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THE EFFECTS OF ANTECEDENT EXERCISE ON STUDENTS’ DISRUPTIVE BEHAVIOURS: AN EXPLORATORY ANALYSIS OF TEMPORAL EFFECTS AND
MECHANISM OF ACTION
by
Anthony Folino
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Human Development and Applied Psychology Ontario Institute for Studies in Education
University of Toronto
© Copyright by Anthony Folino 2011
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The Effects of Antecedent Exercise on Students’ Aggressive and Disruptive Behaviours:
Exploratory Analysis of Temporal Effects and Mechanism of Action
Anthony Folino
Doctor of Philosophy
Department of Human Development and Applied Psychology University of Toronto
2011
Abstract
Low autonomic arousal, as measured through resting heart rate, has been shown to be one
of the best-replicated biological correlates of antisocial and aggressive behaviour. According to
the stimulation seeking theory, low arousal represents an unpleasant physiological state. In line
with this theory, antisocial individuals purposely engage in antisocial and aggressive acts in an
attempt to increase stimulation and achieve more agreeable arousal levels. If, as the stimulation
seeking theory suggests, the function of antisocial behaviour is to increase physiological arousal
levels, exposing antisocial individuals to functionally equivalent forms of arousing situations
(e.g., aerobic exercise) should result in a reduction in aberrant conduct. Although a growing body
of literature indicates that antecedent exercise is effective at reducing antisocial and aggressive
behaviours, the present investigation sets out to explore two fundamental questions about this
approach that remain unclear. First, there is a paucity of research examining the temporal effects
of antecedent exercise. Secondly, little is known about the mechanism of action accounting for
behavioural improvements following exercise.
The present investigation involved 4 students (age range 11-14) enrolled in a closed
behavioural classroom due to severe aggressive, disruptive, and oppositional behaviours.
Through the use of an alternating treatment design with baseline, students were first exposed to
iii
baseline conditions and then to two experimental conditions, (i.e., an antecedent exercise
condition and a control condition) in a randomized fashion. Results indicated that 30 minutes of
moderate to intense aerobic exercise resulted in approximately 90 minutes of behavioural
improvements. In addition, results suggest an inverse relationship between arousal levels and
behavioural difficulties. The potential utility of antecedent exercise as a treatment alternative in
schools for students with severe antisocial behaviours is discussed.
iv
Acknowledgments
This research endeavor would not have been possible without the support of several
individuals. To the students involved in this study, thank you for your enthusiastic participation.
I hope that you learned as much from this experience as I learned from each of you. To my
research assistants, without your dedicated involvement, I would not have been able to obtain the
large volumes of data needed for this project. Thank you all.
To my outstanding supervisor Dr. Joe Ducharme, there are no words to express how
indebted I am for your continued mentorship. You exemplify what excellent supervision is all
about. Please know that your impact in my life extends far beyond the teachings of behavioural
psychology and I am appreciative for all your life lessons. To my committee members Dr.
Peterson-Badali, Dr. Wiener, and Dr.Sugai, your innovative ideas and suggestions helped shape
this dissertation projects in several important ways.
To my wonderful parents, brothers, nieces, grandparents, aunts, uncles, cousins, and in-
laws, your support and encouragement over the years have been unparalleled. In your own
specials ways you have all contributed to me achieving this important life goal. Thank you all for
believing in me and I hope to have made you all very proud.
Most importantly, to my remarkable and inspirational wife Sarah, this journey would not
have been achievable without your continued love, support, and companionship. Throughout this
process we have grown tremendously and have shared countless memories. When I needed you,
you were always there for me. Countless times you have selflessly put my needs ahead of your
own and made me feel incredibly loved. There truly is no other person I would have rather had
by my side throughout this process. Here’s to many more years of love, laughter, and memories.
v
Table of Contents
Abstract…………………………………………………………………………………………...ii
Acknowledgements………....…………………………………………………………………….iv
Table of Contents………………………………………………………………………................v
List of Tables …..……………………………………………………....……………………… ix
List of Figures…………………………………………………………………………………...x.
List of Appendices……………………………………………………………………………. xii
Chapter 1: Introduction………………………………………………………………….............13
1.1 Rationale for the Study……………………………………………………………...13
1.2 Childhood Antisocial Behaviour …...……………………………………………….14
1.3 Antisocial Behaviour in Schools ..……..……………………………………………15
1.4 Treatment Approaches for Antisocial Behaviours…………………………………..16
1.5 New Treatment Directions for Antisocial Behaviour……………………………….18
1.6 The Etiology of Antisocial Behaviour: Biological Contributions…………………..20
1.6.1 Androgens………………………………………………………………20
1.6.2 Hypothalamic-pituitary-adrenal axis activity and Cortisol……………..24
1.6.3 Neurotransmitters……………………………………………………….26
1.6.4 Serotonin (5-HT)……………………………………………………..…26
1.6.5 Norepinephrine (NE)……..…………………………………………..…27
1.6.6 Dopamine (DA)…………………………………………………………28
1.7 Neurophysiological Impairments and Antisocial Behaviour: Frontal Lobe and Executive Functioning Deficits……………………………………………………...28
1.8 Autonomic Nervous System functioning…………………………………………....30
1.9 Resting Heart Rate and the Intergenerational Transmission of Antisocial Behaviours………………………………………………………………………..…33
1.10 How Low Heart Rate May Predispose to Aggressive and Antisocial Behaviour …………………………………………………………………………34
vi
1.11 Stimulation Seeking Theory……………………………………………………….35
1.12 Underarousal and Aggression: Potential Treatment Implications…………………35
1.13 Summary and Rationale for the Current Investigation…………………………….38
1.14 Research Questions and Hypotheses………………………………………………40
1.14.1 Replication ………………………………………………………….….40
1.14.2 Temporality….………………………………………………………….41
1.14.3 Mechanism of Action………………………………………………..….41
Chapter 2: Method……………………………………………………………………………….42
2.1 Participants……………………..………...………………………………………….42 2.1.1 Participant 1 (Bobby)……………………………………………………..42
2.1.2 Participant 2 (Kyle)……………………………………………………….42
2.1.3 Participant 3 (Dan)………………………………………………………..43
2.1.4 Participant 4 (Tom)……………………………………………………….43
2.2 Classroom Setting and Staff………………………………………………………..43
2.3 Research Design…………………………………………………………………….44
2.4 Data Collection and Interobserver Agreement……………………………………...44
2.4.1 Observer Training ...…………………………………..………………….44
2.4.2 Observation Sessions……………………………………………...............44
2.5 Measures…………………………………………………………………………….46
2.5.1 General Health Screener…………………………………………………..46
2.5.2 Teacher Ratings…………………………………………………………...46
2.5.3 Observational Measures ...………………………………………………..47
2.5.4 Disruptive Behaviours………………………………………………….…47 2.5.5 Prosocial Behaviours………………………………...................................47
2.5.6 Compliance to Teacher Requests…………………………………………48
2.5.7 Physiological Measures of Arousal……………………………………….48
2.5.8 Resting Heart Rate………………………………………………………..49
2.5.9 Heart Rate during Exercise and Control Sessions………………………...50
2.5.10 Heart Rate during Observational Periods………………………………..50
2.5.11 Target Heart Rate Zone………………………………………………….51
vii
2.5.12 Self-Report Measures ...…………………………………………………52
2.6 Procedures…………………………………………………………………………..53
2.6.1 Baseline…………………………………………………………………...53
2.6.2 Antecedent Exercise Condition (10 sessions)…………………………….54
2.6.3 Control Condition (9 sessions)…………………………………………...55
Chapter 3: Results……………………………………………………………………………….57
3.1 General Health Screener……………………………………………………............57
3.2 Emotional and Behavioural Functioning ..………………………………………....57
3.2.1 Participant (Bobby)……………………………………………………….57
3.2.2 Participant 2 (Kyle) …………………………………………………..…..58
3.2.3 Participant 3 (Dan)………………………………………………………..58
3.2.4 Participant 4 (Tom) …..…..…….…………………………….……….….58
3.3 Resting and Target Heart Rate (THR)………………………………………………58
3.4. Effects of Antecedent Exercise on Behavioural Functioning……………………...59
3.5. Overall Effects of Antecedent Exercise on Behavioural Functioning……………..60
3.5.1 Disruptive Behaviours………………….…………………………………60
3.5.2 Prosocial Behaviours………………………………………………….…..63
3.5.3 Compliance to Teacher Requests ……………………………………..….66
3.6 Effects of Antecedent Exercise (Temporal Effects)…………………………………69
3.6.1 Disruptive Behaviours…………………………………………………….69
3.6.2 Prosocial Behaviours …………………………………………………..…73
3.6.3 Compliance to Teacher Requests…………………………………………76
3.7 Heart Rate Levels During Exercise and Control Conditions .......………………….79
3.8 Heart Rate Levels during Observational Sessions………………………………….80
3.8.1 Participant 1 (Bobby)……………………………………………………..80
3.8.2 Participant 2 (Kyle)……………………………………………………….80
3.8.3 Participant 3 (Dan)………………………………………………………..80
3.8.4 Participant 4 (Tom)……………………………………………………….81
3.9 Correlational Analysis…………………………………………………………..….83
3.9.1 Participant 1 (Bobby)…………………………………………………..…83
3.9.2 Participant 2 (Kyle)…………………………………………………….…84
3.9.3 Participant 3 (Dan)…………………………………………………….….85
3.9.4 Participant 4 (Tom)..…..………………………………………………….86
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3.10 Self-Report Measures………………………………………………………….….88
3.10.1 Bored/Excited Scale…………………………………………………….88
3.10.2 Tired/Full of Energy Scale……………………………………………...89
3.10.3 Tense/Relaxed Scale……………………………………………….……90
Chapter 4: Discussion……………………………………………………………………………92
4.1 Replication of Previous Findings………………………..………………………….92
4.2 Temporal Effects……………………..……………………………………………..92
4.3 Mechanism of Action …..………………………………..…………………………94
4.3.1 Evidence from Physiological Data …………………………………..….94
4.3.2 Evidence from Self-report Data………………………………………….95
4.4 Implications…………………………………..……………………………………..96
4.4.1 Ruling out Competing Mechanism …..………………………………….96 4.4.2 Potential Generalizability of Antecedent Exercise…………………….…97
4.4.3 Clinical Implications: Antecedent Exercise as a Moderating
Approach………………………………………………………………….99
4.4.4 Implications for Schools and Educators…….………………………….101
4.5 Limitations and Future Directions......….……….…………………………………102
References………………………………………………………………………………............106
ix
List of Tables
Table 1: Resting and Target Heart Rates……………………………………………………59
Table 2: Correlations among Behavioural and Physiological Measures for Participant 1 (N=17)………………………………………………………………………..…….84
Table 3: Correlations among Behavioural and Physiological Measures for Participant 2 (N=17)…………………………………………………………………………..….85
Table 4: Correlations among Behavioural and Physiological Measures for Participant 3 (N=19)……………………………………………………………………………...86
Table 5: Correlations among Behavioural and Physiological Measures for Participant 4 (N=19)…………………………………………………………………………..….87
x
List of Figures
Figure 1: Frequency of disruptive behaviours for all baseline, control, and exercise sessions…………………………………………………………………………..62
Figure 2: Overall mean frequency of disruptive behaviours across baseline, control, and exercise conditions……………………………………………………………....63
Figure 3: Frequency of prosocial behaviours for all baseline, control, and exercise sessions…………………………………………………………………………..65
Figure 4: Overall mean frequency of prosocial behaviours across baseline, control, and exercise conditions……………………………………………………………….66
Figure 5: Percent compliance to teacher requests across all baseline, control, and exercise sessions……………………………………………………………………..……68
Figure 6: Overall percent compliance to teacher requests across baseline, control, and exercise conditions……………………………………………………………….69
Figure 7: Frequency of disruptive behaviours across all baseline, control, and exercise sessions. X axis represents session number and Y axis represents the frequency of disruptive behaviours …...…………………………………………………….72
Figure 8: Mean frequency of disruptive behaviours for baseline, exercise, and control conditions across T1, T2, T3, and T4 ………..………………………………….73
Figure 9: Frequency of prosocial behaviours across all baseline, control, and exercise sessions. X axis represents session number and Y axis represents the frequency of prosocial behaviour…………………………………………………………....75
Figure 10: Mean frequency of prosocial behaviours across all baseline, control, and exercise sessions for T1, T2, T3, and T4…..…..………………………………………….76
Figure 11; Percentage of compliance to teacher requests across all baseline, control, and exercise sessions. X axis represents session number and Y axis represents the percent compliance to teacher requests………………………………………..…78
Figure 12: Average compliance to teacher requests for all baseline, control, and exercise conditions for T1, T2, T3, and T4………………………………………………..79
Figure 13: Average heart rate levels while engaged in experimental conditions……………79
Figure 14: Heart rate during baseline and following experimental conditions across T1, T2, T3, and T4…….…………………………………………………………......82
Figure 15: Overall mean self-report scores for bored/excited visual analog scale………….80
Figure 16: Overall mean self-report scores for tired/full of energy visual analog scale…….90
xi
Figure 17: Overall mean self-report score for tense/relaxed visual analog scale………….91
xii
List of Appendices
Appendix A: General Health Screener………………………………………………………..134
Appendix B: SPORTLINE Solo 920 Heart Rate Watch ®……………………………….….135
Appendix C: Data recording Sheets for Heart Rate during Experimental Conditions…….…136
Appendix D: Data recording Sheets for Heart Rate during Observational Periods………..…137
Appendix E: Visual Analog Scale (Tense-Relaxed Scale) …………………………..………138
Appendix F: Visual Analog Scale (Tired-Full of Energy Scale)………………………..……140
Appendix G: Visual Analog Scale (Bored-Excited Scale)…………………………………....142
Appendix H: Behavioural Coding Sheet……………………………………………………...144
Appendix I: Mann-Whitney U Test Statistics………………………………………………..146
13
Chapter 1: Introduction
1.1 Rationale for the Study
Antisocial behaviour among school-aged children is a major societal and clinical concern.
Notwithstanding extensive efforts to provide support and treatment services to children with such
behavioural repertoires, the prevalence of antisocial behaviour remains high. Advancements in
our understanding of the biological substrates of antisocial behaviour may help us understand
such responding and potentially lead to novel and innovative treatment alternatives. To date, low
resting heart rate is considered one of the best replicated biological correlates of antisocial and
aggressive behaviour. According to the stimulation seeking theory, low arousal represents an
unpleasant physiological state. In line with this theory, antisocial individuals purposely engage in
antisocial and aggressive acts in an attempt to increase stimulation and achieve more agreeable
arousal levels. If the function of antisocial behaviour is to increase physiological arousal levels,
then exposing antisocial individuals to functionally equivalent forms of arousing situations (e.g.,
aerobic exercise) should result in a reduction in maladaptive behaviours.
A substantial body of literature indicates that antecedent exercise (i.e. exercise that is
applied non-contingently with the intent of reducing subsequent disruptive behaviour) is
effective at reducing antisocial and aggressive conduct. The objective of this study is to
investigate two fundamental aspects of antecedent exercise that are not well understood. First,
there is a paucity of research examining the temporal effects of antecedent exercise (i.e., how
long the effects of exercise last). Secondly, very little is known about why exercise results in a
reduction in aberrant behaviours (i.e., the mechanism of action). The present research was
14
designed to further investigate each of these aspects as a means of gaining greater understanding
about antecedent exercise and its biological substrates.
1.2 Childhood Antisocial Behaviour
Childhood antisocial behaviour is a significant social and clinical concern (Scott et al.,
2010; Van Goozen, Fairchild, & Harold, 2008; Mayer, 2001). Youngsters exhibiting chronic
patterns of antisocial behaviour are often identified as having oppositional defiant disorder
(ODD) or conduct disorder (CD) (Reinke & Herman, 2002). ODD is characterized by a recurrent
pattern of negativistic, defiant, disobedient, and hostile behaviour that is directed toward
authority figures (DSM-IV; American Psychiatric Association, 1994). Prominent features of CD
include a repetitive and persistent pattern of behaviour in which the basic rights of others or
major age-appropriate societal norms or rules are violated (DSM-IV; American Psychiatric
Association, 1994). ODD and CD are commonly associated with depression, substance abuse,
and attention deficit hyperactivity disorder and thus often result in a high degree of impairment
(Petermann & Natzke, 2008; Isper & Stein, 2007).
Recent estimates suggest that approximately 5-10% of the general child population meet
diagnostic criteria for ODD or CD (Van Goozen, Fairchild, & Harold, 2008; Stadler, Grasman,
Fegert, Holtman, Poutska, & Schmeck, 2008; Loeber et al., 2000), resulting in one-third to half
of all clinic referrals (Isper & Stein, 2007; Kazdin, 1995) and making child antisocial behaviour
one of the most costly child mental health problems (Kazdin, 2007; Cohen, 1998). Early-onset
antisocial behaviour is an important predictor of major dysfunction and maladjustment in
adolescence and adulthood. Children who exhibit chronic levels of such behaviour prior to age
13 are at increased risk for academic failure and drop-out, violence, unplanned pregnancies,
15
unemployment, substance abuse, depression, suicide, antisocial personality disorder, and
difficulties with interpersonal relationships such as parenting and marriage (Trentacosta, Shaw,
& Cheong, 2009; Van Goozen, Fairchild, & Harold, 2008; Wright, John, Livingstone, Shepard,
& Duku, 2007; Loeber & Farrington, 2000; Ronks & Pulkkinen, 1995; Magnusson, 1992;
Farrington, 1991; Caspi, Elder, & Herbener, 1990).
1.3 Antisocial Behaviour in Schools
Children who engage in antisocial behaviours represent a major challenge in the school
system (Cihak, Kirk, & Boon, 2009) and account for the largest proportion of placements in
special education classes (Knitzer, Steinberg, & Fleisch, 1990). Studies indicate that as many as
20% of students in the primary grades engage in mild but frequent forms of antisocial behaviour
(Wheldall & Merrett, 1988). Despite the high prevalence of these response patterns in schools,
teachers often receive little or no specialized training in behaviour management (Obenchain &
Taylor, 2005) and feel unprepared to deal with these students (Obenchain & Taylor, 2005;
Stromont, Lewis, & Beckner, 2005; Fox, Dunlap, & Cushing, 2002; Gordon, 2001; Silvestri,
2001; Skiba & Peterson, 2000).
When dealing with antisocial and disruptive students, teachers tend to be reactive
(Sherrod, Getch, & Ziomek-Daigle, 2009) and rely on punitive approaches (Skiba & Peterson,
2000; Bear, 1998). Common disciplinary strategies include time-out, exclusion, verbal
reprimands, and suspensions (Geiger, 2000; Bear, 1998). Mounting evidence suggests that the
use of harsh and punitive disciplinary strategies do not result in long-term reduction of
maladaptive behaviours (Sherrod, Getch, & Ziomek-Daigle, 2009; Skiba & Peterson, 2000) and
16
may actually heighten such problems (Doumen, Verschueren, & Buyse, 2009; Sherrod, Getch, &
Ziomek-Daigle, 2009; Safron & Oswald, 2003; Skiba & Peterson, 2000).
Teachers of students with antisocial behaviour often spend a disproportionate amount of
their time and effort addressing disruptive responding instead of academic and teaching tasks
(Sherrod, Getch, & Ziomek-Daigle, 2009; Kulinna, Cothran, & Regualos, 2006; Matheson &
Shriver, 2005; Scates, 2005; Greenwood, 1991). Such behaviour can lead to excessive teacher
stress and burnout, job dissatisfaction, and high attrition rates (Baker, Lang, & O’Reilly, 2009;
Abel & Sewell, 1999; Centre & Callaway, 1999; Frank & McKenzie, 1993; Pullis, 1992; Feitler
& Tokar, 1982). When teachers are stressed, all students in the classroom (those with and
without challenging behaviour) are likely to suffer serious consequences (Bru, 2009). Stressed
teachers may devote less time and energy to job commitment, teacher-pupil rapport, student
motivation, and educational goals (Kulinna, Cothran, & Regualos 2006; Abel & Sewell, 1999).
1.4 Treatment Approaches for Antisocial Behaviours
Given the concerns associated with antisocial behaviour, it is evident that effective
interventions are needed for prevention and treatment. A number of behavioural (e.g., McMahon
& Forehand, 2003; Kazdin, 2003; Barkley & Benton, 1998), cognitive-behavioural (McCloskey,
Noblett, Deffenbacher, Gollan, & Coccaro, 2008; Martsch, 2005; Kendall, Reber, McLeer, Epps,
& Ronan, 1990; Lochman, Lampron, Gremmer, Harris, & Wyckoff, 1989), family (e.g., Markie-
Dadds & Sanders, 2006; Shaw, Dishion, Supplee, Gardner, & Arnds, 2006; Leung et al., 2003;
Webster-Stratton & Hammond, 1997) and multifaceted (e.g., Koegl, Farrington, Augimer &
Day, 2008; Lipman et al., 2008; Webster-Stratton, Reid, & Hammond, 2004) psychotherapeutic
programs have been devised to either prevent or treat early-onset antisocial responding. In
17
addition, several school-based and class-wide interventions have been developed (e.g., Dufrene,
Doggett, Henington, & Watson, 2007; Massey, Boroughs, & Armstrong, 2007; Schechtman &
Ifargn, 2007; Daunic, Smith, Brank, & Penfield, 2006; Smokowski, Fraser, Day, Galinsky, &
Bacallao, 2004).
Although these interventions may result in a range of child gains, significant limitations
have been cited (Baker, Lang, & O’Reilly (2009). First, long-term effectiveness is limited (Van
Goozen et al., 2007; Kazdin, 1997, 1995). Second, notwithstanding demonstrated efficacy in
research settings, generalizations of these interventions to clinical or classroom settings is rarely
established (Scott el., 2005). Third, while there is an abundance of empirically-validated
treatments for children with antisocial behaviour, few have been validated for adolescent
populations (Fossum, Handegard, Martinusssen, & Morch, 2008). Fourth, many of these
interventions are lengthy and require much time and effort to implement (Axelrod, Garland, &
Love, 2009). In fact, the most effective treatments are often the most time-intensive (Wilson &
Lipsey, 2010) and may lead to participant attrition (Fernadez & Eyeberg, 2005). Within the
school setting, psychotherapeutic interventions often demand a great deal of teacher time and
effort to effectively implement (Wagner et al., 2006; Booth & Faribank, 1984) and are therefore
not perceived as practical solutions by teachers and school officials (Boxer, Musher-Eizenman,
Dubow, Danner, & Heretick, 2006).
In addition to psychotherapeutic approaches, pharmacotherapy is frequently considered in
the treatment of children and adolescence with antisocial behaviours (Isper & Stein, 2007).
While there is currently no registered medication for the treatment of maladaptive behaviours
associated with CD or ODD (Isper & Stein, 2007), there has been a dramatic increase in the use
of pharmacological interventions for aggressive, disruptive, violent, and oppositional children
18
(Axelrad, Garland, & Love, 2009). Several different medications have been used for the
treatment of children with conduct difficulties including risperidone (e.g., Pandina, Aman, &
Findling, 2006; Buitelaar, 2000; Findling, McNamara, Branicky, Schluchter, Lemon, & Blumer,
2000; Scheier, 1998), haloperidol (e.g., Campbell et al., 1984), lithium (e.g., Rifkin et al., 1997),
valporic acid (Donovan, Stewart, Nunes, Quitkin, & Parides, 2000; Deltito, Levitan, Damore,
Hajal, & Zambenedetti, 1998) and methylphenidate (e.g., Klein, Abikoff, Klass, Ganeles, Seese,
& Pollack 1997; Gadow, Nolan, Sverd, Sprafkin, & Paolicelli, 1990).
Although pharmacological treatments for children and adolescents have been associated
with varying degrees of success (e.g., see Ipser & Stein, 2007; Bassarath, 2003 for reviews),
several serious concerns have been raised. There may be mild and serious side-effects (Ipser &
Stein, 2007; Wilens, Jefferson, & Biederman, 2006), concerns with long-term safety and efficacy
due to a lack of long-term studies (Oord, Prins, Oosterlaan, & Emmekkamp, 2008; Ipser & Stein,
2007; Bassarath, 2003), and treatment challenges presented by their potential noncompliance to
medication regimens (Charach, Gajaria, Skyba, & Chen, 2008; Charach, Volpe, Boydell, &
Gearing, 2007; Ipser & Stein, 2007 ).
1.5 New Treatment Directions for Antisocial Behaviour
Despite the wide range of psychotherapeutic and pharmacological interventions available,
a number of researchers have emphasized the importance of developing more cost-effective,
safe, and innovative treatment approaches (Scott et al., 2010). As discussed by Carr, Robinson,
and Palumbo (1990), one way to maximize the effectiveness of a treatment is to ensure that it is
“functionally based”. Traditional functional approaches, such as applied behaviour analysis (an
approach to intervention based on operant learning principles), attempt to identify correlations
19
between the behaviour and the environment and involve looking primarily outside rather than
inside the organism to establish functional relations (Thompson, 2007). A hallmark of applied
behaviour analysis is promoting changes in behaviour by carefully modifying various contextual
variables, especially the consequences or outcomes of the responses that contribute to problem
behaviour.
Much research has demonstrated that most problem behaviours occur because they lead
to a more positive environmental outcome for the individual (Conroy & Fox, 1995). Within this
contextualist paradigm, however, some researchers have recognized that these desired outcomes
are sometimes internal to the organism. Skinner (1945), the father of modern applied behaviour
analysis, noted the importance of considering factors “beneath the skin” when examining the
behaviour of an organism. More recently, Thompson (2007) emphasized the potential benefits of
considering endogenous components (especially internal biological factors) when trying to
understand the functions of various behaviours. Thompson (2007) argues that an organism’s
biologically driven processes are intricately related to the behaviours displayed and that this
interplay is influenced by operant principles. To illustrate this point, Thompson (2007) describes
how the biological and genetic abnormalities associated with Prader-Willi Syndrome (PWS)
contribute to the stereotypical behaviours demonstrated by those afflicted with this rare genetic
disorder. PWS is characterized by a specific gene deletion as well as elevated levels of ghrelin (a
specific hormone found in the blood), leading to constant and chronic levels of hunger and
making food a highly potent source of reinforcement. Behaviourally, individuals with PWS have
an insatiable appetite and engage in chronic levels of overeating (Thompson, 2007).
Understanding the disrupted biological state of individuals with PWS allows us to better
understand the function of their frequent eating behaviours.
20
Similar to the case of PWS, investigating disrupted biological mechanisms in individuals
with antisocial behaviours may allow for a better understanding of the various “functions” served
by externalizing conduct. Over the past 15 years there has been much progress in our
understanding of the biological basis of antisocial behaviour (Raine, 2002), potentially providing
the foundation for development of treatment approaches that target key biological substrates
contributing to antisocial behaviours.
1.6 The Etiology of Antisocial Behaviour: Biological Contributions
The etiology of antisocial behaviour is a complex interplay of both environmental and
genetic influences (Hicks, South, DiRago, Iacono, & McGue, 2009). A number of environmental
risk factors have been associated with the development of antisocial behaviours including birth
complications (Raine, 2002), parental divorce (Breivik, Olweus, & Endresen, 2010), single-
parent childrearing (Gagnon, et al., 1995), low socio-economic status (Lahey, et al,. 1988), poor
parental supervision (Frick et al., 1992), and parental psychopathology and criminality (Cadoret,
et al., 1995; Frick et al., 1992). In addition, several biological factors play a role (Van Goozen &
Fairchild, 2008).
1.6.1 Androgens
Androgens are a class of steroid hormones that are more abundant in males than in
females (Kalat, 2001). Testosterone is the major androgen in males and plays a key role in the
development of male reproductive tissues (e.g., testes and prostate) and secondary sexual
characteristics (e.g., muscle and bone mass, hair growth, etc.) (Bagatell & Fairchild 2003, pg.3).
The testes are the source of more than 95% of the circulating testosterone in adult males
(Bagatell & Fairchild, 2003, pg. 3). In addition to testosterone, other major androgens include
21
dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulphate (DHEA-S), androstenedione,
androstenediol, anderosterone, and dihydrotestosterone (Bagatell & Fairchild, 2003, pg 5). Males
have higher concentrations of circulating androgens as well as a higher prevalence of antisocial,
aggressive, and violent behaviours than females (Van Goozen, Fairchild, Snoek, & Harold, 2007;
Pasterski, Hindmarsh, Geffner, Brook, Brain, & Hines, 2007), leading to questions about the
relationship between androgens and antisocial conduct. Notwithstanding the different types of
androgens, testosterone has been the most extensively studied hormone in relation to aggression
and antisociality (Ramirez, 2003).
The relationship between androgens and aggression has been studied extensively in
animals. For the most part, elevated concentrations of androgens in a variety of different species
have been associated with increases in aggressive behaviours (Higley et al, 1993, Brain & Haug,
1992; Higley et al., 1992), although the available findings in humans are more complex. In adults
and older adolescents (between 17 and 18 years of age), elevated levels of testosterone have been
clearly linked with antisocial behaviour and violent crimes (Banks & Dabbs, 1996; Scerbo &
kolko, 1994; Dabbs, Jurkovic, & Frady, 1991; Dabbs & Morris, 1991). In prepubertal children
however, the relationship between testosterone and antisocial and aggressive behaviours does not
appear to be as robust. In a number of well designed studies, researchers have failed to show an
association (Van Goozen, Matthys, Cohen-Kettens, Thijssen, & Van Engeland, 1998;
Constantino et al., 1993), suggesting a need to consider testosterone secretion in a developmental
context.
In typically developing males, testosterone secretion rises in three distinct periods of life.
The first major peak in levels occurs in utero from approximately 2 months of gestation until
birth. The second occurs at approximately 2 months after birth and lasts for a few months. The
22
third and most significant peek in testosterone occurs at puberty (Ramirez, 2003). Thus,
prepubertal children do not have high concentrations of testosterone. In fact, during childhood
(from around age 6 until puberty), children go through a period referred as adrenarche (Van
Goozen, Van den Ban, Matthys, Cohen-Kettenis, Thijssen, & Van Engeland, 2000). In this phase
of life, the androgens in the child’s body are predominately produced by the adrenal cortex and
not the testes (Van Goozen, et al., 2000). Adrenal androgens include DHEA, DHEA-S, and
androstenedione (and not testosterone). Once puberty arrives, gonadal androgens such as
testosterone become much more prevalent in the male body and the levels of adrenal androgens
dramatically decline (Van Goozen et al., 2000). Given the developmental time-line associated
with androgen secretion in males, researchers have started to investigate the relationship between
adrenal androgens (e.g., DHEA, DHEA-S, and androstenedione) and aggressive and antisocial
behaviour among prepubertal children; several studies have found an association (e.g., Maras,
2003; Dmitrieva, Oades, Hauffa, & Eggers, 2001).
For instance, Van Goozen et al. (1998), measured plasma levels of testosterone and
DHEA-S in 15 boys with CD and 25 normal control boys. The two groups of children did not
differ on measures of testosterone; however, boys with CD had significantly higher levels of
DHEA-S compared to the normal controls. Furthermore, results indicated that DHEA-S levels
were significantly positively correlated with the intensity of the children’s aggression and
delinquency. Van Goozen et al. (1998) concluded that adrenal androgen functioning plays an
important role in the onset and maintenance of aggression in young boys. In a more recent study,
Van Goozen et al. (2000) measured DHEA-S in 24 children with ODD, 42 psychiatric controls,
and 30 normal controls. Children with ODD had higher DHEA-S levels than both the psychiatric
23
and normal control groups. DHEA-S levels did not differ between the psychiatric and normal
control groups.
Although several studies have demonstrated an association between increases in adrenal
androgens and child antisocial behaviour, at least one study did not. Constantino et al. (1993)
measured DHEA and DHEA-S in 18 highly aggressive hospitalized prepubertal boys aged 4 to
10. The hospitalized boys were compared to a group of age-and race-matched controls residing
in the same demographic area and were screened negative for aggressive behaviour problems.
There were no significant differences between aggressive and non aggressive boys for either
DHEA and DHEA-S. Based on the findings, Constantino et al. (1993) concluded that androgens
do not appear to be a useful biological marker for aggressivity in early childhood. A major
limitation of the Constantino et al. (1993) study is that 10 out of the 18 aggressive boys had a co-
morbid psychiatric diagnosis. As discussed by Krusi et al. (1990), studies investigating
aggression typically exclude individuals with psychosis because the aggression experienced as
part of a psychotic episode differs from the more persistent and chronic aggression found in
children with ODD and CD.
A number of medical disorders involving androgen abnormalities have also been used to
assess the relationship between testosterone and antisocial and aggressive behaviours. For
instance, congenital adrenal hyperplasia (CAH) is an autosomal recessive disorder occurring in
approximately 1 in 15,000 births (Pang & Shook, 1997). Due to a specific enzymatic deficiency,
CAH results in an over production of adrenal androgens beginning prenatally (Miller & Levine,
1987). As a result of the high androgen concentrations, females with CAH are typically born
with ambiguous genitalia and engage in male-typical behaviours from early childhood (Pasterski,
et al., 2007). Paterski et al. (2007) examined aggression levels in 3- to 11-year old children with
24
CAH (38 girls, 29 boys) and in their unaffected siblings (25 girls, 21 boys). Results from the
study indicated that females with CAH were significantly more aggressive than their unaffected
sisters. These results provide evidence favoring androgens’ role in aggressive and antisocial
behaviour.
Not all studies involving androgen abnormalities provide support for the relationship
between elevated androgen levels and aggression. For example, De La Marche, Prinsen, Boot,
and Ferdinand (2005) evaluated the aggressive behaviours in a 4 year-old boy who had a
testosterone producing testicular tumor. Due to the tumor, the child had androgen levels that
were over 30 times greater than typically developing boys his age. Despite having pubertal levels
of testosterone and DHEA-S, the child did not display any evidence of elevated levels of
antisocial or aggressive behaviours.
In summary, a large body of evidence suggests that elevated concentrations of androgens
are related to aggressive and antisocial behaviours, although some studies have failed to establish
this relationship. Clearly, additional research is needed to further elucidate this relationship,
especially in younger children (Van Goozen, Fairchild, Snoek, & Harold, 2007).
1.6.2 Hypothalamic-pituitary-adrenal Axis Activity (HPA-axis) and Cortisol
The hypothalamic-pituitary-adrenal axis (HPA) is a complex set of interactions involving
the hypothalamus, the pituitary gland, and the adrenal gland (Jansen, Beijers, Riksen-Walraven,
& Weerth, 2010). Among other important functions, the activity of the HPA-axis controls our
reaction to stress, trauma, and injury (Abelson, Khan, Young, & Liberzon, 2010). Cortisol is an
important corticosteroid hormone produced by the adrenal gland and is often used as an index of
25
HPA axis activity (Hawes, Brennan, & Dadds, 2009). Elevated plasma cortisol levels are thought
to reflect increased activation of the HPA-axis.
A number of studies have found a relationship between low resting cortisol levels and
heightened levels of aggressive and antisocial behaviours (Murray-Close, Han, Cicchetti, Crick,
& Rogosch, 2008). The inverse relationship between cortisol and antisociality has been well
established in a number of animal studies (Halasz, Liposits, Kruk, & Haller, 2002; Haller, van de
Schraaf, & Kruk, 2001) as well as human studies involving adults (Virkkunen, 1985; Woodman,
Hinton, & O’Neill, 1978), adolescents (Shoal et al., 2003; Pajer, Gardner, Rubin, Perel, & Neal),
and children (Van Goozen et al., 1998; McBurnett, Lahey, Capasso, & Loeber, 1996).
McBurnett, Lahey, Rathouz, and Loeber (2000) examined salivary cortisol concentrations in
typical school-aged boys. In this investigation, boys with low levels of salivary cortisol had
three times the number of aggressive symptoms than boys with higher levels of cortisol.
Furthermore, when compared to boys with high cortisol, boys with reduced cortisol
concentrations were three times as often identified by peers as being the most aggressive in their
classroom.
Although much evidence suggests that there is an association between hypo-activation of
the HPA-axis (i.e., as reflected in low cortisol concentrations) and antisocial behaviours, some
studies have failed to replicate this relationship (e.g., Azar, Zoccolillo, Paquette, Quiros, Baltzer,
& Tremblay2004; Schulz, Halperin, Newcorn, Sharma, & Gabriel, 1997). In fact, one study
found a positive relationship between cortisol concentration and antisocial behaviours (e.g., Van
Bokhoven et al., 2005). Although these mixed findings may be due in part to the different
methods used to collect cortisol (e.g., salivary, plasma, urinary free cortisol), inconsistent
findings call into question the validity of this relationship. Furthermore, a majority of the studies
26
have been correlational, making it more difficult to conclude a causal relationship or to use
cortisol levels to predict antisocial behaviour (Van Goozen & Fairchild, 2008). Finally, very few
studies have empirically examined the diagnostic specificity of the relationship between cortisol
and antisociality (Van Goozen & Fairchild, 2008). It is plausible that hypo-activation of the
HPA-axis is common among other types of childhood psychopathologies and therefore not
useful as a distinct index of antisocial behaviour.
1.6.3 Neurotransmitters
Neurotransmitters are chemical substances that carry vital information from one neuron
to the next across synapses (Santrock & Mitterer, 2001, pg. 76). Although more than 75
neurotransmitters have been identified in the central nervous system, only the monoamines (i.e.,
norepinephrine, dopamine, and serotonin) have been systematically studied in relation to
antisocial behaviours (Van Goozen & Fairchild, 2008). Among all the monoamines, serotonin
has been most widely studied with respect to antisocial and aggressive behaviours (Van Goozen
& Fairchild, 2008).
1.6.4 Serotonin (5-HT)
The serotonogeric system is either directly or indirectly involved in the regulation and
modulation of mood, emotion, sleep, and appetite (Santrock & Mitterer, 2001, p. 76). Reduced 5-
HT activity has been linked to violent forms of aggressive behaviours for decades (Coccaro, Lee,
& Kavoussi, 2010; Natarajan, de Boer, & Koolhaas, 2009). The so-called 5-HT deficiency
hypothesis of aggression (Brown, Goodwin, Ballenger, Goyer, & Major, 1979) has been
supported in a number of studies involving a variety of animal species (e.g., Belen, Sylvia,
Marta, Gema, Ainara, & Jorge, 2010; Higley, Mehlman, Taub, & Higley, 1992; Higley,
27
Mehlman, Taub, Higley, Suomi, Vickers, & Linnoila, 1992; ) as well as human studies
involving both normative and clinical adult male samples (e.g., Cleare & Bond, 1997;
Virkunnen, Nuutila, Goodwin, & Linnoila, 1987; Lidberg, Tuck, Asberg, Scalia-Tomba, &
Bertilsson, 1985).
The role of 5-HT in childhood antisocial behaviour is less clear than in animal and adult
studies. While some studies have yielded negative correlations between 5-HT and aggression
(e.g., Hanna, Yuwiler, & Coates, 1995) others have found the opposite (e.g., Unis et al., 1997;
Hughes, Petty, Sheikha, & Kramer, 1996). Additional findings suggest that, when compared to
normal and psychiatric controls, antisocial children do not differ on measures of 5-HT
concentrations (e.g., Cook, Stein, Ellison, Unis, & Leventhal, 1995; Rogeness, Hernandez,
Macedo, & Mitchell, 1982).
1.6.5 Norepinephrine (NE)
NE is both a hormone and a neurotransmitter. As a hormone, NE interacts with
epinephrine and helps give our bodies quick bursts of energy in time of stress (Santrock &
Mitterer, 2001, p. 76). As a neurotransmitter, NE is directly or indirectly involved in modulating
arousal, attention, and mood (Santrock & Mitterer, 2001, pg. 76). Animal based studies provide
evidence of a positive correlation between NE activity and aggressive behaviours (Higley et al.,
1992). In studies involving adult humans, a positive relationship has also been found between
antisocial behaviour and NE concentrations. For instance, Brown, Goodwin, Ballanger, and
Goyer (1979) measured a major NE metabolite (3-methoxy-4-hydroxyphenyglycol, also referred
as MHPG) in a group of 26 military men. Results revealed a significant positive correlation
between measures of MHPG concentrations and aggression ratings.
28
Studies assessing the relationship between NE and antisocial behaviours in children have
been mixed (Raine, 2002). Although some studies have found positive correlations between NE
activity and antisocial behaviours (e.g., Gabel, Stadler, Bjorn, Shindledecker, & Bowden, 1993),
other studies have reported negative correlations (e.g., Rogeness, Javors, Maas, & Macedo,
1990) or no relationship at all (Van Goozen, Matthys, Cohen-Kettenis, Westernberg, & Van
Engeland, 1999).
1.6.6 Dopamine (DA)
DA is involved in a number of important functions including voluntary movement,
attention and working memory. In addition, the DA system plays an important role in our
responsiveness to various rewards, punishments and motivations (Wahlstrom, White, & Luciana,
2010; Wahlstrom, Collins, White, & Luciana, 2010). Results from animal studies generally
suggest that increased dopamanergic activity is associated with elevated levels of aggressive
behaviours (e.g., Margolis, Lock, Hjelmstad, & Fields, 2006; Ferrari, van Erp, Tornatzky, &
Miczek, 2003; Louilot, Le Moal, & Simon, H. 1986). Studies investigating the DA role in
antisocial adult and child populations, however, have yielded mixed results. With respect to
adults, studies assessing a DA metabolite (i.e., Homovanillic acid) have shown both an inverse
relationship between DA functioning and antisocial behaviour (e.g., Virkkunen, et al., 1994) as
well as no relationship at all (e.g., Virkkunen, Nuutila, Goodwin, & Linnoila, 1987). With regard
to children, some studies have shown evidence of decreased DA functioning in conduct
disordered youth (e.g., Van Goozen et al., 1999; Gabel, Bjorn, Shinledecker, & Bowden, 1993),
while others have failed to establish this relationship (Kruesi, et al., 1992; 1990).
1.7 Neurophysiological Impairments and Antisocial Behaviour: Frontal Lobe and Executive Functioning Deficits
29
The neurophysiological and neurobiological correlates of antisocial behaviour have also
been extensively studied. Specifically, researchers have explored the relationship between
deficits in frontal lobe functioning and antisocial conduct (Cauffman, Steinberg, & Piquero,
2005; Raine, 2002). The frontal lobe is an important brain structure involved in a number of
higher order cognitive processes related to executive functioning (e.g., planning, impulse control,
affect regulation, attention, etc) (Cauffman, Steinberg, & Piquero, 2005; Morgan & Lilienfeld,
2000). Positron emission tomography (PET), single photon emission computerized tomography
(SPECT), functional magnetic resonance imaging (fMRI), and electroencephalogram (EEG)
activity have all been used to assess frontal lobe functioning (Raine, 2002).
Evidence of deficient frontal lobe functioning (e.g., reduced glucose metabolism in the
prefrontal regions, reduced frontal region cerebral blood flow) in adult antisocial behaviour is
mixed (Raine, 2002). While some studies provide a clear link between frontal lobe deficits and
antisocial behaviour (e.g., Soderstrom, Tullberg, Wikkelsoe, Ejhikm, & Forsman, 2000; Volkow,
et al., 1995), other studies have failed to find this relationship (e.g., Seidenwum, Pounds, Globus,
& Valk, 1997). As discussed by Raine (2002) and in contrast to adult research, there is a dearth
of brain imaging studies (e.g., PET, EEG) assessing the relationship between frontal deficits and
antisocial behaviour in children; instead, researchers have assessed executive functioning
abilities. Given that the frontal cortex controls executive functioning (Raine, 2002; Morgan &
Lilienfeld, 2000), deficits in this area (e.g., impairments in self-regulation, inhibitory control,
sustained attention, planning, and organization) in antisocial children would support the
hypothesis that frontal functioning abnormalities and antisocial behavior are linked. A meta-
analysis conducted by Morgan and Lilienfeld (2000) examined this relationship and showed a
30
significant correlation between executive dysfunction and CD (.40) and executive dysfunction
and juvenile delinquency (.86).
Although there is compelling evidence supporting a relationship between deficient
executive functioning abilities and antisocial behaviours, these findings must be interpreted with
caution. Children with antisocial behaviour (e.g., CD, ODD) often have co-morbid ADHD
(Deault, 2010). It is well established that children with ADHD have significant executive
functioning deficits (e.g., Holmes, Gathercole, Place, Alloway, Elliott, & Hiton, 2010;
Oosterlaan, Scheres, & Sergeant, 2005). Thus, it is possible that the relationship between
executive dysfunction and antisocial behaviour is a result of co-morbid ADHD. Additional
research is needed to examine whether executive functioning deficits prevail in antisocial
children after controlling for ADHD (Raine, 2002).
1.8 Autonomic Nervous System Functioning
The autonomic nervous system (ANS) comprises both the sympathetic nervous system
(SNS) and parasympathetic nervous system (PNS) (Guyton & Hall, 1997). The SNS and PNS
typically function in direct opposition to one another. For instance, when confronted with a
stressful situation, the SNS plays an integral role in preparing the body for a “fight or flight”
response. In order to effectively prepare the body for such a response, the SNS initiates a cascade
of internal physiological reactions resulting in increased heart rate and breathing, along with a
simultaneous reduction in digestive activities (Kalat, 2001, pg. 91). In contrast, the PNS plays an
integral role in calming the body by promoting relaxation and healing (i.e., the so-called “rest
and digest” response; Santrok & Mitterer, 2001, p. 394). Once activated, the PNS causes a
reduction in heart rate and breathing, and an increase in digestive activity (Santrok & Mitterer,
31
2001, p. 394). A substantial body of evidence suggests that antisocial behaviour is strongly
related to ANS functioning (Raine, 2002). Specifically, researchers have examined the role of
resting heart rate (which reflects both SNS and PNS activity; Lang, Tulen, Kallen, Rosberg,
Dieleman, & Ferdinand, 2007) in relation to the development and maintenance of antisocial
behaviours. The relationship between low resting heart rate and antisocial behaviour has been
extensively examined using animal models (e.g., Eisermann, 1992) and human studies involving
toddlers (e.g., Calkins & Dedmon, 2000), children (e.g., Raine, Venables, Sarnoff, & Mednick,
1997) adolescents (e.g., Raine & Venables, 1984) and adults (e.g., Braggio et al., 1992).
Resting heart rate appears to be the best-replicated biological correlate of antisocial and
aggressive behaviours in children and adolescents (Raine, 2002). Results from a recent meta-
analysis involving 40 studies comprising 5,868 children revealed a significant negative
relationship (-.44) between heart rate levels and antisocial behaviours (Ortiz & Raine, 2004) that
was broadly the same for males and females. The relationship between resting heart rate and
antisocial and aggressive behaviours has been replicated across seven different countries,
including the United States (e.g., Rogeness, et al., 1990), Canada (Mezzacappa et al., 1997),
England (Wadsworth, 1976), Germany (Schmeck & Poutska, 1995), New Zealand (Moffit &
Caspi, 2001), Mauritius (Raine, Venables, & Mednick, 1997) and Siberia (Slobodskaya,
Roifman, & Krivoschekov, 1999). Importantly, the relationship between low resting heart rate
and increased antisocial behaviour does not appear to be an artifact of other conditions given that
studies have repeatedly ruled out a range of potential confounds including height, weight, body
bulk, physical development and muscle tone, poor scholastic ability and IQ, drug and alcohol
use, engagement in physical exercise and sports, low social class, divorce, family size, teenage
pregnancy, and other psychosocial adversity (Ortiz & Raine, 2004).
32
Unlike other biological correlates of antisocial behaviour, it appears that resting heart rate
is diagnostically specific to antisocial behaviour. As discussed in the meta-analysis conducted by
Ortiz and Raine (2004), antisocial children were found to have significantly lower heart rates
compared to psychiatric controls as well as normal controls. It appears that no other psychiatric
condition is characterized by low resting heart rate (Ortiz & Raine, 2004). Individuals who have
conditions such as anxiety, depression, schizophrenia, hyperactivity, alcoholism, and
posttraumatic stress disorder demonstrate either elevated levels of heart rate or no difference
from controls. Such diagnostic specificity is considered rare and suggests a potentially unique
perspective from which antisocial behaviour in children can be understood (Ortiz & Raine,
2004).
Other lines of research have investigated the potential utility of employing heart rate
levels as a predictor of future antisocial and criminal behaviours. Kindlon et al. (1995)
demonstrated that low resting heart rate from ages 5-12 years is associated with increased
fighting from ages 9-12. Furthermore, a five year prospective study of crime development by
Raine, Venables and Williams (1990) revealed that low cardiac arousal at age 15 years in normal
unselected school boys predicted criminal behaviour at age 24 years. In this study, measures of
arousal correctly classified 75% of all subjects as criminal/non-criminal, a rate significantly
greater than chance. Lastly, in a longitudinal study conducted by Raine et al. (1997), resting
heart rate at age 3 was assessed in 1,795 male and female children from Mauritius. Aggressive
and non-aggressive forms of antisocial behaviour were then assessed at age 11 through the use of
the Child Behavior Checklist (Achenbach, 1991). The results indicated that aggressive children
had significantly lower heart rates than non-aggressive children, suggesting that low resting heart
rate at age 3 years predisposes children to aggression at age 11. These findings, along with those
33
from the meta-analysis conducted by Ortiz and Raine (2004), suggest that low resting heart rate
is as strong a predictor of children’s future antisocial behaviour as their current behaviour.
Whereas low resting heart rate appears to be a marker for future antisocial behaviour,
mounting evidence suggests that high heart rate may protect against adult crime (Raine,
Venables, & Williams 1995). For instance, Brennan, et al. (1997) found that Danish boys who
had a criminal father but who did not become criminals themselves demonstrated elevated levels
of cardiovascular activity compared to both offspring of non-criminal controls and criminal
offspring with criminal fathers.
1.9 Resting Heart Rate and the Intergenerational Transmission of Antisocial Behaviours
Advancements in the area of genetics have enabled researchers to better understand the
intergenerational transmission of genetic information. Mounting evidence suggests that antisocial
and aggressive behaviour may be passed on in this manner (Eley, Lichenstein, & Stevenson,
1999; Raine, 1993). As discussed by Farrington et al. (2001), support for the genetic
contributions of antisocial behaviours is found in studies highlighting that antisocial behaviour
appears to be concentrated in a fairly small percentage of families. For instance, in a study of a
high-risk population in inner-city London, 63% of boys classified as having delinquent fathers
were convicted of a criminal behaviour compared with only 30% of those whose fathers had
never been accused of any criminal acts (Farrington, 1997). Moreover, data from sophisticated
family, twin, and adoption studies provide additional support for the notion of a substantial
genetic influence in the transmission of antisocial behaviours from one generation to the next
(e.g., Lahey et al., 1988; Stewart, deBlois, & Cummings, 1980).
34
Family studies have consistently reported a two-to three-fold increase in the incidence of
aggressive behaviour among the first and second degree relatives of aggressive boys, compared
to clinic controls (Hamdan-Allen, Stewart, & Beeghly, 1989; Lahey et al., 1988). Genetic factors
appear to exert a moderate to strong influence on the expression of aggression and antisocial
behaviour as it has been shown to account for approximately 28-47% of the variance (Coccaro et
al., 1997).
Given the mounting evidence in support of the intergenerational transmission of
antisocial behaviours, there is increasing interest in investigating heritable biological processes
that may act as markers for antisocial behaviour (Ortiz & Raine, 2004). It is well documented
that heart rate and other cardiovascular properties are highly heritable (Boomsma & Plomin,
1986). Based on this evidence, researchers have questioned whether low cardiac activity is the
neurobiological mechanism passed from antisocial parents to their antisocial offspring. Indeed,
children who have criminal parents have been found to have lower resting heart rate in at least
two independent studies (e.g., Venables, 1987). The fact that antisocial parents and their
antisocial offspring appear to share a similar biological substrate to aggressive behaviours
provides preliminary support for a heritable biological process that may account for the
intergenerational transmission of antisocial and aggressive behaviour.
In summary, it appears that low autonomic arousal as measured through resting heart rate
is one of the best-replicated biological correlates of antisocial and aggressive behaviour in
children and adolescents. This relationship characterizes both males and females, is not
artifactual, has been shown to have diagnostic specificity, and has been replicated in at least
seven different cultures. Low heart rate in childhood and adolescence predicts antisocial and
criminal behaviour in adulthood and high heart rate may protect against crime development.
35
1.10 How Low Heart Rate May Predispose to Aggressive and Antisocial Behaviour
Although low resting heart rate represents one of the best replicated, most easily
measured, and most promising biological correlates of antisocial and aggressive behaviours in
children and adolescents, it is perhaps one of the most poorly understood biological markers
(Raine, 2002). Researchers have questioned why low resting heart rate may predispose
individuals to antisocial behaviours. While several theoretical possibilities exist, one of the most
prominent theories accounting for this phenomenon is the stimulation seeking theory.
1.11 Stimulation Seeking Theory
One of the most parsimonious physiological explanations for the relationship between
low heart rate and increased antisocial and criminal behaviour is that low physiological arousal
predisposes to antisocial and aggressive behaviour (Eysenck, 1997; Raine et al., 1990).
According to the stimulation seeking theory, low arousal represents an unpleasant physiological
state. The underlying premise of any arousal modulation theory is that humans try to maintain
some optimal level of central nervous system arousal and prefer an environment that provides
neither too much nor too little stimulation (Berlyne 1969; as cited in Hughes, 1999). When
desired arousal levels cannot be maintained due to a lack of environmental stimulation, the
person experiences boredom and seeks stimulation. In line with this theory, antisocial individuals
purposely engage in antisocial and aggressive acts in an attempt to increase stimulation and
achieve more agreeable arousal levels (Eysenck, 1997; Quay, 1965; Raine et al., 1997).
1.12 Underarousal and Aggressions: Potential Treatment Implications
If, as the stimulation-seeking theory suggests, one of the functions of children’s antisocial
and aggressive behaviour is to increase their arousal level, the concept of functional equivalence
36
(Carr, 1988; Horner & Day, 1991) may provide a potential pathway to intervention. Functional
equivalence is the behavioural process documented extensively in the applied behaviour analysis
literature whereby the same function or reinforcer for a behaviour is achieved by means of two or
more topographically different responses.
To illustrate, an individual can sometimes achieve the same outcome (e.g., obtaining a
toy from a peer) by means of either a prosocial (e.g., asking the child to share) or antisocial (e.g.,
grabbing the toy without asking) manner. Because the topographically different responses lead
to the same class of reinforcement (i.e., access to the toy), they are considered functionally
equivalent (Ducharme, 2000). Similarly, aggressive and antisocial children may learn that the
easiest and most effective/efficient way to alter underarousal is to engage in socially
inappropriate and aggressive acts. Thus, aggressive behaviours displayed by underaroused
children may serve the specific function of increasing stimulation. The concomitant boost in
arousal may serve as a positive reinforcer, increasing the probability of the response patterns that
led to increased arousal (e.g., aggression).
The concept of functional equivalence can be considered in relation to physiological
arousal. If children with aggressive and antisocial tendencies could increase their arousal level
through socially acceptable alternative behaviours, they may not need aggression to serve that
function. Exercising or physical activity may be one socially acceptable strategy with the
potential to serve that function for children. Based on the stimulation seeking theory, disruptive
children might find that exercise provides enough physiological stimulation to increase arousal,
thereby rendering antisocial responses unnecessary for achieving that outcome.
37
In fact, a substantial body of evidence suggests that children with aggressive and
disruptive behaviours display a decrease in problem behaviour after being exposed to exercise or
physical activity. In a review and meta-analysis of 42 group and single case studies, Allison,
Faith, and Franklin (1995) described the effects of antecedent exercises for the treatment of
disruptive behaviours. The authors used the term antecedent exercises to describe any exercise
condition (i.e., activities that resulted in some degree of physical exertion) that was applied non-
contingently with the intent of reducing subsequent disruptive behaviour (i.e., not following
behaviour as with punishment). The meta-analysis revealed that this approach is effective at
reducing a range of problem behaviours (e.g., disruptive classroom behaviour, self-stimulating
behaviours, aggression, attention-span and impulsivity, etc.) across a variety of populations
(individuals with developmental delays, autism, emotional difficulties, and elementary school
youths referred for disruptive school behaviours).
Although previous research has demonstrated that antecedent exercise is broadly
efficacious, socially acceptable, can be implemented with treatment integrity, and has benign
side-effects (Allison, Faith, & Franklin 1995), two fundamental aspects of this approach remain
unclear and require additional research. First, although the internal validity of antecedent
interventions is well-established, temporal impact has not yet been determined. To our
knowledge, only one study (e.g., Celiberti, Bobo, Kelly, Harris, & Handleman, 1997) has
examined the temporal effects of exercise. In this study, exercise was used to suppress the self-
stimulatory behaviour of a five-year-old boy with autism. Following the exercise condition,
behaviours were observed for a period of 40 minutes. The authors reported sharp reductions in
aberrant behaviours immediately following the exercise intervention. These behaviours gradually
increased but did not return to baseline levels over the 40 minute observational period. Given
38
that the participant’s aberrant behaviours remained below pre-exercise baseline levels at the end
of the observational period, it is evident that the beneficial effects of exercise were still present.
Although this study provides some useful information regarding the temporal effects of exercise
(i.e., the effects last for at least 40 minutes), it fails to delineate the precise length of time that the
child experienced improvements in behaviours. Research assessing the temporal effects of
exercise will be most informative when post-exercise observations occur long enough for target
behaviours to return to pre-exercise baseline levels.
Another important dimension of antecedent exercise that has received considerably less
attention is the mechanism of action accounting for behavioural changes. Although arousal
appears to be a plausible mechanism, fatigue has also been discussed as a possible mechanism
accounting for behavioural improvements (Allison, Faith, & Franklin, 1995). According to the
fatigue hypothesis, individuals expend a high degree of energy while engaged in exercise.
Following exercise, individuals are simply too fatigued to engage in confrontational interactions
with others (Allison, Faith, & Franklin, 1995). To our knowledge no study has been able to
determine what mechanism(s) best accounts for exercise induced behaviour change (i.e., arousal
or fatigue).
1.13 Summary and Rationale for the Current Investigation
Antisocial behaviour in youth represents a serious societal and clinical concern (Scott et
al., 2010; Van Goozen, Fairchild, & Harold, 2008; Mayer, 2001). Left untreated, children who
engage in antisocial behaviours are at serious risk for a number of negative outcomes during
adolescence and adulthood (Trentacosta, Shaw, & Cheong, 2009; Van Goozen, Fairchild,
Harold, 2008; Wright, John, Livingstone, Shepard, & Duku, 2007; Loeber & Farrington, 2000;
39
Ronks & Pulkkinen, 1995; Magnusson, 1992; Farrington, 1991; Caspi, Elder, & Herbener,
1990). Within schools, students who engage in mild but frequent forms of antisocial behaviours
(e.g., talking out of turn, teasing, aggression, etc), represent major challenges for teachers and
contribute to teacher stress, burnout, and attrition (Baker, Lang, & O’Reilly, 2009; Abel &
Sewell, 1999; Peterson, Beekley, Speaker, & Pietrzak, 1996) . Disruptive classroom behaviours
have also been shown to seriously impact both the quality and the quantity of academic
instruction (Bru, 2009).
Given the serious concerns associated with antisocial behaviours, researchers have
explored a variety of different treatment options (e.g., behavioural interventions, cognitive-
behavioural approaches, family-based interventions, multi-faceted treatments, pharmacological
interventions) (e.g., Kazdin, 2003; Barkley & Benton, 1998; McCloskey, Noblett, Deffenbacher,
Gollan, & Coccaro, 2008; Martsch, 2005; Leung et al., 2003; Webster-Stratton & Hammond,
1997; Koegl, Farrington, Augimer & Day, 2008; Isper & Stein, 2007). Notwithstanding the
beneficial effects demonstrated with these approaches, few result in long-term reductions in
antisocial behaviour (Van Goozen et al., 2007; Kazdin, 1997, 1995). Furthermore, the most
beneficial interventions tend to be both time and resource intensive (Axelrod, Garland, & Love,
2009), rendering them impractical for implementation in schools (Wilson & Lipsey, 2010).
Advancements in our understanding of the biological and neurophysiological substrates
of antisocial behaviour may lead to new and innovative treatment alternatives. To date, several
distinct biological and neurophysiological correlates of antisocial behaviour have been identified
(e.g., androgens, neurotransmitters, cortisol, and frontal lobe deficits) (e.g., Banks & Dabbs,
1996; Maras, 2003; Dmitrieva, Oades, Hauffa, & Eggers, 2001; Shoal et al., 2003; Bjork,
Dougherty, Moeller, & Swann, 2000; Soderstrom, Tullberg, Wikkelsoe, Ejhikm, & Forsman,
40
2000). Of all the biological correlates, resting heart rate levels appear to be the best-replicated
biological marker of antisocial behaviour (Raine, 2002). The relationship between low resting
heart rate and increased levels of antisocial behaviour has been demonstrated in animal (e.g.,
Eisermann, 1992) and human studies involving toddlers (e.g., Calkins & Dedmon, 2000),
children (e.g., Raine, Venables, Sarnoff, & Mednick, 1997) adolescents (e.g., Raine & Venables,
1984) and adults (e.g., Braggio et al., 1992). The stimulation seeking theory proposes that low
resting heart rate reflects diminished levels of physiological arousal (Eysenck, 1997; Raine et al.,
1990). Given that all living organisms strive for optimal levels of physiological arousal
(Berlyne, 1969), antisocial individuals may engage in aggressive, disruptive, and violent acts as a
means of increasing their physiological arousal levels to a more optimal state.
If, as the stimulation seeking theory suggests, the function of antisocial behaviour is to
increase physiological arousal levels, exposing antisocial individuals to functionally equivalent
forms of arousing situations (e.g., exercise) should lead to a reduction in antisocial conduct
(Carr, 1988; Horner & Day, 1991) . Although a growing body of literature indicates that
antecedent exercise is associated with substantial reductions in aggressive, disruptive, and
antisocial behaviours (e.g., Allison, Faith, & Franklin, 1995), fundamental questions about this
approach remain unanswered. First, there is a dearth of research examining the temporal effects
of antecedent exercise. Secondly, little is known about the mechanism of action accounting for
behavioural improvements (i.e., why exercise leads to improved behaviours).
1.14 Research Questions and Hypotheses
The present empirical investigation sets out to investigate the following research
questions and hypotheses:
41
1.14.1 Replication
Can the beneficial effects of antecedent exercise (i.e., reduction in disruptive and
aggressive behaviour) be replicated with a group of elementary school children who have low
levels of physiological arousal and demonstrate severe levels of antisocial and aggressive
behaviours? With regards to this question, we hypothesize that school-aged children will exhibit
a reduction in disruptive behaviours following 30 minutes of vigorous aerobic exercise.
1.14.2 Temporality
What are the temporal effects of antecedent exercise (i.e., how long following the
completion of exercise do students display improved behaviours)? We expect that the beneficial
effects of exercise will last for a duration of at least 40 minutes.
1.14.3 Mechanism of Action
Do heightened levels of arousal account for the relationship between antecedent exercise
and reductions in disruptive behaviours? We hypothesize that students’ physiological and self-
report measures of arousal will be inversely related to the frequency of their disruptive
behaviours.
42
Chapter 2: Method
2.1 Participants
Study participants were 4 male students (age range 11 – 14) enrolled in a closed
behavioural classroom due to severe aggressive, oppositional, and disruptive behaviours. All 4
students were described by their teacher as being unresponsive to traditional forms of classroom
based interventions (e.g., social skills training, anger management programs, problem-solving
training).
2.1.1 Participant 1 (Bobby)
Bobby was a 13-year-old Caucasian male in the eighth grade. He was placed in a closed
behavioural classroom with partial integration (i.e., 20% of the time) for Math class, the only
subject area in which he was performing at grade level. According to teacher reports, he was
lacking in social skills, showed extreme opposition to rules and authority figures, and
demonstrated high levels of disruptive and aggressive behaviour. Bobby was formally diagnosed
with a learning disability in the 3rd grade and had a history of behavioural difficulties resulting in
several suspensions.
2.1.2 Participant 2 (Kyle)
Kyle was a 14-year-old Caucasian male enrolled in a grade eight closed behavioural
classroom with no integration. Kyle was performing below grade level in the areas of English,
History, Geography, Science, Math and Religion. Although not formally diagnosed with any
disorders, his high degree of anxiety related to social situations prevented him from attending
school trips or being integrated into other classrooms. He rarely participated in classroom
43
discussions or activities, had unpredictable aggressive outbursts, and was a major distraction to
his classmates due to his disruptive behaviours.
2.1.3 Participant 3 (Dan)
Dan was a 12-year-old Black male in the seventh grade. Dan was placed in a closed
behavioural classroom with partial integration (i.e., 30% of the time). Teacher reports indicated
that he was below grade level in all areas of academic functioning and demonstrated aggression,
short temper and disruptive classroom behaviour. Dan was formally diagnosed with a non-verbal
learning disability in the 4th grade and had a longstanding history of behavioural and academic
difficulties.
2.1.4 Participant 4 (Tom)
Tom was an 11-year-old Black male in the fifth grade. Tom was integrated into
mainstream classrooms for approximately 30% of the day and spent the remainder of his time in
a closed behavioural class. Teacher reports indicated that he was performing below grade level in
all subject areas. He often exhibited disruptive behaviours, poor decision making (e.g., throwing
objects out of the classroom window at students, cutting holes in the school bus seats), and
violations of others property (e.g., stealing). Tom was diagnosed with a learning disability in the
3rd grade and experienced severe fine motor deficits.
2.2 Classroom Setting and Staff
The present study was conducted in a special education classroom within an elementary
school in the local school board. Staffing included one special education teacher and one child
and youth worker. The classroom comprised only the four students participating in this study.
44
2.3 Research Design
An alternating treatment design with baseline (Krishef, 1991; Wacker, McMahon, Steege,
Berg, Sasso, & Melloy, 1990; Barlow & Hayes, 1979; Barlow & Hersen, 1973) was employed.
In this time series design, students were first exposed to baseline conditions and then to two
experimental conditions, (i.e., an antecedent exercise condition and a control condition) in a
randomized fashion. This design allowed for a sequential comparison between baseline and
experimental conditions and a simultaneous comparison between exercise and control
conditions. Research in the field of special education has been increasingly employing single-
subject designs to investigate the effectiveness of educational practices and interventions for
students with a variety of disabilities (Tankersley, Harjusola-Webb, & Landrum, 2008).
2.4 Data Collection and Interobserver Agreement
2.4.1 Observer Training
To assist with observational data collection, eight undergraduate research assistants
(RAs) were recruited from the Psychology department at the University of Toronto. All RAs
received approximately 15 hours of face-to-face training. On the first day of training
(approximately 5 hours), RAs were provided with an information package outlining the nature of
the study. Included in this package were (i) a description of the observational and coding
procedures to be used (ii) a description of the operational definitions of all target behaviours, and
(iii) copies of the data recording sheets that were to be used to collect all behavioural and
physiological measures. After going through the information package with the RAs, the primary
investigator answered their questions related to the material and encouraged them to carefully
review the information provided before the second training session.
45
On the second day of training (approximately 5 hours), the RAs were assigned to small
groups and asked to brainstorm a variety of student behaviours (both positive and negative).
After generating a sufficient list, RAs were asked to consider how they would categorize and
code the behaviours. Finally, group members were instructed to present their list of coded
behaviours to the larger group.
The final training session took place in the actual school where the remainder of the study
was to take place. RAs were introduced to the school staff and the students enrolled in the study.
Following introductions, RAs were assigned to students and asked to code their behaviours. This
session enabled RAs to become familiarized with the observational and coding procedures and
acclimatized research participants to being observed in their classroom.
2.4.2 Observation Sessions
Participant observations took place in the students’ classroom while they were engaged
in regular classroom activities. A RA who was blind to experimental conditions coded the
occurrence of a variety of target behaviours of each participant. For the purpose of interobserver
agreement, 20% of all baseline, exercise, and control sessions were randomly selected and
simultaneously coded by the primary investigator. For the baseline, exercise, and control
conditions, agreement was obtained for both disruptive and prosocial behaviours (see definitions
below) as well as compliance to teacher requests. Percentage agreement was obtained by
dividing the number of agreements by the sum of agreements and disagreements in each session,
and multiplying by 100. Mean interobserver agreement for behaviour was 92% (range = 89% to
94%) for baseline sessions, 93% (range 88% to 100%) for exercise sessions, and 94% (range =
89% to 97%) for control sessions. Mean interobserver agreement for compliance to teacher
46
requests was 91% (range = 84% to 100%) for baseline sessions, 93% (range = 87% to 100%) for
exercise sessions, and 92% (range = 82% to 100%) for control sessions.
2.5 Measures
The measures in this study included a general health screener completed by
parents/caregivers, teacher ratings, observational measures, physiological measures, and student
self-report measures.
2.5.1 General Health Screener
Given that the participants were being asked to engage in physical activities, it was
important to determine whether they had any pre-existing health conditions that could
compromise their well-being during exercise routines. For this reason, parents/caregivers were
asked to complete a general health screener (see Appendix “A”) geared at identifying any health
or medical concerns experienced by their child.
2.5.2 Teacher Ratings
The emotional and behavioural profiles of the participants were assessed through the use
of the Teacher Report Form (TRF) (Achenbach, 1991) at the commencement of the study. The
TRF is an individually administered questionnaire designed to measure teachers’ perceptions of
children’s academic performance, adaptive functioning, and emotional/behavioural problems.
The questionnaire is designed for students between the ages of 6 and 18 and contains 120 items.
The TRF has sound psychometric properties. Achenbach (1991) found the range of test-retest
reliability to be 0.62 to 0.96, the range of internal consistency to be 0.72 to 0.95 and the inter-
rater reliability to be 0.60.
47
2.5.3 Observational Measures
Participant students were observed in their classrooms for a duration of 2 hours for all
observational periods (i.e., baseline, following exercise and following control). The teacher and
classroom assistant were instructed to perform regular classroom routines and activities during
all observational sessions.
2.5.4 Disruptive Behaviours
Disruptive behaviours were divided into 6 categories. Negative verbal behavior was
defined as any aversive or antisocial statements, questions, or comments directed at peers or
teachers including threats, insults, swearing, name-calling, and blaming. Physical aggression
towards others was defined as any aversive or antisocial action directed towards another peer or
teacher, including hitting, kicking, tripping, spitting, and biting. Physical aggression towards
objects was defined as any aversive action involving an object including throwing of objects,
breaking pencils, writing on desks, kicking chairs, etc. Disruptive behaviours towards others
was defined as any behaviour that was disruptive towards peers or teachers including speaking
during lessons, calling out answers, interrupting peers, etc. Out of seat behavior was defined as
the student leaving his seat without asking permission from the teacher or classroom assistant.
Finally, coders used an “other” category for any problem behavior not adequately covered by the
aforementioned categories.
2.5.5 Prosocial Behaviours
Prosocial physical behaviours were defined as any spontaneous or self-initiated
cooperative action directed towards a peer or teacher including helping and sharing. Prosocial
verbal behaviours were defined as any spontaneous or self-initiated friendly or co-operative
48
statements, questions, or comments directed at peers or classroom staff including praising,
thanking, apologizing, or inviting peers to engage in a game or activity.
2.5.6 Compliance to Teacher Requests
Percentage of compliance to teacher requests served as another dependent measure.
Participants were considered compliant if the appropriate response to the teacher request was
initiated within 10 seconds of the request and the student followed through on completion. If the
teacher was required to repeat the request, the participant was coded as non-compliant. All
teacher requests within the observational period were coded.
2.5.7 Physiological Measures of Arousal
In the present investigation, heart rate was used as an objective measure of physiological
arousal and participants’ heart rate was assessed throughout all conditions. Heart rate is
determined by the number of heartbeats per unit of time, typically expressed as beats per minute
(BPM) (Guyton & Hall, 1997). Heart rate levels have frequently been used in research to assess
and quantify autonomic arousal levels (e.g., Borusiak, Bouikidis, Liersch, & Russel, 2008;
Fleming & Rickwood, 2001). Although several different techniques and methods can be used to
assess heart rate (e.g., manually checking the carotid or radial pulse, electrocardiograph, various
commercial heart rate monitors), the present study required a measuring device that allowed for
efficient and accurate recordings yet was simple enough for use by school aged children. For the
present study, all physiological measures of heart rate/arousal were obtained through the use of a
SPORTLINE Solo 920 Heart Rate Watch ® (hereafter referred to as heart rate monitor) (see
Appendix “B”). The heart rate monitor works like a standard watch, but includes an advanced
heart rate sensing technology (i.e., S-PulseTM Technology) that measures the electrical signals on
49
the skin in the same manner that an electrocardiogram (EKG) does. Although the heart rate
monitor is attached to the wrist, it does not measure radial (i.e., wrist) pulse, but instead
measures heart rate by reading the individual’s EKG signal, that is, the electronic signals
generated by the beating heart that pass through the body. Located on the heart rate monitor are
two metal sensors, one on the face of the watch and the other on the back against the wrist. The
EKG measurement is obtained when the individual places their index finger on the face sensor
for 3-8 seconds. This creates a “loop” that is read by the monitor. A beeping sound notifies the
individual of a successful reading and the heart rate is then displayed on the screen. The heart
rate monitor provides EKG accurate readings (SPORTLINE Solo 920 Heart Rate Watch ®
Manual, 2006).
All participants received training on how to correctly monitor their heart rate. To ensure
that the watch did not serve as a distraction during classroom lessons, participants were
permitted to check their heart rate only when instructed by the researchers. Students who were
distracted by their watch during lessons were given a warning by their classroom teacher. If a
second warning was warranted, the student was asked to remove the watch and place it in his
desk. When the watch was required for heart rate measures, the student was then asked to replace
the watch on his wrist.
2.5.8 Resting Heart Rate
Resting heart rate levels were obtained prior to the commencement of baseline sessions.
This measure was taken to assess the level of physiological arousal experienced by each of the
participants and was also required for calculations of participants target heart rate (see below).
To obtain measures of resting heart rate, each participant was asked to join the primary
50
investigator in the hallway in a quiet spot free from distractions. The participant was asked to
relax with eyes closed on a mat for 5 minutes. Following the 5 minutes, each student was asked
to use the heart rate monitor to measure his resting heart rate. To ensure accuracy of
measurement, this procedure was conducted three times. The mean of all 3 recordings was used
as the measure of resting heart rate.
2.5.9 Heart Rate during Exercise and Control Sessions
Participants’ heart rate levels were obtained several times throughout exercise and control
conditions that were each 30 minutes in duration. Heart rate was obtained during the exercise and
control conditions to objectively measure the extent to which arousal levels differed between the
experimental conditions. To obtain arousal levels, each participant was approached by the
primary investigator and asked to use the heart rate monitor to measure his heart rate. The
primary investigator read the heart rate value from the watch and recorded it on a coding sheet
(see Appendix “C”). Participants were asked to refrain from discussing their heart rate levels
with classmates.
2.5.10 Heart Rate during Observational Periods
During baseline and following exercise and control conditions, participants were
observed in their classroom for 2 hours. At several pre-determined times during the observational
periods, participants were approached by a RA and asked to check their heart rate. These values
were verified by the RA and recorded on a coding sheet (see Appendix “D”). These heart rate
measures provided participants’ arousal levels during baseline as well as arousal levels following
exposure to the experimental conditions. Arousal measurements following the experimental
51
conditions allowed for an exploration of the mechanism of action underlying potential
behavioural improvements following exercise.
2.5.11 Target Heart Rate Zone
Target Heart Rate (THR), is the most favorable heart rate range during aerobic exercise,
enabling the heart and lungs to receive optimal benefit from a workout. This theoretical range
varies across individuals based on physical condition, gender, and previous training.
Research suggests that vigorous exercise (defined as moderate to intense) is most
effective at reducing disruptive behaviours (Celiberti et al., 1997). As exercise intensity
increases, individuals experience an elevation in heart rate level. A moderate level is commonly
defined as exercise that enables individuals to achieve 50-70% of their maximum heart rate
(Guyton & Hall, 1997). For the purpose of the present investigation, it was crucial that
participants engaged in moderate levels of exercise intensity (i.e., 50-70% of their maximum
heart rate). To confirm that participants achieved the desired exercise intensity level, we
calculated their individualized THR. During exercise, participants’ heart rates were monitored to
ensure that they were consistently exercising within the predetermined THR zone.
Prior to starting the exercise conditions, the THR for each participant was individually
calculated using the Karvonen method (e.g., Robergs & Landwehn, 2002). This method was
selected because it considers each individual’s unique resting heart rate in calculation of THR.
The Karvonen method uses the following formula:
THR = ((HRmax − HRrest) × % Intensity) + HRrest
52
For demonstration purposes, the Karvonen method is used here to calculate the THR of a 13
year-old-male who has a resting heart rate of 80 beats per minute (and desires to achieve 50% to
70% of his maximum heart rate during exercise).
Step 1: Calculate HRmax
HRmax = 220 – age [of individual]
HRmax = 220 – 13 = 207
HRmax = 207
Step 2: Calculate THR for 50% exercise intensity
THR = ((HRmax − HRrest) × % Intensity) + HRrest
THR = ((207 − 80) × .50) + 80
THR = 143.5
Step 3: Calculate THR for 70% exercise intensity
THR = ((HRmax − HRrest) × % Intensity) + HRrest
THR = ((207 − 80) × .70) + 80
THR = 168.9
Thus, according to the Karvonen method, a 13-year-old male with a resting heat rate of 80 BPM
is exercising at an optimal level (i.e., at a moderate to intense level) when his heart rate is
maintained in the range of 144 to 169 BPM throughout exercise.
2.5.12 Self-Report Measures
In addition to the behavioural and physiological measures, a variety of self-report
measures were used. Visual analog scales were used to obtain participants’ perception of (i) how
relaxed or tense they felt (see Appendix “E”), (ii) how fatigued or full of energy they felt (see
53
Appendix “F”), and (iii) how bored or excited they felt (see Appendix “G”). Participants were
asked to draw a line on the scale that best designated how they were currently feeling. To
quantify the participants’ self-report ratings, a ruler was used to measure where on the line the
participants placed their mark unit of measurement. Participants practiced completing the scale
before the start of the study and were typically able to complete all analogue scales in less than
25 seconds.
2.6 Procedures
2.6.1 Baseline
Before students arrived to class during baseline, RAs were randomly assigned to observe
one of the four participants and a heart rate monitor was placed on each student desk. The 2 hour
observation period began as soon as students entered the classroom. The teacher was instructed
to perform his daily routines and activities. RAs sat at the back of the room and remained out of
the direct view of the participant they were observing. Each RA was provided with data sheets
containing a check list of behaviours to be coded (see Appendix “H”). RAs circled the item on
the check list that best corresponded to the behaviours observed. RAs also obtained heart rate
measurements and analogue self-report measures. Heart rate and self-report measures were
obtained 4 times throughout the 2 hour observational session at 30 minutes, 60 minutes, 90
minutes, and 120 minutes. RAs were instructed to interact with participants in a “neutral”
manner (e.g., no praise statements, no criticism) when obtaining measures. Heart rate and
subjective measures were typically collected in less than 2 minutes and resulted in minimal
disruptions to regular classroom activities.
54
During the observational period, some participants received partial integration, requiring
them to spend part of the observational period in a different classroom. In such circumstances,
the assigned RA followed the student to the alternate classroom and resumed observations. The
only interruption in coding occurred when the students went outside for their 15 minute morning
recess break.
2.6.2 Antecedent Exercise Condition (10 sessions)
All exercise sessions were conducted by the primary investigator and one RA. When a
RA assisted with implementation of the exercise sessions, they were not included in data
collection for that session. All exercise sessions occurred during the students’ first period class
and took place either in the school gymnasium or on the school playground.
Before starting each session, participants were provided with a heart rate monitor. Each
exercise session lasted 30 minutes and comprised the following components:
(i) Warm-up phase (5 minutes): A warm-up phase was conducted to reduce the likelihood of
student injury. In this phase, participants were asked to gather in a circle and demonstrate a
muscle stretch of their choice for the group to imitate. The exercise phase did not begin until all
major muscle groups were adequately stretched.
(ii) Exercise Phase (20 min): The exercise phase was 20 minutes in duration and included a
variety of aerobic exercise activities including jogging, skipping, sprints, and circuit training. To
achieve the goal of increased heart rate, participants were reminded before each exercise session
of their unique target heart rate and were encouraged to achieve this level throughout the
exercise session.
55
(iii) Cool-down Phase (5 minutes): During the cool down phase, participants were asked to
engage in less intense forms of exercise. This involved walking two laps around the gym
followed by a series of stretching exercises (conducted as in the warm-up phase).
Throughout all exercise sessions, students were asked to stop on four occasions (i.e., at
10 minutes, 15 minutes, 20 minutes, and 30 minutes) to provide heart rate and self-report
measures. When students remained below their target heart rate (i.e., below 50% of their
maximum heart rate), they were asked to “work as hard as they could”. If the participants’ heart
rate level exceeded 70% of their maximum heart rate (and were thus at risk of injury due to
overexertion) they were asked to “slow down the pace for a couple of minutes”.
Following the exercise condition, participants returned to their classroom and were
observed by RAs who were blind to the experimental condition. Observations following exercise
sessions lasted 2 hours and followed the same coding procedures as in baseline.
2.6.3 Control Condition (9 sessions)
The 30 min control condition was designed to maintain participant heart rates as close as
possible to the resting state. All control sessions occurred during the participants’ first period
class. Before students arrived at school, the primary investigator placed a variety of reading
materials (e.g., sports magazines, comic books) and heart rate monitors on a desk at the front of
the classroom. Students were instructed to select one or two items from the selection of reading
materials as well as a heart rate monitor. The session started once participants had returned to
their seats with their reading materials. To increase the likelihood that students would engage in
30 minutes of silent reading, participants were informed by the teacher that their daily journal
entry had to include a response to the information that they read. As in the exercise condition,
56
participants provided heart rate and self-report measures at 4 time periods (i.e., 10 minutes, 15
minutes, 20 minutes, and 30 minutes).
Following the 30 minutes of silent reading, students were asked by the teacher to start
working on their daily journal. Participants were then observed for 2 hours by RAs who were
blind to the experimental condition. The same observational coding procedures that were used
during baseline were carried out following control sessions.
57
Chapter 3: Results
3.1 General Health Screener
Results from the general health screener indicated that all participants were in good
health and had no medical or physical conditions that would prevent them from partaking in 30
minutes of aerobic exercise.
3.2 Emotional and Behavioural Functioning
Emotional and behavioural functioning was assessed through the Teacher Report Form
(Achenbach, 1991). Results for each of the 4 participants are described below.
3.2.1 Participant 1 (Bobby)
On the TRF, Bobby scored in the normative range on all measures of internalizing
behaviours. Regarding externalizing behaviours, Bobby fell in the clinical range (T Score = 71).
Within the externalizing domain, Bobby was rated in the borderline clinical range for rule-
breaking behaviour (T Score = 69) and in the clinical range for aggressive behaviours (T Score =
71), oppositional defiant problems (T Score = 70), and conduct problems (T Score = 75).
3.2.2 Participant 2 (Kyle)
TRF scores suggest that Kyle was in the clinical range for both internalizing (T Score =
71) and externalizing (T Score = 68) behaviours. Within the internalizing domain, Kyle fell in
the borderline clinical range for withdrawn/depressed behaviour (T Score = 69) and in the
clinical range for anxiety problems (T Score = 73). Regarding externalizing behaviours, Kyle fell
in the borderline clinical range for rule-breaking behaviour (T Score = 67), aggressive behaviour
58
(T Score = 67), oppositional defiant problems (T Score = 65), and conduct problems (T Score =
68).
3.2.3 Participant 3 (Dan)
Dan did not experience significant difficulties with internalizing behaviours. Dan did,
however, score in the clinical range for externalizing problems (T Score = 65). Within the
externalizing domain, Dan fell in the borderline clinical range for rule-breaking behaviour (T
Score = 68), oppositional defiant problems (T Score = 65), and conduct problems (T Score = 68).
3.2.4 Participant 4 (Tom)
Although Tom did not experience significant difficulties with internalizing behaviours,
he fell in the borderline clinical range for anxiety problems (T Score = 65). With regards to
externalizing difficulties, Tom fell in the borderline clinical range (T Score = 61). Within the
externalizing domain, Tom scored in the borderline clinical range for both rule-breaking
behaviour (T Score = 66) and conduct problems (T Score = 66).
3.3 Resting and Target Heart Rate (THR)
Table 1 provides resting and THR rate values for each of the 4 participants. THR was
calculated using the Karvonen method. For the purpose of the present investigation, the THR for
each participant was calculated to be 50% to 70% of their maximum heart rate.
59
Table 1
Resting and Target Heart Rate
Participant Resting Heart Rate Target Heart Rate
Bobby 77 142-168
Kyle 82 144-169
Dan 72 140-167
Tom 92 151-174
Note. All heart rate levels reflect number of beats per minute (BPM)
3.4 Effects of Antecedent Exercise on Behavioural Functioning
To investigate the effects of antecedent exercise on behavioural functioning, two
measures were included. The first measure was used to investigate the overall extent to which
exercise was associated with improved behaviours. For this measure, observed student
behaviours following experimental conditions were combined over the entire observational
duration (i.e., 2 hours). The second measure was used to investigate potential temporal effects
associated with exercise. For this measure, the two hour duration of observed student behaviours
following experimental conditions was divided into four 30 minute intervals (i.e., 0 to 30
minutes, 30 to 60 minutes, 60 to 90 minutes, and 90 to 120 minutes).
60
3.5 Overall Effects of Antecedent Exercise on Behavioural Functioning (2 hour duration)
3.5.1 Disruptive Behaviours
Baseline. The frequency of disruptive behaviours in baseline and following control and exercise
sessions are presented in Figure 1. The frequency of disruptive behaviours during baseline was
high for all 4 participants. The overall mean frequency of disruptive behaviours across all
participants was 45.4 (range of 20 to 74).
Control Condition. The frequency of disruptive behaviours remained relatively high following
the control sessions for all 4 participants. The overall mean frequency of disruptive behaviours
across all participants was 47.1 (range of 17 to 69).
Exercise condition. All 4 students experienced a substantial reduction in disruptive behaviours
following exercise sessions. The overall mean frequency of disruptive behaviours throughout all
exercise sessions was 26.4 (range of 9 to 47). The mean for disruptive behaviours was 20.75
responses lower per session than in the control condition.
Visual analysis of data trends in Figure 1 suggests that exercise had a very strong
reductive effect on disruptive behaviours for each individual participant. Data for exercise
sessions are characterized by little variability and relatively low frequency. Analysis of Figure 1
also reveals few overlapping data points between exercise and control sessions. These data
suggest that participants consistently engaged in less disruptive behaviour following exercise
sessions than following control sessions.
In addition to visual analysis, Mann-Whitney U tests were used to determine statistical
differences between exercise and control sessions. Separate Mann-Whitney U tests were
61
conducted for each participant (see Appendix “I” for all Mann-Whitney U test statistic values for
each participant). This analysis demonstrated that all participants were significantly less
disruptive following exercise sessions compared to control sessions.
Figure 2 presents the averaged group data for disruptive behaviors across baseline,
control, and exercise sessions.
62
Bobby
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Figure 1: Frequency of disruptive behaviours for all baseline, control, and exercise sessions.
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Figure 2: Overall mean frequency of disruptive behaviours across baseline, control, and exercise conditions.
3.5.2 Prosocial Behaviours
Baseline. The frequency of prosocial behaviours in baseline and following control and exercise
sessions are presented in Figure 3. As can be seen in this figure, baseline rates of prosocial
behaviours were generally low for all 4 students. The overall mean frequency of prosocial
behaviours across all 4 students was 12.8 (range of 8 to 19).
Control Condition. Similar to baseline rates, the frequency of prosocial responding during
control sessions was low for all participants. The overall mean frequency of prosocial behaviours
was 9.5 (range of 1 to 18).
Exercise condition. All 4 students demonstrated an increase in prosocial behaviours following
exercise. The overall mean frequency of prosocial behaviours throughout all exercise sessions
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was 17.6 (range of 7 to 31), an overall mean of 8.11 prosocial behaviours per session higher than
in the control condition.
Visual analysis of data trends in Figure 3 suggests that exercise had a modest effect on
student prosocial behaviours. Data in baseline and control sessions were characterized by a high
degree of variability at generally low frequencies. Although data for exercise sessions were
variable, they were generally at higher levels relative to baseline and control sessions. These data
suggest that following exercise, all 4 participants demonstrated some improvement in prosocial
behaviours.
In addition to visual analysis, Mann-Whitney U tests were conducted to compare exercise
and control conditions. This analysis demonstrated a statistically significant increase in prosocial
responding for all four participants following exercise sessions compared to control sessions.
Figure 4 presents the averaged group data for prosocial behaviours for all baselines,
exercise, and control sessions.
65
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Figure 3: Frequency of prosocial behaviours for all baseline, control, and exercise sessions.
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Figure 4: Overall mean frequency of prosocial behaviours for baseline, control, and exercise conditions.
3.5.3 Compliance to Teacher Requests
Baseline. The percentage of compliance to teacher requests in baseline and following control and
exercise conditions is presented in Figure 5. As can be seen in this figure, baseline levels of
compliance for all 4 students were generally low. The overall mean percentage of compliance
was 52.55% (range of 39% to 74%).
Control Condition. Participants demonstrated low levels of compliance (comparable to baseline)
following control sessions. The overall mean percentage of compliance across all 4 participants
in this condition was 50.60% (range of 27% to 72%).
Exercise condition. Exercise was associated with heightened levels of compliance compared to
the control condition. The overall mean percentage of compliance for all participants was
68.71% (range of 48% to 86%). Compliance levels following exercise was 17.86% higher than
compliance levels following the control condition.
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Visual analysis of data trends in Figure 5 suggests that exercise had a moderate effect on
student compliance. Although there is some overlap between compliance data following exercise
and control sessions, data for the exercise condition is characterized by slightly less variability at
generally higher levels than baseline and control conditions.
With the Mann-Whitney U Tests, significant differences in compliance to teacher
requests were found between exercise and control sessions for all 4 participants.
Figure 6 presents the averaged group data for compliance to teacher requests across all
baseline, exercise, and control sessions.
68
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Figure 5. Percent compliance to teacher requests across all baseline, control, and exercise sessions.
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Figure 6. Overall percent compliance to teacher requests across baseline, control, and exercise conditions.
3.6 Effects of Antecedent Exercise (Temporal Effects)
To determine potential temporal effects of antecedent exercise, we measured behavioural
functioning in baseline and following exercise and control conditions across 4 durations: 0 to 30
minutes (T1), 30 to 60 minutes (T2), 60 to 90 minutes (T3), and 90 to 120 minutes (T4).
3.6.1 Disruptive Behaviours
Baseline. The overall frequency of disruptive behaviours for all 4 participants for baseline and
following exercise and control conditions across all 4 durations is presented in Figure 7.
The mean frequency of disruptive behaviours for all participants during baseline was
11.60 (range of 6.4 to 15.6), 10.53 (range of 5.4 to 15.2), 11.90 (range of 3.6 to 16.4) and 11.60
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(range of 4.6 to 14) for T1, T2, T3, and T4 respectively. As is evident in Figure 7, the frequency
of student disruptive behaviors remained relatively constant over the 2 hour observational period.
Control. The mean frequency of disruptive behaviours following control sessions was 11.07
(range 8.78 to 14.1), 12.77 (range 7.89 to 15.56), 12.57 (range of 7.33 to 15.38), and 11.23
(range 5.67 to 17.38) for T1, T2, T3, and T4 respectively. Consistent with baseline data, the
average frequency of disruptive behaviours was relatively constant throughout the 4 time periods
following control sessions.
Exercise. The mean frequency of disruptive behaviours following exercise sessions was 4.02
(range 2 to 6), 4.81 (range 2.2 to 6.89), 5.99 (range (3.7 to 8) and 11.92 (range 6.5 to 14.3) for
T1, T2, T3, and T4 respectively. In comparison to the control condition, exercise was associated
with 7.05 fewer disruptive behaviours for T1, 7.96 fewer behaviours for T2, and 6.58 fewer
behaviours for T3. The frequency of disruptive behaviours was slightly higher (i.e., 0.69) in the
exercise condition compared to the control condition for T4.
As is evident in Figure 7, the frequency of disruptive behaviours is relatively high and
stable for all participants during baseline and control sessions across the 4 time periods. A
comparison of data points in the exercise and control conditions for T1, T2, and T3 however,
reveals few overlapping data points for all 4 participants (especially for T1, the duration that
immediately followed the exercise condition). A slight degree of caution is warranted when
interpreting the T3 data trends for participant 4. Although the effects of exercise are slightly
harder to discern for this participant, it appears that on average, participant 4 displayed fewer
problems behaviours following exercise compared to control sessions. By examining T3 for
participant 4, it appears that the sessions with the lowest frequency of disruptive behaviours (i.e.,
71
sessions 6, 8, 12, 13, 22, and 23) occurred following exercise. On the contrary, the highest
frequencies of disruptive behaviours for participant 4 occurred following control sessions (i.e.,
sessions 7 and 24). Moreover, the mean frequency of disruptive behaviours following exercise
(i.e., 3.7) was substantially lower than the mean frequency of disruptive behaviours following
control sessions (i.e., 7.3). Taken together, these trends suggest that participant 4 displayed less
disruptive behaviour for T3 following exercise compared to control. For T4, all 4 participants
demonstrated a high degree of overlapping data points between the exercise and control sessions.
Mann-Whitney U tests were conducted for each participant for all 4 time periods. The
frequency of disruptive behaviours was significantly lower following exercise sessions compared
to control sessions for all participants across T1 and T2. With the exception of participant 4,
exercise continued to result in a significant reduction in disruptive behaviour compared to the
control session for T3. It should be emphasized, however, that for T3, participant 4 was just shy
of achieving statistical significance (thus suggesting a trend that exercise sessions were
associated with a reduction in disruptive behaviours compared to control sessions). No
significant differences were found for T4.
In summary, results from the visual analysis suggest that when compared to the control
condition, exercise resulted in reductions in the frequency of disruptive behaviours for
approximately 90 minutes. However, between 90 and 120 minutes post-exercise, the beneficial
effects of exercise appear to subside with little difference between the exercise and control
sessions. With the exception of one finding (T3 for participant 4) results from the Mann-Whitney
U test are highly consistent with the visual analysis.
72
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: Fre
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beha
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cros
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l bas
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e, c
ontr
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Figure 8: Mean frequency of disruptive behaviours for baseline, exercise, and control conditions across T1, T2, T3, and T4.
3.6.2 Prosocial Behaviours
Baseline. The overall frequency of prosocial behaviours for all 4 participants is presented in
Figure 9. Data are presented for baseline and following control and exercise sessions for T1, T2,
T3, and T4. The mean frequency of prosocial behaviours during baseline was 3.15 (range of 2.4
to 3.6), 3.2 (range of 2.4 to 4.2), 2.95 (range of 1.6 to 3.6) and 3.05 (range of 1.8 to 4.0) for T1,
T2, T3, and T4 respectively. During baseline, the frequency of prosocial responding was
relatively low for all participants across all 4 time intervals.
Control. The mean frequencies of prosocial behaviours following control sessions were 2.42
(range 1.88 to 3.11), 2.52 (range 1.25 to 3.44), 1.83 (range of 1.13 to 2.78), and 2.51 (range 2.13
to 3.11) for T1, T2, T3, and T4 respectively.
Exercise. The mean frequencies of prosocial behaviours following exercise sessions were 6.82
(range 4.44 to 8.50), 5.38 (range 3.89 to 6.80), 3.77 (range 2.22 to 4.90) and 1.93 (range 1.22 to
2.60) for T1, T2, T3, and T4 respectively. When compared to control sessions, exercise was
associated with a greater frequency of prosocial responding for T1 (increase of 4.4 prosocial
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behaviours), T2 (increase of 2.86 prosocial behaviours), and T3 (increase of 1.94 prosocial
behaviours) but not T4 (decrease of 0.58 prosocial behaviours).
Visual analysis of data trends in figure 9 reveals that exercise had a positive impact on
prosocial behaviours for all participants for T1, T2, and T3 as evidenced by a small number of
overlapping data points between exercise and control sessions. The positive effects of exercise
on prosocial behaviours were substantially reduced by T4 for all participants, as evidenced by
the large number of overlapping data points between exercise and control sessions.
Results of Mann-Whitney U tests were consistent with visual analysis. When compared
to the control condition, all participants demonstrated statistically significant increases in the
frequency of their prosocial responding following exercise for T1, T2, and T3. No significant
differences were found between exercise and control conditions for T4 for any of the
participants.
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ehav
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s ac
ross
all
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Figure 10. Mean frequency of prosocial behaviours across all baseline, control, and exercise sessions for T1, T2, T3, and T4
3.6.3 Compliance to Teacher Requests
Baseline. The percentage of compliance to teacher requests for baseline and following exercise
and control sessions are presented for T1, T2, T3, and T4 in Figure 11. The mean percentage of
compliance during baseline was 53.25% (range of 49.4% to 58.4%), 51.55% (range of 46.6% to
5.6%), 49.75% (range of 43.6% to 58.6%) and 57.05% (range of 48% to 65.4%) for T1, T2, T3,
and T4 respectively.
Control. Similar to baseline levels, the percentage of compliance to teacher requests during
control sessions was 50.31% (range 45.5% to 56%), 49.75% (range 43.88% to 53.44%), 50.94%
(range of 41% to 63.44%), 51.74% (range 48.5% to 60.67%) for T1, T2, T3, and T4 respectively.
Exercise. The mean frequencies of compliance to teacher requests following exercise sessions
were 82.68% (range 80.7% to 85.67%), 73.05% (range 64.9% to 81.44%), 67.45% (range 52.1%
to 76.9%) and 53.11% (range 45% to 64.56%) for T1, T2, T3, and T4 respectively. In
comparison to the control condition, compliance was higher following exercise for T1
(difference of 32.37%), T2 (difference of 23.33%), T3 (difference of 16.57%) and T4 (slight
difference of 1.37%).
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Visual analysis of data for exercise and control conditions at T1 and T2 reveals few
overlapping data points for all 4 participants. Participants 1, 2 and 4 continued to show few
overlapping data points between exercise and control sessions for T3. This trend is not as
apparent for participant 3. By T4 there was a greater amount of overlapping data points between
exercise and control sessions for all participants with the exception of participant 4, who
continued to experience slight improvements in compliance.
Results from the Mann-Whitney U test differed slightly compared to the visual analysis.
According to the Mann-Whitney U test, all 4 participants were significantly more compliant to
teacher requests following the exercise condition compared to the control condition for the time
periods of T1 and T2. However, only participants 2 and 4 continued to demonstrate significantly
higher levels of compliance following exercise for T3. None of the participants demonstrated
significant differences in compliance levels between exercise and control sessions for T4.
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ntag
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ache
r req
uest
s ac
ross
all
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line,
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trol
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Figure 12. Average compliance to teacher requests for all baseline, control, and exercise conditions for T1, T2, T3, and T4.
3.7 Heart Rate Levels during Exercise and Control conditions
Participants’ average heart rate levels while engaged in the 30 minute experimental
conditions are presented in Figure 13. Results suggest that participants experienced elevated
heart rate levels during exercise sessions compared to control sessions.
Figure 13. Average heart rate levels while engaged in experimental conditions.
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Bobby Kyle Dan Tom
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3.8 Heart Rate Levels during Observational sessions
Figure 14 provides participants average heart rate levels following baseline, control, and
experimental conditions for the time intervals of T1-T4. A summary of results for each
participant are described below.
3.8.1 Participant 1 (Bobby)
Bobby’s heart rate following exercise was consistently higher than his heart rate during
baseline and following the control condition across all 4 time intervals. While Bobby’s heart rate
during baseline and following the control condition was characterized by some degree of
variability with no clear trends across the 4 time intervals, his heart rate following exercise
consistently decreased from T1 to T4 (total decrease of 8.1 BPM). The largest reduction in heart
rate following exercise occurred between T1 and T2 (representing a decrease of 7.1 BPM).
3.8.2 Participant 2 (Kyle)
When compared to both baseline and control conditions, Kyle’s heart rate was
consistently higher following exercise across all 4 time intervals. While Kyle’s heart rate
remained relatively stable across the 4 time intervals during baseline and following the control
condition, he experienced a steady reduction in heart rate from T1 to T4 following exercise (total
decrease of 6.9 BPM). The largest reduction in heart rate following exercise occurred between
T1 and T2 (representing a decrease of 3.2 BPM).
3.8.3 Participant 3 (Dan)
Dan’s heart rate following exercise was consistently higher than his heart rate during
baseline and following the control condition across the 4 time intervals. Throughout baseline,
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there appears to be a steady, albeit, slight increase in heart rate across the 4 time intervals.
Following exercise, his heart rate demonstrated a constant reduction from T1 to T4 (total
decrease of 9.5 BPM). Following exercise, Dan’s heart rate dropped a total of 4.6 BPM between
T1 and T2, representing his largest post-exercise heart rate reduction across the 4 intervals.
3.8.4 Participant 4 (Tom)
Tom’s heart rate following exercise was consistently higher than his heart rate during
baseline and following the control condition across all 4 time intervals. Tom’s heart rate was
variable with no consistent trends across the 4 time intervals throughout baseline and following
the control condition. Following the exercise condition, Tom experienced a constant reduction in
heart rate from T1 to T4 (total decrease of 4.8 BPM). The largest reduction in Tom’s heart rate
following exercise occurred between T1 and T2 (representing a decrease of 2.1 BPM).
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Bobby
Kyle
Dan
Tom
Figure 14. Heart rate during baseline and following experimental conditions across T1, T2, T3, and T4.
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3.9 Correlational Analysis
To determine the extent to which physiological measures (average heart rate during the 2
hour observational period and average heart rate during the experimental condition) were
associated with behavioural measures (i.e., frequency of disruptive behaviours, frequency of
prosocial behaviours, and percent compliance to teacher requests) a series of correlation
coefficients were computed. Correlational analyses were conducted separately for each
participant. The results of the correlational analysis for participants 1, 2, 3, and 4 are presented in
Tables 2, 3, 4, and 5 respectively.
3.9.1 Participant 1 (Bobby)
The results of the correlational analysis presented in Table 2 indicate that Bobby’s
average heart rate during the observational period was negatively correlated with the frequency
of his disruptive behaviours (r = -.60, p = .01 ). Bobby’s average heart rate during the
observational period was not significantly correlated with the frequency of his prosocial
behaviours or his compliance to teacher requests. His average heart rate during the experimental
condition was negatively correlated with the frequency of his disruptive behaviours (r = -.80, p =
.000 ) and positively correlated with the frequency of his prosocial behaviours (r = .52, p = .03 )
and compliance to teacher requests (r = .67 , p = .003).
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Table 2
Correlations among Behavioural and Physiological Measures for Participant 1 (N = 17)
______________________________________________________________________________
1. 2. 3. 4. 5.
______________________________________________________________________________
1. DB 1 -.29 -.52* -.60* -.80**
2. PB . 1 .65** .46 .52*
3. %CTR . . 1 .37 .67**
4. HRObs . . . 1 .67**
5. HRExCond . . . . 1 ______________________________________________________________________________* Correlation is significant at the .05 level ** Correlation is significant at the .01 level
Note: DB = Frequency of Disruptive Behaviours PB = Frequency of Prosocial Behaviours % CTR = Percent Compliance to Teacher Requests HRObs = Average Heart Rate During Observational Session HRExCond = Average Heart Rate During Experimental Condition
3.9.2 Participant 2 (Kyle)
As can be seen in Table 3, Kyle’s average heart rate during the observational period was
negatively correlated with the frequency of his disruptive behaviours (r = -.78, p = .000) and
positively correlated with both the frequency of his prosocial responding (r = .63 , p = .007) and
compliance to teacher requests (r = .64, p = .005). A similar pattern of correlations was found
between Kyle’s average heart rate during the experimental condition and his behavioural
functioning. That is, his average heart rate during the experimental condition was negatively
correlated with the frequency of his disruptive behaviours (r = -.80, p = .000) and positively
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correlated with the frequency of his prosocial responding (r = .76, p = .000) and compliance to
teacher requests (r = .73, p = .001).
Table 3
Correlations among Behavioural and Physiological Measures for Participant 2 (N = 17)
______________________________________________________________________________
1. 2. 3. 4. 5.
______________________________________________________________________________
1. DB 1 -.68** -.68** -.78** -.80**
2. PB . 1 .67** .63** .76**
3. %CTR . . 1 .64** .73**
4. HRObs . . . 1 .87**
5. HRExCond . . . . 1 ______________________________________________________________________________* Correlation is significant at the .05 level ** Correlation is significant at the .01 level
Note: DB = Frequency of Disruptive Behaviours PB = Frequency of Prosocial Behaviours % CTR = Percent Compliance to Teacher Requests HRObs = Average Heart Rate During Observational Session HRExCond = Average Heart Rate During Experimental Condition
3.9.3 Participant 3 (Dan)
The results of the correlational analysis presented in Table 4 indicate that Dan’s average
heart rate during the observational period was negatively correlated to the frequency of his
disruptive behaviours (r = -.68, p = .001). His heart rate during the observational phase was not
significantly correlated with measures of prosocial responding or compliance. Dan’s average
heart rate during the experimental condition was negatively correlated with the frequency of his
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disruptive behaviours (r = -.82, p = .000) and positively correlated with the frequency of his
prosocial behaviours (r = .75, p = .000) and compliance to teacher requests (r = .64, p = .003)
Table 4
Correlations among Behavioural and Physiological Measures for Participant 3 (N = 19) ______________________________________________________________________________
1. 2. 3. 4. 5.
______________________________________________________________________________
1. DB 1 -.52* -.79** -.68** -.82**
2. PB . 1 .54* .41 .75**
3. %CTR . . 1 .32 .64**
4. HRObs . . . 1 .67**
5. HRExCond . . . . 1 ______________________________________________________________________________* Correlation is significant at the .05 level ** Correlation is significant at the .01 level
Note: DB = Frequency of Disruptive Behaviours PB = Frequency of Prosocial Behaviours % CTR = Percent Compliance to Teacher Requests HRObs = Average Heart Rate During Observational Session HRExCond = Average Heart Rate During Experimental Condition
3.9.4 Participant 4 (Tom)
Results of the correlational analysis presented in Table 5 indicate a number of significant
correlations between Tom’s average heart rate and his behavioural functioning. Tom’s heart rate
during the observational period was negatively correlated with the frequency of his disruptive
behaviours (r = -.71, p = .001) and positively correlated with measures of his prosocial (r = .55, p
= .01) and compliant responding (r = .63, p = .004). Similarly, Tom’s average heart rate during
the experimental condition was negatively correlated with the frequency of his disruptive
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behaviours (r = -.73, p = .000) and positively correlated with measures of his prosocial (r = .76 ,
p = .000) and compliant behaviours (r = .64, p = .003).
Table 5
Correlations among Behavioural and Physiological Measures for Participant 4 (N = 19) ______________________________________________________________________________
1. 2. 3. 4. 5.
______________________________________________________________________________
1. DB 1 -.46* -.44 -.71** -.73**
2. PB . 1 .54* .55* .76**
3. %CTR . . 1 .63** .64**
4. HRObs . . . 1 .82**
5. HRExCond . . . . 1 ______________________________________________________________________________* Correlation is significant at the .05 level ** Correlation is significant at the .01 level
Note: DB = Frequency of Disruptive Behaviours PB = Frequency of Prosocial Behaviours % CTR = Percent Compliance to Teacher Requests HRObs = Average Heart Rate During Observational Session HRExCond = Average Heart Rate During Experimental Condition
In summary, results of the correlational analysis revealed a number of significant
correlations between participants’ averaged heart rate (both during the observational period and
experimental condition) and their behavioural functioning. With regards to averaged heart rate
during the observational period, all participants showed a significant and negative correlation
between their heart rate and the frequency of disruptive behaviours. These results suggest that
higher heart rate during the observational period was associated with a reduced frequency of
disruptive behaviours. Two participants (participants 2 and 4) showed significant and positive
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correlations between their averaged heart rate during the observational period and the frequency
of prosocial responding and compliance to teacher requests. For these participants, higher heart
rates during the observational period were associated with an increase in prosocial responding
and compliance. All participants demonstrated the same pattern of significant correlations
between heart rate during the experimental condition and behavioural functioning. More
specifically, results indicated that elevated heart rates during the experimental condition was
associated with reduced levels of disruptive behaviours and elevated levels of both prosocial
responding and compliance to teacher requests.
3.10 Self-report Measures
3.10.1 Bored/Excited Scale
Overall mean scores for the bored/excited visual analog scale are presented in Figure 15.
This score reflects how bored or excited participants perceived themselves to be during all
observational sessions in baseline, control, and exercise conditions (higher scores reflect greater
levels of perceived excitement). Results suggest that participants experienced heightened levels
of excitement following exercise sessions compared to control sessions.
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Figure 15: Overall mean self-report scores for bored/excited visual analog scale.
3.10.2 Tired/full of Energy Scale
Overall means scores for the tired/full of energy visual analog scale are presented in
Figure 16. These scores reflect how tired or full of energy participants perceived themselves to
be during all observational sessions (higher scores reflect elevated levels of perceived energy).
Results suggest that following exercise, participants reported higher levels of energy compared
to the control and baseline condition.
0
1
2
3
4
5
6
7
8
9
Ove
rall Mean Self-Rep
ort Sco
re
Condition
BaselineControlExercise
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Figure 16: Overall mean self-report scores for tired/full of energy visual analog scale.
3.10.3 Tense/Relaxed Scale
Overall mean scores for the tense/relaxed visual analog scale are presented in Figure 17.
These scores reflect how tense or relaxed participants perceived themselves to be during all
observational sessions (higher scores reflects elevated levels of perceived relaxation). Results
suggest that following exercise, participants reported feeling greater levels of relaxation
compared to both baseline and control.
0
1
2
3
4
5
6
7
8
9
Ove
rall Mean Self-Rep
ort Sco
re
Condition
Baseline
Control
Exercise
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Figure 17. Overall mean self-report scores for tense/relaxed visual analog scale.
0
1
2
3
4
5
6
7
8
9
Ove
rall Mean Self-Rep
ort Sco
re
Condition
BaselineControlExercise
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Chapter 4: Discussion
In the present study, we investigated three aspects of antecedent exercise. First, we
replicated the beneficial behavioural effects of antecedent exercise in a group of school-aged
children demonstrating severe antisocial, disruptive, and aggressive behaviours. Second, we
evaluated the temporal effects of exercise and found that behavioural improvements continued
for approximately 90 minutes. Finally, we assessed a potential mechanism that may help explain
the behavior change following exercise. Findings suggested that increased arousal may play a
role in accounting for these improvements.
4.1 Replication of Previous Findings
In a meta-analysis conducted by Allison, Faith, and Franklin (1995), results indicated that
exercise was effective at reducing aberrant behaviour in both children and adults with a variety
of social, emotional, behavioural and medical disorders. Findings from the present investigation
provide additional evidence supporting this effect with 4 students in a behavioural classroom.
During baseline sessions, all 4 students evinced high levels of disruptive behaviours and low
levels of both prosocial responding and compliance to teacher requests. Following 30 minutes of
aerobic exercise, all four participants demonstrated a substantial reduction in the frequency of
their disruptive behaviours and sizeable improvements in both prosocial responding and
compliance to teacher requests. None of the participants demonstrated improved behaviour
following the control condition.
4.2 Temporal Effects
To evaluate the temporal effects of antecedent exercise, behavioural functioning was
systematically evaluated across four 30 minute time-intervals following exercise: 0-30 minutes
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(T1), 30-60 minutes (T2), 60-90 minutes (T3), and 90-120 minutes (T4). Compared to the
control condition, all four participants experienced a reduction in the frequency of their
disruptive behaviours for T1, T2, and T3. However, for T4, this effect dissipated and the
frequency of disruptive behaviours increased to a level comparable to both baseline and control
conditions. A similar temporal trend was observed for prosocial responding. All four participants
demonstrated an increase in the frequency of their prosocial behaviours following exercise for
T1, T2, and T3 compared to the control condition. However, the observed improvement in
prosocial behaviour was no longer present for any of the four participants for T4.
The temporal effects of antecedent exercise on compliance differed slightly from those
found for disruptive and prosocial behaviours. For T1 and T2, all four participants evinced
improved compliance. Although participants 1, 2, and 4 continued to show improved compliance
for T3, the beneficial effects for participant 3 were not as apparent. By T4, compliance gains had
dissipated for all participants except participant 4, who continued to experience slight
improvements in compliance.
In summary, 30 minutes of moderate to intense aerobic exercise resulted in
approximately 90 minutes of behavioural improvement. For some participant behaviours the
effects were slightly shorter lasting (i.e., compliance improved for approximately 60 minute for
Dan) and in others slightly longer (i.e., compliance improved for the entire 2 hour duration for
Kyle).
To date, only one other study has investigated the temporal effects of antecedent exercise
(e.g., Celiberti, Bobbo, Kelly, Harris, & Handleman, 1997). In this study, post-exercise
behaviours were observed in a 5- year-old boy with autism for a period of 40 minutes. Results
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indicated that aberrant behaviours (i.e., physical self-stimulatory and out of seat behaviour)
decreased following exercise and remained below baseline levels at the conclusion of the
observational period. This finding suggests that the participant was still experiencing beneficial
effects of exercise beyond the final behavioural observation. Thus, the precise duration of
positive effects was not established. To our knowledge, the present study is the first to
systematically assess the temporal effects of antecedent exercise through observations of
behaviours until the post-exercise effects have dissipated, providing an estimation of the extent
of post-exercise behavioural improvements.
4.3 Mechanism of Action
4.3.1 Evidence from Physiological Data
Physiological measures of arousal (i.e., heart rate) were obtained to better understand
potential mechanisms accounting for improved behaviours following exercise. Results from the
correlational analyses indicate that elevated arousal levels are associated with reductions in
disruptive conduct and increases in prosocial behaviours.
As expected, exercise resulted in elevated heart rate for all participants that gradually
decreased over time, suggesting a steady reduction in arousal levels. These findings correspond
to those of a study by Forjaz, Matsudaira, Rodrigues, Nunes, & Negrao (1998) in which 12
healthy adults took part in 45 minutes of moderate to intense exercise. Following exercise,
participants’ heart rates were assessed for a period of 90 minutes. Results indicated that for 60
minutes after exercise, heart rates remained significantly higher than baseline levels. However,
between 60 and 90 minutes post-exercise, heart rates returned to baseline levels. These findings,
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along with the present results, suggest that the effects of exercise on physiological arousal
diminish between 60 and 90 minutes post-exercise.
To provide evidence supporting the notion that physiological arousal is a potential
mechanism accounting for behavioural change, it is necessary to demonstrate that post-exercise
behavioural improvements diminish as post-exercise arousal decreases. Our findings indicated
that the behavioural benefits of exercise lasted for approximately 90 minutes, appearing to co-
vary with gradually decreasing heart rates. This association between heart rate and post-exercise
behaviour change suggests that arousal is likely a key variable in explaining the benefits
achieved.
4.3.2 Evidence from Self-report Data
To gain further insight related to mechanism of action, a number of self-report measures
were completed by participants. When compared to the control condition, exercise was
associated with self-reported elevated levels of excitement, greater levels of energy, and
heightened relaxation. Our findings suggesting that exercise is associated with positive affect is
consistent with previous research (e.g., see Berger & Molt, 2000 and Yeung, 1996 for reviews).
For example, in a study conducted by Rendi, Szabo, Szabo, Velenczei, and Kovacs (2008),
participants reported an immediate after-exercise “high” following 20 minutes of exercise. Taken
together, results from our study and previous research suggest that following exercise,
individuals experience a heightened sense of arousal (i.e., greater excitement and energy).
As previously discussed, the stimulation seeking theory (Eysenck, 1997; Raine et al.,
1990) suggests that some children engage in antisocial behaviour because they are underaroused.
Based on this theory, one would predict that when children are bored and underaroused, they
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would engage in more disruptive behaviour than when they are excited (i.e., feeling aroused).
Both the physiological and self-report data in the present research are consistent with this
prediction. The results of the present study show an inverse relationship between arousal levels
and problem behaviour. Thus, it appears that elevated arousal plays a significant role in
accounting for behavioural improvements following exercise.
4.4 Implications
4.4.1 Ruling out Competing Mechanism
As previously discussed, the fatigue hypothesis posits that behaviour problems decrease
following exercise because individuals become tired (Allison, Faith, & Franklin, 1995).
According to this hypothesis, one would predict that participants would report elevated levels of
fatigue following exercise along with the concomitant reduction in problem behaviour. To test
this hypothesis, participants in the present study were asked to provide self-reports of how
“tired” or “full of energy” they felt following experimental sessions. Results indicate that self-
reported fatigue levels were highest following control sessions and lowest following the exercise
condition, in which participants unanimously reported elevated levels of energy. Thus, our
results provide no support for the fatigue hypothesis. In fact, participants in the present study
displayed higher levels of problem behaviour when they reported elevated levels of fatigue
following the control condition. These findings are consistent with previous research showing an
association between fatigue and externalizing conduct (e.g., Haller & Kruk, 2006; Haack &
Mullington, 2005; Kuo & Sullivan, 2001; Whalen, Jamner, Henker, & Delfino, 2001).
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4.4.2 Potential Generalizability of Antecedent Exercise
The average resting heart rate for children 11 to 17 years of age is between 60 to 100
BPM (Johnson & Moller, 2001). Although the 4 participants in the present investigation had
resting heart rate levels within the normative range, a high degree of variability was noted. More
specifically, the average resting heart rate for Bobby (77 BPM) and Kyle (72 BPM) was closer to
the lower end of the normative range whereas the heart rate for Dan (82 BPM) and Tom (92
BPM) fell towards the middle and upper end of the normative range, respectively.
Three previous studies have measured resting heart rate levels among behaviourally
disordered youth in the age range of those in the present study. First, Rogeness et al. (1990)
examined resting heart rate and blood pressure in children and adolescents admitted to a
psychiatric hospital. Of the total admitted, 173 were males diagnosed with conduct disorder
(mean age of 11.6, SD = 3.3); their average resting heart rate was 79 BPM. In a separate study,
Davies and Maliphant (1971) found the average resting heart rate of 30 conduct disordered
English boarding-school pupils (mean age of 13.6 years) to be 77 BPM. Finally, in Zahn and
Kruesi (1993) the average resting heart rate in 34 boys with a diagnosis of conduct disorder
(mean age of 11.1, SD = 3.3) was 80 BPM. Thus, the average resting heart rate in these studies
ranged from 77 to 80 BPM. In the present investigation, only Tom had a resting heart rate (i.e.,
92 BPM) that substantially exceeded this range.
As noted by Ortiz and Raine (2004), only individuals with antisocial, disruptive, and
aggressive behaviours are characterized by low resting heart rate. For instance, in the Rogeness
et al. (1990) study, male participants (mean age 11, SD = 2.2) diagnosed with separation anxiety
had an average resting heart rate of 92 BPM, considerably higher than those with conduct
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difficulties. Similarly, participants with lower resting heart rates in the present investigation (i.e.,
Bobby, Kyle, and Dan) displayed more frequent and severe externalizing difficulties compared
to the participant with a higher resting heart rate (Tom). Tom displayed an average of 20
disruptive behaviours per baseline session while Bobby, Kyle, and Dan demonstrated an average
of 62, 52, and 48 disruptive behaviours respectively. Moreover, the average compliance to
teacher request across all baseline sessions for Bobby (50%), Kyle (53%), and Dan (48%) was
lower than that of Tom (59%). Results from the Teacher Report Form are also indicative of more
severe problem behaviours among the participants with lower resting heart rate levels. On this
measure, all participants were in the clinical range for externalizing difficulties with the
exception of Tom, who fell in the border line clinical range.
In addition to providing further evidence that low resting heart rate is associated with
antisocial, disruptive, and aggressive behaviour, the present results suggest the potential
usefulness of antecedent exercise for children experiencing a broader range of emotional and
behavioural disorders. Tom’s average resting heart rate exceeds what is typically observed in
conduct disordered youth his age and is more reflective of anxious individuals (Rogeness et al.,
1990). Reports from the Teacher Report Form indicated that Tom was in fact within the
borderline-clinical range for anxiety problems (T Score = 65). Notwithstanding this diagnostic
disparity with the other participants, antecedent exercise resulted in substantial reductions in
Tom’s behavioural difficulties. Although one cannot draw firm conclusions from such a small
sample, these findings suggest the possibility that the potential effectiveness of antecedent
exercise may extend beyond individuals whose behavioural difficulties are due solely to
underarousal.
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4.4.3 Clinical Implications: Antecedent Exercise as a Moderating Approach
In the present study, antecedent exercise resulted in immediate reductions in aberrant
behaviours and noticeable improvements in prosocial responding and compliance.
Notwithstanding these behavioural gains, the beneficial effects of exercise were relatively short
lasting (i.e., approximately 90 minutes). Thus, from a treatment perspective, exercise used in
isolation does not appear to result in long-term benefits. Unlike many effective treatment
approaches for antisocial behaviour (e.g., social skills training, anger management training,
problem solving training), our exercise condition did not include any strategies for assisting the
students in interacting effectively with the challenges presented by their environment (i.e., skill
building components). Under such circumstances, it is not surprising that the students failed to
demonstrate longer lasting behavioural improvements.
To better appreciate the potential clinical utility of antecedent exercise, it may be useful
to make the distinction between remedial and moderating approaches. According to Ducharme
(1999), remedial approaches involve teaching individuals various strategies and skills to replace
aberrant behaviours. Once learned, these adaptive skills can be used by the individual to more
effectively manage and/or tolerate conditions that formerly contributed to their aberrant
behaviours. A fundamental aspect of remedial approaches is the long-term clinical benefit they
produce for the individual. On the other hand, moderating approaches lead to immediate
alleviation of problem behaviour, but typically do not provide long-term benefits (Ducharme,
1999). Within a clinical context, moderating approaches serve an important purpose as they can
be used to increase prosocial responding and reduce problem behaviours enough in the short-
term that the individual is more amenable to skill-building approaches. In this regard, Ducharme
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(1999) posits that moderating approaches can potentially open up “windows of opportunity” for
the use of remedial approaches.
A number of remedial or skill building interventions exist for treatment of antisocial
behaviour (e.g., Ducharme, Folino, & DeRosie, 2008; Folino, Ducharme, & Conn, 2008; Sim,
Whiteside, Dittner, & Mellon, 2006; Fraser et al., 2005; Ooi & Ang, 2004; Lane, Wehby,
Menzies, Doukas, Munton, & Gregs, 2003). The underlying goals of these interventions are to
replace problem behaviours with more adaptive skills and strategies. Given that individuals
diagnosed with antisocial disorders typically present with heightened levels of aggression, non-
compliance, disruptiveness, and rule-breaking behaviour (Ladd, Herald, & Kochel, 2006),
intervention agents may have difficulty implementing treatment procedures, such as skill-
building programs, for these individuals, especially in educational settings. Under such
circumstances, exercise may be a useful prelude to remedial approaches. Our findings indicated
that a brief bout of exercise resulted in approximately 90 minutes of behavioural improvement
and cooperation, potentially an ideal “window of opportunity” for use of skill-building
approaches that can greatly increase the likelihood of long-term gains.
In addition to skill building approaches, psychopharmacological interventions are
commonly used to treat antisociality among youth (e.g., Pandina, Aman, & Findling, 2006;
Rifkin et al., 1997). Despite being somewhat effective in the treatment of antisocial conduct
(e.g., see Ipser & Stein, 2007; Bassarath, 2003 for reviews), there is a paucity of controlled
studies assessing the safety and efficacy of drugs (Lazaratou, Anagnostopoulos, Alevizos,
Haviara, & Ploupidis, 2007). Although psychoactive agents may result in short-term behavioural
improvements, implementation of medication alone does not typically teach individuals the
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requisite skills to manage difficult circumstances in their environment. As a result, behavioural
pharmacology may be best conceptualized as a moderating approach.
Generally speaking, parents often express concern about exposing their children to
psychoactive medications (Pescosolido, Perry, Martin, McLeod, & Jensen, 2007) and prefer non-
pharmacological treatments for the management of their child’s psychiatric disorders (Lazaratou,
Anagnostopoulos, Alevizos, Haviara, & Ploupidis, 2007; Pescosolido, Perry, Martin, McLeod, &
Jensen, 2007). Due to the potential risks and side-effects associated with medication (Ipser &
Stein, 2007; Wilens, Jefferson, & Biderman, 2006), child advocates argue that pharmacological
treatments should be used only after less risky psychosocial interventions have failed (Correll,
Kane, & Malhotra, 2010). Given that the potential harm associated with antecedent exercise is
minimal (Allison, Faith, & Franklin, 1995), this approach may be a viable treatment option that
can be used as an alternative to (or in conjunction with) more intrusive treatment alternatives
such as medication. In contrast to pharmacological interventions, the social acceptability of
exercise is high for both parents and children, who consistently report positive attitudes towards
such activity (Graham, 2008).
4.4.4 Implications for Schools and Educators
The present findings are of particular interest to educators, as teachers commonly seek
simple strategies for managing problem behaviours in their classrooms. Moreover, schools have
been identified as ideal settings for the promotion of physical activity (Verstraete, Cardon, De
Clercq, & De Bourdeaudhuij, 2006). For antecedent exercise to be used most effectively as a
means of enhancing prosocial responding in schools, teachers must consider several factors.
First, given that the effects of exercise appear to weaken after approximately 90 minutes,
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teachers may wish to incorporate brief bouts of aerobic exercise throughout the day for students
with severe behavioural difficulties (both gym class and recess provide students with naturally
occurring opportunities to engage in vigorous activity). Moreover, teachers may wish to
strategically embed exercise activities at times of the day when they would be optimally
beneficial to students. For example, our findings suggest that the largest improvements in
behaviour occurred immediately following exercise (i.e., 0-30 minutes). Thus, teachers may
wish to expose students to vigorous activity just before important lessons, tests, etc. In addition,
assuming the student is physically active during recess time, it may be best to plan physical
education class approximately 90 minutes after recess so that the students experience optimal
durations of behavioural benefit.
Secondly, our findings suggest that students must engage in moderate to intense physical
activity to access behavioural gain. As a result, teachers may wish to organize gym and recess
activities that incorporate fun aerobic components such as jogging and skipping that are known
to increase cardiovascular activity and arousal.
4.5 Limitations and Future Directions
The first limitation of the present investigation involves the sample size of only four
students, reducing the potential generalizability of the findings. Although our design allowed for
a detailed evaluation of experimental manipulations on individual participants, we were unable
to conduct additional statistical analysis (i.e., regressions, etc), to further explore the relationship
between resting heart rate, exercise, and behavioural outcomes. It is important to note, however,
that although the number of participants in the present study is considered small for traditional
research designs, it served as an ideal sample size for intensive time-series examination of the
process, temporal outcomes, and physiological effects of the intervention. Given the extensive
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time and resources needed to achieve these research goals with four subjects, a larger sample size
would have far exceeded reasonable limits for dissertation research.
The second limitation is the absence of female students in the sample. Research suggests
that the relationship between resting heart rate and antisocial behaviours is largely the same for
males and females (Ortiz & Raine, 2004); however, the present sample precluded an examination
of the potential utility of antecedent exercise for school aged females. Although conduct
disorders are much more prevalent among males than females (Kindlon, Trremblay,
Mezzacappa, Earls, Laurent, & Schaal, 1994), it would be informative in future studies to
determine the effectiveness of antecedent exercise with female participants.
The third limitation of the present study is the narrow age range of the participants
involved. In our investigation all four participants were either teenagers or pre-teens. Given that
behavioural difficulties often begin at much younger ages, it would be useful to include younger
participants in a study examining the effects of antecedent exercise.
A fourth limitation involves the manner in which we explored the temporal effects of
antecedent exercise. For the temporal analysis, we evaluated student behaviour across four 30
minute time intervals (i.e., 0-30 minutes, 30-60 minutes, 60-90 minutes, and 90-120 minutes) for
a total duration of 2 hours. Our decision to segment behavioural observations into 30 minute time
intervals was arbitrary. Although this measurement tactic enabled us to determine that the effects
of antecedent exercise diminish somewhere between 90 and 120 minutes, shorter time intervals
(e.g., every 10 minutes) would have enabled us to make more precise conclusions regarding
temporal effects.
Another potential limitation of the present study involved use of a relatively inexpensive
heart rate monitor. Given that we needed to record participant heart rates on several occasions
104
throughout the school day, it was essential to conduct these measurements in an efficient and
non-intrusive manner. Although the monitor we used provided such practicality, there are a
number of more technically sophisticated devices that can provide greater measurement
precision. Note, however, that in their meta-analytic findings on the effects of heart rate on
antisocial behaviour, Ortiz and Raine (2004) found that studies involving simple devices
(comparable to those used in the present study) produced just as strong an effect size as those
using more sophisticated equipment, leading these authors to conclude that more sophisticated
technology is not required for these studies.
One final shortcoming of the present investigation relates to the narrow range of
circumstances in which observations were conducted. Following all experimental conditions,
participants were observed only in their classroom. To determine the persistence of behavioural
improvements in a wider range of contexts, it would be informative to conduct observations in
alternative settings such as the playground, school assemblies, and hallways where problem
behaviours commonly occur.
Another consideration for future research involves the relationship between the intensity
of physical activity and the magnitude of the behavioural effects. Although previous research
suggests that “vigorous exercise” is most effective at reducing disruptive behaviours (Celiberti et
al., 1997; Kern, Koegel, & Dunlap, 1984), there is little research evaluating the minimum
duration and intensity of aerobic exercise necessary to produce positive behavioural changes.
Although the present study included 30 minute exercise sessions, it is possible that similar
behavioural effects could have been achieved with less student effort. Manipulation of duration
and intensity in future studies might help to determine the most efficient exercise dosage for
optimal behavioural effects.
105
Future research is also needed to explore the effectiveness of antecedent exercise with
other diagnostic groups such as those with anxiety disorder. In our sample, one of the students
who scored high on measures of anxiety difficulties demonstrated a reduction in aberrant
behaviours following exercise. Although the effectiveness of exercise has been examined most
extensively for students with conduct difficulties, additional research is needed to determine if
exercise is suitable and effective for individuals from other diagnostic groups.
Finally, although exercise offers a socially acceptable and relatively safe way to increase
physiological arousal (Allison, Faith, & Franklin, 1995), physical activity may not be suitable for
all students (e.g., those with physical impairments). Future research should investigate the effects
on problem behaviour of other forms of arousing stimuli that can be easily incorporated in the
classroom. For example, music has been shown to influence cardiovascular activity and heighten
physiological arousal (e.g., Oliver, Reinhard, & Eckart, 2009; Lemmer, 2008; Riganello,
Quintieri, Candelieri, Conforti, & Dolce, 2008).
In summary, our findings suggest that antecedent exercise is an effective, safe, and
socially accepted way to temporarily reduce maladaptive behaviours and increase compliance
among school-aged children with severe antisocial behaviours. Given the trend towards inclusive
classrooms, teachers require interventions that are not only effective at improving behaviour but
also result in the least amount of disruption and ostracization for the student(s) involved. With
these goals in mind, exercise based interventions may be a welcomed strategy for teachers
developing intervention plans for challenging students.
106
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Appendix A
General Health Screener
Dear Parent/Guardian,
To ensure the safety and well-being of your child, we kindly ask that you inform us of any pre-existing health or medical conditions that your child may experience. Only those children with no pre-existing health difficulties or prohibitive physical conditions will be permitted to participate. Please answer the questions below to the best of your ability.
1) Does your child have any health, medical, or physical concerns that would prevent them from engaging in 20 minutes of physical activity?
[ ] Yes [ ] No
If yes, please explain:
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
2) Does your child participate in his/her regular physical education class?
[ ] Yes [ ] No
If No, please explain:
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
3) Is your child currently taking any medication(s) that may increase their risks of injury or health complications if they engage in exercise or physical activities?
[ ] Yes [ ] No
If yes, please explain:
________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
135
Appendix B
SPORTLINE Solo 920 Heart Rate Watch ®
136
Appendix C
Data Recording Sheets for Heart Rate during Experimental Conditions
Date of observation: _____________________
Coders Name: _________________________
ID of student being observed: _________________________
Study Phase: ______________________
Time 1: (10 min)
Please write down the number that is on your watch: _______________
Time 2: (15 min)
Please write down the number that is on your watch: _______________
Time 3: (20 min)
Please write down the number that is on your watch: _______________
Time 4: (30 min)
Please write down the number that is on your watch: _______________
Instructions: Please look down at your watch and write down the number that you see on it.
137
Appendix D
Data Recording Sheets for Heart Rate during Observational Periods
Date of observation: _____________________
Coders Name: _________________________
ID of student being observed: _________________________
Study Phase: __________________________
Time 1: (30 min)
Please write down the number that is on your watch: _______________
Time 2: (60 min)
Please write down the number that is on your watch: _______________
Time 3: (90 min)
Please write down the number that is on your watch: _______________
Time 4: (120 min)
Please write down the number that is on your watch: _______________
Instructions: Please look down at your watch and write down the number that you see on it.
138
Appendix E
Visual Analog Scale (Tense - Relaxed Scale)
Time 1 (30 min)
Time 2 (60 min)
Tense Relaxed
Tense Relaxed
Instructions: Please place a mark on the line below that best
describes how you are feeling right now.
139
Time 3 (90 min)
Time 4 (120 min)
Tense Relaxed
Tense Relaxed
140
Appendix F
Visual Analog Scale (Tired – Full of Energy Scale)
Time 1 (30 min)
Time 2 (60 min)
Tired Full of Energy
Tired Full of Energy
Instructions: Please place a mark on the line below that best describes how you are feeling right now.
141
Time 3 (90 min)
Time 4 (120 min)
Tired Full of Energy
Tired Full of Energy
142
Appendix G
Visual Analog Scale (Bored – Excited Scale)
Time 1 (30 min)
Time 2 (60 min)
Bored Excited
Bored Excited
Instructions: Please place a mark on the line below that best describes how you are feeling right now.
.
143
Time 3 (90 min)
Time 4 (120 min)
Bored Excited
Bored Excited
144
Appendix H
Behavioural Coding Sheets
Coders Name: _________________________
Date of observation: _____________________
ID of student being observed: ________________________
Disruptive Behaviours Prosocial Behaviours
Compliance to teacher requests
Comments
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
V PO POBJ DO OS O PV PP Y N
145
Legend
Disruptive Behaviours
V = Student demonstrates verbal aggression towards self or others
PO = Student demonstrates physical aggression towards others
POBJ = Student demonstrates physical aggression towards an object
DO = Student is disruptive towards peer or teacher (e.g., speaks to student during lesson, calls out answers without raising hand, etc.)
OS = Student leaves seat without permission
O = Other forms of disruptive behaviours
Prosocial Behaviours
PV = Student demonstrates a prosocial verbal behaviour (e.g., complimenting a student)
PP = Student demonstrates a prosocial physical behaviour (e.g., physically helping a student or teacher)
Compliance to Teacher Requests
Y = Complied to teacher request
N = Failed to comply to teacher request
146
Appendix I
Mann-Whitney U Test Statistics
Mann-Whitney U Test Statistics for the Overall Effects of Antecedent Exercise on Disruptive Behaviours (2 hour duration) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 5.5 15 Yes
Kyle 8 9 6 15 Yes
Dan 9 10 5.5 20 Yes
Tom 9 10 10 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
147
Mann-Whitney U Test Statistics for the Overall Effects of Antecedent Exercise on Prosocial Behaviours (2 hour duration) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 9.5 15 Yes
Kyle 8 9 -6.5 15 Yes
Dan 9 10 -1 20 Yes
Tom 9 10 3.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
148
Mann-Whitney U Test Statistics for the Overall Effects of Antecedent Exercise on Compliance to Teacher Requests (2 hour duration) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 3 15 Yes
Kyle 8 9 -1.5 15 Yes
Dan 9 10 5.5 20 Yes
Tom 9 10 5.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
149
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Disruptive Behaviours (0-30 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 7.5 15 Yes
Kyle 8 9 7 15 Yes
Dan 9 10 4.5 20 Yes
Tom 9 10 4.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
150
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Disruptive Behaviours (30-60 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 12.5 15 Yes
Kyle 8 9 13.5 15 Yes
Dan 9 10 4.5 20 Yes
Tom 9 10 18.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
151
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Disruptive Behaviours (60-90 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 9 15 Yes
Kyle 8 9 4.5 15 Yes
Dan 9 10 18.5 20 Yes
Tom 9 10 22 20 No
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
152
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Disruptive Behaviours (90-120 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 24 15 No
Kyle 8 9 56.5 15 No
Dan 9 10 76 20 No
Tom 9 10 58.5 20 No
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
153
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Prosocial Behaviours (0-30 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 0.5 15 Yes
Kyle 8 9 5 15 Yes
Dan 9 10 -8.5 20 Yes
Tom 9 10 -1.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
154
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Prosocial Behaviours (30-60 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 13.5 15 Yes
Kyle 8 9 -2.5 15 Yes
Dan 9 10 2.5 20 Yes
Tom 9 10 8 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
155
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Disruptive Behaviours (60-90 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 14 15 Yes
Kyle 8 9 7 15 Yes
Dan 9 10 13.5 20 Yes
Tom 9 10 20 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
156
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Prosocial Behaviours (90-120 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 41.5 15 No
Kyle 8 9 43.5 15 No
Dan 9 10 40 20 No
Tom 9 10 50 20 No
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
157
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Compliance to Teacher Requests (0-30 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 0 15 Yes
Kyle 8 9 1.5 15 Yes
Dan 9 10 -4.5 20 Yes
Tom 9 10 4.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
158
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Compliance to Teacher Requests (30-60 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 5.5 15 Yes
Kyle 8 9 6.5 15 Yes
Dan 9 10 12.5 20 Yes
Tom 9 10 10 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
159
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Compliance to Teacher Requests (60-90 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 16.5 15 No
Kyle 8 9 9 15 Yes
Dan 9 10 33.5 20 No
Tom 9 10 7.5 20 Yes
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
160
Mann-Whitney U Test Statistics for the Effects of Antecedent Exercise on Compliance to Teacher Requests (90-120 min) ______________________________________________________________________________
Participant n1 n2 U Critical Value Sig.
(U) (.05)
______________________________________________________________________________
Bobby 8 9 28.5 15 No
Kyle 8 9 15.5 15 No
Dan 9 10 39.5 20 No
Tom 9 10 54 20 No
______________________________________________________________________________
Note: n1 = Number of data points in the control condition; n2 = Number of data points in the
exercise condition; Sig = significant difference between exercise and control condition.
