Personality and Individual Differences xxx (2013) xxx–xxx

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Personality and Individual Differences

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An investigation of schizotypy in injecting amphetamine users

0191-8869/$ - see front matter � 2013 Published by Elsevier Ltd.http://dx.doi.org/10.1016/j.paid.2013.04.024

⇑ Corresponding author. Address: School of Applied Psychology, Griffith Univer-sity, Brisbane, Queensland 4111, Australia. Tel.: +61 7 3735 3371; fax: +61 7 37353388.

E-mail address: s.dawe@griffith.edu.au (S. Dawe).

Please cite this article in press as: Dawe, S., et al. An investigation of schizotypy in injecting amphetamine users. Personality and Individual Diff(2013), http://dx.doi.org/10.1016/j.paid.2013.04.024

Sharon Dawe a,⇑, Matthew J. Gullo b, Sam Minge a, Rebecca McKetin c, Leanne Hides d, David J. Kavanagh d,Ross McD. Young d

a School of Applied Psychology, Griffith University, Mt. Gravatt, Brisbane, Australiab Centre for Youth Substance Abuse Research, The University of Queensland, Brisbane, Australiac Centre for Research on Ageing, Health and Well-being, the Australian National University, Canberra, Australiad School of Psychology & Institute of Health & Biomedical Innovation, Queensland University of Technology, Brisbane, Australia

a r t i c l e i n f o

Article history:Received 10 February 2013Received in revised form 4 April 2013Accepted 19 April 2013Available online xxxx

Keywords:SchizotypyPersonalityAmphetamineO-LIFEPsychosis

a b s t r a c t

A fully dimensional view of psychiatric disorder conceptualises schizotypy as both a continuous person-ality trait and an underlying vulnerability to the development of psychotic illness. Such a model wouldpredict that the structure of schizotypal traits would closely parallel the structure of schizophrenia orpsychosis. This was investigated in injecting amphetamine users (N = 322), a clinical population whohave high rates of acute psychotic episodes and subclinical schizotypal experiences. Schizotypy wasassessed using the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE), and psychotic symp-toms were assessed using the Brief Psychiatric Rating Scale (BPRS). Using confirmatory factor analysis, O-LIFE subscale scores were mapped onto latent variables with their more clinical counterparts from theBPRS. A four-factor model comprising positive schizotypy, disorganisation, negative schizotypy, and dis-inhibition provided the best model fit, consistent with prior research into the structure of schizotypy. Themodel provided a good fit to the data, lending support to the theory that schizotypy and psychotic symp-toms map onto common underlying dimensions.

� 2013 Published by Elsevier Ltd.

1. Introduction

The relationship between schizotypy and schizophrenia hasbeen the subject of considerable theoretical debate and empiricalinvestigation. In what has been termed the ‘‘North American tradi-tion’’ schizotypy has been viewed as quasi dimensional, in whichboth schizotypy and the related construct of schizophrenia fallwithin a specific category of illness. The quasi dimensional compo-nent refers to the proposed variations in illness severity that occurwithin this category. A dimensional model reflects the conceptuali-sation of schizotypy as a personality trait normally distributedwithin the population that extends from non pathological manifes-tations through to psychosis proneness and ultimately to psychosis(see Claridge, 1997; Kwapil & Barrantes-Vidal, 2012). This dimen-sional view of psychosis predicts that the structure of schizotypyat the trait level closely parallels the structure of psychotic orschizophrenic symptoms.

The underlying factor structure of both schizophrenic symp-toms and schizotypal traits has been widely investigated, althoughnot in the same clinical groups. For example structural investiga-

tions of psychosis point to at least three classes of symptoms la-belled positive symptoms (perceptual aberrations and unusualbeliefs), negative symptoms (blunted affect, social anxiety, andlack of close friends), and disorganisation (odd behaviour andspeech). When mood symptoms are included in analyses, theyseem to constitute a separate factor. Positive and negative symp-toms appear to be orthogonal, whereas disorganised and positivesymptoms are typically correlated (e.g., Peralta & Cuesta, 2000,2001).

The structure of fully dimensional, trait-level schizotypy hasalso been widely investigated and it appears that schizotypy, likeschizophrenia, is multidimensional. Mirroring the distinction be-tween positive and negative symptoms in schizophrenia, the twomost reliable factors that emerge are positive schizotypy (unusualbeliefs, magical thinking, and perceptual aberrations) and negativeschizotypy (anhedonia and a lack of close friends). A third group oftraits comprising attentional difficulties and social anxiety hassometimes loaded on the positive schizotypy factor (Kelley & Cour-sey, 1992; Muntaner, Garcia, Fernandez, & Torrubia, 1988; Raine &Allbutt, 1989; Venables, 1990; Venables, Wilkins, Mitchell, Raine, &Bailes, 1990), but more often a separate factor labelled disorganisa-tion. When Eysenck’s Psychoticism scale is included, an impulsivityfactor reliably emerges (Claridge et al., 1996; Kendler & Hewitt,1992; Muntaner et al., 1988). More recent studies of schizotypymeasurement have investigated a shortened form of the original

erences

2 S. Dawe et al. / Personality and Individual Differences xxx (2013) xxx–xxx

Chapman’s Wisconsin Schizotypy Scales (WSS), in which originaland shortened versions of the Magical Ideation, Perceptual Aberra-tion, Social Anhedonia and Physcial Anhedonia scales were inter-nally consistent and highly intercorrelated (Gross, Silvia,Barrantes-Vidal, & Kwapil, 2012). Later work has found a two-fac-tor model with positive and negative symptom dimensions (Kwa-pil, Ros-Morente, Silvia, & Barrantes-Vidal, 2012).

Perhaps the largest structural investigation of schizotypy scaleswas initiated by Bentall and colleagues (Bentall, Claridge, & Slade,1989), who collated 10 existing psychosis-proneness scales to formthe Combined Schizotypal Traits Questionnaire (CSTQ). They re-ported a four-factor solution, corresponding to cognitive-percep-tual (‘‘positive’’) features, introverted anhedonia (‘‘negative’’features, with a strong negative loading for Eysenck’s Extraver-sion), a factor representing a mixture of cognitive disorganisationand social anxiety (on which Neuroticism also loaded highly),and a factor labelled impulsive nonconformity (defined largely byEysenck’s Psychoticism and Lie Scales). Subsequent studies usingthe CSTQ have showed this 4-factor structure to be robust (Cla-ridge et al., 1996; Mason, Claridge, & Jackson, 1995). Mason et al.(1995) used these studies to devise their 4-subscale schizotypyinstrument: the Oxford-Liverpool Inventory of Feelings and Experi-ences (O-LIFE). In summary, while previous work suggested theexistence of a 2-factor or 3-factor model of schizotypy, more recentresearch strongly argues for an underlying 4-factor structure.

The comparability between the factor structure of schizophre-nia symptoms and questionnaire measurement of schizotypy isstriking. However, to date, there has not been any investigationof the convergence between questionnaire measurement and ob-served schizophrenia-like symptoms. This is a difficult undertakingas nonclinical groups have low rates of psychotic symptoms, whilepeople with a psychotic disorder are elevated across most pro-posed dimensions. However, this line of investigation could takeplace in a sample that would be expected to show greater variabil-ity in symptoms than either a non clinical group or those withschizophrenia. One such group would be regular users of amphet-amines. Prolonged and high dose use of amphetamines is known tocause psychotic symptoms in otherwise healthy humans, and reg-ular users show increased rates of subclinical psychotic-like expe-riences such as suspiciousness, hostility and delusional thinking(Lapworth et al., 2009; McKetin, Lubman, Baker, Dawe, & Ali,2013). If psychotic symptoms lie on a continuum with healthyfunctioning and amphetamine psychosis provides a sound ana-logue of psychoses in general, it is reasonable to assume thatamphetamine-induced subclinical psychotic experiences wouldclosely resemble high schizotypy.

The current research makes a unique contribution to the schizo-typy literature, by investigating the construct in a sample ofamphetamine users. Psychometric properties of the O-LIFE havebeen widely investigated in non-clinical samples, and while suchresearch is based on the continuum model of schizotypal traits,there is a problem with low frequencies of symptoms in the gen-eral population. A sample with higher rates of subclinical symp-toms of psychosis provides a more sensitive test of schizotypalfeatures, and allows an application of observational symptom mea-sures such as the Brief Psychiatric Rating Scale (Ventura, Nuechter-lein, Subotnik, Gutkind, & Gilbert, 2000), which provide a uniquetest of the convergence between self-report and observationalmeasurement.

The central aim of the study is to examine relationships be-tween schizotypal traits as measured by the O-LIFE, and observedpsychiatric symptoms, using confirmatory factor analysis (CFA).Importantly, competing factorial models will be compared, whichwill help to clarify the structure of schizotypy. It is expected thatO-LIFE scores and psychiatric symptoms will both map onto thefour-factor model as described by Ventura et al. (2000), adding

Please cite this article in press as: Dawe, S., et al. An investigation of schizoty(2013), http://dx.doi.org/10.1016/j.paid.2013.04.024

support for a common structure and for a severity continuumunderlying features of psychosis.

2. Methods

2.1. Participants and procedure

Three hundred and twenty-nine injecting drug users, who re-ported that amphetamine was their primary drug and had usedit in the last month were recruited from two needle exchangecentres in Brisbane, Australia. Interviews were conducted bygraduate level psychology students trained in the administrationof the BPRS. The study received approval from participating hos-pital and university Ethics Committees. Participants provided in-formed consent, and received A$10 as compensation for theirtime.

2.2. Measures

Following completion of a basic demographic and history ques-tionnaire, participants completed measures of recent drug andalcohol use using the calendar based Timeline Follow Back proce-dure (Sobell & Sobell, 1992). The TLFB method has good test–retestreliability (r P .79) as well as convergent and divergent validitywith other measures of substance use (Fals-Stewart, O’Farrell, Fre-itas, McFarlin, & Rutigliano, 2000). Severity of Dependence (SDS;Gossop et al., 1995) was used to assess amphetamine dependencewith a score P4 indicative of dependence (Topp & Mattick, 1997).Participants then completed the Oxford-Liverpool Inventory ofFeelings and Experiences (O-LIFE; Mason et al., 1995) containing104 true/false questions divided into four schizotypy scales: Unu-sual Experiences, Cognitive Disorganisation, Introvertive Anhedo-nia, and Impulsive Nonconformity. Mason and colleagues (Mason& Claridge, 2006; Mason et al., 1995) reported alpha coefficientsof between .77 (Impulsive Nonconformity) and .89 (Unusual Expe-riences). Test–retest reliability (3–6 month interval) has yieldedcoefficients between .77 and .93 (Burch, Steel, & Hemsley, 1998).Cronbach’s alpha for the current study was Unusual Experience,.91; Cognitive Disorganisation, .92; Introverted Anhedonia, .85;Impulsive Nonconformity, .74.

The expanded version of the Brief Psychiatric Rating Scale(BPRS) assesses 24 different symptoms, measured on a 7 pointscale from 1 (not present) to 7 (extremely severe). A score of P4represents a symptom considered to be of pathological intensity(Lukoff, Nuechterlein, & Ventura, 1986). The BPRS can also be usedto produce scores on four broad symptom domains, positive symp-toms (bizarre behaviour, unusual thought content, disorientation,hallucinations, and suspiciousness), negative symptoms (bluntedaffect, motor retardation, emotional withdrawal, and self-neglect),manic excitement (motor hyperactivity, elevated mood, excite-ment, distractibility, hostility and grandiosity), and depression/anxiety (Ventura et al., 2000).

2.3. Statistical analysis

Sociodemographic and clinical characteristics of the samplewere analysed using Student’s t tests. A series of ConfirmatoryFactor Analyses (CFA) models involving O-LIFE and Blom-trans-formed BPRS scores (Cantrell, Finn, Rickert, & Lucas, 2008; vanden Oord et al., 2000) were tested. BPRS items of Disorientation,Bizarre Behaviour, and Motor Retardation were excluded fromthe analyses because they were the most severely skewed withalmost all participants scoring zero (see online supplementarymaterial).

py in injecting amphetamine users. Personality and Individual Differences

Table 1Sample characteristics.

Mean SD

Drug useAge of first use amphetamines 18.7 5.5Severity of dependence score: amphetamines 4.4 3.8Amphetamine days used in last 30 days 10.2 8.7Cannabis used in last 30 days 12.0 12.3Alcohol use in last 30 days 4.3 8.1Heroin use in last 30 days 2.2 6.6

BPRS scoresPositive symptoms 6.7 2.6Negative symptoms 5.6 2.3Manic-excitement 9.2 3.5BPRS depression-anxiety 8.7 4.7BPRS total symptom 37.2 10.6

O-LIFEUnusual experiences 10.7 7.4Cognitive disorganisation 11.0 7.0Introvertive anhedonia 8.5 5.6Impulsive nonconformity 10.6 4.2

S. Dawe et al. / Personality and Individual Differences xxx (2013) xxx–xxx 3

3. Results

3.1. Sociodemographic characteristics

Tables 1 and 2 display descriptive statistics for the sample. Themajority of the sample was male (68%), with a mean age of 29(SD = 7.1) years. Most were single (70%), and 69% were unem-ployed, with the remainder employed (26%) or studying (4%). Thevast majority (96%) reported being regular users of amphetamines,and 274 (83%) said they were regular users of cannabis. Using anSDS cut-off of P4 (Topp & Mattick, 1997), 160 participants (49%of the sample) were classified as amphetamine dependent. See Ta-ble 3 for correlations between OLIFE subscales and BPRS scores andonline supplementary material for Correlations Between O-LIFEScale Scores and Selected Blom-Transformed BPRS SymptomScores.

Table 2Correlations between O-LIFE Scale Scores, Blom-transformed BPRS symptom domains, and

Variable 1 2 3 4

1. Unusual experiences –2. Cognitive disorganisation .71** –3. Introvertive anhedonia .25** .45** –4. Impulsive nonconformity .52** .50** .22** –5. BPRS positive symptoms .56** .43** .18** .46. BPRS negative symptoms .22** .21** .35** .17. BPRS manic symptoms .34** .21** .04 .38. BPRS depression-anxiety .48** .60** .38** .39. Days of use amphetamines (30 days) .01 �.04 �.01 .010. Days of use cannabis (30 days) .12* .06 .00 .011. Severity of amphetamine dependence .27** .43** .23** .2

* p < .05.** p < .01.

Table 3Goodness-of-fit indices for the different CFA models.

Model v2/df Bollen-Stin

Original model* 4.43 (314.71/71)4-Factor Mania 4.43 (265.86/60)

Modified 4-Factor 2.33 (86.20/37) .0013-Factor 3.03 (118.21/39)2-Factor 3.06 (125.26/41)

Note: RMSEA = root mean square error of approximation; CFI = comparative fit index; CA* This model was inadmissible.

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There were also significant relationships between the severityof amphetamine dependence and measures of psychosis symptom-atology, particularly so for positive (r = .35) and manic symptoms(r = .44). It is also notable that severity of dependence was also sig-nificantly correlated with all O-LIFE scales. Thus, the current find-ings add to a growing body of evidence in which there is a clearrelationship between amphetamine use and severity of psychoticsymptomatology (McKetin et al., 2013).

3.2. Testing a 4-factor model

Using confirmatory factor analysis, the first tested model wasthe predicted four-factor model. Covariances were drawn betweenall latent variables because of intercorrelations between all O-LIFEscores (See online supplementary material). The assumption ofmultivariate normality was violated (Mardia’s normalisedcoefficient = 7.27, p < .001), but was still acceptable for the pur-poses of maximum-likelihood (ML) estimation. Results indicatedthat the solution was inadmissible, as the covariance matrix wasnon-positive definite (Wothke, 1993). Closer inspection of resultsrevealed that the latent factor Disorganisation showed standard-ised covariances of greater than unity (an impossible value) foreach of the other latent factors (1.45 for Positive Schizotypy, 1.27for Inhibition, and 1.04 for Negative Schizotypy), indicating a pos-sible problem with that latent variable. Further, the latent Disorga-nisation factor accounted for only 3% of the variance in BPRSConceptual Disorganisation, suggesting the BPRS subscale was apoor indicator of the latent factor.

In the next model, (‘‘4-Factor Mania’’), the BPRS Conceptual Dis-organisation variable was removed leaving the Disorganisation fac-tor defined by only a single variable. The residual error variancewas set to 3.942, according to Bollen’s (1989) formula (SD2

[1 � Cronbach’s a]) for single-indicator latent factors. Multivariatenormality was improved over the original model (Mardia’s norma-lised coefficient = 4.64), although the assumption of multivariatenormality was still violated. Therefore, in addition to normedchi-square, the Bollen-Stine bootstrap p, a boostrap modificationof model chi-square, was also calculated to assess model fit. The

measures of drug use.

5 6 7 8 9 10 11

1** –3* .29** –6** .42** .14* –7** .48** .33** .34** –4 .11 .11 .12* �.06 –7 .06 .09 .01 .09 .10 –7** .35** .16* .17** .44** .20** .00 –

e p RMSEA CFI CAIC

.102 .766 545.78

.102 .790 476.54

.064 .946 283.26

.079 .913 301.70

.079 .908 295.16

IC = Bozdogan’s consistent Akaike information criterian (Bozdogan, 1987).

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4 S. Dawe et al. / Personality and Individual Differences xxx (2013) xxx–xxx

solution was admissible, but the 4-Factor Mania Model provided apoor fit to the data (Table 3). Notably, the Disinhibition factor ac-counted for only 3% and 4% of the variance in Excitement and Ele-vated Mood, respectively. This suggested that these two maniaitems were poor indicators of the Disinhibition factor.

Because of this poor fit, and given the strong theoretical andempirical support for a four-factor model of schizotypal traits (Masonet al., 1995), modifications were made to the model (Byrne, 2009).Substantial improvements were made by correlating two pairs of er-ror terms: those for Emotional Withdrawal and Blunted Affect, andthose for Suspiciousness and Unusual Thought Content (see Fig. 1).

3.3. Modified 4-Factor Model

The resulting ‘‘Modified 4-Factor Model’’ is shown in Fig. 2. Themultivariate normality assumption was again violated (Mardia’s

.78

.38 Cognitive

Disorganisation

Positive Schizotypy

Negative Schizotypy

Disinhibition

.89

.50

.4

.35

.78

.5

.

.4

.73

.54

.2

.1

.70

.80

.38

.57

Fig. 1. The 4-factor mania model. Note: Ellipses represent latent constructs, rectangles rthe right of observed variables represent the amount of variance explained. Parameter esvariable Cognitive Disorganisation has been constrained to 3.942, according to Bollen’s

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normalised coefficient = 5.40, p < .001), but was acceptable for MLestimation. As seen in Table 3, the two modifications provided asubstantial improvement, with a resulting acceptable fit to thedata and best fitting model according to the CAIC statistic. In thismodel there was only one standardised residual covariance abovethe cutoff of 2.58, which was that between Suspiciousness andSelf-Neglect (3.81). The parameter estimates are shown in Fig. 2.All latent factors were moderately to strongly intercorrelated(Fig. 1). Positive Schizotypy shared 62% of its variance with Disor-ganisation and 59% with Disinhibition. Disinhibition also shared52% of its variance with Disorganisation.

Because the assumption of multivariate normality was violated,all parameter estimates were tested with 95% confidence intervalsusing the bias-corrected bootstrap percentile method (1000samples; Efron, 1988). Using this correction, all indicator variablescontinued to load significantly on their latent factors.

.79

.28

Unusual Experiences

Unusual Thought Content

Hallucinations

Suspiciousness

e7 Blunted Affect

Introvertive Anhedonia

Cognitive Disorganisation

Emotional Withdrawal

Hostility

Elevated Mood

Excitement

Impulsive Nonconformity

Self Neglect

.25

.22

.28

.08

.61

.04

.16

.54

.30

.04

.03

.12

7

3

21

1

1

6

e1

e3

e2

e4

e5

e6

e8

e10

e9

e13

e12

e11

3.942

epresent observed variables, and circles represent residuals. Numbers above and totimates are standardised values. The residual error variance for the observed O-LIFE(1989) formula (SD2[1 – a]). This value is not standardised.

py in injecting amphetamine users. Personality and Individual Differences

Fig. 2. The Modified 4-Factor Model of schizotypy.

S. Dawe et al. / Personality and Individual Differences xxx (2013) xxx–xxx 5

3.4. Alternative models

In order to bolster confidence in the fit of the hypothesisedmodel, it was compared to two alternative, non-hypothesisedmodels (McDonald & Ho, 2002). The alternative 2- and 3-factormodels tested were based both on the observed correlations andprior research (Claridge et al., 1996; Kendler & Hewitt, 1992; Kwa-pil et al., 2012; Muntaner et al., 1988). It should be noted that, toensure the most rigorous comparison, the 2- and 3-factor modelsalso omitted BPRS Conceptual Disorganisation and included thesame residual covariances as the Modified 4-Factor Model. Thatis, they benefited from the same modifications that were madeto the 4-factor model to improve fit. Because of the high degreeof shared variance between Positive Schizotypy and Disorganisa-tion, the 3-factor model was analysed with these two latent factorscollapsed into a single ‘‘Positive Schizotypy’’ factor (see Fig. S1).Although Cognitive Disorganisation loaded strongly onto the Posi-tive Schizotypy factor and the model approached acceptable fit,CAIC scores suggest that the model provided a poorer, less parsi-monious fit to the data than did the Modified 4-Factor Model

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(see Table 3). The 2-Factor Model specified a Positive Schizotypyand Negative Schizotypy factor (see Fig. S2). As can be seen in Ta-ble 3, this model provided similar fit to the 3-Factor Model, andwas also a poorer fit than the Modified 4-Factor Model. Taken to-gether, these findings provided further support for the Modified4-Factor Model.

4. Discussion

The current study makes a significant contribution to the inves-tigation of schizotypy, by testing the underlying structure of theconstruct using self-report and observational measures in a clinicalpopulation. The current sample of injecting amphetamine userswas experiencing a range of symptoms. Using a score of four orgreater (moderate to severe), approximately 14% of the sample re-ported scoring at least moderately on one positive symptom score;24% for manic excitement, and over 30% on depression or anxiety.The current investigation provided further support for the four-fac-tor structure of schizotypal traits when measured with the O-LIFE.

py in injecting amphetamine users. Personality and Individual Differences

6 S. Dawe et al. / Personality and Individual Differences xxx (2013) xxx–xxx

The most robust (and the least correlated) factors in the four-factormodel were positive and negative schizotypy. Each factor was de-fined by its relevant O-LIFE scale (Unusual Experiences and Intro-vertive Anhedonia respectively) as well as three psychiatricsymptoms (although in the case of emotional withdrawal, onlymarginally). There can be little doubt from the results of this studythat Unusual Experiences relates to positive symptoms and Intro-vertive Anhedonia relates to negative symptoms, and our data sug-gests that these relationships exist because each pair taps anunderlying, continuous latent construct. The results for the othertwo O-LIFE scales, however, are more equivocal. Further modeltesting was undertaken to ensure that the 2 and 3 factor structuredid not provide a better fit for the data. Notably these models weretested with the same post hoc modifications as the 4-factor model.That is, they were afforded the same ‘‘flexibility’’ that the 4-factormodel was to provide the most rigorous test possible.

A weakness of the model was the failure to find a BPRS symp-tom that mapped onto the Disorganisation factor with the O-LIFECognitive Disorganisation subscale, which Mason and Claridge(2006) suggest relates to thought disorder and other disorganisedpsychotic symptoms. The two most obvious candidates here weredisorientation and conceptual disorganisation, a measure that isproposed to correspond to thought disorder (Lukoff et al., 1986).However, the former was highly skewed whilst the latter showedvery little variability, and its inclusion in the model resulted in anon-positive definite covariance matrix.

Further, the correlations between conceptual disorganisationand both Unusual Experiences and Impulsive Nonconformity wereweak (r = .19 and r = .12 respectively). While this is in line with theBPRS principal components analysis conducted by Ventura et al.(2000), which found that conceptual disorganisation crossloaded(about .30) on both positive symptoms and manic symptoms, itis not consistent with the hypothesis that Cognitive Disorganisa-tion represents an attenuated variant of formal thought disorder.

This leaves the question of exactly what Cognitive Disorganisa-tion measures, and within a dimensional model what its more se-vere clinical counterpart might be. Although CognitiveDisorganisation was significantly correlated with several BPRS psy-chotic symptoms (most notably the positive symptoms), therewere no psychotic symptoms with which it correlated more highlythan any other O-LIFE subscale. It did, however, correlate morestrongly with anxiety and depression than did the other O-LIFEscales. This is consistent with previous O-LIFE studies which showthat Cognitive Disorganisation is strongly related to Eysenck’sNeurotism dimension (Claridge et al., 1996; Mason et al., 1995).This does not mean that Cognitive Disorganisation is not applicableto schizotypy – the scale shared over 50% of its variance with Unu-sual Experiences in the present study and, social anxiety is a recog-nised symptom of SPD – but the data suggest that high scorers onthis dimension may be at risk of developing an anxiety or mooddisorder rather than a psychotic disorder.

In line with a unitary theory of psychosis, the Impulsive Non-confirmity scale of the OLIFE has been proposed to reflect a broaderconstruct of psychosis proneness, in which schizophrenia andbipolar disorder have symptom overlap and a common biologicalsusceptibility (Mason & Claridge, 2006). Although significant corre-lations were obtained between Impulsive Nonconformity and BPRSMania, the 4-factor Mania model did not provide an adequate fit ofthe data. However, removing elevated mood and excitement andleaving only hostility in the model resulted in improved fit andsuccessfully mapped onto the disinhibition factor. Thus, it is possi-ble that the disinhibition factor may reflect antisociality andaggression rather than psychosis proneness characterised by man-ia-type symptoms. Notably, however, BPRS mania items were alsohighly correlated with Unusual Experiences, which is consistentwith previous research suggesting that hypomanic personality

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tends to cross-load onto these two O-LIFE factors (Claridge et al.,1996; Mason et al., 1995).

According to a dimensional model of schizotypy, personalitytraits are normally distributed in the general population and, de-spite resembling attenuated psychotic symptoms, are proposedto be adaptive in moderate levels. While the present study didnot provide data on the potential adaptability of schizotypal traits,it constituted a test of the continuity hypothesis, by investigatingboth schizotypy and psychiatric symptoms in a sample of amphet-amine users. Interestingly, schizotypal personality traits sharedpredictable relationships with their corresponding psychiatricsymptoms providing support for the dimensional model ofschizotypy.

Acknowledgements

Financial support was provided by the National Health andMedical Research Council (NHMRC) – Project Grant Number326220; The Prince Charles Hospital Research Fund.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.paid.2013.04.024.

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