trait anxious) for accuracy rates, did not approach significance, F(1,
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42) = 0.01, ns. To determine if participants differed in their speed to identify initial
lexical decision targets, response latencies to determine the lexical status of negative and
non-negative words were analysed. A trend suggesting that all participants were faster to
identify negative as compared to non-negative words was evident, F(1, 42) = 3.76, p =
0.06, however, this was not modified by trait anxiety group F(1, 42) = 1.78, ns.
The probe discrimination latencies for the critical trials measuring biased
attentional disengagement from the locus of semantically processed words for high and
low trait anxious participants are provided in Table 3.2. These data were subjected to a 2
x 2 x 2 mixed design ANOVA, consisting of one between group factor, and two within
group factors. The between group factor was trait anxiety (high or low) and the two
within group factors were word valence (negative or non-negative) and probe locus
(move locus or stay locus). The Biased Attentional Disengagement account would predict
a significant three-way interaction. Specifically, this account predicts that on trials where
the lexical target acts to ensure initial attentional processing of words, high trait anxious
participants will show disproportionate slowing to shift attention to identify the probe in
the opposite location, when the initially processed word is negative, rather than non-
negative in valence.
The three-way ANOVA revealed a significant main effect of probe locus F(1, 42)
= 510.49, p <.01. This main effects reflects the fact that trials requiring participants to
relocate attention to the opposite screen location result in longer latencies to identify
probes. This was specifically demonstrated in longer latencies to identify probes on move
locus trials (M = 662.18, SD = 11.33) and relatively shorter latencies to identify probes
on stay locus trials (M = 516.56, SD = 8.66). The only other significant effect to emerge
was a two-way interaction between probe locus and trait anxiety group F(1, 42) = 5.25, p
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<.05. This interaction demonstrated that, while both high and low trait anxious
individuals were slower to identify probes on move locus trials, as compared to stay locus
trials, the difference in latencies across these two trial types was greater for the high trait
anxious participants (move locus M = 681.31, SD = 16.39; stay locus M = 520.95, SD =
12.53; difference = 160.72ms) as compared to the low trait anxious participants (move
locus M = 643.04, SD = 15.66; stay locus M = 512.17, SD = 11.97; difference =
130.87ms). The three-way interaction between trait anxiety, word valence and probe
locus predicted by the Biased Attentional Disengage account did not approach
significance F(1, 42) = 0.00, ns.
Table 3.2
Mean probe discrimination latencies in milliseconds across critical experimental
conditions and trait anxiety groups. Standard deviations given in parenthesis.
Word Valence Probe Locus High Trait Group Low Trait Group
Negative Stay locus 519.76 (57.76) 510.87 (56.07)
Move locus 680.47 (90.17) 642.17 (68.74)
Non-negative Stay locus 522.14 (54.42) 513.48 (63.02)
Move locus 682.14 (75.51) 643.91 (70.69)
In order to examine the relationship between measures of attentional
disengagement from negative and non-negative words and measures of state and trait
anxiety, it was necessary to compute an index of impaired attentional disengagement. A
measure of slowing to disengage from negative words was first generated by subtracting
participant‟s response latencies on move locus trials from response latencies on stay locus
79
trials, for trials containing negative words. The equivalent measure was also calculated
for impaired disengagement from non-negative stimuli by subtracting latencies on move
locus trials from latencies on stay locus trials for trials containing non-negative words.
An overall index representing impaired disengagement from negative words was then
computed by subtracting the measure of slowing to disengage from non-negative words,
from the measure of slowing to disengage from negative words. Higher scores on this
index therefore represent greater difficulty disengaging from negative as compared to
non-negative words. This index of impaired disengagement from negative words was not
observed to be significantly correlated with either STAI-T scores, r(43) = 0.05, ns, or and
STAI-S scores, r(43) = 0.01, ns. This result contradicts the predictions of the Biased
Attentional Disengagement account of anxiety-linked attentional bias which suggest that
increased difficulty disengaging from negative stimuli should be associated with higher
levels of anxiety vulnerability.
Discussion
The high overall accuracy rates on both the lexical decision and probe
discrimination components of the task provide reassurance that participants were
processing the semantic content of initially attended words and non-words, and were also
attending to the spatial locus of the subsequent probe. The fact that no differences were
observed across trait anxiety groups on the lexical decision component of the task, either
in terms of accuracy, or lexical decision response latencies to negative and non-negative
stimuli, also provides confidence that trait anxiety groups did not differ in assessing the
lexical status of these initially attended stimuli. The main effect of probe locus
demonstrated that relocating attention to the opposite screen location from the locus of
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initial attention, in order to identify a probe, resulted in longer response latencies than
keeping attention in the same screen locus to identify a probe, consistent with results of
Experiment 1. The task therefore appeared to function in accordance with its designed
purpose of not only securing attention to an initial spatial locus but also ensuring that the
semantic content of the material in that locus was processed before either requiring
participants to relocate attention to a spatially removed locus, or remain in the same
locus.
Despite assurances that the task was able to ensure equivalent semantic
processing of the differentially valenced words presented initially, the results clearly
failed to support the hypothesis that attentional bias in anxiety is characterised by greater
difficulty disengaging attention from the locus of semantically processed negative
stimuli. This was demonstrated by the absence of a significant three-way interaction
between trait anxiety group, word valence and probe locus factors. Similarly, no
significant correlations were observed between indices of impaired attentional
disengagement and measures of state and trait anxiety suggesting little association
between such measures and current anxious mood or more general susceptibility to
anxious mood. The most direct implication of these results is that, even when equivalent
initial semantic processing of negative and non-negative stimuli is ensured, no anxiety-
linked differences emerge in subsequent speed to disengage attention from the spatial
locus of these stimuli.
Having highlighted the possibility that not controlling the initial locus of spatial
attention could potentially compromise measures of attentional disengagement,
Experiment 1 sought to examine whether a bias in attentional disengagement would
emerge when the task included a means of spatially securing initial attention. The results
81
of the first experiment demonstrated that, having initially secured attention in the spatial
locus of differentially valenced stimuli, high and low trait anxious individuals did not
then differ in the speed with which they were able to relocate attention to a spatially
removed location. This second study was designed to address the additional possibility
highlighted in the conclusion of Experiment 1, that despite the absence of a
disengagement effect, when equivalent engagement with a locus is ensured, it is possible
that biased attentional disengagement from negative material may only emerge when
both high and low trait anxious individuals are required to equivalently process the
semantic content of stimuli presented in an attended locus. The results of the second
study therefore expand the finding of the first study to highlight that when this additional
requirement is met, whereby participants were compelled to process the semantic content
of the material in the initially attended locus, no anxiety-linked differences in capacity to
then relocate attention to a spatially removed locus was evident. Such a lack of support
does not preclude the possibility that an attentional disengagement bias could manifest
under alternative task conditions. The present results, however, do not provide support
for the existence of anxiety-linked attentional disengagement bias when relocating
attention from the locus of semantically processed negative and non-negative words.
Together with the findings of Experiment 1, the results of the current study have
therefore failed to support the hypothesis that Biased Attentional Disengagement
underpins attentional bias favouring the locus of negative stimuli observed in high trait
anxious individuals.
The logical alternative to the Biased Attentional Disengagement hypothesis that
could also account for previous findings demonstrating that high trait anxious individuals
selectively attend to the locus of negative stimuli, is the Biased Attentional Engagement
82
account. The results of Experiment 1 failed to demonstrate an anxiety-linked difference
in attentional engagement, however, the potential reason that the task in the first study did
not demonstrate an anxiety-linked attentional disengagement effect, which was addressed
in the current study, also applies to the Biased Attentional Engagement account.
Specifically, the observation that ensuring equivalent engagement with a particular locus
does not necessarily equate with equivalent engagement with the content of the stimulus
in that locus. In relation to the measurement of attentional engagement, it is possible that
having secured individuals in an initially attended locus, the requirement to then
discriminate a probe appearing in the locus of a spatially removed negative of non-
negative word either allows for the potential influence of differential processing of the
content of these stimuli, or an absence of processing these stimuli at all. The measure of
biased attentional engagement derived from the task in the first study therefore allowed
conclusions to be drawn about relative speeding to attend to a given locus, but not about
potential differences to process the content of information in that locus. In order to
achieve this it would be necessary to develop a measure of speeding to process the
content of words appearing in a spatially removed locus. Such a task would allow the
assessment of the speed with which individuals engage with the semantic content of
differentially valenced material, and not simply the speed to allocate attention to the
spatial locus of such information. Assessing anxiety-linked differences in relative
speeding to engage with the semantic content of negative and non-negative stimuli was
therefore the principal aim of Experiment 3.
In summary, the current study was designed to examine whether attentional bias
in anxiety is characterised by Biased Attentional Disengagement from the locus of
semantically processed negative and non-negative words. While the task ensured
83
equivalent semantic processing of initially attended information for both high and low
trait anxious individuals, the results provided no support for the hypothesis that anxiety-
linked differences exist in Biased Attentional Disengagement from differentially
valenced stimuli. The results of Experiments 1 and 2 therefore provide no support for the
Biased Attentional Disengagement hypothesis. Examining whether anxiety-linked
differences exist in biased attentional engagement with the content of differentially
valenced stimuli presented in a spatially removed locus is therefore the focus of
Experiment 3.
84
CHAPTER 4
EXPERIMENT 3
The principal aim of Experiment 3 was to measure anxiety-linked differences in
the speed with which spatial attention can move to the locus of negative and non-negative
words when individuals are required to semantically process this information. The
rationale for the current study is similar to that underpinning Experiment 2, but with the
present focus placed on attentional engagement rather than attentional disengagement.
The argument previously highlighted in Chapter 2 regarding the measurement of
attentional disengagement applies equally to the measurement of attentional engagement.
That is, by not including a task which required participants to process the semantic
content of negative and non-negative stimuli, Experiment 1 was limited to drawing
conclusions regarding selective attention to spatial loci rather than to different types of
semantic information. Therefore, Experiment 1 was unable to establish whether attention
to a spatial locus involved processing the content of the stimulus appearing in that locus.
The current study seeks to address the possibility that high trait anxious individuals
selectively process the content of negative material appearing in an unattended location.
The Biased Attentional Engagement account of anxiety-linked attentional bias predicts
that the presence of negative material in an unattended locus will result in a level of
semantic activation that will facilitate the processing of the content of this information for
high trait anxious individuals. If this account is correct then we would expect that such
activation would result in high trait anxious individuals being disproportionately fast to
process the content of negative, as compared to non-negative, stimuli when required to
spatially relocate attention to process these stimuli.
85
The aim of the current study was to examine whether attentional bias in anxiety is
characterised by disproportionate speeding to selectively orient spatial attention to the
locus where the semantic content of negative material is processed. In order to measure
this it was necessary for the experimental task to first secure attention in a given location
where no semantic information is present, before requiring participants to process the
semantic content of a subsequently presented negative or non-negative word appearing
either in the same initially attended locus, or in a spatially removed location. The relative
speed with which participants are able to process the semantic content of differentially
valenced stimuli appearing in the initially attended location, versus the opposite location,
will provide a measure of the speed with which participants can relocate spatial attention
to the new position and engagement with the semantic content of the negative or non-
negative stimulus presented in that location.
As in the second experiment, the task in the current study used lexical decisions to
ensure that participants were processing the semantic content of negative and non-
negative words, and a probe task to ensure attention was located in the desired position.
The order in which the probe and lexical decision tasks were performed was reversed
from the order employed in Experiment 2. In the present study, participants were first
required to discriminate the identity of a probe presented in one of two locations on the
screen, before then being required to determine the lexical status of one of two
subsequently presented letter strings, one of which appeared in the same screen location
as the initial probe and the other in the opposite screen location. The task therefore started
with an initial cue which signaled the position where the probe would appear, followed
by the probe which remained on the screen until participants responded. Two letter
strings were then presented on the screen at the same time that a tone was sounded which
86
signaled to participants which of these two strings they were required to determine the
lexical status of. On experimental trials, letter strings consisted of a negative or non-
negative word paired with a graphemically legitimate non-word and participants were
required to determine the lexical status of the word, which on half the trials was presented
in the opposite position to the probe, requiring participants to relocate spatial attention in
order to engage with the semantic information, and on the remaining trials was presented
in the same position as the probe, requiring no such spatial shift in attention. Trials that
involved a spatial shift in attention were those where the lexical decision target was a
negative or non-negative word appearing in the opposite screen position to the initial
probe. These trials therefore required participants to process the probe before relocating
spatial attention to process the semantic content of this negative or non-negative word.
Trials that did not involve a spatial shift in attention were those on which the lexical
decision target was a negative or non-negative word appearing in the same locus as the
initially presented probe. If attentional bias in anxiety is characterised by biased
attentional engagement then high trait anxious participants will be disproportionately fast
to determine the lexical status of negative as compared to non-negative stimuli. Such an
effect would be represented by shorter latencies for high trait anxious individuals to
identify negative as compared to non-negative lexical decision targets on trials where
participants are required to shift attention to the opposite screen position.
Method
Overview
The aim of the current experiment was to assess anxiety-linked differences in
biased attentional engagement with spatially distal, differentially valenced words. In
87
order to measure this it was necessary to secure participants‟ attention in an initial locus
before then requiring them to engage with the semantic content of stimuli appearing in
either the same, or opposite, screen location. It is important to note that the current task
requires participants to make a lexical decision on a negative or non-negative word either
in the initially attended locus, requiring no spatial shift in attention, or in the opposite
screen position, requiring a spatial shift in attention. Although effects relating to word
valence in either location may yield information about the ease with which participants
can access the content of the stimuli, given that the processing of these stimuli will be
equivalent, the key measure of concern in the current task is whether the requirement that
participants spatially relocate attention results in anxiety-linked differences in speed to
process the content of stimuli, as compared to when participants are not required to
relocate attention from the initially attended locus. Speed to stay versus speed to move
attention to the locus of differentially valenced words that participants semantically
process, therefore form the dependent measure in the current task. Participants were
required to initially identify a probe which acted to secure attention in either the locus
where a word or non-word then appeared before they either kept spatial attention in the
same locus or relocated attention to the opposite screen location to process the semantic
content of the material appearing in this locus.
The relevant trials which allowed the current task to measure differences in speed
to move spatial attention to process the semantic content of differentially valenced
stimuli, were those on which participants were required to determine the lexical status of
a negative or non-negative word. On half these trials, initial probe presentation acted to
secure attention in the opposite screen location to where the word was subsequently
presented, requiring participants to relocate spatial attention to a negative or non-negative
88
word in the other screen location thus providing a measure of speeding to engage with the
content of these spatially removed stimuli. As it is these trials that require a spatial shift
in attention, they are referred to as „move locus trials‟. On the remaining trials, the probe
acted to secure participant‟s initial attention in the same locus as the subsequently
presented negative or non-negative words before requiring that they determine the lexical
status of these stimuli in the same location, therefore providing a baseline for the move
locus trials. As these trials do not require a spatial shift in attention, they are referred to as
„stay locus trials‟. The Biased Attentional Engagement account predicts that high trait
anxious individuals will be disproportionately fast to identify the lexical status of
negative as compared to non-negative words on the move locus trials, when a shift in
spatial attention is required, relative to stay locus trials, where no spatial shift in attention
is required. Trials where participants made lexical decisions on non-words were a
necessary task feature in order to maintain the expectation that the lexical target could
equally be a word or non-word, but these trials were not informative in terms of biased
attentional engagement with word content.
Participants
To compare measures of attentional engagement across individuals who differ in
anxiety vulnerability, recruitment of potential participants was guided by the screening of
undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory
(STAI-T; Spielberger, et al., 1983) which took place in a session prior to the
commencement of the study. Of the 426 participants screened, potential participants were
those whose STAI-T score fell in the upper third (at or above 46) or lower third (at or
below 39) of the distribution. Of those recruited for the study, 24 were from the upper
third of the distribution (high trait anxious group) and 24 were from the lower third of the
89
distribution (low trait anxious group). The low trait anxious group comprised four male
and 20 female participants with an average age of 18.29 years (SD =1.45) while the high
trait anxious group comprised five male and 18 female participants with an average age
of 19.25 (SD = 2.86). The high and low trait anxious groups did not differ significantly in
terms of age, t(46) = 1.46, ns, or gender ratio, ²(1,46) = 1.21, ns.
Materials
Emotional Assessment Measure
The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)
was again employed as the emotional assessment measure.
Stimulus Words
The same 48 negative and non-negative words, along with their non-word
partners that were used in Experiment 2 were again employed in the current study. The
key purpose of the move locus trials in the current task was to require participants to shift
attention to the locus of the word in the opposite screen location to identify its lexical
status. The possibility that participants could determine the lexical status of words
appearing in the opposite screen location without attending to them would obviously
undermine the purpose of the current task. If all trials contained word/non-word pairs,
participants could accurately infer the lexical status of the word in the unattended locus
simply by determining the lexical status of a word in the initially attended locus. To
eliminate this possibility, an equal number of foil trials containing either non-word/non-
word pairs or word/word pairs were included to ensure that participants always needed to
attend to the appropriate lexical target to process its content. Therefore, an additional set
of 48 non-word/non-word stimulus pairs and 48 word/word stimulus pairs (comprising
only non-negative words) was therefore constructed for this purpose (see Appendix C).
90
An appropriate stimulus set was also constructed for use in the practice trials comprising
48 word/non-word pairs, 24 word/word pairs and 24 non-word/non-word pairs. All words
used in the practice trials were non-negative in emotional tone.
Experimental Hardware
An Acorn Archimedes 5000 computer, with high resolution monitor, was used to
deliver the experimental task.
Experimental Task
The task used in the current study was similar in structure to the previous
modified probe task used in the Experiment 2, however, the lexical decision was now the
second decision in each trial, and latency to determine the lexical status of these words
was the dependent measure. Each trial began with the words “next trial” appearing in the
centre of the screen for 500ms. A small cue consisting of a cross was then presented in
either the upper or lower screen location for 200ms. This cue informed participants where
the probe was to appear and they were instructed to attend to this locus. The probe
stimulus was then presented, which again consisted of a right or left facing arrow, and
participants were required to indicate the direction of the arrow by pressing the left
mouse key for a left facing arrow and a right mouse key for a right facing arrow using
their right hand. Immediately following registration of this response, two vertically
aligned letter strings were presented, one in the location just vacated by the probe and one
in the opposite screen location. At the onset of this stimulus display a tone
simultaneously sounded to signal which of the two letter strings participants were
required to determine the lexical status of. A high pitched tone indicated that participants
were to make a lexical decision on the top letter string and a low pitched tone indicated
that they were to make a lexical decision on the bottom letter string. Participants were
91
required to respond by pressing a key labeled “non-word” if the string was a non-word
and pressing a key labeled “word” if the string was a word using their left hand.
Latencies to correctly identify the lexical status of the letter string were taken as the
dependent measure. Participants‟ lexical decision response cleared the screen and the
next trial began 500ms later.
The task consisted of 768 experimental trials in total, with each letter string pair
(word/non-word pair, non-word/non-word pair and word/word pair) being presented once
before any were repeated. The presentation of the 96 word/non-word, 48 word/word and
48 non-word/non-word letter string pairs was randomised within each presentation
sequence of 192 trials, with each pair appearing four times throughout the task. Initial cue
position (upper or lower screen location) and probe type (left or right facing arrow) were
determined randomly on each trial within the constraint that each was presented an equal
number of times across the 768 trials. On the trials that provided the dependent measure
of interest (trials where the lexical decision target was a negative or non-negative word)
there were four possible trial types given by the combination the two experimental factors
of word valence (negative or non-negative) and word position (stay locus or move locus).
Across the 768 trials, each experimental letter string pair (96 negative/non-word and 96
non-negative/non-word pairs) was presented in half of these four possible trial conditions.
This stimulus presentation was therefore counter-balanced across participants such that
after two participants had been tested, each stimulus had appeared once in each of these
task conditions. The four conditions providing the dependent measure of interest are
provided in Figure 4.1. During the task, participants had two brief, self-paced rest periods
after the completion of every 256 trials.
92
Inter-trial interval Cue Probe Discrimination Lexical Decision
500ms 200ms Remain until response Remain until response
Figure 4.1. Four trial combinations resulting from the task factors of word valence (negative or
non-negative) and word position (stay locus or move locus) including temporal parameters.
Probe type and position shown randomly. High and low tones indicated in brackets.
Procedure
Upon arrival participants were first administered the state and trait forms of the
Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) questionnaire,
before completing the computer task in a sound attenuated cubicle. The task structure was
then described and participants were informed that they would be required to make two
responses on each trial, the first being to determine the orientation of the probe, and the
second being to determine the lexical decision of the signaled letter string. Participants
were instructed to attend to the location of the initial cue as this signaled the location
NON-NEG (High Tone)
NONWORD
NEGATIVE (High Tone)
NONWORD
NON-NEG (High Tone)
NONWORD
NEXT TRIAL
NEXT TRIAL
NEXT TRIAL
Negative Stimulus
Stay locus
Engage with negative
baseline
Non-negative Stimulus
Stay locus
Engage with non-negative
baseline
NEGATIVE (High Tone)
NONWORD
NONWORD
NEXT TRIAL
Negative Stimulus
Move locus
Engage with negative
Non-negative stimulus
Move locus
Engage with non-negative
+
+
+
+
93
where the probe would appear. The importance of noting the pitch of the signal tone was
also impressed upon participants as this directed their attention to the appropriate letter
string upon which to perform the lexical decision. Participants were directed to be as fast
in their responses as possible without compromising accuracy. The 96 practice trials were
first completed before participants began the experimental task.
Results
A summary of participant characteristics, including measures of state and trait
anxiety taken at the time of testing, is provided in Table 4.1. STAI-T scores taken at the
time of testing confirmed that the high trait anxious group (M = 45.71, SD = 6.82)
continued to score significantly higher than the low trait anxious group (M = 33.50, SD =
4.16) as required, t(46) = 7.48, p < .01. The high and low trait anxious groups were also
observed to differ in terms of STAI-S scores, t(46) = 4.01, p < .01. While this is not
unexpected, it would also potentially allow for group differences to be attributed to
differences in state anxiety rather than trait anxiety. Therefore, as with the previous
attentional probe tasks, correlational analyses w performed to determine whether
observed effects are associated to a greater degree with measures of either state or trait
anxiety.
Information regarding speed to move spatial attention towards the locus of
differentially valenced stimuli was derived from trials where the second trial decision
involved the lexical decision of a word. This is because it was these trials that required
participants to process the content of negative or non-negative words appearing in either
same locus as the initial probe, or the opposite screen location to the initial probe. Biased
attentional engagement with spatially removed negative and non-negative words would
94
therefore be revealed by relative speeding to identify the lexical status of differentially
valenced words in the opposite screen location as compared to the speed to identify these
words in the same screen locus. If a general tendency to shift spatial attention to process
the semantic meaning of one specific stimulus valence exists, this would be revealed by a
significant two-way interaction between word valence and word position. The Biased
Attentional Engagement account would predict that such an interaction would be further
modified by trait anxiety, whereby, across stay locus and move locus trials, low trait
anxious individuals would not show a significant difference in relative speeding to
identify negative versus non negative words, while for the high trait anxious individuals
the time taken to identify words on move locus as compared to stay locus trials will be
less for negative as compared to non-negative stimuli.
Table 4.1
Characteristics of participants in Experiment 3. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F
High Trait Anxious 45.71 (6.82) 38.29 (7.95) 19.25 (2.86) 5:18
Low Trait Anxious 33.50 (4.16) 30.33 (5.61) 18.29 (1.46) 4:20
All Participants 39.74 (8.31) 34.39 (8.15) 18.80 (2.29) 9:38
Accuracy for the probe discrimination and lexical decision responses was again
high overall with participants averaging 98.54% (SD = 2.18) and 89.6% (SD = 10.72)
accuracy for these two measures respectively. As with the previous studies, a high rate of
incorrect probe discrimination responses would suggest insufficient engagement with the
probe locus and similarly, a high rate of incorrect lexical decision responses would
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suggest an individual was not semantically processing these letter strings. In keeping with
the exclusion criteria applied in the previous experiments, it was deemed inappropriate to
include participants who failed to obtain greater than 80% accuracy on either of these
tasks. This resulted in three exclusions, two from the low trait anxious group, and one
from the high trait anxious group. No significant differences for high and low trait
anxious groups were observed in the pattern of incorrect responses for lexical decisions,
F(1, 44) = 0.03, ns, or probe decisions, F(1, 44) = 0.43. Similarly, no anxiety group
differences in incorrect responses were observed across different trial types included in
analyses below. As with the previous studies, median lexical decision latencies were used
to minimise the influence of outlying data. The latencies for the critical trials where the
lexical decision target was a word, across the high and low trait anxious participants are
provided in Table 4.2.
Table 4.2
Mean lexical decision latencies in milliseconds across critical experimental trials and
trait anxiety groups. Standard deviations given in parenthesis.
Word Valence Word Position High Trait Group Low Trait Group
Negative Stay locus 1084.56 (317.07) 1012.27 (180.61)
Move locus 1215.65 (395.44) 1061.36 (167.83)
Non-negative Stay locus 1135.00 (336.51) 1010.45 (187.57)
Move locus 1158.91 (290.03) 1050.23 (195.32)
The above lexical decision response data were subjected to a 2 x 2 x 2 mixed
design ANOVA consisting of one between group factor and two within group factors.
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The between group factor being trait anxiety group (high or low) and the two within
group factors being word valence (negative or non-negative) and word position (stay
locus or move locus). As previously outlined, the Biased Attentional Engagement
account predicts a significant three-way interaction on this analysis, whereby the relative
speed for high trait anxious individuals to process the content of words on move locus, as
compared to stay locus trials, will be disproportionately fast for negative as compared to
non-negative words.
The three-way ANOVA revealed a significant main effect of word position, F(1,
44) = 26.53, p < .01, demonstrating that participants were faster to make a lexical
decision of a word appearing in the same position as initial fixation (stay locus trials; M =
1060.57, SD = 38.85) than to make a lexical decision of a word appearing in the opposite
position to initial fixation (move locus trials; M = 1121.54, SD = 40.43). Consistent with
both the first and second studies, this main effect reflects the relative slowing resulting
from participants relocating spatial attention to the opposite screen location to make the
critical decision, in this case a lexical decision. More importantly for the interest of the
current study, this main effect highlights the task achieved the requirement of detecting
the speed of this spatial shift in attention, and therefore has the potential to reveal
valence-linked and anxiety-linked differences that may exist in this spatial shift in
attention. A two-way interaction between word valence (negative or non-negative) and
word position (move locus or stay locus) also emerged from this analysis F(1, 44) = 6.22,
p < .05. The nature of this interaction was such that, on move locus trials participants
lexical decisions were faster for non-negative words (M = 1104.57, SD = 37.05) and
slower for negative words (M = 1138.51, SD = 45.66), while on stay locus trials lexical
decisions were faster for negative words (M = 1048.42 , SD = 38.70) and slower for non-
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negative words (M = 1072.73, SD = 40.87). This interaction indicates that in general,
participants were slower to move spatial attention to the locus of a negative word than to
move spatial attention toward the locus of a non-negative word on this task. The Biased
Attentional Engagement hypothesis suggests that this effect would be attenuated for the
high trait anxious group, such that these individuals would be disproportionately fast to
identify the lexical status of negative words appearing in the opposite as compared to the
same screen position in relation to low trait anxious individuals. Indeed this two-way
interaction was observed to be further modified by trait anxiety as demonstrated in a
significant a three-way interaction between trait anxiety group, word valence and probe
locus F(1, 44) = 4.39, p < .05. As can be observed from Figure 4.2 however, the pattern
of this interaction was the opposite of what would be predicted by the Biased Attentional
Engagement account. This can be seen most specifically across the component two-way
interactions for the high and low trait anxious individuals. Whereas the low trait anxious
group showed no relative slowing to identify the lexical status of negative or non-
negative stimuli across move locus and stay locus trials F(1, 21) = 0.08, ns, high trait
anxious individuals showed disproportionate slowing for negative as compared to non-
negative words on the move locus trials, as compared to the stay locus trials F(1, 22) =
10.38, p < .01. This two-way interaction for the high trait anxious group suggests that
these individuals are in fact relatively slower to shift spatial attention to semantically
process negative material and relatively faster to shift spatial attention to semantically
process the content of non-negative material. This runs counter to the expectations of the
Biased Attentional Engagement account which would instead predict that the relative
speed for high trait anxious individuals to spatially shift attention would be faster for
negative material as compared to non-negative material.
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Figure 4.2. Three-way interaction between trait anxiety group (low or high), word
valence (negative or non-negative) and word position (stay locus or move locus).
This observed interaction for the high trait anxious group would suggest that these
individuals have greater difficulty spatially relocating attention to the locus of negative
relative to non-negative words. It is possible, however, that this effect may not simply be
attributable to the speed to process negative and non-negative material on move locus
trials, but instead may be due to differences in the speed to process such differentially
valenced material in the initially attended location on the stay locus trials. If this was the
case, we would predict a main effect to be present on the stay locus trials that would be
absent on the move locus trials. Consistent with this, simple main effects analysis on the
attentional move locus trials for the high trait anxious participants only, revealed that
when participants were required to move spatial attention, no relative speeding to identify
negative (M = 1215.65, SD = 82.46) as compared to non-negative words (M = 1158.91,
Low Trait Anxious
980
1020
1060
1100
1140
Negative Non-Negative
Word Valence
Re
sp
on
se
La
ten
cy
(m
s)
High Trait Anxious
1080
1120
1160
1200
1240
Negative Non-Negative
Word Valence
Resp
on
se L
ate
ncy (
ms)
Stay locus
Move locus
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SD = 60.52), F(1, 22) = 2.06, ns. Analysis of the stay locus trials however revealed that
there was a strong trend showing high trait anxious individuals were faster to
semantically process negative (M = 1084.57, SD = 66.11) as compared to non-negative
stimuli (M = 1135.00, SD = 70.17) when no shift in spatial attention was required F(1,
22) = 4.01, p = .06. Clearly this pattern of results cannot reflect a differential spatial shift
in attention as no such spatial shift is present on stay locus trials. The breakdown of this
interaction for high trait anxious individuals therefore suggests that the observed pattern
of speeding to identify the semantic content of negative words was present on stay locus
trials but was lost on move locus trials. What these data may therefore be showing is a
non-spatial engagement bias, whereby high trait anxious individuals show greater
tendency to engage with the semantic content of negative words, as compared to non-
negative words, appearing in the focus of spatial attention, which is eliminated by a shift
in spatial attention. Such a conception of attentional engagement is obviously a departure
from that considered in both Experiment 1 and the current study. The possibility that the
current data demonstrate an attentional engagement bias operating in the absence of a
spatial shift in attention will be returned to in the discussion.
As with the first and second studies, the degree of association between measures
of attentional engagement and measures of state and trait anxiety were assessed. An index
of biased attentional engagement was generated by first computing a measure of speeding
to process negative words by subtracting participant response latencies on stay locus
trials containing negative words from latencies on move locus trials containing negative
words. This resulted in a measure whereby higher scores represent greater speeding to
process the content of spatially removed negative words. The equivalent measure of
speeding to process non-negative words was also created by subtracting response
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latencies on stay locus trials containing non-negative words from latencies on move locus
trials containing non-negative words. Higher scores on the resulting measure represent
greater speeding to process the content of non-negative stimuli appearing in a spatially
removed locus. A single index of biased attentional engagement with spatially removed
negative words was created by subtracting the measure of speeding to process non-
negative words from the measure of speeding to process negative words. Higher scores
on this index therefore represent greater speeding to spatially shift attention to process
negative, as compared to, non-negative words. Correlations between this biased
attentional engagement index and STAI-T, r(45) = .05, ns, and STAI-S, r(45) = -.03, ns,
scores did not prove to be significant. The absence of a correlation between this biased
attentional engagement index and measures of state and trait anxiety would suggest that
there is little association between the relative speeding to spatially shift attention to the
locus of negative or non-negative material and either current anxious mood or more
general anxiety vulnerability.
Discussion
The high overall accuracy of participants‟ responses provided assurance that the
task was being performed as instructed with participants attending to the locus of the
probe before processing the word or non-word stimuli for semantic content. The
significant main effect of probe locus, further suggests that the task was capable of
indexing the speed of the attentional shift from the first attended locus to the
subsequently attended locus. A significant three-way interaction between trait anxiety
group, word valence and word position demonstrated that differences in speeding to
spatially shift attention to process the semantic content of negative and non-negative
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material did indeed emerge across trait anxiety groups. However, the pattern of this
interaction clearly disconfirmed the prediction generated by the Biased Attentional
Engagement account concerning differences in speeding to spatially shift attention to
process the semantic content of negative and non-negative words. Specifically this
interaction demonstrated that, while low trait anxious participants did not differ in their
pattern of responding to identify negative and non-negative stimuli, high trait anxious
participants showed disproportionate slowing to relocate spatial attention to semantically
process negative material appearing in the opposite screen location and disproportionate
speeding to semantically process non-negative material appearing in the opposite screen
location. This clearly contradicts the predictions of the Biased Attentional Engagement
account which instead state that high trait anxious individuals should demonstrated
disproportionate speeding to spatially shift attention to the process the content of negative
material appearing in the opposite screen location. Correlational analyses failed to
provide any support for the association between speed to spatially shift attention, to
process negative, as opposed to non-negative, material and measures of either state or
trait anxiety.
The Biased Attentional Engagement account of anxiety-linked attentional bias
predicted that high trait anxious individuals would demonstrate disproportionate speeding
to spatially shift attention to process the content of negative as compared to non-negative
words. According to this account, differences in speeding to spatially shift attention
would be demonstrated when participants were required to move attention from the
position of a neutral probe to engage with the semantic content of a spatially removed
negative or non-negative word. It was expected that such differences would emerge
against hypothesised baseline trials where no anxiety-linked differences were necessarily
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expected as participants did not spatially disengage attention from the neutral probe to
engage with the semantic meaning of a spatially removed negative or non-negative word.
The results of the current study did indeed demonstrate anxiety-linked differences in
speeding to spatially shift attention to engage with the semantic content of negative and
non-negative material across trials where participants were required to remain in the
initially attended locus, versus trials where they were required to relocate to a spatially
removed locus to identify the word. The specific prediction that high trait anxious
participants would evidence disproportionate speeding to process the semantic content of
negative words when they were presented in a spatially removed locus was not met
however. This is clearly inconsistent with the biased attentional engagement account of
anxiety-linked attentional bias which predicts that high trait anxious individuals will
show disproportionate speeding to engage with the content of spatially removed negative,
as compared to non-negative words.
The effect showing that high trait anxious individuals were disproportionately
slow to shift spatial attention to process the semantic content of negative material was
based on the comparison of latencies to semantically process negative and non-negative
words across move locus and stay locus trials. When considered together, the
comparative speeding observed across these two trial types clearly contradicts the
prediction of the Biased Attentional Engagement account that high trait anxious
individuals will be disproportionately fast to spatially shift attention to process the
semantic content of negative material. However, analysis of the component effects for
these individual trial types for the high trait anxious group highlights the possibility that
what appeared to reflect a slowness to move spatial attention to the locus of negative as
compared to non-negative words, resulted instead from a disproportionate speeding to
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process the content of material appearing in the initially attended location. This was
demonstrated in the main effects analysis of the stay locus trials where the high trait
anxious individuals demonstrated disproportionate speeding to semantically process the
content of negative words appearing in the same attended location. The equivalent
analysis of the move locus trials, however, failed to approach significance. These results
suggest that the effect of disproportionate slowing to spatially shift attention to process
the semantic content of negative material observed across move locus and stay locus trial
types for the high trait anxious individuals, is actually due to the relative speeding of
these individuals to process negative material in the stay locus trials that is absent in the
move locus trials.
As the previous three experiments have principally be concerned with examining
spatial engagement and disengagement, trials where no spatial shift in attention occurs
were considered to be „baseline‟ trials. This assumption was premised on the interest in
examining the properties of attentional engagement and disengagement in the allocation
of attention to negative material when a spatial shift in attention does occur. It was
therefore assumed that these baseline trials would not yield information about biased
attentional engagement and disengagement as there was no requirement that participants
spatially relocate attention from one stimulus to another. The observation in the current
task that high trait anxious participants were disproportionately fast to process the
semantic content of negative material on trials where no attentional shift was required,
highlights the very real possibility of a attentional engagement bias operating in the
absence of a spatial shift in attention. Such an engagement bias would represent relative
speeding from processing a non-emotional aspect of a stimulus presented in a spatially
attended locus, to processing a different aspect of this stimulus that conveys negative as
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compared to non-negative information. It is equally possible that such a bias could exist
in attentional disengagement also. This bias would be represented by relative speeding to
orient attention from processing an emotional aspect of a negative or non-negative
stimulus to processing a non-emotional aspect of the same stimulus.
In the current study, the faster response latencies for high trait anxious
participants to identify negative words presented in the same locus as initial attention
could represent such biased attentional engagement within a single locus. That is, this
result may be due to an effect of switching from the task of discerning the identity of a
probe, to the alternative task of processing the content of the material presented in the
attended locus. The absence of this effect when the subsequent lexical target is presented
in the opposite screen position would further suggest that this effect is limited to
switching of attention between different aspects of a stimulus in the same attended locus
and requiring participants to relocate attention to a different spatial locus eliminates this
effect.
An equally plausible alternative to the operation of a within-locus attentional
engagement process for the effect observed in the current task could be that high trait
anxious individuals merely exhibit a tendency to rapidly process the semantic content of
negative material presented to the locus of spatial attention. If this result does simply
represent such a general tendency for high trait anxious individuals to rapidly process the
meaning of negative material in the attended spatial locus, then we would also predicted
that high trait anxious individuals will demonstrate shorter latencies to semantically
process negative as compared to non-negative words when they have not previously been
processing an alternative aspect of a stimulus in the same spatial locus. In considering
this possibility, it is noted that such a condition was present in Experiment 2 where
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participants were initially required to identify the lexical status of negative or non-
negative word before responding to a probe appearing in either the same or opposite
screen location. As the task in this experiment required participants to first make a lexical
decision on each trial prior to any other response, no switch from initially processing a
different dimension of stimulus information in this spatial locus had occurred. If high trait
anxious individuals do simply process the content of negative material more rapidly, then
we would have expected an anxiety-linked difference in response latencies also to emerge
on this initial lexical decision component of the task. Consistent with a non-spatial
attentional engagement account, the results of Experiment 2 clearly demonstrated that no
differences in response latencies for negative and non-negative words on the initial
lexical decision task were present across trait anxiety groups, F(1, 42) = 1.78, ns. Taken
together with the result in the current experiment, suggesting that high trait anxious
individuals are disproportionately fast to determine the lexical status of negative words
following probe discrimination in the same location, these findings would point to the
possibility that attentional bias in anxiety may be characterised by biased attentional
engagement with the semantic content of negative material presented in an attended
locus.
This hypothesis that anxiety may be characterised by an enhanced speed to switch
attention from processing non-emotional stimulus information to instead engage with
processing a different stimulus dimension communicating negative, as opposed to non-
negative meaning, may be thought of as implicating a bias in „set shifting‟ rather than the
shifting of spatial attention. A set shift task typically requires individuals to initially focus
on using one dimension of stimuli which vary in several dimensions (e.g. form, and
colour; Wolff, 1967). A set shift is said to occur when a participant is then required to
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change the dimension of the stimuli used to make their responses. Slamecka (1968)
describes an extradimensional set shift as involving a switch that renders a previously
irrelevant stimulus dimension relevant to task performance. Hence, in the current task the
set shift on each trial involves participants shifting from processing structural information
(the probe discrimination) to processing semantic information (lexical decision) and this
set shift occurs even when no spatial shift is required.
In the present study, the stay locus trials were initially considered a condition that
did not require an attentional shift, as participants did not need to relocate spatial
attention to a different screen position to perform the lexical decision. Applying the
concept of a set shift outlined above however, it can be seen that these trials nevertheless
always required an attentional shift, moving from one aspect of a presented stimulus, in
this case the structural form of the probe, to an alternative dimension in the same locus,
this being the semantic content of the word. Having entertained the possibility that
differences may exist in shifting of attention between alternative dimensions of stimulus
information in a spatially attended locus, it becomes necessary to distinguish between
two distinct types of attentional shifting; attentional shifting that occurs between
dimensions of information within a given spatial locus and attentional shifting that occurs
between stimuli appearing in alternative spatial loci. In principle, anxiety-linked bias in
attentional engagement and disengagement could be evidenced for either, or both, of
these types of attentional shifting.
These first three modified attentional probe experiments have principally been
concerned with attentional engagement and disengagement during spatial shifting of
attention. The results of the current study however have underscored the possibility of
anxiety-liked differences in non-spatial attentional engagement and disengagement
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evidenced when participants make set shifts from one dimension to another dimension of
stimuli occurring within the same spatial locus. The prospect of an anxiety-linked bias in
attention operating within a single locus would not be without empirical basis. Indeed one
of the most reliable measures to consistently demonstrate selective attentional bias
favouring negative stimuli involves the presentation of only a single stimulus. As
discussed in the general introduction, the emotional Stroop task developed by Mathews
and MacLeod (1985) utilised an adapted version of the traditional Stroop task (Stroop,
1938) in which participants are required to name the text colour of negative and non-
negative words while ignoring the content, with response latencies taken to indicated the
degree to which individuals have been able to avoid processing the semantic content of
these words. Mathews and MacLeod (1985) demonstrated that clinically anxious
individuals in this study exhibited significantly longer colour-naming latencies for
negative as compared to non-negative stimuli. Such effects have been repeated a number
of times with high trait anxious members of the general population (e.g. MacLeod &
Rutherford, 1992). The observation of such effects using the emotional Stroop task
strongly suggest that an anxiety-linked attentional bias can be demonstrated in a task
involving a single stimulus with two salient dimensions.
The results of the current study suggest that high trait anxious individuals may be
disproportionately fast to switch from processing neutral stimulus information to negative
stimulus information, when task conditions do not require that they relocate spatial
attention. However, as the current task was specifically designed to assess relative
speeding to spatially shift attention, conclusions regarding the existence of an anxiety-
linked attentional engagement bias operating within a single locus based on results of the
current task are tentative, though worthy of further enquiry. To assess whether anxiety-
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linked attentional bias is characterised by enhanced attentional engagement with, or
impaired attentional disengagement from, the content of negative material presented
within a single spatial location, it would be necessary to construct a task requiring
participants to process either of two dimensions of simple stimuli, only one of which is
semantic content. In order to measure biased attentional engagement it would be
necessary to first require participants process the non-emotional dimension of the
stimulus (e.g. form) before requiring that they process an emotional dimension of the
stimulus (e.g. semantic meaning). The relative speed to process the emotional dimension
of a negative or non-negative stimulus, after having processed the non-emotional
dimension, would therefore provide an index of attentional engagement. By reversing the
order in which the stimulus dimensions are processed by first requiring the emotional
dimension to be processed before the non-emotional dimension, the task could also yield
a measure of attentional disengagement. Such a condition would provide an index of the
speed with which an individual could disengage from processing the emotional content of
a negative or non-negative stimulus to process a non-emotional dimension of the same
stimulus.
An adapted version of the emotional Stroop task could provide the conditions
necessary to yield measures of both non-spatial attentional engagement and
disengagement. The negative and non-negative words presented in coloured text in the
emotional Stroop task provide the necessary stimuli in that it contains both a non-
emotional dimension, in the text colour, and an emotional dimension, in the word
content. Requiring participants to switch between these different stimulus dimensions
could therefore yield a measure of both non-spatial attentional engagement and
disengagement. By consecutively revealing structural and conceptual elements of a single
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stimulus that participants are required to process, such a „decoupled‟ Stroop task could
act to clarify whether the current findings suggesting that high trait anxious individuals
selectively engage with the semantic content of negative words in an attended locus are in
fact reliable. The principal focus of Experiment 4 therefore was to measure whether
attentional bias in anxiety is characterised by biased attentional engagement with or
disengagement from the emotional dimension of negative and non-negative words.
While the results of the present experiment implicate the possibility of an
attentional engagement bias operating within a spatial locus, it should be noted that the
variants of the attentional probe task used in Experiments 1, 2 and 3 have not produced
evidence to support the presence of either an anxiety-linked attentional engagement bias,
or attentional disengagement bias operating in the preferential allocation of spatial
attention to negative stimuli. The absence of either an anxiety-linked engagement or
disengagement bias in spatial attention would clearly oppose predictions derived from
past results using the original attentional probe task. These past experiments (e.g.
MacLeod et al., 1986) have consistently revealed that high trait anxious individuals
preferentially attend to the locus of negative as compared to non-negative stimuli. Such
finding would implicate the role of either enhanced attentional engagement with, or
impaired disengagement from negative stimuli in the spatial allocation of attention for
these high trait anxious individuals. The past findings regarding anxiety-linked
attentional bias and the spatial allocation of attention therefore stand in contrast to the
present results which have not demonstrated an anxiety-inked attentional engagement or
disengagement effect favouring negative stimuli in the spatial allocation of attention.
The inconsistency between past and present findings in relation to selective
allocation of spatial attention may plausibly be attributed to subtle, but possibly important
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differences between the specific formats of the tasks used. While this possibility will be
considered more fully in the final discussion, it can be noted here that a necessary
innovation in the present task has been the introduction of a requirement for attention to
be initially assigned to a prescribed location, followed by the requirement for attention
either to disengage from this locus or not. If anxiety-linked attentional bias reflects
individual differences in the tendency to allocate attention to a particular region, rather
than individual differences in the ability to fulfill a requirement to do so then this may
explain the differential sensitivity of previously employed attentional probe tasks, which
do not include such a requirement, as compared to the current experimental tasks. This is
an issue that will be returned to and expanded upon in the general discussion.
In summary, the aim of the current study was to assess anxiety-linked differences
in relative speeding to spatially shift attention to engage with the semantic content of
negative and non-negative words. Contrary to the predictions of the Biased Attentional
Engagement hypothesis, high trait anxious individuals evidenced disproportionate
slowing to shift spatial attention to process the semantic content of negative words as
compared to remaining in the same locus to semantically process these stimuli.
Subsequent analyses of the component effects suggest that what appeared to be slowing
to spatially shift attention the opposite screen position in fact may be due to
disproportionate speeding to process the content of negative material on trials where no
spatial shift in attention is required. This result highlighted the possibility that biases in
attentional engagement and disengagement could occur in the absence of a spatial shift
between different stimuli and instead occur within an attended spatial locus between
different dimensions of the same stimulus. Based on these results, the aim of the
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Experiment 4 was to further examine anxiety-linked differences in attentional
engagement with, or disengagement from, emotional dimensions of a single stimulus.
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CHAPTER 5
EXPERIMENT 4
The results of Experiment 3 highlighted the possibility that attentional bias in
anxiety may be characterised by a tendency to selectively engage attention with the
semantic content of a negatively valenced word, after having processed non-emotional
information occupying the same spatial location (i.e. probe structure). It is equally
possible that the equivalent process could also operate for attentional disengagement,
where individuals more vulnerable to anxious mood may have greater difficulty
disengaging attention from the emotional content of a negatively valenced word to non-
emotional information occupying the same spatial location.
As distinct from the assumption that attention stays or moves depending on
whether a stimulus appears in the same or different location, the results of Experiment 3
highlight that attention can move between different stimulus information within a single
locus. Entertaining the possibility that attentional shifts, and indeed attentional biases, can
occur within a single locus moves from the preconception of the past studies that it is
necessary to cause spatial shifts in attention to elicit and measure individual differences
in attentional engagement and disengagement. While the presence of an attentional
engagement or attentional disengagement bias occurring within a single locus would not
eliminate the need to account for the absence of findings in relation to spatial engagement
and disengagement, it is nevertheless important to establish the pattern of attentional bias
that may be present for shifts in attention occurring within a single locus. A clear
implication of attentional shifts occurring within a single locus is that when two pieces of
information are processed in sequence, there is always an attentional shift from one to the
other, regardless of whether a spatial shift in attention is required. Thus, attention must
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always disengage from one initially attended piece of information and engage with the
subsequently attended piece of information. Therefore, rather than attempting to
experimentally control whether an attentional shift occurs or not, it becomes more useful
to control the emotionality of the stimulus being shifted from, or the emotionality of the
stimulus being shifted towards, in order to differentiate processing biases in attentional
disengagement and attentional engagement. Having individuals initially process
emotional content of a stimulus before then requiring that they process a non-emotional
dimension of this stimulus would provide a measure of biased attentional disengagement
from differentially valenced semantic content. Conversely, requiring an individual to first
process a non-emotional dimension of a stimulus before engaging with the semantic
content of the stimulus would provide a measure of biased attentional engagement with
the semantic content. A key purpose of the current study was to move from the previous
focus on whether attention stays within, or moves from, differing spatial loci, to instead
develop and employ a methodology capable of measuring biased attentional engagement
with and disengagement from emotional content occurring within a single locus.
One of the most commonly used tasks for assessing attentional bias already
provides a methodology capable of measuring biased attention within a single locus.
Specifically, the emotional Stroop task has been a frequently used and reliable means of
measuring attentional bias. Research conducted using this task has consistently
demonstrated that individuals with clinical levels of anxiety, relative to low anxious
controls, are significantly slower to colour-name negative as compared to non-negative
words (e.g. Mathews & MacLeod, 1985; Mogg, et al., 1989), suggesting selective
processing of negative stimulus content, as opposed to stimulus colour, by those with
higher anxiety vulnerability. It has further been demonstrated that this pattern of effects
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generalises to high trait anxious members of the general population including
undergraduate university students (e.g. MacLeod & Rutherford, 1992). As reviewed in
the introduction, studies have also shown that the attentional preference for negative
content revealed by performance on the emotional Stroop task reduces with improvement
in anxious mood resulting from psychological treatment (Mathews, Mogg, Kentish, &
Eysenck, 1995), and also is predictive of the severity of emotional response to a future
stressful life event (MacLeod & Hagen, 1992). The original emotional Stroop task
therefore provides a reliable and robust measure of anxiety-linked attentional bias to
negative and non-negative dimensions of stimuli presented in a single spatial locus.
However, the anxiety-linked attentional bias observed using the emotional Stroop
task could readily be accounted for by either biased attentional engagement with, or
biased disengagement from, negative semantic content. The Biased Attentional
Engagement account of anxiety-linked attentional bias suggests that high trait anxious
individuals may preferentially engage with the semantic content of negative words which
in turn results in longer latencies to perform the task of colour-naming the text of such
stimuli, as the colour information has received less attention. Alternatively, the Biased
Attentional Disengagement account suggests that both high and low trait anxious
individuals have an equal tendency to attend initially to the semantic content of negative
or neutral words, but high trait anxious individuals have greater difficulty then
disengaging attention from this semantic information when it is negatively valenced, as is
required to efficiently perform the task of colour-naming the text.
The great majority of studies using the emotional Stroop task have instructed
participants to ignore the semantic content of the stimulus while naming the colour and
have inferred enhanced processing of negative material by slowing to colour-name the
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text. On occasion however, researchers have employed assessment versions of this task
where participants have been directed to ignore the colour and process the content. Here,
increased processing of negative material would instead be revealed by speeding to
register the semantic content of the stimulus. Campbell (2001) used such a version of the
emotional Stroop to assess attentional bias in a group of individuals exposed to a
manipulation designed to induce an attentional bias to negative words. Her study found
that, on trials where these participants were instructed to ignore the word content, they
were slow to colour-name the text of negative, as compared to non-negative words,
whereas on trials where they were required to process semantic content by performing a
grammatical judgment decision, they were relatively faster to make this decision for
negative as compared to non-negative words.
Campbell‟s version of the emotional Stroop demonstrates how assessing either the
speed to process a word‟s colour, or assessing speed to process that word‟s semantic
content, can reveal selective attention favoring information of a particular valence. A
modified version of the emotional Stroop used by Campbell (2001) could readily fulfill
the task requirements associated with the present goal of distinguishing biased attentional
engagement with and biased attentional disengagement from emotional information.
Rather than requiring participants to either process semantic content or colour on a given
trial, they could instead be required to process both colour and semantic content on each
trial, in either of the two possible orders in which these two decisions could be made. In
these trials, latencies to perform the second decision can reveal the biases of relevance.
Specifically, on trials where participants initially process colour information before
processing semantic content, the second decision latency will reveal the time taken to
switch attention from processing colour to engage with the semantic content. Conversely,
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on trials where the decision order is reversed and participants first process semantic
content before colour information, latency to perform the second decision will reveal the
time taken to disengage attention from the semantic content and switch attention to
process colour information. A measure of biased attentional engagement with
differentially valenced word content would be provided by requiring participants to
initially identify the colour of the stimulus before then requiring them to semantically
process the content of a negative or non-negative word by making a grammatical
classification decision. The speed of this second decision would provide an indication of
individual differences in biased attentional engagement with the semantic content of
these words as participants move attention to this information after first processing the
text colour. A measure of biased attentional disengagement from differentially valenced
word content would instead be obtained by first requiring participants to process the
semantic content of the negative or non-negative word, by making a grammatical
classification judgment, before then identifying the text colour. Now, this second decision
latency (to identify text colour) would provide a measure of biased attentional
disengagement from the initially processed semantic information, as participants would
need to move attention from this emotional information to instead process the non-
emotional colour information to make the second decision.
A modified version of the emotional Stroop task was therefore constructed to
enable the measurement of biased attentional engagement with and disengagement from
semantic content of negative and non-negative words. It should be noted that this variant
the emotional Stroop was modified to a task switching variant, with attention orienting
between colour and content dimensions of the stimulus which become available for
processing at different stages. Because the biased attentional engagement and
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disengagement accounts of the emotional Stroop effect are in essence competing task-
switching based accounts, it was necessary to modify the task in a way that could
discriminate these task switching accounts. Therefore while the modified variant involves
task switching, it is still referred to as a modified emotional Stroop, albeit one that is
modified to test alternative task switching (biased attentional engagement or
disengagement) accounts of the emotional Stroop effect.
The Biased Attentional Engagement and Biased Attentional Disengagement
accounts of attentional bias both make different predictions about the pattern of effects
that are expected to emerge in the current study. Specifically, the Biased Attentional
Disengagement hypothesis predicts that high trait anxious individuals will exhibit greater
difficulty disengaging attention from the semantic content of negative words as revealed
by disproportionate slowing to colour-name negative words on the second trial decision,
after having processed their semantic meaning on the first trial decision. The biased
attentional engagement hypothesis however predicts that high trait anxious individuals
will be disproportionately fast to grammatically classify negative as compared to non-
negative stimulus words, after having identified the stimulus text colour as the first trial
decision, thereby demonstrating enhanced attentional engagement with the semantic
content of these words on the second trial decision.
Method
Overview
To achieve measures of biased attentional engagement with, and disengagement
from, emotional content, the task used in the current study utilised two distinct trial types
involving a different sequence of stimulus processing requirements. These two trial types
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will be referred to as Semantic Engagement Trials and Semantic Disengagement Trials
for those assessing biased attentional engagement with, and biased attentional
disengagement from, the semantic content of differentially valenced words respectively.
An instruction was given at the beginning of each trial to indicate whether the trial would
first require the processing of colour, followed by the semantic processing of word
content, or the semantic processing of word content, followed by the processing of
colour. As in Campbell‟s (2001) version of the emotional Stroop, grammatical judgment
was used to ensure participants semantically processed the word. The measures of
attentional engagement and disengagement were provided by the latency to make the
critical second decision on each trial. On this second decision, participants were always
looking at a coloured word. The difference across the two trial types was that, for
Semantic Engagement Trials, participants were switching to process the word meaning
having previously been exposed to the colour information, while for Semantic
Disengagement Trials, participants were switching to process the colour information
having processed the stimulus meaning. To ensure that these measures of attentional
engagement and disengagement were not compromised by the premature processing of
the stimulus information needed to make the second decision, this stimulus information
did not become available until participants made their first decision in the trial.
Therefore, on Semantic Engagement Trials, participants were initially presented with the
colour information, delivered in the form of a coloured string of random letters. As soon
as their colour-naming response was detected, the letter string transformed into the word
that participants were required to make a grammatical classification of. If anxiety is
characterised by biased attentional engagement with emotional content then high trait
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anxious individuals should be disproportionately fast to grammatically judge the negative
as compared to the non-negative words on these trials.
For Semantic Disengagement Trials, the sequence in which stimulus information
became available was reversed. A negative or non-negative word in white text first was
presented and participants were required to grammatically classify this word. As soon as
this response was detected, colour information was added to the stimulus and participants
were required to verbally name this colour aloud. If anxiety is characterised by difficulty
disengaging attention from the semantic content of a negative stimulus, then high trait
anxious individuals will be disproportionately slow to make this colour naming-response
when they had initially been required to grammatically classify negative as compared to
non-negative word content.
Participants
To ensure that participants differed in trait anxiety as required at the time of
testing, selection of potential participants was again guided by the screening of
undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory
(STAI-T; Spielberger et al., 1983) prior to the commencement of the study. Six hundred
and one participants were screened, with those obtaining scores on the STAI-T which fell
in the upper third (at or above 42) or the lower third (at or below 35) of the distribution
being considered eligible for the study. Of those recruited, 20 were from the upper third
of the distribution (high trait anxious group) and 20 were from the lower third of the
distribution (low trait anxious group). The low trait anxious group comprised five male
and 14 female participants with an average age of 18.35 years (SD = 1.66), while the high
trait anxious group consisted of five male and 15 female participants with a mean age of
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19.95 years (SD = 6.30). The high and low trait anxious groups did not differ
significantly in terms of age, t(38) = 1.10, ns, or gender ratio ²(1,38) = 0.12, ns.
Materials
Emotional Assessment Measure
The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)
was again employed as the emotional assessment measure.
Stimulus Words
The same 48 negative and 48 non-negative words used in each of the previous
studies were again used in the current task. An additional stimulus set consisting of 20
non-negative words was also created for use in practice trials.
Experimental Hardware
Experimental task delivery was again controlled by an Acorn Archimedes 5000
computer, with high resolution monitor. A microphone and voice key were also attached
for detection of colour-naming responses.
Experimental Task
Each trial began with an instruction string presented in text 10mm in height in the
centre of a blank screen which informed participants of the order in which they would
have to perform the two decisions of colour-naming and grammatical classification. The
task contained two distinct trial types measuring either biased attentional engagement
with (Semantic Engagement Trials) or disengagement from (Semantic Disengagement
Trials) the semantic content of negative and non-negative words. For the Semantic
Disengage Trials, the initial instruction string was either the word VERB, NOUN or
ADJECTIVE paired with the word COLOUR (e.g. “NOUN/COLOUR”). This signaled to
participants that they were first required to make a grammatical classification, as to
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whether the stimulus word belonged to the stated grammatical category, then to make a
colour naming decision. This initial instruction remained on the screen until participants
pressed the spacebar to begin the trial. A negative or non-negative word in white text was
then presented and participants were required to decide as to whether the word belonged
to the grammatical category presented in the instruction string, and respond by pressing
mouse key labeled “yes” or “no”. Response latency and accuracy were recorded for this
decision. Immediately following the registration of this response, the letter string changed
from white to one of four colours (red, blue green or yellow). Participants were required
to name this colour aloud and their latency to colour name the text, taken as the interval
between the onset of the colour and the detection of the colour naming response by a
voice activated microphone, was recorded. This response terminated the trial and the
instruction for the next trial appeared 1000ms later. Figure 5.1a provides an example
illustration of these trials assessing biased attentional disengagement, when either
negative or non-negative words were employed.
On Semantic Engagement Trials, the instruction string consisted of the word
COLOUR paired with either the word VERB, NOUN or ADJECTIVE (e.g.
“COLOUR/VERB”) indicating that participants were required to make a colour naming
decision before a grammatical judgment. Once participants had registered this instruction
and pressed the spacebar to proceed, a random letter string, automatically generated on
these trials, was first presented in one of four colours (red, blue, green or yellow) and
participants were required to name aloud the colour of the letter string. When this
response was detected, the colour information remained, but the random letter string
transformed into a negative or non-negative word of equal length, and participants were
required to determine whether this word belonged to the grammatical category presented
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in the instruction string by pressing the corresponding “yes” or “no” mouse key.
Response latency and accuracy for this grammatical judgment was recorded on these
trials. Figure 5.1b provides an example of Semantic Disengage Trials, using a negative
and a non-negative word.
5.1 a) Semantic Disengagement Trials
Instruction Grammatical Judgment Colour Name
5.1 b) Semantic Engagement Trials
Instruction Colour Name Grammatical Judgment
Figure 5.1. Trials assessing biased attentional engagement with and disengagement from
negative and non-negative word content. Colour type and grammatical class shown
randomly.
Grammatical Judgment/
Colour name trial
Using Negative Word
Grammatical Judgment/
Colour name trial
Using Non-Negative Word
NOUN/COLOUR
FEAR
FEAR
VERB/COLOUR
SOFTENER
SOFTENER
Colour Name/
Grammatical Judgment Trial
Using Negative Word
COLOUR/NOUN
DBSLMWQI
RIDICULE
COLOUR/VERB
KCYMSQAILK
WATERPROOF
Colour Name/
Grammatical Judgment Trial
Using Non-Negative Word
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The task consisted of 384 experimental trials in total. Each of the 48 negative and
48 non-negative words was presented once within each presentation sequence of 96 trials
before any were repeated again. An equal number of Semantic Disengagement Trials and
Semantic Engagement Trials were included within a presentation sequence of 96 trials
with the presentation order of trial type being randomised within these 96 trials. Text
colour was also randomised within each sequence of 96 trials, with the constraint that
each colour (red, blue, green, yellow) was presented an equal number of times. Thus
across all 348 trials each stimulus was presented four times, two times in the Semantic
Disengagement Trials and two times in the Semantic Engagement Trials. To minimise
potential practice effects resulting from repeating the required grammatical classification
for the same words, the grammatical class specified in the instruction string was changed
when a given word was presented for a second time. Therefore, if participants had been
required to determine if the word “powerless” was a verb at an early point in the task,
they would decide whether it was an adjective when it again appeared later in the task.
The correct response to a grammatical classification was balanced across the stimuli such
that correct performance of the task required an equal number of “yes” and “no”
responses across the 348 trials. Across participants, the allocation of stimuli to each trial
type was counterbalanced such that after two participants had been tested, each stimulus
word had appeared in each possible condition once. Word stimuli, the part of speech
category used to classify each word on first and second presentations and correct
responses to these are provided in Appendix D. Participants were given the opportunity
of a brief self-paced rest period after the completion of 192 trials.
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Procedure
All participants were tested individually in a sound attenuated cubicle. On arrival
participants first completed both state and trait sections of the Spielberger State-Trait
Anxiety Inventory (STAI; Spielberger et al., 1983) before beginning the experimental
task. Prior to commencing the experimental task participants were provided instructions
highlighting that the task would require them to make two responses on each trial, a
grammatical judgment response and a colour naming response, and that the order in
which they were required to make these responses would be specified at the start of each
trial. The nature of the initial instruction string, and the method of responding was then
described to participants. They were informed that colour-naming responses would be
detected by a microphone, and directed to respond verbally to name the text colour. They
were told that their grammatical judgment responses were to be made by pressing the
corresponding mouse key labeled “yes” or “no” according to whether or not the word
could belong to the part of speech specified in the instruction string. Participants were
directed to be as fast as possible in responding without compromising accuracy. Practice
trials were then completed before participants commenced the experimental task. These
trials used the neutral words created for this purpose and presented 10 Semantic
Disengage Trials and 10 Semantic Engagement Trials in random sequence.
Results
Participant characteristics at the time of testing are provided in Table 5.1.
Measures of trait anxiety using the STAI-T taken at the time of testing confirmed that
high and low trait anxious groups continued to differ in terms of trait anxiety, t(38) =
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9.50, p < .01, with the high trait anxious group displaying a mean score of 49.80 (SD =
8.37) and the low trait anxious group with a mean of 30.50 (3.53).
Table 5.1
Characteristics of participants in Experiment 4. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F
High Trait Anxious 49.80 (8.37) 43.05 (7.96) 19.95 (6.30) 5:15
Low Trait Anxious 30.50 (3.53) 29.90 (3.53) 18.35 (1.66) 6:14
All Participants 40.15 (11.65) 36.02 (9.58) 19.15 (4.62) 11:29
Not surprisingly, high and low trait anxious individuals were also observed to
differ in terms state anxiety as measured by the STAI-S score t(38) = 6.83, p < .01. The
presence of this group difference in state anxiety means that any observed group
differences in task performance in this study could be attributable to state, rather than
trait anxiety. For this reason, correlational analyses will be conducted to determine
whether observed effects are associated to a greater extent with either state or trait
anxiety.
As high rates of inaccuracy for grammatical judgment responses could signal that
participants were not processing the semantic content of stimulus words as required, it
was necessary to exclude those participants with high rates of error. Accuracy of
grammatical judgments proved to be rather low with participants averaging only 81.64%
correct responses for the grammatical judgment component of the task. This higher rate
of error carries important implications that will be returned to in the discussion section
and will bear upon the design of the next experiment. For the present, however, it should
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be noted that application of the inclusion criteria used in the previous three studies of
minimum 80% accuracy resulted in 16 participants being excluded from the final
analysis, which significantly reduced statistical power in the current study. Although an
argument might be made to be more liberal with respect to acceptable error rate to
increase power, this too would compromise comparisons by including those participants
with a larger error rate. Given that chance responding would have secured an accuracy of
50%, the predetermined inclusion criterion of 80% accuracy was retained. However, the
analyses were also performed with the inclusion of all participants. As will be reported in
footnotes, no difference in the pattern of obtained effects was observed when all
participants were included in the analysis. Of the 16 participants excluded on the basis of
low accuracy, nine came from the high trait anxious group and seven came from the low
trait anxious group. A significant differences was observed between high and low trait
anxious groups in rates of accuracy for those not excluded, F(1, 22) = 6.72, p < .05,
whereby the high trait anxious individuals obtained significantly fewer incorrect
responses (M = 51.81, SD = 7.61) than the low trait anxious individuals (M = 61.46, SD =
51.82). This difference was not significant, however, when all participants were included
in the analysis F(1, 38) = 0.24, ns. Analyses for trials assessing biased attentional
disengagement from, and biased attentional engagement with emotional content are
considered separately in consecutive analyses below.
Assessment of Biased Attentional Disengagement from Semantic Content
Semantic Disengagement Trials assessing biased attentional disengagement from
semantic content were those requiring participants to first make a grammatical judgment
of negative or non-negative words before switching to then colour-name the text of these
stimuli. Latencies to colour name the text, reflecting the speed of this second decision,
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were recorded as the dependent measure on these trials with longer latencies taken to
indicate greater difficulty disengaging from the semantic content of the word. As
disengagement from this initially presented semantic material can only be assessed when
participants did initially engage with this semantic content, the colour-naming latencies
were included only from trials on which participants had recorded correct grammatical
judgments as their first decision. To minimise the influence of outlying colour-naming
latencies, median response latencies were computed, and these latencies are provided in
Table 5.2.
Table 5.2
Latencies for second trial responses (colour-naming) in milliseconds on Semantic
Disengage Trials, across negative and non-negative word stimuli for high and low trait
anxiety groups. Standard deviations given in parenthesis.
Word Valence High Trait Group Low Trait Group
Negative Word Trials 625.00 (141.01) 594.61 (123.27)
Non-Negative Word Trials 622.27 (148.87) 600.77 (117.08)
These data were subjected to a 2 x 2 mixed design ANOVA with word valence
(negative or non-negative) as the within group factor and trait anxiety group (high or low)
as the between group factor. According to the Biased Disengagement account of
attentional bias in anxiety, on Semantic Disengagement Trials high trait anxious
individuals should exhibit disproportionately slow colour-naming responses after having
grammatically classified negative as compared to non-negative words, resulting in a two
way interaction between word valence and trait anxiety group. The two-way interaction
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predicted by the biased attentional disengagement account did not approach significance
F(1, 22) = 0.04, ns2, and no other significant effects emerged from the interaction. This
result is inconsistent with the hypothesis that anxiety-linked attentional bias is associated
with biased attentional disengagement from emotional content. It is not however
inconsistent with the Biased Attentional Engagement account of anxiety-linked
attentional bias.
While no group differences were observed to suggest biased attentional
disengagement from emotional content, potential associations between this measure and
either state or trait anxiety could potentially still exist. Correlational analyses were
therefore conducted to establish if this was the case. A single index of impaired
attentional disengagement from negative content was therefore computed. This was
achieved by subtracting colour-naming response latencies following grammatical
judgment on non-negative words from colour-naming response latencies following
grammatical judgment on negative words on Semantic Disengagement Trials. The
resulting index represented a measure of impaired attentional disengagement from
negative word content, with higher scores indicating greater slowing to disengage
attention from negative as compared to non-negative words. Pearson‟s correlations
between this index of impaired attentional disengagement from negative content and
STAI-T scores, r(24) = .08, ns, and STAI-S scores, r(24) = .06, ns, did not prove to be
significant3. Again the absence of such associations is inconsistent with the Biased
2 This two-way interaction remained non-significant when the analysis was conducted including all
participants regardless of accuracy levels F(1, 38) = 0.41, ns. 3 These correlations between the index of biased attentional disengagement and STAI-T scores, r(40) = .00,
ns, and biased attentional disengagement STAI-S scores, r(40) = -.05, ns, remained non-significant when
all participants were included in the analysis, regardless of accuracy levels.
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Attentional Disengagement account of attentional bias, but is not inconsistent with the
Biased Attentional Engagement account.
Assessment of Biased Attentional Engagement with Emotional Content
The trials assessing biased attentional engagement with emotional content were
those where participants first made a colour-naming decision before switching to make a
grammatical decision of a negative or non-negative word. Speeding to make grammatical
decisions for negative, as compared to non-negative words on these trials would suggest
enhanced attentional engagement with the semantic content of these stimuli. The
grammatical decision latencies comprised dependent measure on these trials. Only trials
on which participants made correct grammatical decisions were include in the analysis,
and median grammatical decision response latencies were again used to minimise the
influence of outlying data. The average of these grammatical decision latencies for
negative and non-negative words across high and low trait anxious individuals are
provided in Table 5.3.
Data from these trials assessing biased attentional engagement with emotional
content were subjected to a 2 x 2 repeated measures ANOVA with one between group
factor, being trait anxiety group (high or low) and one within group factor, being word
valence (negative or non-negative). The Biased Attentional Engagement account of
anxiety-linked attentional bias predicts that on Semantic Engagement Trials, high trait
anxious individuals will be faster to make grammatical decisions for negative as
compared to non-negative words, resulting in a two-way interaction between word
valence and trait anxiety group. No significant effects emerged from this analysis, with
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the interaction between trait anxiety group and word valence predicted by the biased
attentional engagement account not approaching significance, F(1, 22) = 0.69, ns4.
Table 5.3
Latencies for second trial responses (grammatical decision) in milliseconds on Semantic
Engage Trials, across negative and non-negative word stimuli for high and low trait
anxiety groups. Standard deviations given in parenthesis.
Word Valence High Trait Group Low Trait Group
Negative Word Trials 1795.91 (364.70) 1632.31 (710.08)
Non-Negative Word Trials 1622.73 (283.15) 1569.23 (675.03)
As before, correlational analyses were also conducted to determine if any
relationships could be observed between an index of this attentional bias and state or trait
anxiety. An index of enhanced attentional engagement with negative information was
therefore computed by subtracting grammatical judgment latencies for negative words
from grammatical judgment latencies for non-negative words. Higher scores on the
resulting index therefore represent speeding to switch from processing word colour to
process the content of negative as compared to non-negative words. Neither of the
correlations between this index of enhanced attentional engagement with negative
information and STAI-T scores, r(24) = -.16, ns, or STAI-S scores, r(24) = -.14, ns,
proved to be significant5.
4 This two-way interaction remained non-significant when the analysis was conducted including all
participants regardless of accuracy levels F(1, 38) = 2.65, ns. 5 The correlation between the index of biased attentional engagement and STAI-T scores, r(40) = -.28, ns,
and the index of biased attentional engagement and STAI-S scores, r(40) = -.21, ns, remained non-
significant when all participants were included in the analysis, regardless of accuracy level.
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Discussion
The aim of the present study was to develop a task capable of measuring biased
attentional engagement with and disengagement from emotional content when orienting
attention between emotional and non-emotional information contained within the same
stimulus. The current task was designed to measure biased attentional engagement with
emotional content by examining the speed with which participants could switch from
processing colour to instead semantically process the content of negative and non-
negative words. Biased attentional disengagement was measured by examining how
rapidly participants were able to switch from processing the content of negative and non-
negative words to instead process the colour of such stimuli. The results of the present
study provided no support for either the Biased Engagement or Biased Disengagement
accounts of anxiety-linked attentional bias. Correlational analyses similarly revealed no
evidence for associations between measures of biased attentional engagement with and
disengagement from emotional content and measures of state or trait anxiety.
While the current experiment failed to provide support for either Biased
Attentional Engagement or Biased Attentional Disengagement accounts of anxiety-linked
attentional bias, the high rate of inaccuracy on the grammatical judgment component of
the task would suggest caution against prematurely dismissing either account based on
the present findings. The purpose of including a grammatical judgment response in the
current experiment was twofold; to ensure participants engaged with the semantic
meaning of stimulus words before assessing their ability to disengage from this
information and, to provide a measure of the speed with which participants could switch
from processing colour to instead engage with emotionally valenced content of the
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stimuli. The low rate of accuracy observed in the current task could have been due to
participants not reliably processing word content when required to do so or, may have
been due to their difficulty determining the grammatical class of stimulus words even
after accessing their meaning. Indeed, it was noted when conducting testing that a
number of participants requested clarification as to the definition of the part of speech
categories included in the task (verb, noun and adjective) suggesting that there may have
been some confusion in making grammatical judgments.
The results derived from the current task do not allow us to discriminate whether
the high error rate was due to unreliable processing of word content or difficulty with
making grammatical judgments. Either of these possibilities would be problematic for
measuring biased attentional engagement and disengagement however. Indeed, if the
error rate was principally due to participants not having processed the content of the
stimuli, it would mean that the task was not indexing engagement with or disengagement
from such stimulus content. However, even if we assume that participants were
processing the stimuli, and the high error rate reflects greater difficulty making
grammatical judgments, this raises concerns as to whether the latency to make this
decision provides an accurate indication of speed to access the semantic content of the
stimulus.
It is possible that determining the grammatical class of a word involves
considerable post-lexical processing after the semantic content of the word has been
identified. If this were the case, the variance in such post-lexical processing may obscure
individual differences in the tendency to process negative and non-negative word content
across individuals who vary in anxiety vulnerability. The observed difference in average
latency to perform a grammatical judgment responses on the current task (M = 1650.52)
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as compared to the average latency to perform lexical decision responses on the task used
in Experiment 3 (M = 1127.61) further reinforces the notion that performing grammatical
judgments may involve extensive post-lexical processing of stimulus words as compared
to performing a lexical decision. If we accept that a lexical decision results in participants
accessing a words meaning and responding in around 1100ms in Experiment 3, then the
longer latencies when performing grammatical judgment in the current task would
suggest that participants are doing considerably more post-lexical processing of the
stimulus. The degree of variance observed in grammatical decision latencies in the
current study (SD = 524.11) as compared to lexical decision latencies in Experiment 3
(SD = 272.86) would further suggest that any post-lexical processing that occurs when
making grammatical judgments is likely to be highly variable. The longer decision
latencies and greater variance in performing a grammatical decision could therefore be
obscuring the speed to access semantic content of the stimuli and any effects relating to
biases in engagement with or disengagement from the content of such stimuli.
Based on these concerns it was decided to modify the task used in the current
study by employing a better means of ensuring that participants process semantic
information, and measuring the speed with which this occurs. The key purpose of
Experiment 5 was therefore to modify the current task by adopting an improved means of
securing lexical access, which would minimise post-lexical processing and allow the high
levels of accuracy necessary to permit confidence that stimulus meaning was accessed. It
was anticipated that using lexical decision as a means of assessing lexical access would
instead minimise additional time and variance associated with performing a grammatical
judgment decision and will provide a more consistent response time that is more
representative of speed to access word meaning. Such a decision is also likely to permit
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the high levels of accuracy necessary to allow confidence that stimulus meaning has
indeed been accessed.
In summary, this present experiment adopted a novel means of assessing whether
anxiety-linked attentional bias is characterised by enhanced attentional engagement with
or impaired disengagement from negatively valenced information. This was achieved by
requiring participants to switch to processing the colour of negative and non-negative
stimuli after first processing their emotional content to assess biased attentional
disengagement, and by requiring participants to switch to process semantic content of
negative and non-negative words after first processing the colour of these words to assess
biased attentional engagement. The results provided no support for either the Biased
Engagement or Biased Disengagement accounts of anxiety-linked attentional bias, but
high rates of error, slow response times and high variance in response latencies in the
grammatical judgment component of the task highlight the possibility that participants
may have experienced difficulty performing this grammatical judgment decision. This
may be due to greater post-lexical processing involved in performing this decision, which
would obscure anxiety-linked differences of interest. Experiment 5 therefore aimed to
modify the task used in this study to include a decision that would ensure participants
processed word content, and enable the precise measurement of speed with which
semantic access occurred. The use of lexical decisions was therefore adopted in place of
grammatical judgment in Experiment 5.
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CHAPTER 6
EXPERIMENT 5
The principal purpose of Experiment 5 was identical that of the previous study in
that the aim was to measure anxiety-linked differences in biased attentional engagement
with and disengagement from negative and non-negative word content of single stimuli.
The approach taken in the current experiment was to refine the task employed in the
previous study, to provide a better measure of these attentional processes. As highlighted
in the discussion of Chapter 5, the use of grammatical judgment as a means of assessing
participants‟ speed to access the semantic representation of a word may in fact implicate
variable and time consuming cognitive processes beyond those required to simply access
the semantic meaning of a word. If this is the case then measures of speed to make such
grammatical judgments will not necessarily provide an accurate measure of time taken to
process the semantic content of a stimulus and therefore are unlikely to be sensitive to
anxiety-linked differences in accessing the semantic representation of a word due to the
effects of these post-lexical processes. The grammatical classification component of this
process may therefore obscure anxiety-linked differences in attentional engagement or
disengagement that are present at the point where participants are simply accessing the
meaning of the word. In the present study it was therefore desirable to include a simple
measure of access to semantic meaning that minimises the need for any post-lexical
processing. Such a response would ideally require a participant only to identify the
content of the word by acknowledging that the presented stimulus word has an analogous
stored representation in memory. A lexical decision can only be performed by accessing
the representation of a word, including its associated semantic meaning (James, 1975;
Schvaneveldt et al., 1976). Such a decision also has the benefit of requiring only a simple
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decision with minimal post-lexical processing, in that the task of determining the lexical
status of a real word is complete once the representation of that word has been accessed.
To include a measure of semantic access that would be less affected by post-lexical
processes it was therefore deemed suitable to include a lexical decision response in the
current task in place of the grammatical classification response used previously by
Campbell (2001) and adopted in Experiment 4.
As with the previous study, the methodology employed in the current experiment
acknowledges that it is not possible to measure attentional engagement and
disengagement processes in isolation as attention is always moving from one piece of
information to another. Instead, the current study aims to control the emotionality of the
information that is either being shifted from or towards. The current variant of the
emotional Stroop task manipulates whether participants process the emotional content of
a stimulus as either the first or second decision on the task. By requiring participants to
first process the non-emotional (colour) stimulus information before then processing the
emotional content of negative and non-negative stimuli, the task is able to yield a
measure of the relative speed with which individuals switch attention to process such
differentially valenced information. Conversely, by requiring participants to first process
the semantic content of differentially valenced words before then processing the non-
emotional stimulus information (text colour), the task is able to provide a measure of the
relative difficulty to switch attention away from the emotional content of negative and
non-negative information. The modified emotional Stroop developed in the current study
was therefore similar in format to that used in the previous experiment. The key
modification in the current task was that the means of ensuring that semantic access took
place was achieved by requiring a lexical decision rather than grammatical judgment.
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Each trial again began with an instruction signaling to participants the order in
which they were required to perform the tasks of colour-naming and semantic processing
of word content. The instruction “COLOUR/WORD” therefore signaled that participants
were required to colour-name the presented text before determining the lexical status of
the word or non-word letter string while a “WORD/COLOUR” instruction signaled that
participants were first required to determine the lexical status of a letter string before
colour-naming the text. As in the emotional Stroop task used in Experiment 4, the
information required for the second decision was not added to the stimulus until
participants had made their first decision. Therefore, on trials assessing biased attentional
engagement with emotional content, the information on which participants performed the
lexical decision was not revealed until participants colour-named the text, while on trials
assessing biased attentional disengagement from emotional content, the text colour was
not revealed until participants recorded a lexical decision response to the initially
presented letter string. The purpose of revealing only one stimulus dimension at a time
was to ensure that participants did not have access to the stimulus dimension processed
second, which allowed confidence that the second decision was not contaminated by
premature processing of this information.
If, in accordance with the Biased Attentional Engagement account, attentional
bias in anxiety is characterised by selective attentional engagement with the semantic
content of negative stimuli, then we would predict that effects on the task would be
limited to trials where participants are required to switch attention to process the semantic
meaning of negative and non-negative stimuli having processed the colour information of
these stimuli, whereby high trait anxious individuals will be faster to determine the
lexical status of negative as compared to non-negative words. The Biased Attentional
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Disengagement account however predicts that anxiety-linked differences will only
emerge in the current task on trials where participants switch to process non-emotional
stimulus information having previously determined the semantic content of negative and
non-negative words, whereby high trait anxious individuals will be disproportionately
slow to colour-name the text of negative as compared to non-negative words.
Method
Overview
The principal purpose of the present study was to produce a modified variant of
the decoupled emotional Stroop task used in the previous experiment capable of
measuring biased attentional engagement with, and disengagement from, the semantic
content of negative and non-negative stimuli. The task delivered two different trial types,
one designed to specifically measure the speed with which high and low trait anxious
individuals could engage attention with the semantic content of a negative or non-
negative stimulus (Semantic Engagement Trials) the other designed to measure the speed
with which these individuals could disengage attention from the semantic content of a
negative or non-negative stimulus (Semantic Disengagement Trials).
In Semantic Disengagement Trials the semantic meaning of a letter string was
first revealed before the colour dimension was added to this stimulus. Participants were
therefore required first process the material for semantic content by performing a lexical
decision before disengaging attention from this to colour-name the letter string. On the
trials of interest, this letter string was a negative or non-negative word that was initially
presented in white text. Immediately following the lexical decision response the letter
string acquired the hue of one of four colours and the latency to name this colour was
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recorded. If anxiety is characterised by difficulty disengaging attention from the semantic
content of a negative stimulus then colour-naming responses will be disproportionately
slow for high trait anxious individuals when they are first required to lexically classify a
negative as compared to a non-negative word.
In the Semantic Engagement Trials the colour dimension of the stimulus was first
made available to participants while the semantic content of this stimulus was only
revealed subsequent to participants recording a colour-naming response. Latencies to
identify the lexical status of the semantic content were taken as a measure of the speed to
engage with the semantic meaning. On trials of interest the letter string revealed was
either a negative or non-negative word. If anxiety is associated with biased attentional
engagement with the semantic content of negative stimuli then the lexical decision
response will be disproportionately fast for high trait anxious participants on trials when
the string is a negative word.
Participants
To ensure that participants differed at test time in trait anxiety as required,
participant selection was again guided by the screening of undergraduates on the STAI-T
prior to the commencement of the study. Of the 601 participants screened, those who
obtained scores on the STAI-T which fell in the upper third (at or above 42) or the lower
third (at or below 35) of the distribution were considered eligible for the study. Of those
recruited for the study, 20 were from the upper third of the distribution (high trait anxious
group) and 20 were from the lower third of the distribution (low trait anxious group). The
low trait anxious group comprised eight male and 12 female participants with an average
age of 18.40 years (SD = 1.76) while the high trait anxious group consisted of five male
and 15 female participants with a mean age of 17.70 years (SD = 1.21). The high and low
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trait anxious groups did not differ significantly in terms of age, t(38) = 1.46, ns, or gender
ratio ²(1,38) = 1.21, ns.
Materials
Emotional Assessment Measure
The Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983)
was again employed as the emotional assessment measure.
Stimulus Words
As lexical decisions were required in the current task it was necessary to include
an equal number of non-word lexical decision targets to supplement word stimuli to
ensure participants attempted lexical access for all words. As discussed in Chapter 3, it is
necessary for non-words used in a lexical decision task to be graphemically legitimate to
ensure that participants process stimuli for potential meaning rather than being able to
make a judgment of lexical status based on graphemic legitimacy alone. Lexical stimuli
was therefore identical to those used in Experiments 2 and 3 with the same 48 negative
and 48 non-negative words, along with 96 length-matched, graphemically legitimate non-
words again being employed in the current study. While trials containing non-words were
not informative in assessing biased attentional engagement with, or disengagement from
semantic content, they were a necessary task feature in order to maintain the expectation
that a lexical decision response could be a word or non-word with equal frequency. An
additional stimulus set consisting of 20 non-negative words and 20 graphemically
legitimate non-words was also created for use in practice trials.
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Experimental Hardware
Experimental hardware was identical to that used in Experiment 4, comprising an
Acorn Archimedes 5000 computer, with high resolution monitor and attached
microphone and voice key for detection of colour-naming responses.
Experimental Task
The structure of the current task was similar to that used in Experiment 4 with the
principal difference being that the lexical decision responses replaced the grammatical
classification response. The task again consisted of two distinct trial types. On Semantic
Disengagement Trials the instruction string “WORD/COLOUR” was presented in upper
case letters, 10mm in height, in the centre of the screen signaling to participants that they
were first required to make a lexical decision followed by a colour-naming decision. This
instruction string remained on the screen until participants pressed the spacebar to begin
the trial. A word or non-word in white text was then presented in the same location and
participants were required to indicate its lexical status by pressing the corresponding
“word” or “non-word” mouse key. Response latency and accuracy to make this decision
was recorded. Immediately following the registration of this response the letter string
changed from white to one of four colours (red, blue green or yellow). Participant‟s
latency to name this colour was detected by a voice activated microphone and was
recorded as the interval between the onset of the colour and the detection of the colour-
naming response. This response terminated the trial and the instruction for the next trial
appeared 1000ms later. Figure 6.1a provides a summary of experimental trials assessing
biased attentional disengagement from negative and non-negative words.
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6.1 a) Semantic Disengagement Trials
Instruction Lexical Decision Colour Name
6.1 b) Semantic Engagement Trials
Instruction Colour Name Lexical Decision
Figure 5.1. Semantic Disengagement Trials and Semantic Engagement Trials
with negative and non-negative stimulus words. Colour type shown randomly.
On Semantic Engagement Trials, the initial instruction consisted of the text
“COLOUR/WORD” which informed participants that they would be required to make a
colour-naming decision before a lexical decision. After pressing the spacebar, this
instruction display was terminated and replaced by the stimulus which was presented
devoid of content permitting lexical classification, but containing colour. Immediately
following participants recording a verbal colour-naming response, colour information
Colour Name/
Lexical Decision
Negative Word
COLOUR/WORD
XXXXXXXX
RIDICULE
COLOUR/WORD
XXXXXXXXXX
WATERPROOF
Colour Name/
Lexical Decision
Non-Negative Word
Lexical Decision/
Colour name trial
Negative Word
Lexical Decision/
Colour name trial
Non-Negative Word
WORD/COLOUR
FEAR
FEAR
WORD/COLOUR
SOFTENER
SOFTENER
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remained, however, the letter content was added such that it now spelled a negative word,
a non-negative word, or a graphemically legitimate non-word. Participants were then
required to determine the lexical status of this string by pressing the corresponding
“word” or “non-word” mouse key. Response latency and accuracy to make this decision
was recorded on these trials. Figure 6.1b provides a summary of experimental trials
assessing biased attentional engagement with negative and non-negative words.
The task consisted of 384 trials in total. Each of the 48 negative, 48 non-negative
and 96 non-words was presented once before any were repeated and the order of the type
of trial presented (Semantic Disengagement Trials or Semantic Engagement Trials) was
randomised within each presentation sequence of 192 trials. Each stimulus was presented
twice, once in Semantic Disengagement Trials and once Semantic Engagement Trials.
Those stimuli which appeared in the Semantic Disengagement Trials in the first
presentation sequence appeared in the Semantic Engagement Trials in the second
sequence and vice versa. The allocation of each stimulus to each trial type across the two
presentation repetitions was counterbalanced such that after every two participants had
been tested, each stimulus had appeared in each trial type once within each of the first
and second repetition sequences. Text colour presented on each trial was random within
the constraint that each of the four colours appeared an equal number of times across all
trials. During the task participants were given the opportunity of a brief self-paced rest
period after the completion of 192 trials.
Procedure
Participants were tested individually in a sound attenuated cubicle. Upon arrival
they first completed the Spielberger State-Trait Anxiety Inventory (STAI; Spielberger et
al., 1983) before beginning the experimental task. Prior to commencing the task
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participants were informed that each trial would require two different decisions, each
requiring a different response, and the order in which they would perform these would be
provided at the beginning of each trial. They were instructed that one decision involved
colour-naming, and they should respond verbally, while the other decision involving
determining lexical status of a letter string, and they should respond by pressing one of
two alternately labeled “word” and “non-word” buttons on the computer mouse.
Participants were directed to be as fast as possible without compromising accuracy. Forty
practice trials were then completed before participants began the experimental task.
These trials contained an equal number of Semantic Engagement Trials and Semantic
Disengagement Trials using both non-negative words and graphemically legitimate non-
words not used in the experimental task.
Results
Participant STAI-T scores taken at the time of testing confirmed that the high and
low trait anxious groups continued to differ on measures of trait anxiety when completing
the experiment, t(38) = 7.26, p < .01, with the high trait anxious group displaying a mean
score of 45.80 (SD = 8.60) and the low trait anxious group with a mean of 30.80 (3.38).
A summary of participant characteristics taken at the time of testing are provided in Table
6.1. The high and low trait anxious groups were also observed to differ according to
STAI-S score t(38) = 6.14, p < .01. While unsurprising, this difference also allows for the
possibility that any effects which discriminate high and low trait anxious groups could
also potentially relate to state anxiety. Subsequent correlational analyses are therefore
employed to determine whether observed effects were associated to a greater extent with
measures of either state or trait anxiety.
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Table 6.1
Characteristics of participants in Experiment 5. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F
High Trait Anxious 45.80 (8.60) 40.10 (8.07) 17.70 (1.21) 5:15
Low Trait Anxious 30.80 (3.38) 26.90 (5.32) 18.40 (1.76) 8:12
All Participants 38.30 (9.96) 33.50 (9.47) 18.05 (1.53) 13:27
As high rates of inaccuracy for lexical decision responses could signal that a
participant was not semantically processing letter strings, it was desirable to exclude
participants with high rates of error. Therefore, participant accuracy in performing the
lexical decision component of the task was first examined. Overall accuracy for this
measure was high with participants averaging 96.41% (SD = 3.39). In keeping with the
exclusion criteria applied in previous experiments, it was deemed inappropriate to include
participants who failed to achieve 80% accuracy on this task. No participants in the
current study recorded over 20% incorrect responses however, and therefore none were
excluded from the final analysis. The consistent high accuracy in the current experiment
contrasts sharply with the low rates of accuracy and high number of exclusions for the
emotional Stroop task used in Experiment 4. This contrast would tend to vindicate the use
of lexical decision as a means of ensuring participants process word content over the use
of grammatical judgment. No significant difference between high and low trait anxious
groups were observed in the rates of incorrect lexical decision responses, F(1, 38) = 0.00,
ns.
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Assessment of Biased Attentional Disengagement from Semantic Content
Semantic Disengagement Trials consisted of those where participants were first
required to determine the lexical status of negative or non-negative words before
switching to then colour-name the text of the stimuli. Latencies to colour-name the text
was therefore taken as the dependent measure on these trials whereby longer latencies
would suggest greater difficulty disengaging attention from the semantic content of the
word. As semantic processing of the negative and non-negative words was essential to
the measurement of the relative ease with which participants could subsequently
disengage attention from this stimulus dimension, only trials where participants correctly
identified the word on the first response were included in the analysis. To minimise the
influence of outlying data, median colour-naming response latencies for each condition
were used in analyses. The average of these median colour-naming latencies for negative
and non-negative words across high and low trait anxious groups are provided in Table
6.2.
Table 6.2
Latencies in milliseconds for second trial responses (colour-naming) on Semantic
Disengagement Trials, across negative and non-negative word stimuli for high and low
trait anxiety groups. Standard deviations given in parenthesis.
Word Valence High Trait Group Low Trait Group
Negative Word Trials 546.50 (116.87) 501.50 (135.37)
Non-Negative Word Trials 547.75 (117.03) 497.75 (141.45)
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Data were subjected to a 2 x 2 mixed design ANOVA with word valence
(negative or non-negative) as the within subject factor and trait anxiety group (high or
low) as the between subject factor. According to the Biased Attentional Disengagement
account of anxiety-linked attentional bias, on Semantic Disengagement Trials, high trait
anxious individuals should exhibit disproportionately slow colour-naming responses after
semantically processing negative words on the preceding lexical decision response
compared to low trait anxious individuals, resulting in a two-way interaction between
word valence and trait anxiety group. No significant effects emerged from this analysis.
Of particular note was the absence of a two-way interaction between word valence and
trait anxiety, F(1, 38) = 0.33, ns, which is clearly inconsistent with the prediction that
anxiety-linked attentional bias is associated with biased attentional disengagement from
emotional content.
Although no group differences were observed in biased attentional disengagement
from emotional content it remains possible that associations may exist between measures
of this and state and trait anxiety. Correlational analyses were therefore conducted to
determine if such relationships were present. A single index of impaired attentional
disengagement from negative content was first computed. This was achieved by
subtracting colour-naming response latencies following lexical decision of non-negative
words from colour-naming response latencies following lexical decision of negative
words. This resulted in an index of impaired disengagement where higher scores
represent slowing to disengage attention from negative as compared to non-negative
words. Pearson‟s correlations between this index and STAI-T and STAI-S scores did not
prove to be significant (r(40) = -.14, ns and r(40) = -.20, ns, respectively), providing no
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support for the association between biased attentional disengagement with either state or
trait anxiety.
Assessment of Biased Attentional Engagement with Semantic Content
Semantic Engagement Trials consisted of those on which participants made a
colour-naming decision before determining the lexical status of a negative or non-
negative word. More rapid discrimination of negative over non-negative words would
suggest enhanced attentional engagement with the content of these stimuli. Latencies to
determine the word‟s lexical status was therefore taken as the dependent measure on
these trials. As with trials assessing biased attentional disengagement from word content,
semantic processing of word stimuli was essential in measuring the speed with which
participants processed the content of these words. Therefore, only trials where
participants recorded a correct response to discriminating the lexical decision target were
included in the analysis. Median lexical decision response latencies were used to
minimise the influence of outlying data. The average of these lexical decision response
latencies for negative and non-negative stimuli across high and low trait anxious groups
are provided in Table 6.3.
Table 6.3
Latencies in milliseconds for second trial responses (lexical decision) on Semantic
Engagement Trials, across negative and non-negative word stimuli for high and low trait
anxiety groups. Standard deviations given in parenthesis.
Word Valence High Trait Group Low Trait Group
Negative Word Trials 1313.88 (186.76) 1302.25 (206.23)
Non-Negative Word Trials 1341.62 (187.63) 1291.00 (205.85)
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Data from the Semantic Engagement Trials were subjected to a 2 x 2 repeated
measures ANOVA with one between group factor of trait anxiety (high or low) and one
within group factor of word valence (negative or non-negative). The Biased Attentional
Engagement account of attentional bias in anxiety predicts that on these trials, high trait
anxious individuals will be faster to determine the lexical status of negative words
relative to non-negative words after having processed the text colour of these stimuli,
resulting in a two-way interaction between word valence and trait anxiety group. This
analysis revealed a significant two way interaction between trait anxiety and word
valence, F(1, 38) = 5.64, p < .05. As illustrated in Figure 6.2 the nature of this interaction
is precisely the pattern predicted by the Biased Attentional Engagement account. That is,
following colour-naming, high trait anxious individuals were disproportionately fast, in
relation to low trait anxious participants, to determine the lexical status of negative as
compared to non-negative words. Simple main effects analysis revealed that high trait
anxious individuals were faster to discriminate negative as compared to non-negative
words, F(1, 19) = 5.41, p < .05). Low trait anxious individuals in contrast showed a non-
significant effect in the opposite direction, F(1, 19) = .99, ns.
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1280
1290
1300
1310
1320
1330
1340
1350
Negative Non-Negative
Word Valence
Resp
on
se L
ate
ncy (
ms)
High trait anxious
Low trait anxious
While an anxiety-linked group difference was observed in biased attentional
engagement with semantic content, it is possible that this effect may not be linear in
nature. It was therefore deemed suitable to examine correlational analyses to determine if
any linear component of this effect can be detected and if so, whether this is more a
function of trait or state anxiety. To assess the degree of association between biased
attentional engagement with semantic content and state and trait anxiety, an index of
enhanced attentional engagement with negative stimuli was first computed. This was
achieved by subtracting lexical decision latencies for negative words from lexical
decision latencies for non-negative words on Semantic Engagement Trials. Higher scores
on this index represent speeding to switch attention to process the semantic content of
negative words having previously performed a colour-naming decision. This index was
Figure 6.2. Two-way interaction showing lexical decision response latencies across trait
anxiety groups and word valence for Semantic Engagement Trials.
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observed to be significantly correlated with measures of trait anxiety, r(40) = .27, p < .05,
but not with measures of state anxiety, r(40) = .19, ns. This correlation with STAI-T
scores supports the contention that relative speeding to switch attention to engage with
the emotional dimension of a negative, as compared to non-negative stimulus, is more
associated with vulnerability to anxious mood rather than current anxious state and is
consistent with the Biased Attentional Engagement account of attentional bias.
While the above results provide support for the hypothesis that anxiety is
characterised by biased attentional engagement with the content of negative material, an
alternative possibility could also provide an equally plausible account of these findings.
Rather than the observed interaction being specifically attributable to a bias in orienting
attention from a non-emotional to an emotional dimension of the same stimulus, it is
possible that high trait anxious individuals are simply faster to discriminate the lexical
status of negative over non-negative material. As lexical decision responses were
recorded as the first decision on Semantic Disengagement Trials, the current task permits
the examination of this alternative account. If high trait anxious individuals are simply
faster to process the content of negative over non-negative words then it is expected that
high trait anxious individuals will also demonstrate disproportionately fast lexical
decision response times for negative words when required to discriminate the lexical
status of letter strings as the first trial decision. It is worthy to note that overall lexical
decision response latencies which occurred as the first decision on a trial (M = 770.81,
SD = 150.12) were substantially faster than those lexical decision response latencies
which occurred as the second decision on a trial (M = 1312.19 SD = 193.25), t(38) =
33.37, p < .01. This slowing on the second decision is consistent with what would be
expected if participants were required to disengage attention from the initially attended
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information before discriminating the lexical status of the subsequently attended letter
string6. This pattern alone does not however address the possibility that the interaction
observed for Semantic Engagement Trials is specific to trials where attention is required
to switch from one stimulus dimension to another. To address this, lexical decision
responses on trials where this decision occurred as the first response (Semantic
Disengagement Trials) were subjected to a 2 x 2 ANOVA with one within group factor of
word valence (negative and non-negative) and one between group factor of trait anxiety
(high or low). As with the previous analyses, median lexical decision response latencies
were used and only correct responses were included to ensure that participants had indeed
processed the semantic content of the stimuli. The results of this analysis provided no
support for the possibility that high trait anxious individuals are simply faster to process
the content of negative material with the analysis failing to reveal a significant interaction
between trait anxiety group and word valence, F(1, 38) = .90, ns.
Discussion
The key aim of the current study was to refine the version of the decoupled
emotional Stroop task used in Experiment 4 to provide an improved measure of biased
attentional engagement with and disengagement from semantic content of negative and
non-negative stimuli. The high overall accuracy rate for lexical decision responses allows
confidence that participants who performed the task were semantically processing the
negative and non-negative material when required to do so. The most striking finding of
the current study was the clear support for Biased Attentional Engagement account of
6 Similarly it should be noted that colour naming responses were also slower when they occurred as the
second decision (M = 585.06, SD = 109.47) as compared to the first decision (M = 523.38, SD = 128.04),
t(38) = 4.24, p < .01, as would be expected if the process of colour-naming in influenced by disengaging
from the content of the information processed in the first decision.
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anxiety-linked attentional bias and the absence of support for the Biased Attentional
Disengagement hypothesis.
It was assumed that trials where participants colour-named the text of negative
and non-negative words after having semantically processed their content would provide
an indication of relative difficulty disengaging attention from the semantic content of
differentially valenced stimuli in order to process the non-emotional dimension of the
stimulus. The results revealed no difference between high and low trait anxious
participants in the relative speed to switch attention away from the content of negative as
compared to non-negative words. Nor was there any evidence found of an association
between relative speeding to orient attention away from the semantic content of negative
and non-negative words with measures of either state or trait anxiety. These null effects
stand in stark contrast to the pattern of findings observed for the trials assessing biased
attentional engagement with emotional content. The biased engagement account of
anxiety-linked attentional bias predicted that high trait anxious individuals would be
disproportionately fast to switch attention to discriminate the identity of negative over
non-negative words after initially colour-naming this stimulus. The results obtained on
Semantic Engagement Trials were entirely consistent with these predictions. It was
observed that high trait anxious individuals were significantly faster to switch attention to
successfully access the semantic content of negative as compared to non-negative words,
having initially processing colour information. This difference was not observed for the
low trait anxious group. Correlational analyses also revealed that an index of enhanced
engagement with negative as compared to non-negative semantic content was a
significant predictor of current trait anxiety (STAI-T) but was not significantly associated
with current state anxiety (STAI-S).
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The current results also addressed an alternative possibility which could account
for the observed findings. In order to examine the possibility that this effect may be due
to a more general pattern of speeding to process the semantic content of negative words,
an analysis was conducted on lexical decision response latencies for trials where the
lexical decision occurred as the first, rather than the second response, thus requiring no
attentional shift. The results demonstrated that when participants were required to
semantically process word content as the first response, no anxiety-linked differences
were observed. This provides further support for the specific prediction that it is only
when participants are required to make an attentional shift from one stimulus dimension
to another, that biased attentional engagement will be evident. It should be noted,
however, that while this pattern of effects is consistent with predictions of the differential
engagement account of attentional bias, the overall three-way interaction involving
lexical decision time (first or second decision), word valence (negative or non-negative)
and trait anxiety group (high or low) did not prove to be significant, F(1, 38) = 0.13, ns.
The present experimental findings also provide converging support for the pattern
of findings observed across Experiments 2 and 3. In Experiment 3 it was demonstrated
that on trials where participants were first required to process a probe before making a
lexical decision on a negative or non-negative word appearing subsequently in the same
spatial position, high trait anxious individuals were faster to identify negative as
compared to non-negative words. Additionally, this pattern of speeding to determine the
lexical status of negative compared to non-negative words was absent in Experiment 2
when participant‟s first response on each trial was a lexical decision. This pattern of
effects is consistent with the observations in the current study which demonstrated that
high trait anxious individuals are only faster to semantically process the content of
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negative material when orienting attention from a non-emotional dimension of a stimulus
to an emotional dimension of a stimulus occupying that same location. Furthermore, as
with the current study, Experiment 2 also failed to find evidence for biased attentional
disengagement when orienting attention away from an emotional dimension of a stimulus
to a non-emotional dimension of a stimulus presented in the same locus. This was
demonstrated in Experiment 2 by the absence of anxiety-linked differences in probe
detection latencies on trials where participants first processed the semantic content of
negative and non-negative words, before then orienting attention to process the non-
emotional information that appeared in this same spatial locus. The current results are
therefore consistent with the effects observed across Experiments 2 and 3, and together
provide support for the hypothesis that attentional bias in anxiety is characterised by
enhanced attentional engagement with the emotional dimension of negative stimuli, while
providing no support for the biased attentional disengagement hypothesis.
The results obtained using the present emotional Stroop task variant shed light
upon the attentional mechanism likely to underpin the anxiety-linked bias evident in the
traditional emotional Stroop task. The separating of emotional (semantic) and non-
emotional (text colour) dimensions of the stimuli allowed the current task to reveal
anxiety-linked differences when participants shifted between these two dimensions of the
stimulus. The most direct implication of this pattern of effects for the emotional Stroop is
that the consistently observed slowing of high trait anxious individuals to colour-name
negative as compared to non-negative words is likely to reflect their enhanced attentional
engagement with the semantic meaning of negative material, which interferes with the
task of colour-naming the stimulus text. This stands in contrast to the alternative
explanation of the traditional emotional Stroop effect, that high trait anxious individual‟s
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slower colour-naming latencies on negative words reflect their greater difficulty
switching attention to the non-emotional dimension of the word‟s text colour, whenever
the content has initially been attended to.
The results of the present experiment clearly demonstrated that, while high trait
anxious individuals show disproportionate speeding to determine the lexical status of
negative words when orienting attention from an alternative stimulus dimension, when a
lexical decision is made as a first response, no anxiety-linked differences in response
latency are observed. While this result is consistent with the Biased Attentional
Engagement account of attentional bias, it could also be considered somewhat
counterintuitive. That is, it would tend to pose the question as to why high trait anxious
individuals do not always show more rapid processing of negative stimuli, regardless of
whether they are orienting attention from an alternative stimulus dimension. A potential
answer to this can be found in research examining how the allocation of processing
priorities among competing alternatives affects attentional bias in anxiety. In a modified
lexical decision task, MacLeod and Mathews (1991) presented letter strings to individuals
who differed in vulnerability to anxious mood. Their findings indicated that when a
single letter string was presented, no anxiety-linked differences in processing negative
and non-negative material emerged. However, the study demonstrated that high trait
anxious individuals did evidence selective processing of negative material under
conditions where competing negative and non-negative information was introduced at the
same time. These results were taken to suggest that the facilitated processing of negative
words in anxiety reflects the allocation of processing priorities when competing
alternatives are present, rather than a more general tendency to selectively process the
semantic meaning of negative information. These results could be considered consistent
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with the results of the present study. As with MacLeod and Mathews (1991), the present
study found no evidence of selective processing of negative material for high trait
anxious individuals when negative material was presented initially in the absence of other
stimulus information (i.e. without competing stimulus dimensions). The implications of
this previous study for the current experiment would suggest that, it is the introduction of
competing stimulus information (i.e. both semantic content and colour information
present simultaneously) at the point where participants have made the first task decision
that results in the selective allocation of processing priorities between these competing
alternatives. The present study acts to further clarify these past findings to highlight that
it is not simply the introduction of competing alternatives which is sufficient to elicit
selective processing of negative material. Rather, by controlling the order in which this
information becomes available in the current study, it was possible to demonstrate that an
anxiety-linked attentional bias favoring the processing of negative content is only evident
when moving attention from non-emotional information to emotional information and not
when moving attention from emotional information to non-emotional information.
Therefore while it appears that the introduction of competing information is necessary to
elicit anxiety-linked selective processing of negative content, the current research
suggests that this will only occur when orienting attention toward emotional content
(engaging attention) and not when orienting attentional away from such material
(disengaging attention).
The fact that the results of the present study failed to demonstrate evidence for an
anxiety-linked bias in attentional disengagement from the semantic content of negative
and non-negative words is inconsistent with the predictions of this hypothesis. Indeed, the
results of all studies conducted in the current research program have not produced
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evidence of a bias in attentional disengagement. The relative absence of evidence for
anxiety-linked impaired disengagement, along with the pattern of results observed in the
present study suggesting the operation of biased attentional engagement, could be
considered to implicate the role of enhanced attentional engagement with the content of
negative material over impaired attentional disengagement from this negative
information.
One aspect of the task used in the present study however, would suggest the
possibility that the means of assessing attentional disengagement may not have been
adequately sensitive to measure individual differences in this attentional process. The
recording of lexical decision accuracy and response latency allowed confidence that on
Semantic Engagement Trials, participants did indeed engage with the semantic content of
the stimuli after they recorded their initial colour-naming response. Thus the speed to
orient attention from processing colour information to instead semantically process the
word was reliably indexed by the final lexical decision latency, providing a measure of
participant‟s ability to engage with the content of such words when required to do so.
With the trials assessing biased attentional disengagement from negative and non-
negative semantic content, it was similarly believed that having participants colour-name
text after processing the semantic meaning of a stimulus would provide a measure of the
relative difficulty disengaging attention from the word‟s semantic meaning to process its
colour. It is entirely plausible, however, that a participant may be able to colour-name a
stimulus while still processing its meaning. That is, naming the text colour of a word does
not necessarily occur at the exclusion of maintaining the representation of its semantic
meaning in current cognitive operations. This therefore highlights a possible
incongruence between trials assessing biased attentional engagement; where correct
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performance of the lexical decision provides confidence that participants have indeed
engaged with the content of this stimuli, and trials assessing biased attentional
disengagement; where correct performance of the colour-naming decision does not
necessarily confirm attentional disengagement from the content of the previously
processed word.
The possibility that participants continue to processing stimulus content while
performing an alternate response is an issue relevant to all prior studies examining biased
attentional disengagement from differentially valenced stimuli including those in the
current research program. The results of both Experiments 1 and 2 revealed no evidence
for anxiety-linked differences in the selective disengagement of attention from negative
and non-negative words. The possibility remains however, that participants were able to
orient attention to a spatially removed locus while still processing the content of the
initially attended stimulus. If such ongoing semantic activation of negative material was
occurring for high trait anxious individuals, this would suggest that these individuals
have greater difficulty disengaging from the emotional content of negative stimuli.
The issue of whether biased attentional disengagement is characterised by
ongoing activation of negative stimuli in current cognitive operations also relates more
generally to research on working memory. Recent research has suggested that the ability
to maintain information in current cognitive operations is associated with individual
differences in self-regulatory behaviour such as consumption of tempting food
(Hofmann, Gschwendner, Friese, Wiers, & Schmitt, 2008) and drug use (Grenard, et al.,
2008; Thush et al., 2008). It is entirely possible therefore, that individual differences in
the way negative and non-negative information is maintained in current cognitive
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operations could hold implications for the way in which people differ in their emotional
reactions to such stimuli.
The structure of the current and previous tasks has not provided a means of
assessing whether anxiety is characterised by the ongoing semantic activation of
negatively valenced stimuli. To address the possibility that such a manifestation of biased
attentional disengagement may operate in those more prone to anxious mood, two related
task modifications could be pursued. The first of these would involve changing the nature
of the second decision on a trial such that it becomes less plausible that the continued
processing of the initial stimulus could be sustained while making the second decision.
Selective difficulty disengaging from negatively valenced stimuli would therefore be
demonstrated by a slower response to perform the second trial decision which would
recruit the same decision making processes used in the first. Another approach, not
inconsistent with that mentioned above, would be to take a measure of the degree to
which a word‟s semantic representation remains active after having performed the second
trial decision. By examining the decline in stimulus activation when required to perform a
subsequent decision, it would become possible to infer the degree to which participants
have disengaged from its content. In the final experiment of this thesis, both of the
methodological approaches outlined above will be adopted to yield a task variant which;
a) reduces the probability of ongoing semantic activation of the stimulus representation
on the second trial decision and, b) reveals whether the decline in activation of negative
and non-negative stimulus representations occurs differentially for high and low trait
anxious individuals.
In summarising the key finding of the present study, a refined task variant of the
emotional Stroop task used in Experiment 4 was employed to assess whether elevated
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trait anxiety is characterised by biased attentional engagement with the semantic content
of negative words or biased attentional disengagement from the semantic content of
negative words. The results support the former position with high trait anxious
individuals showing speeded engagement with the semantic content of negative words
after processing the non-emotional information of the stimulus. The results provided no
support for presence of an anxiety-linked bias in attentional disengagement from the
semantic content of differentially valenced stimuli. The possibility that measures of
biased attentional disengagement used in the current and previous studies may not be
sensitive to the ongoing semantic activation of a stimulus representation was discussed. It
was therefore the aim of the final study to examine the possibility that high and low trait
anxious individuals differ in the degree to which the semantic representation of negative
and non-negative stimuli remain active in current cognitive processes.
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CHAPTER 7
EXPERIMENT 6
None of the experiments conducted as part of the current research program have
found support for the hypothesis that individuals vulnerable to anxious mood have
selective difficulty disengaging attention from the emotional content of negatively
valenced material. However, as highlighted in the discussion of Experiment 5, none of
the tasks employed to date have been sensitive to the possibility that anxious individuals
may continue to process the content of more negative material while making a
subsequent, unrelated decision about another stimulus or different stimulus dimension.
The key aim of this final experiment was to specifically examine this possibility by
including a task modification which will increase the likelihood that participants will
disengage from the semantic content of the initially attended stimulus and also include a
measure of representational activation of stimulus content to assess whether this has
occurred.
In assessing biased attentional disengagement the tasks employed in the current
research program (with the exception of Experiment 1) have included the requirement
that participants initially process the semantic content of negative or non-negative
information before assessing the relative ease with which they can then switch to perform
a second, unrelated decision, such as identifying the structure of a probe or colour-
naming stimulus text. It has been assumed that bias reflecting impaired attentional
disengagement from negative information would be revealed by slowing to perform this
second decision after having first processed the semantic content of a negative rather than
a non-negative word, with such longer latencies on this second decision reflecting
difficulty disengaging from the content of the initially processed word. However, because
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the second task decisions have consistently involved processing, and responding to,
structural rather than semantic information, it is possible ongoing semantic activation of
the original stimulus content may continue with minimal disruption. That is, making a
decision regarding stimulus form or colour need not preclude the ongoing processing of
the previously encoded semantic meaning. If this is the case, then the latency to make this
second decision would not represent an index of the speed with which disengagement
from processing this meaning occurs.
The possibility that minimal disruption to the ongoing processing of
verbal/semantic information may be produced by the processing of visual-spatial
information is consistent with Baddeley‟s (1992; 2001) model of working memory. This
model proposes that there are separate cognitive subsystems devoted to maintaining
visual-spatial information and verbal information within current cognitive operations.
Research has provided support for the existence of these separate subsystems, and
yielded evidence that when a secondary or distracter task differs in the processing
demands from a primary task (i.e. visual-spatial primary task with verbal secondary task
or vice versa) no major reduction in task performance is observed (Robbins et al., 1996).
In contrast, it has also been observed that performance on visual-spatial tasks is disrupted
when new visual-spatial information must be processed during the task completion
(Logie, 1986; Quinn & McConnell, 1996). Similarly, and most importantly for current
considerations, performance on tasks involving the processing of verbal information is
adversely affected when new verbal information is included in the task (Salame &
Baddeley, 1982).
The implication of Baddley‟s (1992; 2001) model of working memory is that the
continued processing of negative or non-negative verbal information could be maintained
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while subsequently processing the structure of a visual probe or the colour of text. In
order to maximise the likelihood of disengagement from processing verbal information
presented in the first decision, the second task decision should require the processing of
different verbal information. A simple modification to previous tasks which could be
implemented to assess biased attentional disengagement would involve having
participants first make a lexical decision on a negative or non-negative word, as before,
but then go on to make another new semantic decision on a second stimulus string. By
requiring participants to again process the second stimulus for semantic meaning the
same cognitive subsystem would be recruited and so disengagement from the previous
semantic processing would be required. A measure of biased disengagement from the
processing of differential emotional content would therefore be obtained when
participants first determine the lexical status of a negative or non-negative word and are
subsequently required to determine the lexical status of a non-word. Longer latencies to
determine the lexical status of this subsequently presented non-word would indicate
greater difficulty disengaging from the content of the initially processed stimulus word.
While this approach seems likely to discourage continued processing of initial
word content in ways that make the second decision latency a better index of
disengagement from such processing, it remains possible that participants may sometimes
continue to process the initially presented stimulus information to some degree across the
entire trial. Therefore, an additional aim of the present experiment was to include a
measure of ongoing activation of this initial stimulus representation to assess the degree
to which participants continued to process the initial stimulus word after performing the
second task decision. If the second task decision is successful in limiting ongoing
processing of initial negative and non-negative word content then we would expect little
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evidence for anxiety-linked differences in the continued processing of negative over non-
negative words. If however, anxiety-linked attentional bias results in impaired
disengagement from negative stimuli in spite of this second trial decision, then any
ongoing processing of initially presented negative words is likely to be greater for high as
compared to low trait anxious individuals. By including a measure of ongoing semantic
activation the current task would therefore have the capacity to reveal if high trait anxious
individuals do experience greater ongoing activation of initially processed negative words
as compared to low trait anxious individuals.
The well established „repetition priming effect‟ would seem to offer an
appropriate measure of ongoing activation of initially processed stimulus words. It has
been consistently demonstrated that the presentation of a word facilitates its later
identification in word-naming tasks (Fowler, Napps, & Feldman, 1985; Scarborough,
Cortese, & Scarborough, 1977). This priming effect is thought to result from the
continued activation of this word‟s representation in long-term memory. Following its
initial activation, Besner and Swan (1982) theorise that the cognitive representation of a
word returns to baseline activation slowly, meaning that it remains partially active for
some time following recognition. They suggest that when a word is presented subsequent
to its first exposure, the duration required for its representation to meet the critical level
of activation for it to be recognised, and hence available as a word-naming response, will
be less due to its ongoing partial activation from having been previously identified.
Latencies to name previously presented words, or „repetition priming‟, therefore provides
a measure of the degree to which a word‟s semantic representation remains active in
current cognitive operations (Feldman & Moskovljevic, 1987).
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Correctly discriminating the lexical status of an initially presented word requires
its representation to become active. Presumably the continued processing of this word
will sustain this activation whereas disengagement from such processing will permit this
activation to subside. If anxiety-linked attentional bias is characterised by impaired
disengagement from the processing of negative words, then it follows that individuals
more vulnerable to anxious mood will demonstrate slower decline in the activation of
initially processed negative as compared to non-negative words. By including at the end
of each trial a priming measure capable of revealing the level of sustained activation of
the initial word representation, it should be possible to reveal anxiety-linked differences
in disengagement from processing these initially presented negative and non-negative
words. Hence, each trial on the current task included such a repetition priming
component. This involved participants naming aloud a final word, presented immediately
after the second lexical decision. This final word was „primed‟ if it had appeared as either
the first or second lexical decision target earlier in the trial and „unprimed‟ if it had not.
The relative speeding to name primed as compared to unprimed words provided a
measure of the ongoing semantic activation of these previously presented negative and
non-negative words. Thus, primed words should be named faster than unprimed words.
The Biased Attentional Disengagement account of attentional bias suggests that high trait
anxious individuals will demonstrate less disengagement from processing negative words
than non-negative words when performing the second task decision. If so, then after
activating the representation of a stimulus word on the first lexical decision, high trait
anxious individuals should evidence less decline in subsequent activation of the word‟s
representation following the second trial decision, when these words are negative rather
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than non-negative. This will be evidenced by disproportionately large priming effects for
initially processed negative words for high as compared to low trait anxious individuals.
The current study aimed to examine the possibility that previous tasks assessing
biased attentional disengagement have not found evidence for such a bias because it is
characterised by high trait anxious individuals continuing to process negative material
while performing subsequent, unrelated task decisions. Two key task features were
included to address this possibility. The first involved the inclusion of a second trial
decision that recruited the same decision-making processes as the first. This was intended
to increase the likelihood that participants would have to disengage from processing the
content of the initially attended stimulus to performing the second task decision. Biased
attentional disengagement from the content of the initially processed word would be
revealed in longer latencies to identify the lexical status of the non-word target on the
second trial decision. The Biased Attentional Disengagement account of attentional bias
predicts that high trait anxious individuals should be slower to determine the lexical
status of non-words after having processed negative as compared to non-negative words
on the first task decision. The second inclusion in the current task was designed to
measure differences in ongoing activation of initially processed words using a repetition
priming task. If the inclusion of a lexical decision on the second trial decision is
successful in ensuring that participants equivalently disengage from the content of the
initial negative or non-negative word then we would expect no anxiety-linked differences
in ongoing activation of negative and non-negative words. If the second lexical decision
is not able to prevent ongoing processing of word content then priming measures will
reveal whether anxiety linked differences are present in the continued processing of
negative and non-negative words. If, as predicted by the Biased Attentional
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Disengagement account of attentional bias, high trait anxious individuals do maintain the
representation of negative words in current cognitive operations longer than low trait
anxious individuals, then these individuals will show greater priming for negative as
compared to non-negative words at the end of the trial, after having identified these on
the lexical decision at the beginning of the trial.
Method
Overview
The purpose of the current experiment was to assess anxiety-linked differences in
biased attentional disengagement from the content of negative and non-negative words
and, to measure differences in the degree of ongoing activation of such stimulus words
for high and low trait anxious individuals. These objectives were achieved by including
measures of attentional disengagement from word content and ongoing semantic
activation of a stimulus word within a single trial. On each trial a single letter string
consisting of a negative word, non-negative word or a non-word was initially presented,
and participants were required to make a lexical decision on this string. Following this
decision a second letter string was presented in the same spatial locus, again consisting of
either a negative word, non-negative word or a non-word, and participants performed a
second lexical decision. Critical trials measuring biased attentional disengagement from
word content were those where participants first performed a lexical decision on a
negative or non-negative word before then making a lexical decision of a non-word.
Latencies to correctly make this second decision, classifying the second string as a non-
word, were taken as an indication of relative difficulty disengaging from the processing
of the initially attended negative or non-negative word.
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Immediately following the second lexical decision a word-naming response was
required to a final word appearing in the locus vacated by the second lexical decision
string. Participants were instructed to verbally name the word as quickly as possible. On
half the trials a new word, not previously presented on that trial as a lexical decision
target, was shown for this word-naming (unprimed words) while on the remaining trials
the word was identical to a negative or non-negative lexical decision target word that had
been presented on that same trial (primed words). It was expected that latencies would be
shorter to name primed versus unprimed words, and the magnitude of this priming effect
provided a measure of the ongoing processing of negative and non-negative words
previously presented as the as the first lexical decision target.
Participants
Selection of high and low trait anxious participants was again guided by screening
of undergraduates on the trait version of the Spielberger State-Trait Anxiety Inventory
(STAI-T; Spielberger et al., 1983) to ensure participants differed in trait anxiety as
required. Five hundred and sixty seven undergraduates were screened on this measure
and those who obtained scores on the STAI-T which fell in the upper third (at or above
46) or the lower third (at or below 37) of the distribution were considered eligible to
participate. Of those who participated in the study, 24 fell in the upper third of the
distribution (high trait anxious group) and 24 fell in the lower third of the distribution
(low trait anxious group). The high trait anxious group consisted of 6 males and 18
females while the low trait anxious group comprised 7 males and 17 females. Chi-square
analyses revealed that these groups did not differ significantly in terms of gender ratio,
²(1,46) = 0.11, ns. Similarly, high and low trait anxious groups did not differ
significantly in terms of age, t(46) = 0.13, ns.
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Materials
Emotional Assessment Measure
As in previous studies, the Spielberger State Trait Anxiety Inventory (STAI;
Spielberger et al., 1983) was again employed as the emotional assessment measure.
Word Stimuli
The same 48 negative, 48 non-negative and 96 length matched non-words as used
in Experiment 5 were used in the current experiment. These stimuli were divided into two
subsets for use in the task, subset A and subset B, each consisting of 24 negative and 24
non-negative words along with their length-matched non-words. An additional stimulus
set consisting of 48 non-negative words and 48 graphemically legitimate non-words was
also created for use in practice trials.
Experimental Hardware
An Acorn Archimedes 5000 computer was used to deliver the experimental task
and record participant responses. A microphone and voice key was also attached for
detecting word-naming responses.
Experimental Task
Each trial began with a row of white crosses presented for 500ms in the centre of
the screen. A single letter string then replaced this, presented in block letters 10mm in
height. This was either a negative word, a non-negative word or a non-word. Participants
were required to determine the lexical status of this string by pressing one of two keys,
with response latency and accuracy being recorded. Once this response was detected a
second letter string immediately replaced the first, appearing in the same location, with
the same size font and also in white text. This letter string was either another negative or
non-negative word or a non-word and participants were again required to determine its
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lexical status in the same manner as the first string. Immediately following this response,
a word in yellow text was presented in the same location. Participants were required to
verbally name this word aloud. Latency to make this response was recorded via a
microphone. Detection of the participant‟s utterance signaled the end of the trial and the
next trial began 1000ms later.
Thus, from participants perspective, there was an equal probability that either of
the first two stimuli would be a word or a non-word, an equal probability that any word
would be negative or non-negative, and an equal probability that the final yellow word
would repeat any previous word presented on a given trial or not. However, the critical
trials for assessing biased attentional disengagement from emotional content were only
those where the first lexical decision target was a negative or non-negative word, the
second lexical decision target was a non-word, with the final word being either primed or
unprimed. The latency of the second decision on these trials to correctly discriminate the
non-word was taken as a measure of the relative difficulty disengaging from the content
of the initially presented word. The relative latency to name the final primed versus
unprimed word in yellow, provided a measure of ongoing activation of the initially
presented word. Shorter latencies to name primed words would signal greater ongoing
activation of that stimulus word in current cognitive operations.
The entire task consisted of 192 trials, of which 48 were critical trials where
participants first determined the lexical status of a negative or non-negative word before
then identifying a non-word lexical target. The remaining filler trials were a necessity to
maintain the expectation that each lexical decision target could be either a word or non-
word with equal frequency. Therefore, of these filler trials, 48 were delivered in which
the first lexical decision target was a word and the second was a non-word, 48 in which
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both the first and second lexical decision targets were words, and 48 in which both the
first and second lexical decision targets were non-words. Each of the critical and filler
trial types occurred 12 times during the task. For the 48 critical trials there were 4 unique
conditions given by the combination of the two, two level task factors of stimulus valence
(negative or non-negative word), and prime condition (final word primed or unprimed).
Figure 7.1 provides a summary of these critical trials.
Lexical Decision 1 Lexical Decision 2 Word Naming Response
Figure 7.1. Critical trials for Experiment 6 where negative and non-negative words are
presented as the first lexical decision target, and named words are either primed or unprimed.
Allocation of stimuli was such that, for each participant, either stimulus subset A
or subset B was allocated to those trials where one lexical decision was performed on a
Lexical Decision 1: Negative word
Lexical Decision 2: Non-Word
Word Naming Response: Primed
FEAR
ERAF
FEAR
SOFTENER
ROSFNETE
SOFTENER
Lexical Decision 1: Non-Negative word
Lexical Decision 2: Non-Word
Word Naming Response: Primed
SOFTENER
ROSFNETE
QUANTITY
Lexical Decision 1: Non-Negative word
Lexical Decision 2: Non-Word
Word Naming Response: Unprimed
Lexical Decision 1: Negative word
Lexical Decision 2: Non-Word
Word Naming Response: Unprimed
FEAR
ERAF
NOTE
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word and one lexical decision was performed on a non-word (i.e. word – non-word or
non-word – word trials). The remaining stimulus subset was allocated to trials where both
lexical decisions were performed on a word (word – word trials), or both lexical
decisions were performed on a non-word (non-word – non-word trials). Within trials
where one lexical decision was performed on a word and the other performed on a non-
word, half of the stimulus subset was assigned to trials where the word appeared as the
first lexical decision target while the remainder were assigned to trials where the word
appeared as the second lexical decision target. The allocation of stimuli for the verbal
naming task was such that, in trials where the word was primed, the named word was
identical to the word that had appeared earlier in the trial. When the named word was
unprimed, a valenced-matched word belonging to the stimulus subset assigned to trials
where both lexical decisions were performed on a word (word – word trials) was used.
Stimulus allocations were counterbalanced such that after eight people had been tested,
each stimulus had appeared once in each of the unique conditions possible for that
stimulus type.
Procedure
As with prior studies, all participants completed the experimental task
individually in a sound attenuated room. Both state and trait versions of the Spielberger
State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) questionnaire were first
completed before participants began the computer task. Participants were informed that
the task would require them to perform three responses on each trial, a lexical decision
followed by another lexical decision followed by a verbal word-naming response. They
were instructed to indicate the lexical status of the first and second letter strings by
pressing one of two keys alternately labeled “word” or “non-word” as quickly as possible
174
without sacrificing accuracy. Participants were told that following the second lexical
decision response, a word in yellow would appear and they should verbally name this
word aloud as rapidly as possible. Participants then completed 48 practice trials using the
stimuli created for this purpose to ensure they were familiar with the task before
beginning the experiment. These practice trials were balanced in a similar manner as
experimental trials such that there was an equal probability that the first or second lexical
decision would be a word or non-word, and an equal probability that the final named
word was primed or unprimed.
Results
A summary of participant characteristics taken at the time of testing is provided in
Table 7.1. STAI-T scores taken at the time of testing revealed the high trait anxious
group demonstrated a mean score of 51.58 (SD = 6.49) on this measure while the low
trait anxious group had a mean of 32.75 (SD = 5.50). The difference between these two
groups on this measure of trait anxiety was significant as required, t(46) = 10.84, p < .01.
As with all previous studies, the two groups also differed in terms of STAI-S score, t(46)
= 3.67, p < .01. Correlational analyses will therefore be needed to determine if any
observed group differences in task performance are more strongly associated with state or
trait anxiety.
High rates of error in performing lexical decisions would preclude confidence that
a participant was performing the task according to instructions. Accuracy in performing
both the first and second lexical decision responses was therefore examined first. Lexical
decision accuracy was high, with participants averaging 93.86% correct responses (SD =
4.58). As with all prior studies, a minimum of 80% accuracy was deemed a requirement
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for inclusion in the final analysis, and so as before, any participant recording over 20%
incorrect responses were therefore excluded from further analysis. This resulted in one
participant being excluded, from the high trait anxious group. No significant difference
between high and low trait anxious groups were observed in the rates of incorrect lexical
decision responses, F(1, 37) = 0.71, ns. Median latencies were again used as the response
time measure for lexical decisions and for word naming, to minimise the influence of
outlying data. Lexical decision and word-naming data examining biased attentional
disengagement from emotional content are reported in turn below.
Table 7.1
Characteristics of participants in Experiment 6. Standard deviations given in parentheses.
Group STAI-T (Trait) STAI-S (State) Age (years) Gender Ratio M:F
High Trait Anxious 51.58 (6.49) 41.70 (7.94) 20.91 (7.92) 6:18
Low Trait Anxious 32.75 (5.50) 33.04 (8.42) 20.67 (5.40) 7:17
All Participants 42.17 (11.22) 37.37 (9.20) 20.79 (6.71) 13:35
Analysis of Lexical Decision Latency Data
Critical trials assessing biased attentional disengagement from emotional content
were those where participants were first required to determine the lexical status of
negative and non-negative stimulus words before then determining the lexical status of a
subsequently presented non-word. Latencies to correctly classify non-words as the
second decision on these trials were taken as the dependent measure with longer latencies
suggesting greater difficulty disengaging attention from the content of the first lexical
decision target. Only trials where the first and second lexical decisions were preformed
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correctly were included in the analysis. The average of these latencies across trials where
the first lexical decision had been a negative or non-negative word, for high and low trait
anxious individuals, is given in Table 7.2.
A 2 x 2 ANOVA was performed on this data with word valence (negative or non-
negative) as the within subject factor and trait anxiety group (high or low) as the between
subject factor. If high trait anxiety is characterised by biased attentional disengagement
from the content of the initially presented negative material, then we would predict that
high as compared to low trait anxious individuals will be disproportionately slow to
determine the lexical status of the subsequent non-word after having first processed the
content of negative as compared to non-negative words on the preceding lexical decision.
This would result in a two-way interaction between valence of the lexical decision target
word and trait anxiety group. The two-way interaction between trait anxiety group and
word valence did not approach significance, F(1, 45) = 0.96, ns, contradicting the pattern
of effects predicted by the biased disengagement account. No other significant effects
emerged from this analysis.
Table 7.2
Latencies in milliseconds for the second (non-word) lexical decision on trials where
negative and non-negative word stimuli was presented as the first lexical decision target
for high and low trait anxiety groups. Standard deviations given in parenthesis.
Word Valence High Trait Group Low Trait Group
Negative Words as First Lexical Decision 745.43 (220.34) 729.17 (224.71)
Non-Negative Words as First Lexical Decision 711.30 (160.15) 721.67 (172.14)
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While no group differences were observed to suggest differential biased
attentional disengagement from negative information across trait anxiety groups, the
possibility remains that a measure of such bias may co-vary with state or trait anxiety. To
address this possibility correlational analyses were conducted. It was first necessary to
calculate an index of the effect that would represent biased attentional disengagement
from emotional content. This was computed by subtracting second word lexical decision
latencies for non-words on trials where the first lexical decision target had been a non-
negative word from second word lexical decision latencies for non-words on trials where
the first lexical decision target had been a negative word. The result was an index of
impaired attentional disengagement from emotional content, where higher scores
represent disproportionate slowing to identify non-word targets after having processed
negative as compared to non-negative stimuli. Pearson‟s correlations between this index
and STAI-T and STAI-S scores did not approach significance (r(47) = .08, ns and r(40) =
-.15, ns, respectively). The absence of significant correlations between these measures
provides no support for the existence of associations between biased attentional
disengagement from emotional content and either state or trait anxiety.
Analysis of Word-Naming Latency Data
The inclusion of word naming responses in the current task was intended to
provide a measure of ongoing activation of initially processed word content by assessing
the relative priming for negative and non-negative stimuli after participants had
performed the second (non-word) lexical decision. The absence of the effect on lexical
decision data that would be indicative of anxiety-linked biased attentional disengagement
suggests one of two possibilities for the word-naming latency data. If the absence of such
effects was due to the current task‟s inability to ensure that participants disengaged from
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the content of the initially processed word, then it is possible that anxiety-linked
differences in ongoing activation of negative and non-negative words will emerge in
word-naming latency data. However, if the task was successful in ensuring that
participants disengage from word content and high and low trait anxious participants did
not differ in the degree to which they could disengage from such stimuli, no anxiety-
linked differences in ongoing activation of negative and non-negative words would be
expected to emerge from word-naming latency data.
In order to assess whether any such differences in ongoing activation of
differentially valenced stimulus content was present, word-naming latency data were
examined. These data were the latencies to name the word presented last on each trial
across conditions where the word had appeared earlier in the same trial as a lexical
decision target (primed words) and trials where the word had not previously been
presented as a lexical decision target (unprimed words). As with prior analyses, median
naming latencies were used to minimise the influence of outlying data and only trials
where both prior lexical decision responses were correct were included. The average of
these naming latencies across the task conditions of stimulus valence (negative and non-
negative), and prime condition (primed or unprimed) for high and low trait anxious
individuals is provided in Table 7.3.
These data were subjected to a mixed design 2 x 2 x 2 ANOVA with two within
subject factors of stimulus valence (negative and non-negative) and prime condition
(primed or unprimed) and the between subject factor of trait anxiety group (high and low
trait anxious). The Biased Attentional Disengagement account of attentional bias predicts
that individuals more vulnerable to anxious mood will continue to process the content of
negative as compared to non-negative stimuli and that differences in such ongoing
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processing will be demonstrated by greater priming effects for negative words as
compared to non-negative words for high trait anxious participants.
Table 7.3
Word-naming latencies in milliseconds for trials where negative and non-negative
stimulus words are presented as the first lexical decision target, and named words are
either primed or unprimed for high and low trait anxiety groups. Standard deviations
given in parenthesis.
Word Valence Prime Condition High Trait Group Low Trait Group
Negative Primed 590.65 (99.68) 537.50 (81.52)
Unprimed 610.87 (112.50) 569.37 (115.22)
Non-negative Primed 581.30 (109.84) 538.12 (80.43)
Unprimed 631.09 (97.72) 572.71 (113.32)
The analysis revealed a main effect of prime condition, revealing the fact that all
participants were faster to name primed words (M = 561.90, SD = 12.92) as compared to
unprimed words (M = 596.01, SD = 15.76), F (1, 45) = 19.98, p < .01. This demonstrated
that when named words were identical to the first lexical decision target there was indeed
a priming effect for these stimuli. This suggests that participants were continuing to
process the content of these initially presented words to some degree. This was the only
significant effect to emerge from this analysis however. Of particular note was the
absence of a significant three-way interaction between stimulus valence, prime condition
and trait anxiety group predicted by the Biased Attentional Disengagement account of
attentional bias, F (1, 45) = 1.51, ns. Thus, word-naming latency data provided no
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support for the existence of an anxiety-linked difference in priming for negative and non-
negative stimulus words.
As with the lexical decision data, correlation analyses also were conducted with
word-naming data, to assess whether an index reflecting increased ongoing activation of
negative word representations were associated with measures of state or trait anxiety. To
compute this index, priming effects for both negative word trials and non-negative word
trials were first calculated for critical trials where these words appeared as the first lexical
decision target. These two measures were calculated in the same manner with trials where
the named word was primed being taken from trials where the named word was
unprimed. This resulted in two measures of priming, one for negative word trials and one
for non-negative word trials where higher scores represented shorter latencies to name
primed negative or non-negative words as compared to unprimed negative or non-
negative words. The measure of priming for non-negative word trials were then taken
from the measure of priming for the negative word trials to produce one overall index of
ongoing activation of stimulus content whereby higher scores represent greater ongoing
activation of negative as compared to non-negative words. If anxiety-linked attentional
bias is associated with a disengage bias characterised by ongoing semantic activation of
emotionally negative stimuli, then we would predict a positive correlation between this
index and measures of anxiety vulnerability. However, correlations conducted with this
index of ongoing semantic activation of negative content did not reveal any significant
association with either STAI-T, r(47) = -.21, ns, or STAI-S scores, r(47) = -.11, ns. The
absence of a significant effect does not provide support for an association between
ongoing activation of negative words and either current anxious mood or general anxiety
vulnerability.
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Discussion
The current study introduced two key task modifications designed to test the
possibility that biased attentional disengagement from negative material in high trait
anxiety will result in continued processing of initially attended negative words. The first
was the inclusion of consecutive lexical decisions on each trial. It was believed that the
inclusion of a second trial decision which recruited the same decision making process as
the first decision may discourage continued processing of initial word content and
provide an index of disengagement from such processing. If the task was successful in
requiring participants to disengage from processing the content of negative and non-
negative words then the Biased Attentional Disengagement account of anxiety-linked
attentional bias predicts differences to emerge across stimulus valence and trait anxiety
groups. Specifically, it predicts that high trait anxious individuals will be slower to
determine the lexical status of non-words having initially processed negative as compared
to non-negative words, thereby demonstrating greater difficulty disengaging from the
emotional content of these negative words. This pattern of results did not emerge
however with no significant interaction being observed between trait anxiety group and
word valence. Correlational analyses conducted with lexical decision data similarly
provided no support for an association between biased attentional disengagement from
negative words and state or trait anxiety. Given that no anxiety-linked differences were
observed in disengagement from negative and non-negative words, it is possible that
either no anxiety-linked differences in ongoing processing of negative and non-negative
words was present or, that the task was not successful in requiring participants to
disengage from word content. Indeed, it was acknowledged that the inclusion of two task
decisions which recruited the same decision-making process could not preclude the
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possibility that participants may continue to process word content to a different degree
while identifying a subsequent non-word target. Examination of priming data allows
conclusions to be drawn regarding this.
The second key task inclusion was designed to assess the degree of ongoing
activation of initially processed stimulus words. This permitted the examination of
whether the task was successful in requiring disengagement from word content and if the
task did not achieve this, allowed us to assess potential anxiety-linked differences in
continued processing of negative and non-negative words. The presence of a priming
effect for words presented as the first lexical decision target indicated that performing the
second lexical decision on a non-word did not require participants to disengage from the
representation of initially processed word. This suggested that participants instead
continued to process the content of these words after the second lexical decision,
allowing potential differences to emerge in ongoing processing of negative and non-
negative words. As the task was not successful in requiring complete disengagement
when performing the second task decision, the Biased Attentional Disengagement
account of anxiety-linked attentional bias predicts that high, relative to low trait anxious
individuals, would exhibit greater ongoing processing of negative stimulus words as
represented by greater priming for these words when processed as the first lexical
decision target. No anxiety-linked differences in priming effects for negative and non-
negative word targets were observed in the current task however, providing no support
for the Biased Attentional Disengagement hypothesis.
As repetition priming has been demonstrated to be a reliable and robust means of
assessing the representational activation of a stimulus word (cf. Besner & Swan, 1982)
priming data obtained in the current study perhaps provide the most compelling evidence
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for the absence of a bias in attentional disengagement from emotional content. If we
accept that priming provides a reliable means of indexing the activation of a stimulus
word, then the results of the present experiment clearly suggest that the degree to which
participants can disengaging from the content of such stimuli it is not affected by the
emotional valence of the word or by the relative vulnerability to anxious mood of the
individual. Correlational analyses conducted using priming data similarly provided no
support for an association between measures ongoing activation of word content with
vulnerability to anxious mood. These results are clearly problematic for the Biased
Attentional Disengagement account of anxiety-linked attentional bias.
One possibility that could account for the absence of differences in ongoing
semantic activation is that no disengagement occurred for any participants on each trial in
the current task, with ceiling levels of engagement with word content obscuring evidence
of any individual differences in differential disengagement from the content of such
words. It is plausible that the intervening lexical decision response was either not
adequate to elicit natural differences in ongoing processing of differentially valenced
word content or, the brief duration between stimulus activation (when performing the
first lexical decision) and the final word-naming response may not have been sufficient
for any such differences to emerge. Indeed, the strong priming effect observed for
initially presented negative and non-negative words could suggest that the subsequent
processing of the non-word lexical target did not require participants to disengage from
processing the content of these stimuli at all. As the current task included both word and
non-word stimuli on the second trial decision it is possible to assess whether there was
indeed a decline in the stimulus activation evoked by the word encountered in the first
lexical decision by the time this was assessed by the final word-naming response. If there
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is a reduction in priming effect for words presented immediately prior to the word-
naming response (the second lexical decision target) as compared to words presented
initially (the first lexical decision target), this could be taken to suggest that such a
decline in activation did occur, indicating that the task is sensitive to disengagement from
initial word content.
To assess this possibility a two-way ANOVA was conducted with word recency
(word as first or second lexical decision target) and priming condition (primed or
unprimed) as within subject factors. A significant two-way interaction between lexical
decision order and priming condition was indeed observed, F (1, 45) = 20.69, p < .01.
Simple main effects analyses of this interaction revealed that the magnitude of the
priming effect for primed words (M = 561.90, SD = 12.92) versus unprimed words (M =
596.01, SD = 15.76), on trials where such words were presented as the first lexical
decision target, F (1, 45) = 19.98, p < .01, was less than the magnitude of the priming
effect for primed words (M = 510.19, SD = 11.84) versus unprimed words (M = 595.51,
SD = 15.55), on trials where such words were presented as the second lexical decision
target, F (1, 45) = 67.22, p < .01. Thus the priming effect for words presented as the first
lexical decision target (34.11ms) was less than half the magnitude of the priming effect
for words presented as the second lexical decision target (85.32ms effect). This pattern is
entirely consistent with what would be expected from the decline in representational
activation of stimulus content when it has been presented as the first as compared to the
second lexical decision target before then being verbally named. Therefore, while
priming data suggest that a word processed first will remain active to some degree, the
above result suggests that the inclusion of the second (non-word) lexical decision after
initially processing a word will result in some decline in the representation of the
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stimulus. This result permits confidence that the current task was indeed sensitive to the
decline in activation of a stimulus representation when disengaging from the initial
stimulus to process the subsequent non-word. This would further suggest that the absence
of effects implicating biased attentional disengagement are unlikely to be due to the
task‟s inability to require disengagement from processing the content of negative and
non-negative words.
Therefore, the results of the current study provide no support for the Biased
Attentional Disengagement account, likewise, although the results of Experiments 5
suggested that anxiety is characterised by the rapid engagement of attention with the
content of negative as compared to non-negative stimuli, it revealed no evidence of
biased attentional disengagement. However, in Experiments 5 it was noted that
conclusions were limited due to the insensitivity of the task (and indeed all previous
tasks) to ongoing semantic processing of stimulus content while performing the second
trial decision. The results of the current study therefore build on the findings of
Experiment 5 to suggest that, once the representation of a word has been activated, high
trait anxious individuals are not disproportionately slow to perform a subsequent
decision, even when this decision recruits the same cognitive subsystem as the first
response. Furthermore, the results highlight that while all participants experience some
decline in the activation of the initially processed word content when they perform the
second lexical decision, the degree of this disengagement from stimulus content does not
differ according to anxiety vulnerability or stimulus valence. Therefore, taken together
with the findings of Experiment 5, the results of the current study implicate the role of
biased attentional engagement with emotional content as the mechanism underpinning
anxiety-linked attentional bias.
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While repetition priming provides a reliable, consistent means of assessing
ongoing activation of stimulus words, past researchers have questioned whether
repetition priming tasks necessarily measure conceptual activation of stimulus meaning.
Some researchers have argued that the priming effect observed in such tasks could be
attributed to the encoding of perceptual rather than conceptual aspects of a stimulus
(Morris, Bransford, & Franks, 1977). This suggests that the stimulus word may equally
be encoded according to its form rather than its semantic properties. If this were the case,
it is possible that the absence of anxiety-linked differences in ongoing processing of
negative and non-negative words in the current study could be due to the encoding of
lexical targets according to perceptual rather than conceptual properties. This would
suggest that stimuli were perceptually primed rather than conceptually primed. However,
a number of studies have highlighted that repetition priming effects on word-naming
tasks results from both perceptual and conceptual encoding. In a demonstration of this,
Strain, Patterson, and Seidenberg (1995) revealed that words with imageable meanings
(e.g. soot) have shorter naming latencies when subsequently presented than words with
abstract meanings (e.g. scarce). This result was taken to suggest that the associated
conceptual properties of words were automatically activated and this more readily
occurred for imageable words resulting in greater priming effects as compared to words
with abstract meanings. Subsequent research has provided converging support for the
contention that repetition priming results from both conceptual and perceptual encoding
of stimulus words (MacLeod & Masson, 2000). This research provides reassurance that
the priming results of the current task do reflect the conceptual activation of stimulus
words. It would further suggest that the absence of differences for high and low trait
anxious individuals in ongoing activation of negative and non-negative words is an
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accurate reflection of the ongoing conceptual processing of these words and not merely a
reflection of a lack of conceptual encoding.
As highlighted in the discussion of Experiment 5, despite yielding evidence of
effects consistent with enhanced attentional engagement, the results of all previous
studies conducted in the current research program have failed to yield evidence for a bias
in attentional disengagement from negative stimuli. The results of the present study pose
further difficulties for the Biased Attentional Disengagement account, suggesting that
high trait anxious individuals are not disproportionately slow to disengage attention
having initially discriminated a negative word as compared to a non-negative word and
further, that the relative decline in activation for these differentially valenced words,
having performing a subsequent lexical decision, does not significantly differ for high
and low trait anxious individuals. Thus the weight of evidence as revealed by the present
series of experiments would strongly suggest that attentional bias in anxiety is
characterised by a propensity to selectively engage attention with the content of more
negative stimuli but is not associated with a relative difficulty disengaging attention from
such material once it has been identified.
In summary, the current study aimed to address the possibility that previous
measures of biased attentional disengagement from emotional content were insensitive to
potential differences in continued processing of negative and non-negative word content
while performing a second, unrelated task decision. Two key modifications were made in
the current task in order to address this question. The first was to change the second
decision on each trial such that it required the same decision making process as the first.
It was anticipated that greater ongoing activation of the initially attended stimulus content
would result in slowing to perform the second decision, thus representing greater
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difficulty disengaging attention from the emotional content of the initial stimulus. The
second key feature of the task was the inclusion of a repetition priming measure. This
was designed to yield a measure of ongoing activation of initially processed negative and
non-negative words subsequent to performing the second trial decision. Analyses
revealed no anxiety-linked differences in latencies to identify non-words after initially
processing negative or non-negative words. Similarly, despite reassurance that priming
measures were sensitive to the decline in activation of a stimulus content resulting from
performing the second lexical decision, no anxiety-linked differences in the ongoing
activation of negative and non-negative stimulus content were observed. The current
results provide further problems for the Biased Attentional Disengagement account of
attentional bias and together with the results of Experiment 5, implicate the role of biased
attentional engagement with emotional content in anxiety-linked attentional bias.
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CHAPTER 8
GENERAL DISCUSSION
Review of Research Findings
The central purpose of the current research program was to evaluate two
hypothetical accounts of anxiety-linked attentional bias, the Biased Attentional
Disengagement account and the Biased Attentional Engagement account. The Biased
Attentional Disengagement account of anxiety-linked biased attention contends that
vulnerability to anxious mood is associated with greater difficulty orienting attention
away from negative, as compared to non-negative material, once such material has
recruited attention, while the Biased Attentional Engagement account contends that
attentional bias in anxiety will be associated with enhanced engagement of attention with
negative, as compared to non-negative material. Past experimental approaches which
have demonstrated an attentional bias in anxiety have been unable to differentiate
whether individuals vulnerable to anxious mood selectively attend to more negative
material due to a heightened tendency to selective engage attention with such
information, or due to a greater difficulty disengaging attention from such information.
As reviewed in the introduction, recent research which has claimed support for the
existence of impaired attentional disengagement from negative material (e.g. Fox et al,
2001, 2002; Koster et al., 2004) has employed experimental methodologies which cannot
differentially attribute observed effects to biased attentional engagement or
disengagement with confidence. The present series of experiments employed a number of
task variants designed to overcome past methodological limitations and so determine
whether anxiety-linked attentional bias is associated with biased disengagement from, or
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biased attentional engagement with negative stimuli. The evidence obtained for each of
these hypotheses in the current research program will be reviewed in turn below.
Evidence for the Biased Attentional Disengagement account of anxiety-linked attentional bias
As described in the introduction, a problem with previous tasks designed to
examine individual differences in attentional disengagement from negative stimuli, has
been that the cue used to secure initial attention has been an emotionally valenced
stimulus. Slowing to process a probe appearing in an opposite screen location to this
initial cue could therefore equally well be caused by increased initial engagement of
attention with this information, or by greater difficulty subsequently disengaging
attention from this information. Experiments 1 and 2 examined anxiety-linked differences
in alternatively valenced material with variants of the attentional probe task (MacLeod &
Mathews, 1986), designed to overcome this problem. Specifically, to measure biased
attentional disengagement, attention was initially secured with a neutral cue before a
negative or non-negative word then was presented in the cued spatial locus, with
participants subsequently being required to keep attention in the same locus as this
valenced word, or relocate attention to a spatially removed location. The results of
Experiment 1 demonstrated that, when the task ensures attention has been equivalently
secured in the locus of a differentially valenced stimulus word, high and low trait anxious
participants do not exhibit disproportionately slow responding to identify probes
appearing opposite negative, as compared to non-negative stimuli. Such findings are
clearly inconsistent with the predictions of the Biased Attentional Disengagement
account of anxiety-linked attentional bias.
The probe task used in Experiment 1 also produced some seemingly
counterintuitive results, whereby high trait anxious participants were slower to process
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probes appearing in the locus of negative as opposed to non-negative words and faster to
process probes in the location opposite negative as compared to non-negative words,
regardless of the location of initial attention. As this pattern of results did not involve the
initial cue locus factor, it was not informative in differentiating attentional engagement
and disengagement processes. However, this pattern of effects was clearly inconsistent
with past results using attentional probe tasks which have reliably demonstrated that high
trait anxious individuals are faster to process probes appearing in the locus of negative, as
compared to non-negative material. In discussing possible reasons for obtaining such a
result, it was highlighted that while the task used in Experiment 1 permitted confidence
that initial attention was equivalently located in the spatial vicinity of a word, it still
allowed for possible differences in the semantic processing of the word in this spatially
attended region. The second probe task variant employed in Experiment 2 therefore
included the requirement that all participants must process the semantic content of the
initial stimulus word, before then discriminating a probe in the same position, or in the
opposite screen position. Again, this study observed no anxiety-linked differences in
latencies to discriminate probes appearing in the opposite, as compared to the same locus
as initially processed negative and non-negative words, thereby providing no evidence for
biased attentional disengagement of spatial attention from negative stimuli for high trait
anxious individuals.
Hence, the evidence obtained from modified probe tasks in the current research
program does not support the position that anxiety vulnerability is characterised by an
impaired ability to disengage attention from the spatial locus of more negative material.
This is inconsistent with the claims of researchers such as Yiend and Mathews (2001) and
Koster et al. (2004) who propose that high trait anxiety is associated with an impaired
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ability to relocate spatial attention away from the locus of initially attended negative
material. The current research instead suggests that when initial attention is equivalently
secured in the locus of a differentially valenced stimulus word, and participants then
process the semantic content of the word appearing in that initial locus, then high and low
trait anxious individuals are not observed to differ in the speed with which they can
subsequently relocate attention away from this region to a different spatial locus.
The modified Stroop tasks employed in the current research program moved from
exclusively focusing on spatial disengagement of attention to instead examine whether
individuals who vary in anxiety vulnerability may have differential difficulty switching
attention between differentially emotional dimensions of a single stimulus. The modified
Stroop tasks which assessed biased attentional disengagement required participants to
first process the semantic content of negative or non-negative words, before then
switching attention to process a non-emotional dimension of these stimuli which
immediately became available, namely the colour of the word. These modified Stroop
tasks employed in Experiments 4 and 5 did not reveal any anxiety-linked differences in
latencies to colour-name negative or non-negative stimulus words, having initially
processed the content of these stimuli. The absence of such an effect on this task means
that these modified emotional Stroop task also revealed no evidence that heightened
anxiety vulnerability is associated with selective difficulty disengaging attention from
negative information.
In considering the implication of examining non-spatial or dimensional shifts in
attention in the modified Stroop task, it was noted that, if attentional engagement can be
considered to occur when a word‟s representation becomes active, then it could be argued
that attentional disengagement can only be considered to occur when the activation of the
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stimulus representation returns to baseline. By this definition, a shift in spatial attention,
or an attentional shift to a non-semantic stimulus dimension, may or may not involve
attentional disengagement from the processing of stimulus meaning. It was considered
possible, therefore, that individual differences in disengagement may be revealed by
measuring the degree to which there is a decline in the activation of the initial
representation following the second decision. The investigation of this possibility formed
the basis of the final study. The task in Experiment 6 was designed to maximise the
possibility that participants would be required to cease processing the initial stimulus
meaning in order to execute the required decision about the second stimulus. It also
provided a measure of any ongoing activation of this first stimulus content, capable of
revealing individual differences in the continued activation of the first stimulus content,
as a function of its valence and participant anxiety level. The results indicated that the
performance of the second decision was accompanied by a reduction in the activation of
the first stimulus content, but there was no significant differences in continued activation
of negative and non-negative word content between high and low trait anxious
individuals. Again, this result yields no support for the Biased Attentional
Disengagement account of anxiety-linked attentional bias.
In summary therefore, the results of the current research program have
consistently failed to find support for the existence of an anxiety-linked difference in
attentional disengagement from negative stimuli. Specifically, when it is ensured that
high and low trait anxious participants equivalently engage attention initially with
negative or non-negative information, these groups do not subsequently differ in their
speed to shift attention away from either category of information to a spatially removed
locus. Furthermore, high and low trait anxious participants do not evidence differences in
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the speed with which they can switch attention from processing the emotional content of
a negative or non-negative word, to instead process a non-emotional dimension of this
stimulus. Also, high and low trait anxious individuals do not evidence differences in the
ongoing activation of these initially attended stimulus words, when a subsequent task
invites the attenuation of this activation. Collectively, these results are inconsistent with
the Biased Attentional Disengagement hypothesis.
Evidence for the Biased Attentional Engagement account of anxiety-linked attentional bias
To test the hypothesis that anxiety-linked attentional bias is associated with biased
attentional engagement with negative material in high trait anxious individuals, the
current research program again employed variants of the two tasks that have most
consistently demonstrated attentional bias favouring negative material, the dot probe and
emotional Stroop tasks. The versions of these tasks developed for this purpose overcame
methodological limitations of previous tasks by securing initial attention with a non-
emotional stimulus, or non-emotional stimulus dimension, before then measuring speed
to subsequently engage attention with the spatial locus, or semantic content of
differentially valenced stimuli.
Measures of individual differences in attentional engagement with negative and
non-negative material were assessed by the probe task in Experiment 1 by first requiring
participants to attend to the locus of a non-word before either discriminating a probe in
this same locus, or orienting attention to a spatially removed position to discriminate a
probe in that region. Contrary to the predictions generated by the Biased Attentional
Engagement account, no anxiety-linked differences in the relative speed to orient
attention toward the spatial locus of probes appearing in the vicinity of negative or non-
negative words was revealed in probe discrimination latencies. However, participants
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were not required to process the semantic content of stimulus words on this task, and so it
was possible that attention could be moved to the spatial vicinity of a particular word
without a participant engaging attention with its semantic meaning. The possibility
therefore remained that anxiety-linked differences may exist in the engagement of
attention with the semantic content of negative words.
Assessing whether attentional bias in anxiety is characterised by disproportionate
speeding to spatially shift attention to engage with the semantic content of negative and
non-negative words formed the basis of investigation in Experiment 3. The probe task
was modified such that participants first attended to a probe before then processing the
content of a negative or non-negative word appearing in the same or spatially distal
position to the initial probe. Again, however, results did not support the predictions of the
biased engagement hypothesis. No difference in latencies for participants to process
probes appearing in the vicinity of either negative or non-negative stimuli in the opposite
location to initial fixation was observed, suggesting no anxiety-linked difference in
speeding to shift spatial attention to process negative rather than neutral words. However,
it was observed that high trait anxious participants were faster to process the content of
negative, relative to non-negative words, that appeared within the initial locus of spatial
attention, a pattern that was not observed for low trait anxious participants. The results of
Experiment 3 therefore underscored the possibility that attentional switching between
alternative stimulus information within an attended spatial locus may be associated with
an anxiety-linked bias in attentional engagement, favouring the content of negative
information within the spatially attended region. This possibility highlighted the
appropriateness of examining biased attentional engagement using a task methodology
which would not require such spatial shifts in attention.
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Experiments 4 and 5 therefore adopted a modified version of the emotional Stroop
task to assess whether anxiety vulnerability is associated with biased attentional
engagement with the content of negative words appearing within a spatially attended
region. Attentional engagement was indexed on these tasks by relative speeding to
process the content of negative and non-negative words, having previously processed the
colour dimension of these stimuli. The high rate of error in performing grammatical
judgments on the task in Experiment 4 undermined confidence in measures of attentional
engagement obtained in this study, which revealed no significant effects. However, the
equivalent measures for attentional engagement obtained in Experiment 5 using lexical
decision latencies to infer speed of engagement with semantic content of words clearly
supported the Biased Attentional Engagement account. The results demonstrated that
high trait anxious individuals were disproportionately fast to engage in processing the
content of negative relative to non-negative words appearing within the spatially attended
region, while low trait anxious individuals demonstrated the reverse pattern. This result
was consistent with the predictions of the Biased Attentional Engagement account of
anxiety-linked attentional bias, however, it specifically suggests that this engagement bias
operates only in selectively processing the content of negative stimuli already within an
attended locus.
Theoretical Implications and Future Theoretical Research Directions
The current research program set out to address the question of whether the
anxiety-linked attentional bias favouring negative material reflects either enhanced
engagement with or impaired disengagement from negatively valenced stimuli. As
previously acknowledged, it is not possible to dismiss the possibility that a
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disengagement bias may be observed under different conditions and it remains uncertain
whether the engagement bias always will explain observed attentional selectivity.
However, if future research confirms that the attentional bias shown in those with
elevated anxiety vulnerability reflects enhanced engagement of attention with negative
stimuli, and not impaired disengagement of attention from such negative stimuli once it
has recruited attention then this will have important implications.
The findings of the present research program could generally be considered
consistent with past research regarding attentional bias in anxiety, in that it provides
further evidence that high trait anxious individuals preferentially process negative as
compared to non-negative stimuli. Such findings support the common prediction of the
three cognitive models of anxiety vulnerability described in some detail in the
introduction, that high trait anxious individuals will selectively attend to more negative
information. Bower‟s associative network model (Bower, 1981; Bower, 1987; Bower, et
al., 1994) contends the operation of emotion nodes and their associated structures
containing anxiety-congruent information. This model suggests that stronger connections
between emotion nodes and associated structures resulting from frequent state anxiety
responses will contribute to cognitive biases in information processing and greater
emotional vulnerability to anxious mood, including an attentional bias favouring anxiety-
congruent information. Beck‟s schema model (1976; Beck & Clark, 1988; 1997; Beck, et
al., 1985) contends that anxiety vulnerability is characterised by the presence of danger
schemata, which develop as a result of historical events involving personal threat. When
activated by a stressful event or stimulus, these schemata act to bias information
processing in a anxiety-congruent manner. This model therefore predicts that high trait
anxious individuals will exhibit biased processing of stimuli which are emotionally
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negative or threatening in tone. Williams et al.‟s (1988; 1997) integrative processing
model of emotional vulnerability proposes that high trait anxiety is associated with highly
integrated representations of negative information. Such integrated representations will
lead to partial matches in the environment activating the entire representation. Williams
et al.‟s model specifically predicts that this will contribute to a lower threshold for
detecting anxiety-congruent information in individuals more vulnerable to anxious mood
and this in turn will result in rapid detection of negative material.
Clearly the studies which demonstrated selective attention in the present research
are consistent with the general predictions of all of these cognitive models, in that high
trait anxious individuals did exhibit an attentional bias favouring more negative material.
The present research went beyond the scope of past research examining the presence of
attentional bias in anxiety, to examine the precise nature of this bias with respect to
attentional engagement and disengagement. When anxiety-linked attentional bias has
been demonstrated within the present research program it has always been the case that
this has involved differential engagement. The present findings therefore specifically
implicate the role of biased attentional engagement with emotional content as
underpinning anxiety-linked attentional bias. In considering the implications of these
finding for the specific cognitive models discussed above, both Beck and Bower‟s
models suggest general activation of anxiety-congruent cognitive structures, and so
predict a very wide range of processing biases associated with anxiety, including, but not
restricted to, an attentional preference for negative stimuli. While neither of these models
makes specific reference to attentional engagement or disengagement processes, the
generality of their predictions in relation to information processing biases suggests that
these models lead to the expected operation of a bias in both attentional engagement and
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disengagement among individuals vulnerable to anxious mood. However, the Williams et
al. (1988; 1997) model specifically indicates that the highly integrated nature of anxiety-
related information in the cognitive system will lead to enhanced detection of negative
information, which would be expected to influence attentional engagement with such
information rather than attentional disengagement from it. In studies which have
demonstrated an attentional bias in the current research, the pattern of findings obtained
suggest that attentional bias in anxiety is indeed associated with a tendency to selectively
engage attention with the content of negative stimuli. Alternatively, the present research
has failed to demonstrate support for the position that such an anxiety-linked bias is
associated with an impaired ability to disengage attention from such stimuli once it has
been identified. Thus, this pattern of support for the Biased Attentional Engagement
account of attentional bias could be considered most consistent with Williams et al.‟s
model of anxiety-linked cognitive bias, which specifically implicates the role of enhanced
detection of negative material in anxiety, but not impaired reallocation of attention from
such stimuli once they have been identified.
The present research findings lend weight to the concerns expressed in the general
introduction regarding previous studies that have claimed to demonstrate anxiety-related
impaired disengagement from negative material. It will be recalled that one of the most
consistently used tasks employed to examine biased attentional disengagement from
negative stimuli has been based on Posner‟s (1980, Posner et al., 1987) attentional cueing
paradigm. The modified version of this task has involved presenting negative or non-
negative stimuli to a left or right screen position as initial cues, and then requiring
participants to identify the position of a subsequently presented probe which appears in
either the same location as the initial stimuli, or the opposite screen position. Slowing to
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identify the location of the probes appearing opposite the initial cue stimulus has been
taken as a measure of the latency to disengage attention from the initial valenced stimuli.
A number of studies have reported an anxiety-linked difference in the response latencies
for probes appearing in the screen position opposite negative as compared to non-
negative stimuli and have attributed this to differences in attentional disengagement from
emotional info (Fox et al., 2001; 2002; Koster et al, 2006; Yiend & Mathews, 2001).
However, one of the key criticisms previously discussed regarding the use of this task for
measuring biased attentional disengagement was the absence of a means of ensuring that
participants equivalently attend to the initially presented stimuli, and process its content
to the same degree. Without this, it is impossible to attribute the observed effects
specifically to either attentional engagement or attentional disengagement as initial
attentional engagement is not controlled.
The consistent absence of support for the Biased Attentional Disengagement
account in the current research could be taken to suggest that when care is taken to ensure
equivalent initial engagement with the locus and content of emotional stimuli, no anxiety-
linked differences emerge in the subsequent disengagement of attention from
differentially valenced stimuli. Conversely, the present research findings in relation to
anxiety-linked attentional bias suggest that when initial attention is equivalently focused
on non-emotional information then high trait anxious individuals subsequently display
enhanced attentional engagement with the content of newly presented negative over non-
negative information. It is entirely possible therefore, that past research claiming to have
revealed anxiety-linked impaired disengagement from negative material has in fact been
demonstrating a flow on effect of the same attentional engagement bias observed in the
current research. A clear implication is that any task designed to assess differential biases
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in attentional engagement and attentional disengagement must be able to ensure
equivalent attentional engagement with the valence of the information being shifted from.
The experimental tasks employed in the current research therefore provide a model for
future studies wishing to assess the unique contributions made by attentional engagement
and disengagement processes to any observed pattern of attentional bias.
The presence of support for the Biased Attentional Engagement account in the
current research allows us to discount the possibility that all past research which has
demonstrated an anxiety-linked attentional bias has actually been disengagement effects
wrongly interpreted as engagement effects. Indeed the present findings have shown that
some recent research claiming to reveal biased attentional disengagement effects could
plausibly be instead attributed to reflect attentional engagement effects. Although the
present research has revealed evidence for selective attentional engagement that is not
attributable to biased disengagement, it is also the case that across the present series of
studies evidence for anxiety-linked attentional engagement was not always found. Indeed,
the series of studies described in the current thesis suggests that whether or not evidence
is obtained for an engagement bias at least depends upon the nature of the task used to
assess such a bias. Therefore, while we can be confident that future research is likely to
reveal the presence of an engagement bias, it is unlikely that such a bias will be
universally observed. An important line of future research will therefore be to establish
which set of experimental circumstances do and do not reveal such an effect, which will
likely advance understanding of the precise mechanisms that give rise to anxiety-linked
engagement bias.
While the present program of research has revealed no evidence of an anxiety-
linked engagement bias on any of the six experiments conducted it would be
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inappropriate to dismiss the possibility that biased attentional disengagement effects may
occur under some circumstances, or in certain populations, on the basis of the current null
findings. For example, in the present research we compared patterns of attentional
disengagement for high and low trait anxious members of the normal population,
however, it is possible that a group difference in attentional disengagement from threat
would emerge if we compared clinically anxious individuals with normal members of the
population. It is conceivable that while high trait anxious members of the normal
population may not demonstrate biased disengagement, an impaired ability to disengage
attention from negative stimuli may be a feature of clinically anxious populations and
form a key difference between these groups. Indeed, different clinical conditions may
also reflect different combinations of biased attentional disengagement and engagement.
Clinical disorders associated with a high degree of emotional reactivity to perceived
threat (e.g. Panic Disorder) could conceivably be more associated with high levels of
biased attentional engagement with emotionally negative stimuli. This may therefore
increase the likelihood that individuals possessing such a bias will identify and react
strongly to negative stimuli in their environment but also experience a relatively rapid
reduction in their anxiety. Alternatively, those conditions which reflect greater
perseveration of an anxiety response (e.g. Generalised Anxiety Disorder) may be more
associated with an impaired ability to disengage attention. Therefore, while these
individuals may not demonstrated enhanced detection of negative material, an impaired
ability to reallocate attention away from emotionally negative material once it is
identified may prolong elevated anxiety levels. It is plausible therefore, that comparing a
population based on anxiety reactivity and anxiety perseveration could reveal a different
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pattern of biased attentional engagement and disengagement to that observed in the
present series of studies.
While such possibilities are certainly intriguing it should be emphasised that their
identification in this discussion is not intended to persuade the reader of their validity.
Indeed, to date no demonstrated anxiety-linked attentional bias requires the conclusion
that elevated anxiety is ever associated with impaired disengagement from threat. The
main point being made here is that the absence of evidence to confirm the existence of an
anxiety-linked disengagement bias does not permit confidence that such a bias does not
exists or makes a distinctive contribution to certain aspects of anxiety not investigated in
the present research program.
Setting aside the important distinction between attentional engagement and
attentional disengagement, it is important to note that some present variants of the
attentional probe task revealed no evidence of any anxiety-linked attentional bias despite
this having been demonstrated on previous attention probe task variants. Prior studies
employing attentional probe methodologies have consistently demonstrated that
individuals more vulnerable to anxious mood show an attentional bias favouring the
spatial locus of negative as compared to non-negative stimuli (e.g. MacLeod et al., 1986;
MacLeod & Mathews, 1988, Mogg, et al., 1992). However, the modified probe tasks
used in Experiments 1, 2 and 3 provided no evidence for an anxiety-related bias in either
spatial engagement with or spatial disengagement from the locus of emotionally valenced
stimuli. Indeed, the results of Experiment 3 suggested that the attentional bias observed in
high trait anxious individuals when orienting attention from the probe to engage with the
content of a negative word in the same spatial locus was eliminated when they were
required to relocate spatial attention to engage with the content of such words. The fact
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that an attentional bias favouring negative stimuli is consistently revealed for high trait
anxious individuals in traditional probe tasks, poses the question as to why the current
studies were unable to reveal biases in the allocation of spatial attention for either
attentional engagement or disengagement.
It is possible to introduce a conceptual dichotomy to distinguish two hypothetical
ways in which either an attentional engagement or disengagement bias might operate,
that could account for the absence of anxiety-linked effects in spatial attention in the
present probe task variants. This dichotomy concerns the potential difference between an
individual‟s ability to selectively attend to one type of stimulus rather than another, and
their tendency to attend to one type of stimulus rather than another. When an individual is
presented with processing options and is permitted but not required to attend to one class
of stimuli then the degree to which they attend to this stimulus, will depend upon their
tendency to preferentially allocate attention to this stimulus. However, when an
individual is presented with a processing option and is required to attend to one type of
stimulus rather than another, then a measure of their compliance with this requirement
will reflect their relative ability to preferentially attend to this stimulus. Given that
traditional attentional probe tasks require participants to move attention to the probe locus
to make the discriminate response, but also permit individual differences in which locus
was preferentially attended to prior to the probe presentation, it follows that these
traditional tasks may either assess high trait anxious individuals‟ ability to selectively
attend to the vicinity of negative stimuli, or their tendency to do so.
In order to accurately measure attentional engagement with and disengagement
from valenced stimuli, the probe task variants used in the current series of studies
required participants to attend to an initial location, before then requiring participants to
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either remain in the same locus, or relocate attention toward or away from differentially
valenced stimuli. The necessity of requiring that participants equivalently attended to an
initial locus and/or stimulus then move attention or not, essentially meant that the current
probe tasks provided a measure of participants‟ ability to engage attention with, or their
ability to disengage attention from, the spatial vicinity of a negative or non-negative
word. Unlike traditional probe tasks, these new variants would not assess differences in
the tendency to allocate attention between competing stimuli. It is possible therefore, that
the anxiety-linked bias observed on traditional probe task variants may reflect a
heightened tendency for participants to attend to negative material, but no increased
ability to do so. Most conventional tasks would, however, have difficulty distinguishing
whether observed attentional bias effects are due to a differential ability or a differential
tendency. For example, time to perform a task which requires attentional disengagement
may be influenced by tendency rather than ability if at an earlier point in the task
disengagement has been possible, even though not required. To develop tasks capable of
sensitively distinguishing ability and tendency requires a consistent concentrated and
creative effort.
Developing future probe tasks capable of distinguishing between biases in ability
and tendency to engage with and to disengage from valenced stimuli could provide a
means of pursuing the possibility that the anxiety-linked bias observed on traditional
probe tasks may reflect tendency to attend to negative material, but not the ability to do
so. In order to achieve this, it would be necessary to construct two variants of the
modified probe task; one which assesses the ability of participants to spatially engage
attention with, and disengage attention from valenced stimuli, and one which assesses the
tendency of participants to spatially engage attention with and disengage attention from
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valenced stimuli. Such a task could be structurally similar to that employed in
Experiment 1 with a few critical modifications. All trials could involve securing attention
in an initial locus with a cue that participants are required to note the structure of (e.g. an
arrow facing left or right). Two letter strings would then be presented (a negative or non-
negative word paired with a non-word), one in the same position as the initial cue the
other in the opposite screen position. For trials assessing participant‟s ability to engage
attention with, and disengage attention from valenced stimuli, a single arrow probe would
subsequently appear on the screen with participants being required to indicate if this
probe arrow is a match or mismatch to the initial cue arrow. Those trials assessing
engagement ability therefore would reveal participants‟ speed to engage with the location
of a negative or non-negative word, when this was required. Trials assessing
disengagement ability would be identical, except initial attention would be secured in the
locus of a negative or non-negative word with the probe arrow appearing opposite this.
Here the decision latency would reveal participants‟ ability to disengage from the
location of the negative or non-negative word, when required to do so. In contrast, on
trials assessing engagement and disengagement tendency, two arrows would instead be
presented, one in the vicinity of each of the two letter strings and each facing a different
direction. These would appear only briefly with participants being instructed to respond
by indicating whether the first arrow that they see matches the cue arrow or not. This
would therefore provide an indication of the location that participants tended to be in
when the probe appeared, revealed by the direction of the arrow that they reported. Thus
for trials assessing disengage tendency, attention would be secured in the locus of a
negative or non-negative word and whether participants identify the arrow in the same
versus the opposite screen position would provide an indication of their tendency to
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disengage from this initial position. Conversely, for trials assessing engage tendency,
attention would be secured in the locus of a non-word and participants‟ response to either
the arrow in the same location or the arrow in the locus of a negative or non-negative
word in the opposite screen position would provide an indication of their tendency to
engage with these differentially valenced stimuli. A task with this structure would have
the capacity to differentiate relative ability and relative tendency to demonstrate biased
attentional engagement with, and disengagement from the spatial locus of valenced
stimuli.
Probe
Fixation Cue Brief Stimulus Cue Word stimuli Remain until response
Probe
Fixation Cue Brief Stimulus Cue Word stimuli Very brief presentation
Figure 8.1. Example of a probe task which could reveal individual differences in the tendency and
ability to engage with and disengage from valenced stimuli. Initial cue position and match/mismatch
between cue and probe shown randomly. Actual task would also include non-negative stimuli.
+
+
CRITICISE
IVFKLZJID
+
CRUEL
LFGPQ
+
CRUEL
LFGPQ
CRITICISE
IVFKLZJID
NONWORD
Ability to Engage
Secure attention in locus of nonword
Require shift toward the locus of a
valenced word
Ability to Disengage
Secure attention in locus of
valenced word
Require shift away from this locus
Tendency to Engage
Secure attention in locus of a nonword
Tendency to engage revealed by which
probe is identified
Tendency to Disengage
Secure attention in locus of valenced word
Tendency to disengage revealed by which
probe is identified
CRITICISE
IVFKLZJID
CRUEL
LFGPQ
CRUEL
LFGPQ
CRITICISE
IVFKLZJID
NONWORD
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While it is possible that differences in ability and tendency could account for the
absence of anxiety-linked differences in attentional engagement and disengagement of
spatial attention on the present probe task variants, an alternative account could also
provide a plausible explanation for the absence of such effects. The central finding
resulting from the present series of studies suggests that high trait anxious individuals
selectively engage with the content of negative over non-negative stimuli, when this
material is presented within an already attended locus. Such an attentional bias could
accommodate the pattern of results from prior probe tasks which indicate that high trait
anxious individuals are faster to discriminate probes presented in the vicinity of negative
stimuli. It is possible that high trait anxious individuals may attend with equal frequency
to either the locus of negative or non-negative stimuli, but, the likelihood that they will
engage with the content of the word in that locus will be disproportionately great when
the word is negatively valenced. If we consider that greater engagement with the content
of such material may result in attention pausing longer in this locus than would be the
case if word meaning was not processed, this then would facilitate identification of
probes appearing in the vicinity of negative as compared to non-negative stimuli. An
attentional engagement bias which involves selective processing of the content of
negative stimuli in an already attended locus could readily accommodate findings in the
traditional probe task. Also, such a bias would not emerge on present variants of the
attentional probe task as these tasks controlled for engagement with the content (or locus
of) differentially valenced stimuli, which may underlie this individuals difference, while
focusing on differences in speed to move attention from or toward such information.
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A non-spatial attentional bias favouring engagement with the content of negative
stimuli could also accommodate the pattern of findings on previous research examining
attentional engagement with and disengagement from differentially valenced stimuli
using variants of Posner‟s (1980, Posner et al., 1987) attentional cueing paradigm (e.g.
Fox et al., 2001; 2002, Yiend & Mathews, 2001). Such a non-spatial attentional
engagement bias could resemble a spatial disengage bias in that, once attention is in a
spatial region, it would not move away as quickly if the material in that locus was
negative in valence. This slowing would reflect enhanced engagement with the semantic
content of negative words in whatever spatial locus happened to be attended to, rather
than a selective difficulty orienting attention away from such information. It is plausible
therefore that in modified variants of the attentional cueing task (e.g. Yiend & Mathews,
2001) the slower responses to process probes presented opposite cues containing
negative, as compared to non-negative information for high trait anxious individuals,
could represent biased engagement with the content of these negative stimuli when
attention is directed to their locus, rather than a selective difficulty to spatially relocate
attention away from such material.
When turning to findings regarding non-spatial attention, the results obtained in
the current research program are less inconsistent with past research. The pattern of
effects observed on the modified Stroop task in Experiment 5 is entirely consistent with
past findings using the traditional emotional Stroop task, which have demonstrated
disproportionate slowing for high trait anxious individuals to colour-name negative as
compared to non-negative words. The results of the present modified Stroop tasks
specifically suggest that such slowing to colour-name negative stimuli on traditional
emotional Stroop tasks may reflect a bias in selective attentional engagement with the
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content of negative words for high trait anxious individuals. Such a selective processing
bias could readily cause slowing to colour name negative stimuli for high trait anxious
individuals, as greater engagement with the content of negative stimuli for these
individuals is likely to result in greater interference with the task of colour-naming than
for those who do not engage with this stimuli to the same degree.
When one considers the engagement effect observed on the present modified
Stroop task with reference to the distinction discussed between biased ability and
tendency, clearly the present emotional Stroop task provides a measure of engagement
ability. That is, the nature of the present variant of the emotional Stroop task required that
participants access the meaning of the stimulus word and assessed the speed with which
they were able to do so. The results derived from this task would therefore suggest that
high trait anxious individuals do show enhanced engagement with the content of negative
stimuli, and that this bias reflects engagement ability. It is less clear, however, whether
the component of the present emotional Stroop task variant assessing attentional
disengagement measured ability or tendency to disengage, and it is also unknown what
pattern of results would be revealed if the task had also measured engagement tendency.
A recent study conducted within our research group (Barnes, 2008; unpublished
manuscript) used an extension of the modified emotional Stroop task used in Experiment
5 to distinguish anxiety-linked differences in ability and tendency to engage with and
disengage from emotional material. The study confirmed the presence of an anxiety-
linked bias in engagement using an ability version of the task, with results again
suggesting that high trait anxious participants switch attention to selectively process the
content of negative stimuli when required to do so. The study also revealed that such an
engagement bias was absent on the tendency version of the task. The study did not reveal
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any evidence to support the existence of an anxiety-linked bias in tendency or ability to
disengage attention from negative or non-negative stimuli. Therefore, while the present
series of experiments did not directly examine differential tendency, the finding that high
trait anxious individuals have an increased ability to engage with negative stimuli on a
task assessing both ability and tendency is consistent with the results observed on the
emotional Stroop task employed in Experiment 5. This finding also acts to clarify the
question of whether the absence of anxiety-linked effects on the disengagement version
of the emotional Stroop task in the present research reflects the absence of differential
disengagement ability, tendency or both, suggesting that for neither of these processes is
differential disengagement evident.
The current research program has produced findings consistent with the presence
of an attentional bias favouring negative stimuli for high trait anxious individuals. More
specifically, these findings suggest that anxiety-linked attentional bias may be
characterised by Biased Attentional Engagement with negative stimuli. The present
research could therefore be considered most consistent with theoretical models, such as
Williams et al. (1988; 1997) integrative processing model, that implicate enhanced
attentional engagement with emotionally negative material.
Applied Implications and Future Applied Research Directions
There are a number of applied reasons that researchers or clinicians may seek to
assess attentional bias. For example, indices of such a bias predict future emotional
reactions to adverse events (MacLeod & Hagen, 1992) or long term stress (Clarke,
MacLeod, & Shirazee, 2008), and measures of attentional bias have been used as an
index of progress and/or recovery from anxiety dysfunction (Mathews et al., 1995). The
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present research strongly suggests that such measures will be of greatest applied value
when they index biased attentional engagement with the content of negative material,
rather than biased attentional disengagement from such material. If, as the present
findings suggest, the attentional bias associated with anxiety vulnerability reflects
selective engagement with negative stimuli, then the most useful measures of anxiety-
linked attentional bias will specifically reveal individual differences in selective
attentional engagement with negative information. This could lead to more precise means
of indexing attentional biases for a number of purposes including improved measures for
predicting negative emotional reactions to stressful life events, or for monitoring the
degree to which psychological interventions remediate the specific forms of cognitive
processing biases most strongly associated with anxiety vulnerability.
The observation that biases in attentional engagement with negative information
underlie the anxiety-linked attentional bias favouring negative material can also inform
cognitive rehabilitation approaches designed to reduce anxiety vulnerability by directly
modifying the pattern of selective attention characteristic of such vulnerability. It will be
recalled from the introduction that a modified version of the attentional probe task has
proven capable of directly manipulating attentional response to negative stimuli, by
presenting probes consistently in the location of non-negative words or consistently in the
location of negative words (MacLeod et al., 2002). This previous research has further
demonstrated that induced processing biases can systematically modify emotional
reactivity to a stressor, such that individuals become more or less vulnerable to anxious
mood depending on whether the contingency has encouraged attentional processing of
negative or non-negative material respectively (MacLeod et al., 2002). Preliminary
research has also suggested that extended exposure to such attentional training
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procedures designed to induce attentional avoidance of negative stimuli, can reduce
symptoms of anxiety in high trait anxious members of the general population (Amir,
Selvina, Elias & Rousseau, 2002) and in clinically anxious patients (Vasey, Hazen, &
Schmitd, 2002).
The present research clearly suggests that such attentional training procedures
should be rendered maximally effective by optimising their ability to reduce selective
engagement with the content of negative material while promoting engagement with the
content of non-negative stimuli. A training task designed to specifically modify
attentional engagement bias could take a similar format to the emotional Stroop variant
used in Experiment 5. In order to reduce an attentional engagement bias favouring
negative stimuli, an attentional training variant of this task could introduce a contingency
such that, having initially processed the text colour of the stimulus, individuals then
consistently must processes the content of non-negative stimuli, while instead performing
a second structural judgment on negative stimuli. While speculative, it is possible that a
task which specifically targets biased attentional engagement with negative stimuli may
be more effective in reducing anxiety vulnerability. The scope of such investigation lies
considerably beyond the current research program but presents as a potentially rich area
for future studies.
Limitations of Present Research and Future Research Directions to Overcome These
As is the case with all research programs, the present series of studies reported in
the current dissertation are subject to certain limitations in population samples, stimulus
materials, experimental tasks and measures which it is appropriate to recognise.
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The focus on high trait anxious individuals as a population sample of emotionally
vulnerable individuals was deliberate in that the purpose of the research was to address
the hypothesis concerning the specific information processing biases that distinguish high
trait anxious individuals from individuals who are lower in vulnerability to anxious
mood. Nevertheless, the fact that participants have not been selected on the basis of
anxiety pathology clearly limits the capacity to extrapolate conclusions to such clinically
anxious groups. It is possible therefore, that factors which differentiate high trait anxious
from low trait anxious members of the normal population, may not be related to those
that distinguish clinically anxious people from those without anxiety dysfunction.
Some confidence that the present pattern of findings may replicate in individuals
with clinical levels of anxiety can be drawn from the previously demonstrated similarities
between patterns of attentional effects shown by both clinically anxious and high trait
anxious individuals. For example, the emotional Stroop task has consistently
demonstrated that both high trait anxious individuals and clinically anxious patients
exhibit a disproportionate slowing to colour-name negative stimulus words (cf. Williams,
Mathews, & MacLeod, 1996). Similarly, selective attention favouring the locus of
negative words in the dot probe task has been observed in both high trait anxious
members of the general population (Mogg, et al., 1994) and clinically anxious individuals
(MacLeod, et al, 1986). Also, the observation that high trait anxiety represents a powerful
risk factor for the development of clinical anxiety disorders (Eysenck, 1992), supports the
notion that patterns of information processing associated with high trait anxiety are also
likely to be features of clinical pathology. Nevertheless, as earlier discussed, it is possible
that features which distinguish high trait anxious members of the normal population with
clinically anxious individuals may include differences in the pattern of attentional
215
engagement and disengagement. Therefore, despite confidence that attentional bias exists
in both high trait anxious and clinically anxious groups, it cannot be concluded that the
contribution made by engagement and disengagement mechanisms to the occurrence of
these biases is equivalent for clinically anxious individuals and high trait anxious
members of the normal population. This is because previous research paradigms which
have demonstrated consistency in attentional bias across high trait anxious and clinically
anxious groups have not been able to distinguish engagement and disengagement aspects
of attentional bias. A clear avenue for future research will therefore be to assess whether
the present findings implicating the role of biased attentional engagement with the
content of negative stimuli generalise to clinically anxious populations.
Another noteworthy issue regarding the sample employed in the present series of
studies is that it does not readily allow differentiation of the relative roles of state and
trait anxiety. Individuals were deliberately selected for participation in the present
experiments due to the interest in individual differences in vulnerability to anxious mood.
However, because state and trait anxiety are generally highly correlated it can be difficult
to attribute observed findings to the effects of one or the other. It is entirely plausible
therefore that the pattern of biased attentional engagement and disengagement exhibited
by individuals may differ depending on both their general vulnerability to anxious mood
and their current anxious state. It is possible to envisage a research design capable of
differentiating the role of these two dimension of anxiety. One way of doing this would
be to examine measures of biased attentional engagement and disengagement in high and
low trait anxious individuals at times of relatively high and low stress. This would
provide an indication of whether these components of attention differ with respect to the
processing of negative and non-negative stimuli depending on current anxious mood. At
216
present, however, the findings observed in this thesis must be limited to patterns of
attention in individuals who differ in general vulnerability to anxious mood.
The key findings of this dissertation were based on tasks that exclusively
employed lexical information, with the critical stimuli being negative and non-negative
words. Of course, the purpose of the current research was to resolve alternative
explanations of attentional bias in anxiety which have been demonstrated in past research
using lexical information making this the appropriate material for use in the present
studies. There were also a number of practical advantages to using these stimuli in the
present experimental tasks. In the current research program the majority of tasks (with the
exception of Experiment 1) included a stimulus that could require processing of its
content and a measure of the speed with which that content could either be engaged with
and/or disengaged from. With lexical representations, the nature of the content is readily
contained within a single stimulus and there are tasks which readily enable measurement
of the speed to access the representation of that information (e.g. lexical decision). Word
stimuli therefore provided an appropriate stimulus that fulfilled these experimental
requirements.
Not only did lexical stimuli provide an appropriate stimulus for use in these
assessment tasks, but it is worth noting that a large amount of information that we obtain
naturally is conveyed lexically, either through written material or verbal communication.
Researchers have estimated that between 50% and 80% of the workday is spent
transmitting or receiving verbal information, either through text or spoken language
(Klemmer & Snyder, 1972). Other research has found that the amount of time spent on
„information behaviour‟ (using printed media, computers, personal communication and
visual media) is in excess of 7 hours a day (Suzuki, Hashimoto, & Ishii, 1997).
217
Considering the considerable amount of time devoted to expressing or receiving written
or verbal lexical information and the amount of information conveyed in this form, the
use of lexical stimuli could therefore be considered highly appropriate. Nevertheless, this
does not mean that future research should neglect to examine biases in attentional
engagement with and disengagement from non-lexical information.
In considering types of stimuli that could be adapted for use in tasks assessing
biased attentional engagement with and disengagement from emotional material, an
obvious alternative is pictorial stimuli. Using pictorial stimuli which convey negative or
non-negative information could potentially yield different effects to those obtained in the
current research. Constructing a task capable of measuring attentional engagement with
and disengagement from such information could prove challenging. To ensure
participants processed these stimuli, and to obtain a measure confirming that this was
achieved, decisions regarding content would need to be uncomplicated and readily
performed on the stimulus. This itself could necessitate a contrivance of pictorial stimuli
which may undermine the ecological validity derived from using such stimuli in the first
place. Such a dilemma essentially reflects the tradeoff between isolating and measuring a
construct under contrived circumstances, and accurately approximating the conditions as
they occur naturally, whereby the closer approximation of naturalistic conditions often
leads to a diminished capacity for control that compromise measurement of the critical
processes under consideration.
It would be possible, however, to design a task measuring biased attentional
engagement with and disengagement from emotional content that could employ non-
lexical stimuli. Such a variant could include pictorial stimuli, such as faces whose
expressions differ in emotional tone to convey either negative (e.g. angry) or non-
218
negative meanings (e.g. happy). Indeed, variants of the traditional probe task utilising
negative and non-negative face stimuli have obtained results consistent with past probe
methodologies using word stimuli, demonstrating that individuals more vulnerable to
anxious mood show disproportionate speeding to detect probes appearing in the locus of
faces conveying negative expressions relative to faces showing non-negative expressions
(e.g. Pishyar, Harris, & Menzies, 2004; e.g. Santesso et al., 2008). Variants of the
emotional Stroop task using coloured faces in place of words have also demonstrated
consistent results with traditional Stroop tasks where higher levels of anxiety are
associated with disproportionate slowing to colour-name negative faces (Heim-Dreger,
Kohlmann, Eschenbeck, & Burkhardt, 2006).
To develop a pictorial variant of the emotional Stroop or probe task capable of
assessing biased attentional engagement with or disengagement from emotional content,
it would be necessary to include a means of assessing engagement with the content of
pictorial stimuli. By using face stimuli, such as that outlined above depicting negative
and non-negative emotions, and requiring judgments based on a variable such as age (e.g.
young vs old) it would be possible to infer engagement with the stimulus content.
Requiring participants to make such a judgment based on stimulus content before then
processing a structural (non-emotional) aspect of the image would provide a measure of
attentional disengagement from the content of such stimuli, while processing non-
emotional information before then engaging with the content of the pictorial stimuli
would provide a measure of attentional engagement. While the consistency in past
findings regarding attentional bias and anxiety using both lexical and pictorial stimuli
could encourage speculation that the pattern of results observed in the present series of
experiments may generalise to other, non-lexical information, until this research is
219
replicated with such non-lexical stimuli the implications of the present findings should be
limited to lexical information.
Another aspect of the stimuli used in the current research that must be recognised
is the relatively mild valence of the negative emotional material used. Again, because the
current research was attempting to clarify whether effects demonstrated in past research
could be attributed to alternative accounts of anxiety-linked attentional bias, using stimuli
that was similar in emotional tone to that employed in past research was entirely
appropriate in the present series of studies. Nevertheless, it is readily apparent that these
word stimuli are not likely to be highly evocative in terms of anxiety responses.
However, in considering the nature of adaptive relative to problematic anxiety, it is
apparent that stimuli which conveys moderately negative emotional tone may be
preferable than highly negative stimuli when examining individual differences in anxiety
vulnerability. It will be recalled from the introduction that the function of adaptive
anxiety is to anticipate and avoid potentially adverse events or situations. Identifying
genuine sources of threat in the environment is therefore likely to be highly adaptive to
avoiding negative consequences associated with these. Alternatively, problematic anxiety
is tending to become anxious in response to material that only mildly represents threat.
Indeed, diagnostic criteria for some anxiety pathology specify that the level of anxiety
experienced is disproportionate to the actual level of threat. In order to receive a
diagnosis of Specific Phobia for example, an individual must experience “marked and
persistent fear that is excessive or unreasonable” (American Psychiatric Association,
1994, p. 449).
Based on this understanding of adaptive versus problematic anxiety, it could be
anticipated that highly threatening or intensely negative stimuli might elicit similar
220
affective and cognitive responses across all individuals, because detecting genuine
sources of threat will be highly functional. Problematic anxiety may involve
disproportionate attention to, and disproportionate anxiety responses to, only relatively
mild negative information. Therefore, if research seeks to examine the basis of the
individual differences in anxiety vulnerability then it makes sense to be using only mildly
negative stimuli that will differentiate responses across individuals with high and low
levels of anxiety vulnerability. Highly negative stimuli may instead produce a consistent
attentional response for all individuals.
While this logic suggests that the use of more strongly negative stimuli may be
less effective in eliciting individual differences in information processing biases, the
question remains however, as to whether similar results would be obtained in the current
research with more extremely negative stimuli. There are empirical reasons to believe
that such materials may be less effective in eliciting valenced-linked information
processing biases than moderately negative stimuli. Wilson and MacLeod (2003)
conducted a study aimed at examining whether stimuli that systematically varied in terms
of threat value would elicit different patterns of selective attention for high and low trait
anxious individuals. Using a probe task methodology, their study suggested that for
stimuli with very low and very high threat value, high and low trait anxious individuals
did not significantly differ in their pattern of attention, with both groups attending away
from stimuli with very low threat value and toward stimuli with very high threat value. It
was only for stimuli with intermediate threat value that the participants demonstrated a
different pattern of attention, with results suggesting that low trait anxious individuals
attended away from such moderately threatening stimuli and high trait anxious
individuals attended toward them. While these results lend credence to the argument that
221
moderately negative stimuli are more likely to elicit individual differences in information
processing biases, it is true that we do not know if there are anxiety-related differences in
the more specific processes of biased attentional engagement with or disengagement from
more extremely negative stimuli. The conclusions drawn in the present research program
cannot yet be extended beyond the mild to moderately negative stimuli employed in the
current series of studies.
An additional limitation of the current research, concerns the nature of the
experimental measures gathered in the current research program. The key measures of
selective information processing were based only on reaction-time data. In these studies,
reaction time data provided an appropriate measure of the speed with which participants
processed information in a given location or, processed a particular stimulus dimension,
which allowed us to infer speed of allocation of attention across different stimuli and
participant groups. Depending on the structure of the experimental task, reaction time
measures can reveal and distinguish many different types of processes, including implicit
and explicit memory (Bradley, Mogg, & Williams, 1995), biases in processing
ambiguous information (Richards & French, 1992), acquisition of conditioned responses
(Hermans et al., 2005), and the effects of medication on task performance (Tucha et al.,
2006) to name merely a few.
While reaction time data can yield useful information for many different
empirical questions, there are other measures of attentional distribution that also could
potentially be used to assess anxiety-linked biases in attentional engagement and
disengagement, and it would be useful to establish whether similar conclusions would be
warranted from studies using such measures. One such methodology could involve
tracking an individual‟s foveal vision when presented with various visual stimuli, to
222
assess dimensions of eye gaze such as initial shift direction or „orienting response‟ and
the length of dwell time on particular stimuli. Using such techniques researchers have
demonstrated that when presented with a stimulus array containing a number of words,
one of which is negative in valence, individuals with clinical levels of anxiety
(Posttraumatic Stress Disorder) preferentially fixate on negative stimuli as compared to
controls (Bryant, Harvey, Gordon, & Barry, 1995). Such eye tracking methodology has
also been used with variants of the traditional dot probe task. Mogg, Millar, & Bradley
(2000) demonstrated that on such a task, clinically anxious individuals (Generalised
Anxiety Disorder) were more likely to demonstrate initial eye movement in the direction
of negative stimuli as compared to controls. While the design of their study was not
constructed to differentiate attentional engagement and disengagement processes, their
finding that clinically anxious individuals preferentially orient eye-gaze toward the locus
of negative material could be considered indicative of selective engagement with such
stimuli. Clearly such eye tracking methodology could readily be combined with the kinds
of experimental tasks developed for use in the current research program, to provide
converging support for conclusions regarding biased attentional engagement with and
disengagement from emotional material. Future research examining these processes is
therefore likely to benefit from the inclusion of such techniques.
While eye movement research may provide converging evidence to compliment
other sources, such as those obtained from reaction-time data, it should be noted that
measures of eye gaze do not necessarily provide a superior means of assessing attentional
distribution. There is considerable research to suggest that, while visual attention and eye
gaze are closely related, individuals can readily attend to information that is not the
current focus of foveal vision and conversely, that information that is the focus of foveal
223
vision is not always the focus of attention. Indeed, early research by Posner (1980, Posner
et al., 1987) was explicitly designed to assess the cueing of attention in the absence of eye
movements and demonstrated that this could readily be achieved. Therefore, while eye-
gaze data would provide useful, complimentary evidence to the information gained from
reaction time studies, such studies would not be without their own limitations.
The various limitations outlined above serve to identify potential avenues for
future research. In addition to these it will also be the role of further research to
determine the relative reliability of the task designs employed in the present series of
experiments and whether the observed findings will generalise. Should it be the case that
such research demonstrates converging support for the pattern of effects observed in the
current research program, using different sample populations, stimulus materials, and
assessment methodologies, then the clear implication would be that vulnerability to
anxious mood is characterised by biased attentional engagement with the emotional
content of negative as compared to non-negative material.
Concluding Comments
The current research program introduced a number of novel task variants to
address the question of whether the anxiety-linked attentional bias favouring negative
stimuli reflects Biased Attentional Engagement with or Biased Attentional
Disengagement from negative stimuli. The key finding arising from studies which
revealed an anxiety-linked attentional bias was that high trait anxious individuals show
facilitated attentional engagement with the content of negative stimuli. Alternatively, the
present series of studies consistently failed to find evidence to support the presence of an
anxiety-linked attentional disengagement bias. Thus, the present findings provide support
224
for the role of biased attentional engagement with negative information in the patterns of
attentional selectivity that characterise heightened anxiety vulnerability, and identify a
number of potentially fruitful avenues for future inquiry.
225
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240
APPENDIX A
STIMULUS SET USED IN EXPERIMENT 1: NEGATIVE AND NON-NEGATIVE
WORDS WITM MEAN NEGATIVITY AND RELEVANCE RATINGS WITH LENGTH
MATCHED NON-WORDS
Negative Words
Word Non-Word Pair Mean Relevance Mean Valence
AGGRESSIVE ZWYGPRNBLZ 2.57 2.29
ALONE XZBRT 3.79 1.93
ATTACKS RMNZKPW 2 1.79
BRUTAL VKWRZB 1.21 1.64
CANCER ZRYWKB 2.86 1.57
CONDEMN OKWBMNZ 2 1.79
CRISIS JGWBNK 2.21 2.07
CRITICISE YRBWKLZXD 3.43 2.21
CRUEL LFGPQ 2.71 2
DAMAGE QTNPRB 1.71 2.57
DANGER SWBZGR 3.36 1.85
DEATHBED KVWBGMDP 2.5 1.5
DESPISED HNPWKDNF 2.14 1.86
EMERGENCY YLZGWKRQP 2.57 2.14
EVIL MGBN 1.5 1.64
FAIL NQZF 4.36 2.21
FATAL FJSKW 2.21 1.64
FEAR PZWD 2.36 2.07
FEARFUL GMJBZQR 2.07 2.14
GRAVE TBWGR 1.5 2.14
GRIEVING BZWRNMQV 1.93 1.93
HOSTILE TJKBWMF 3.36 2.14
HUMILIATED JBMGZVRDFP 2.86 1.57
HURT OBZF 3.71 2.29
IGNORED WPVGBFN 4.07 2.14
241
Negative Words Continued
LOATHED VQPWXZB 2.14 2
LOST ZUMB 3 1.93
MISERY FXCPZY 2.86 2.14
PAIN VTST 2.93 2.21
PETRIFIED QXZPVRFYB 1.93 2.21
POWERLESS SZPFKQMWN 4.36 2.07
PREJUDICE XZRBWNVHY 3.86 1.79
REJECTED LMFVKPDG 4.07 1.93
RIDICULE MFPWJGTN 3.07 2.07
SHAMEFUL DKGBMZRL 2.79 2.14
SORROW WBXYMZ 2.36 2.07
STRANGLED BFCWHNZLD 2.29 1.57
STRESS YHDCBL 5.57 2.07
SUFFER KXBZWQ 3.07 1.85
SUFFOCATING PFZDBQWZUNF 2.43 1.64
SUICIDE KDINGFP 2.29 1.07
TERROR PVNXDJ 2.21 2
THREAT CJRDQN 2.14 2.07
TORMENTED SPBQHMVKJ 2.21 1.71
TRAGEDY WZYQVMP 1.93 1.64
TRAUMA HVPBQR 1.86 2.07
UNHAPPY RZQBMVH 3.64 2.21
USELESS ZFTPBMQ 2.86 1.86
242
Neutral Words
Word Non-Word Pair Mean Relevance Mean Valence
ILLUSTRATE YOBFHQMZCL 0.5 4.21
WOMEN NFPWH 2.5 4.29
PHYSICS SWPGNFV 0.71 3.14
SPONGE NPKWRT 0.21 4.21
SADDLE QSMVXR 0.64 4.07
HOPPING TZXVQMF 0.5 4.21
PRODUCE CMRSKNM 0.57 4.21
DELICIOUS GFQDLWZTN 1.57 6.29
ONION XHDVM 0.07 4.14
CAMPUS DPHQMF 1.71 4.21
LEAGUE ZWRHFJ 0.36 4.14
SOFTNER JHCBTSYM 0.14 4.36
TOMATOES LXRMSQBG 0.79 4.14
LISTENING VBDWGSMLH 3.71 5
HILL FBHS 0.5 4.29
EARS RQBW 0.71 4.07
CROWN CVNPX 0.79 4.57
NOTE SZMH 0.5 4.14
POSTURE DFBMUXG 1.93 4
STEMS MZXVP 0.07 4.36
HALLMARK NRVZWJDS 0.14 4.21
ROLLING TVBZHFX 0.21 4.14
WATERPROOF BQHFXRTMWP 0.21 4.21
CORE GPMF 0.07 4.21
LIGHTED NWZHQVY 0.57 4.57
FILTERS WPRZHDC 0 4
READ YCLQ 1.64 4.29
ANCHOR LXBNJF 0.29 4
LAWS ZRQF 1.93 4.15
243
Neutral Words Continued
JUNCTURES YJGKQSZMW 0.43 4
MULTITUDE WTCZMPFHN 0.79 4
FRAMEWORK PZLFMQNTW 0.5 4.14
QUANTITY FZRHQPNQ 0.43 4.21
BANNISTER XFHBZNPVT 0.14 4.07
LEAPFROG HZLFWMBX 0.14 4.36
CHEESE TPFQZM 0.21 4.21
SIGNATURE RQSZMWVPF 0.07 4
CITIES JXFZPW 1.07 4.29
PARKED MDQBVH 0.29 4.07
CONSTITUENT SZBWQFMHTPG 0.29 4.14
SUMMERS OSWUTVJ 1.36 5.36
PUPILS GZMFLT 0.57 4
VARIED NZLBYP 0 4.43
MYTHOLOGY BPZRQMFTW 0.64 4.5
REQUEST KWFPMDR 1.07 4.5
ENJOIN CPDVLT 0 4.21
BRIDGES JTMQSPF 0.79 4.29
FLOWING GZRNXQT 0.57 4.86
244
APPENDIX B
REVISED STIMULUS SET: NEGATIVE AND NON-NEGATIVE WORDS WITH LENGTH
MATCHED GRAPHEMICALLY LEGITIMATE NON-WORDS USED IN EXPERIMENT 2
Negative/Non-Word Pairs Non-Negative/Non-Word Pairs
AGGRESSIVE GRAVASEGIS ANCHOR RHANCO
ALONE NELOA BANNISTER NISTRABEN
ATTACKS SKACTAT BRIDGES SRIBEOG
BRUTAL TARLUB CAMPUS PUCSAM
CANCER ARCNEC CHEESE ESHECE
CONDEMN DONNCEM CITIES STICIE
CRISIS SCIRIS CONSTITUENT STINOCTUNET
CRITICIZE TIRCISECI CORE ECRO
CRUEL ERLUC CROWN WROCN
DAMAGE MAGEDA DELICIOUS ILIDESUCO
DANGER GADRNE EARS RESA
DEATHBED TEDDAHEB ENJOIN JOENIN
DESPISED SPEDDISE FILTERS STRILFE
EMERGENCY GRECYNEME FLOWING GIFLONW
EVIL ILVE FRAMEWORK WAFREMROK
FAIL LAFI HALLMARK KRAHLMAL
FATAL TAFLA HILL LIHL
FEAR ERAF HOPPING PHINPOG
FEARFUL RELAFUF ILLUSTRATE LIRTALUTES
GRAVE AVERG JUNCTURES JENCURTUS
GRIEVING VEIGNIRG LAWS ASWL
HOSTILE LISHOTE LEAGUE AGULEE
HUMILIATED TUMHILIADE LEAPFROG GROFPALE
HURT TRUH LIGHTED DEGHILT
IGNORED ROGEDIN LISTENING TILNENGIS
LOATHED DOTLAEH MULTITUDE MITTULUDE
245
Negative/Non-Word Pairs Continued Non-Negative/Non-Word Pairs Continued
LOST SOTL MYTHOLOGY GHOMYLOTY
MISERY IRMSEY NOTE ENOT
PAIN NAPI ONION NOINO
PETRIFIED IFIPETRED PARKED KRADEP
POWERLESS SELWROSEP PHYSICS SHYCIPS
PREJUDICE UDREJICPE POSTURE RUSPOTE
REJECTED JERTEDCE PRODUCE CREPUDO
RIDICULE LUCIRDIE PUPILS SLUPIP
SHAMEFUL MAFESHLU QUANTITY NATIQUYT
SORROW WROSOR READ ERDA
STRANGLED DARSTNELG REQUEST QUETRES
STRESS ASESSR ROLLING LIRGNOL
SUFFER FRUSFE SADDLE DLASED
SUFFOCATING OFSUCTAFING SIGNATURE NAGITUSER
SUICIDE DUISICE SOFTENER ROSFNETE
TERROR RERTRO SPONGE PEGONS
THREAT ERTATH STEMS MESTS
TORMENTED MERONTTED SUMMERS MEMSRUS
TRAGEDY GARYDET TOMATOES MOOTEAST
TRAUMA AMURTA VARIED DRAIVE
UNHAPPY PHAYNUP WATERPROOF FOWPRORETA
USELESS SUSLESE WOMEN MEWNO
246
APPENDIX C
ADDITIONAL NON-WORD/NON-WORD AND WORD/WORD STIMULI USED IN
EXPERIMENT 3
Non-Word/Non-Word Pairs Word/Word Pairs
ANOTEQUI PSYHOMNY ABDOMEN COMPOSE
BLERMUP GISTNAC ABOARD PARADE
BONADEM SOOPMEC ALLOCATION REFLECTING
CHAMSUTE TILLCOYA ALLOTMENT SELECTION
CINIPC MELUHI BOAT WINE
CLUHN ESADL BRANCH POLAND
CRABNH NADLOP BRASS LODGE
DITHR LATEB CLIMATE TANGENT
DRIVAYEN HOBKODAN COTTAGE OPTICAL
EGTA HAWS DRUMMING GENERATE
ESEWP WRAST DUPLICATE RATIONALE
GARCNIT NOBCIME EQUATION SYMPHONY
GENHELTN REEMPUFD FACTOR ASKING
GNAPKIC GNALDRI FOAM ATOM
HISTINH NETILGM GATE WASH
IDEW MARF GRACED UMPIRE
LEMTIY HEPWEN GYMNASTIC ENTOURAGE
LOBMAVE RUNTEEV HOLD DATA
LODH TAAD INSIGHT MELTING
MEERNTAPY RIGOTURGE INSTRUCT FOOTNOTE
MOAF TAMO INTRODUCE SCULPTURE
NETTMOLAL OLEESNICT JACKET NAMELY
NOPEED MEDARC LANTERN VISITOR
NUGRUMIM REENEGAT LENGTHEN PERFUMED
ONCORENI LUPTCUSE LUNCH LEADS
OTBA NIWE MOVABLE VENTURE
247
Non-Word/Non-Word Pairs Continued Word/Word Pairs Continued
PALECUDIT LARITANOE MUSTACHE LOCALITY
RACTOF GISKAN OPENED MARKED
REGCAD REPUMI PACKING DARLING
RENNLAT IRIVSOT PARAPHRASE COLLOQUIAL
RESAPPARAH QUALOOLCIL PASS KING
RODABA REDAPA PASSAGE SPEAKER
SAPEGAS RASEPKE PICNIC HELIUM
SBSRA EDGLO PLUMBER CASTING
SOTALP MUSEDM POSTAL SUMMED
SPEERDOSREC GREALNUTRAC PREDECESSOR RECTANGULAR
SPSA GINK PRETTY SEASON
TACALOIONL GNERECLIFT PROTOTYPE INCLUSION
TAJECK NYEALM QUOTATION LETTERING
TAMSICGNY TEENOARGT REPAYMENT OUTRIGGER
TILEMAC TENANGT SMOOTH GOLDEN
TOGCATE TOPILAC SUBTLE JERSEY
TOOQUINOA TEELTGRIN SWEEP STRAW
TOSOHM NELDOG THIRD TABLE
TREPTY OSSNEA TIMELY NEPHEW
TROOPYEPT CONNISULI TRACING COMBINE
TUSLEB SYJEER VINEYARD HANDBOOK
URSTTCIN TENOOTOF WIDE FARM
248
APPENDIX D
WORD STIMULI, PART OF SPEECH CLASSIFICATION CATEGORY AND CORRECT
RESPONSES USED IN EXPERIMENT 4
Negative Words
Word
Part of speech
category 1 Correct Answer
Part of speech
category 2 Correct Answer
AGGRESSIVE Verb No Noun No
ALONE Noun No Adjective Yes
ATTACKS Verb Yes Noun Yes
BRUTAL Noun No Verb No
CANCER Verb No Noun Yes
CONDEMN Verb Yes Noun No
CRISIS Verb No Noun Yes
CRITICISE Verb Yes Noun No
CRUEL Noun No Verb No
DAMAGE Verb No Noun Yes
DANGER Noun Yes Verb No
DEATHBED Noun Yes Adjective Yes
DESPISED Noun No Adjective No
EMERGENCY Adjective Yes Noun Yes
EVIL Verb No Noun No
FAIL Noun No Verb Yes
FATAL Adjective Yes Noun Yes
FEAR Noun Yes Adjective No
FEARFUL Verb No Adjective Yes
GRAVE Verb No Adjective Yes
GRIEVING Noun No Adjective No
HOSTILE Noun Yes Adjective Yes
HUMILIATED Verb Yes Noun No
HURT Noun Yes Verb Yes
249
Negative Words Continued
Word
Part of speech
category 1 Correct Answer
Part of speech
category 2 Correct Answer
IGNORED Noun Yes Adjective No
LOATHED Noun No Verb Yes
LOST Adjective Yes Verb Yes
MISERY Verb No Noun Yes
PAIN Noun Yes Verb No
PETRIFIED Verb Yes Noun No
POWERLESS Verb No Noun No
PREJUDICE Verb No Noun Yes
REJECTED Noun Yes Verb No
RIDICULE Verb Yes Noun Yes
SHAMEFUL Verb No Adjective Yes
SORROW Noun Yes Verb No
STRANGLED Noun No Verb Yes
STRESS Noun Yes Verb No
SUFFER Verb Yes Noun No
SUFFOCATING Verb Yes Noun No
SUICIDE Noun Yes Verb No
TERROR Verb No Noun Yes
THREAT Noun Yes Verb Yes
TORMENTED Verb No Adjective No
TRAGEDY Verb No Noun Yes
TRAUMA Noun Yes Verb No
UNHAPPY Noun No Verb No
USELESS Verb No Adjective Yes
250
Non-Negative Words
Word
Part of speech
category 1 Correct Answer
Part of speech
category 2 Correct Answer
ILLUSTRATE Adjective No Noun No
WOMEN Noun Yes Verb No
PHYSICS Noun Yes Verb No
SPONGE Adjective No Verb No
SADDLE Noun Yes Verb No
HOPPING Verb Yes Noun No
PRODUCE Verb Yes Noun Yes
DELICIOUS Verb No Adjective Yes
ONION Noun Yes Verb No
CAMPUS Verb No Adjective No
LEAGUE Verb No Noun Yes
SOFTNER Verb No Noun Yes
TOMATOES Verb No Noun Yes
LISTENING Verb Yes Noun No
HILL Adjective No Verb No
EARS Verb No Noun Yes
CROWN Noun Yes Verb No
NOTE Noun Yes Verb No
POSTURE Verb Yes Noun Yes
STEMS Verb No Noun Yes
HALLMARK Verb No Noun Yes
ROLLING Adjective Yes Verb Yes
WATERPROOF Verb No Adjective Yes
CORE Noun Yes Adjective Yes
LIGHTED Noun Yes Verb Yes
FILTERS Noun Yes Verb No
READ Noun No Verb Yes
251
Non-Negative Words Continued
Word
Part of speech
category 1 Correct Answer
Part of speech
category 2 Correct Answer
ANCHOR Verb No Noun Yes
LAWS Verb No Adjective No
JUNCTURES Verb No Noun Yes
MULTITUDE Verb No Adjective No
FRAMEWORK Noun Yes Verb No
QUANTITY Noun Yes Verb No
BANNISTER Noun Yes Verb No
LEAPFROG Noun Yes Verb No
CHEESE Noun Yes Verb No
SIGNATURE Noun Yes Verb No
CITIES Verb No Noun Yes
PARKED Noun No Adjective No
CONSTITUENT Adjective Yes Noun Yes
SUMMERS Verb No Noun Yes
PUPILS Verb No Noun Yes
VARIED Verb No Adjective Yes
MYTHOLOGY Verb No Adjective No
REQUEST Verb Yes Noun Yes
ENJOIN Verb Yes Noun No
BRIDGES Verb No Noun Yes
FLOWING Verb Yes Noun Yes