Personality and Individual Differences 53 (2012) 974–979

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Personality and Individual Differences

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The relationship between sociomoral reasoning and intelligence in mentallydisordered offenders

Emily J. Goodwin a, Gisli H. Gudjonsson a, Robin Morris a, Derek Perkins b, Susan Young a,b,⇑a King’s College London, Institute of Psychiatry, UKb Broadmoor Hospital, Crowthorne, UK

a r t i c l e i n f o a b s t r a c t

Article history:Received 13 March 2012Received in revised form 20 June 2012Accepted 9 July 2012Available online 9 August 2012

Keywords:Sociomoral reasoningAntisocial personalitySevere mental illnessOffendingIntelligencePsychopathy

0191-8869/$ - see front matter � 2012 Elsevier Ltd. Ahttp://dx.doi.org/10.1016/j.paid.2012.07.015

⇑ Corresponding author. Address: Department ofmental Sciences, PO23, Institute of Psychiatry, De CreUK. Tel.: +44 20 7848 5280; fax: +44 20 7848 0754.

E-mail address: susan.young@kcl.ac.uk (S. Young).

To date research has been inconclusive in explaining the relationship between sociomoral reasoning andadult offending, with some researchers suggesting that this relationship is mediated by intelligence. Thisstudy investigated sociomoral reasoning among 100 mentally disordered offenders in a maximum secu-rity hospital, 50 with a primary diagnosis of personality disorder (PD) including psychopathy and 50 withsevere mental illness (SMI). Participants completed a battery of measures including the Gough Socialisa-tion Scale, the Wechsler Abbreviated Scale of Intelligence, and the Sociomoral Reflection Measure – ShortForm. Between-group differences showed that, compared with the PD group, the SMI group had signifi-cantly fewer antisocial personality traits, lower IQ, and lower-level sociomoral reasoning. Hierarchicalmultiple regressions showed that IQ was the most powerful predictor of sociomoral reasoning after con-trolling for a number of other variables including social desirability. While psychiatric diagnosis mayappear to predict sociomoral reasoning, intellectual function is an important mediator of the process.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

1.1. Sociomoral reasoning

Cognitive developmental theories of moral reasoning haveundergone a number of revisions since the early work of Piaget(1932), in which it was proposed that moral reasoning developssequentially alongside logical reasoning. In particular, Kohlberg(1969) updated the theory to include development into adoles-cence and adulthood, proposing six stages of moral reasoning dur-ing this period. In turn, his revision was criticised due to lack ofcross-cultural evidence for the highest levels of moral reasoning,which were removed by Gibbs and colleagues in the developmentof a Sociomoral Stage theory (Gibbs, Basinger, & Fuller, 1992). Sincethen, research has demonstrated improved cross-cultural validityfor sociomoral theory (Gibbs, Basinger, Grime, & Snarey, 2007),which focuses more on the sociomoral justifications that peoplegive to explain their behaviour.

As described by Gibbs et al. (1992), sociomoral stage theorycomprises two main levels of reasoning, each split further intotwo stages (mature reasoning: Stages 1 and 2; and immature rea-soning: Stages 3 and 4). At each stage, reasoning becomes less ego-

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centric and more related to the complexities of society: Stage 1 ischaracterised by moral justifications of responses that are rule-based, for example obeying authority or avoiding punishment, orbased on physical size or power of the individual. Stage 2 requiresan understanding of social interaction, although this remains ego-centric, for example helping others because they may help you inreturn. Stage 3 is the beginning of mature reasoning, and is charac-terised by justifications that include prosocial/emotional aspectssuch as trust. Finally, Stage 4, the highest stage of reasoning, is evi-denced by even more complex justifications for behaviour includ-ing those based on social justice, the rights and responsibilities ofan individual within society, and conscience.

1.2. Sociomoral reasoning in offenders

It has been suggested that higher level sociomoral reasoning isunderpinned by the ability to justify sociomoral behaviour throughperspective-taking and consideration of consequences to others(Palmer, 2003). It thus seems reasonable to expect a relationshipbetween poor sociomoral development and antisocial behaviour/offending. This has been supported by a meta-analysis indicatingthat, among youth, developmentally delayed moral judgement isassociated with delinquency, with an effect size of .76, the relation-ship remaining after controlling for socioeconomic status, gender,age and intelligence (Stams et al., 2006).

In adulthood, the limited research available suggests a morecomplex relationship between sociomoral reasoning and behaviour.

E.J. Goodwin et al. / Personality and Individual Differences 53 (2012) 974–979 975

In a small sample of adult male and female offenders and femalenon-offenders, Watt, Frausin, Dixon, and Nimmo (2000) reportedno significant differences in moral reasoning between the threegroups. Stevenson, Hall, and Innes (2003) have also reported that,although offenders show a lower overall mean score obtained forsociomoral reasoning, they are capable of reasoning at middle tohigher levels (i.e. at Stage 3), which demonstrates a ‘mature’ levelof reasoning reflecting cultural norms (Gibbs, Potter, & Goldstein,1995). This suggests that offenders possess the capacity to reasonat a sociomoral level on a par with non-offending controls but thisis not reflected in their behaviour, and has been particularly a focusof research in psychopathy.

1.3. Sociomoral reasoning and psychopathy

It has been suggested that moral reasoning comprises an intui-tive decision about whether an action is morally permissible,which is linked with our emotions such that our moral judgementsoriginate with our feelings about a behaviour and its outcome (e.g.see Haidt, 2001). Research involving individuals with deficits inemotional processing has been taken to support this position, forexample the finding that, unlike controls, those with psychopathyjudged a conventional societal transgression such as a child walk-ing out of a classroom without permission and a moral transgres-sion such as a child hitting another child, as equally wrong (e.g.Blair, 1995). However, recent research has suggested that emo-tional processing deficits alone may not explain moral judgements(Cima, Tonnaer, & Hauser, 2010).

Cima et al. (2010) reported that even though psychopaths intheir study showed diminished emotional processing, they re-sponded similarly to controls in that all groups judged personalmoral actions (i.e. those that required another person to beharmed/killed by an agent in order for a goal to be reached; specif-ically the agent must generate the harm themselves; Greene, Som-merville, Nystrom, Darley, & Cohen, 2001) as less permissible thanimpersonal actions (i.e. those that did not have some of the aboveaspects). There were no differences between the groups in thisstudy in relation to the overall moral judgements made for eithertype of scenario and there was no relationship between psychopa-thy score or nature of offence, and moral judgements. The authorsproposed that either a sufficient level or type of emotion remainedintact, or that non-emotional processes were sufficient to evaluateparticular moral scenarios. Social desirability should also beacknowledged, especially in this population, as the measures usedare typically self-report (Gudjonsson & Young, 2010). Indeed thiscould be implicated in the conclusion that ‘‘psychopaths knowright from wrong, but simply don’t care’’ (Cima et al., 2010, p 8),suggesting they perhaps know what answer they should give andendeavour to give the ‘correct’ response.

1.4. Sociomoral reasoning and intelligence

A further consideration, especially given the nature of tasksused, which typically require verbal understanding to provide awritten or verbal response to the dilemmas, is intelligence. Indeed,research of adults with intellectual disability suggests that therelationship between sociomoral reasoning and illegal behaviourmay be curvilinear rather than linear, such that both low and highstages of reasoning are associated with lower levels of delinquency,with this relationship moderated by intelligence (Langdon, Clare, &Murphy, 2011; Langdon, Murphy, Clare, & Palmer, 2010). This mayexplain the finding of Stevenson et al. (2003) that many offenderswere capable of reasoning at Stage 3 level. Furthermore, it has beenreported that a significant relationship found between higher psy-chopathy scores and lower sociomoral reasoning among mentallydisordered offenders did not remain when IQ was partialled out

(O’Kane, Fawcett, & Blackburn, 1996). These findings suggest thatintelligence may also be an important mediator of sociomoralreasoning.

In summary, research among adult offenders has not yet founda conclusive relationship between levels of sociomoral reasoningand offending. Explanations of moral reasoning based on emo-tional processing appear insufficient to explain findings thatoffenders, including psychopaths, can reason on a par with con-trols, and there are indications that the relationship may be med-iated by intelligence. Studies exploring other potentialmoderators, such as antisocial personality traits and psychiatricdiagnosis, have not yet been published. The present study there-fore aimed to investigate the extent to which sociomoral reasoningis related to relevant underlying factors in a sample of mentallydisordered offenders (MDOs), including psychiatric diagnosis, psy-chopathy, antisocial personality traits, social desirability, and intel-ligence. It was hypothesised that (H1) there would be a significantnegative correlation between sociomoral scores and antisocial per-sonality traits (i.e. those with higher sociomoral scores would ex-hibit fewer antisocial traits); and (H2) there would be asignificant positive correlation between sociomoral scores andestimated full-scale IQ. Additionally, (H3) it was hypothesised thatpatients with a primary diagnosis of personality disorder (PD)would obtain lower sociomoral scores than patients with a primarydiagnosis of severe mental illness (SMI).

2. Method

2.1. Participants

The sample consisted of 100 male MDOs from a UK high-securepsychiatric hospital; 50 with a primary diagnosis of PD (antisocialn = 36, 72%; borderline n = 6, 12%; schizotypal n = 4, 8%; paranoidn = 3, 6%; and narcissistic n = 1, 2%) and 50 with a primary diagno-sis of SMI including schizophrenia (n = 43, 86%) and schizoaffectivedisorder (n = 7, 14%). Six participants with a primary diagnosis ofSMI had a comorbid personality disorder. There was no comorbid-ity outside the primary diagnostic category for the PD groupalthough over half had more than one personality disorder.

The group had a range of index offences leading to their currentsentence including 64 (64%) with violent offences, 17 (17%) withsexual offences, and 19 (19%) other offences (robbery/burglaryn = 11; arson n = 6; abducting a child n = 1; and false imprisonmentn = 1). The sample had an average age of 37.32 years (SD = 9.87); 67were of Caucasian ethnic background, and 33 non-Caucasian (seeTable 1).

Prior to recruitment, a list of 270 resident patients was obtainedfrom the hospital. Suitability for participation was determined byResponsible Clinicians (RC) in line with the following exclusion cri-teria: 25 patients were excluded due to active psychosis; 9 due tolack of capacity to consent; 4 due to risk of assault; 3 due to neu-rological impairment/learning disability; 2 were non-Englishspeaking; 1 was terminally ill and very unwell; and 1 for anunspecified reason. Eight patients were transferred out of the hos-pital during recruitment and 16 were on trial leave. Nine patientswere approved by their RC but the intended sample size wasreached without their recruitment, although all were affordedthe same initial opportunity to volunteer when the research waspresented at ward community meetings. Of the remaining patientswho were approved as potential participants, 89 declined to takepart, 1 was unable to take part as the task battery for the overallstudy required a computer and he was restricted from using themachine, and 2 began the study but wished to withdraw beforecompleting the measures.

Table 1Descriptive data for the PD and SMI groups.

Primary diagnosis SMI(n = 50)

Primary diagnosis PD(n = 50)

Age mean (SD) 35.40 (9.49) 39.24 (9.96)

Ethnicity n (%)Caucasian 26 (52) 41 (82)Non-Caucasian 24 (48) 9 (18)

Comorbid diagnoses n (%)PD 6 (12) 29 (58)SMI 2 (4) 0Other 1 (2) Autistic spectrum 2 (4) Asperger’sNone

documented41 (82) 19 (38)

Index offence type n (%)Violent 39 (78) 25 (50)Sexual 1 (2) 16 (32)Other 10 (20) 9 (18)

Table 2Frequency of SRM-SF global stages for the PD and SMI groups.

SRM-SF global stage SMI (n = 50) PD (n = 50) All offenders (n = 100)

n (%) n (%) N

Unscorable 2 (4) 1 (2) 3Stage 1 - - -

976 E.J. Goodwin et al. / Personality and Individual Differences 53 (2012) 974–979

2.2. Measures

2.2.1. Sociomoral Reflection Measure – Short Form (SRM-SF; Gibbset al., 1992)

This measure includes 11 questions (e.g. ‘Think about whenyou’ve made a promise to a friend of yours. How important is itfor people to keep promises, if they can, to friends’?). For eachquestion the response choice is ‘Very important’, ‘Important’ or‘Not important’, and the participant is asked to rationalise their an-swer. The response is scored using a set of heuristic rules detailedin the SRM manual (Gibbs et al., 1992). Scoring yields a SociomoralReflection Maturity Score (SRMS) of between 1 and 4, pertaining toan overall global sociomoral reasoning stage. As part of the SRM-SFprocedure, this is multiplied by 100, with a higher score indicatinghigher sociomoral reasoning.

Each SRMS can be further classified within a developmentalrange based on point boundaries as specified in the manual. Thisclassification system includes the four main stages, with two tran-sition stages between each, creating ten Global Stages, as follows:Stage 1: 100–125 (Transition stages between 1 and 2: 126–149 and150–174); Stage 2: 175–225 (Transition Stages between 2 and 3:226–249 and 250–274); Stage 3: 275–325 (Transition Stages be-tween 3 and 4: 326–349 and 350–374); Stage 4: 375–400.

The SRM-SF is reported to be a valid measure among both malesand females of various age-groups, including university students,adults, and delinquent adolescents (Basinger, Gibbs, & Fuller,1995), and has good psychometric properties such that it is anacceptable alternative to previously developed, more time-con-suming, measures (see Palmer, 2003).

In the current study, the inter-rater reliability of the SRM-SFwas ascertained by every fifth questionnaire (n = 20) being blind-scored by a second rater. Scoring agreement was within recom-mended parameters on all indices of inter-rater reliability set inthe manual at r = .80 for the SRMS (achieved r = .98, p < .01); meanSRMS discrepancy within 20 points (achieved discrepancy = 5.45;Rater 1 mean = 284.60, Rater 2 mean = 279.15); global stage agree-ment within one interval in at least 80% of cases (achieved in 100%of cases); and exact global stage agreement in at least 50% of cases(achieved in 55% of cases).

Transition 1–2 (1) - - -Transition 1–2 (2) - 1 (2) 1Stage 2 2 (4) - 2Transition 2–3 (1) 4 (8) 1 (2) 5Transition 2–3 (2) 14 (28) 7 (14) 21Stage 3 25 (50) 23 (46) 48Transition 3–4 (1) 2 (4) 10 (20) 12Transition 3–4 (2) 1 (2) 7 (14) 8Stage 4 - - -

2.2.2. Gough Socialisation Scale (GSS; Gough, 1960)This self-report questionnaire measures the extent to which

participants have internalised the values of society and includes54 items rated ‘True’ or ‘False’. Possible scores range from 0 to 54with lower scores indicating proneness to antisocial behaviourproblems (Gudjonsson, Einarsson, Bragason, & Sigurdsson, 2006).

2.2.3. Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler,1999)

The shortened version of the WASI, comprising the Vocabularyand Matrix Reasoning subtests, was used to provide an estimatedFull Scale IQ (FSIQ).

2.2.4. Paulhus Deception Scales (PDS; Paulhus, 2006)This self-report questionnaire comprises two subscales measur-

ing socially desirable responding either as impression manage-ment or self-deceptive enhancement. Each sub-scale consists of20 items and is rated on a 5-point scale ranging from ‘Not True’(1) to ‘Very True’ (5). Possible scores range from 0 to 20 and canbe added to give a total score of socially desirable responding with(minimum = 0, maximum = 40).

2.2.5. Psychopathy Checklist-Revised (PCL-R; Hare, 2003) andPsychopathy Checklist-Screening Version (PCL-SV; Hart, Cox, &Hare,1995)

As a measure of psychopathy, scores on the PCL-R or PCL-SVwere obtained from patient files. As not all patients with psychop-athy scores had been assessed using the same version of the check-list, available scores were converted to a percentile rank.

2.3. Procedure

The data reported here were collected as part of a larger batteryof measures in a NIHR:RISC funded study of decision-making. Thestudy was introduced across the hospital at ward/communitymeetings, and patients approved by RCs were approached individ-ually for participation by a Research Worker. Participants gave in-formed written consent to participate and were informed thatresults would be anonymous and confidential and would not affecttheir care/time at the hospital. They participated individually, inprivate ward-based interview rooms. Ethical approval for the studywas granted by the Ealing and West London Research EthicsCommittee.

3. Results

3.1. Descriptive information

Table 1 presents descriptive information about the SMI and PDgroups, including ethnicity, offences and comorbidity within each.

3.2. Sociomoral level scores

Table 2 shows the frequency with which different sociomorallevel scores were obtained for the SMI and PD groups. The patternof scores is similar for the two samples with most of the scores fall-ing at Stage 3. Three participants (1 from the PD group and 2 from

Table 3Correlations between measures for the two patient groups (severe mental illnessabove the diagonal, and personality disorder below).

Age SMRS GSS FSIQ PDS-Total

PCL-R% SMIn = 10

Age - �.01 �.06 .00 .01 .36SMRS .36* - .15a .19a .06 �.39GSS .00 �.09a - .23 .28* �.57FSIQ �.05 .24*,a .06 - �.13 �.83**

PDS-Total .03 �.06 .50** �.08 - .09PCL-R% PD

n = 39.35* .41** �.05 �.05 .11 -

GSS = Gough Socialisation Scale total; FSIQ = WASI estimated full-scale IQ;SMRS = Sociomoral reflection total; PDS-Total = Paulhus Deception Scale totalscore; PCL-R = Psychopathy Checklist percentile.

a One-tailed in relation to specific hypotheses.* p < .05.** p < .01.

Table 5Summary of hierarchical regression predicting sociomoral reasoning for the combinedgroup of offenders (n = 100).

Model 1 constant 208.41 30.47 – 6.84***

Age 0.99 0.64 0.16 1.55Ethnicity �1.15 13.68 �.01 �.08Diagnosis (SMI or PD) 28.92 13.33 0.27 2.17*

Cross-categorycomorbidity

1.82 26.52 0.01 .07 .06F(4, 95) = 2.43

Model 2 constant 199.28 45.78 – 4.35***

Age 0.99 0.65 0.16 1.53Ethnicity �1.11 13.92 �.01 �.08Diagnosis (SMI or PD) 30.2 14.22 0.25 2.12*

Cross-categorycomorbidity

3.04 27.15 0.01 .11

GSS 0.32 1.15 0.03 .28Paulhus total score -0.1 1.08 �.01 �.10 .04

F(6, 93) = 1.60

Model 3 constant 136.88 52.89 2.59*

Age 1.04 0.63 0.17 1.64Ethnicity �4.01 13.7 �.03 �.29Diagnosis (SMI or PD) 20.67 14.57 0.17 1.42Cross-category

comorbidity2.1 26.59 0.01 .08

GSS �.21 1.15 �.02 �.18Paulhus total score 0.31 1.07 0.03 .29WASI FSIQ 0.91 0.41 0.23 2.22* .07

F(7, 92) = 2.14*

* p < .05 level.*** p < .001 level.

E.J. Goodwin et al. / Personality and Individual Differences 53 (2012) 974–979 977

the SMI group) did not provide scorable forms for the SRM-SF (e.g.they provided justifications such as ‘‘Don’t know’’ or repeated‘‘Because it is important’’, with no elaboration).

3.3. Correlations

For the whole group (n = 100), a significant positive correlationwas found between the SRMS and WASI score (r = .28, p < .01). Po-sitive correlations were also significant (two-tailed) between theSRMS and age (r = .20, p < .05) and SRMS and PCL percentile(r = .33, p < .05). When the two patient groups were analysed sep-arately, SRMS and WAIS score were significantly correlated for theSMI group only (r = .24, p < 0.05), and between the SRMS and age(r = .36, p < .05) and psychopathy (r = .41, p < .01) for the PD grouponly. These are low effect sizes (Cohen, 1992). No significant corre-lations were found between the GSS and SRMS (see Table 3 for re-sults of correlations by group).

3.4. Group differences

There were significantly more participants of non-Caucasianethnic background in the SMI group (v2(1) = 10.18, p < .01). Inde-pendent samples t-test also indicated that the difference in meanage between the two groups was very close to significance(t = �1.97, p = .051), with the PD participants being the older group(see Table 1).

Independent samples t-tests indicated some significant differ-ences with medium effect between the SMI and PD patients (Table4): SMI patients scored significantly lower on the sociomoral mea-sure, significantly higher on the GSS (indicating fewer antisocialpersonality traits), and obtained a significantly lower estimatedfull scale IQ. No significant differences were found between the

Table 4Differences in mean scores between the PD and SMI groups.

Measure SMI Mean (SD)

SRM-SF 269.7 (65.0)Gough 26.7 (6.1)WAIS IQ 92.8 (16.0)

Paulhus Deception ScaleImpression management 7.12 (3.64)Self-deception 3.84 (3.59)Total 10.96 (6.36)

Psychopathy percentile 62.86 (31.49) n = 10

* p < .01.

two groups with regard to the Paulhus Deception scales or psy-chopathy percentile ranking.

3.5. Hierarchical multiple regression

In order to investigate the incremental contribution of antiso-cial personality traits and intelligence to sociomoral reasoningamong offenders, a multiple regression using a hierarchical (block-wise) entry method was conducted on the data (n = 100) (see Table5). Age, ethnicity, diagnostic group and ‘cross category’ comorbid-ity (i.e. a comorbid diagnosis of SMI where the primary diagnosiswas PD, or vice versa) were entered in the first block to accountfor their possible effects, the GSS score for antisocial traits andPaulhus total score for social desirability were added in the secondblock, followed by WASI FSIQ in the third block. Model 1 ap-proached significance (p = .053) and Model 3 was significant(p < .05). In Model 1, diagnosis type was a significant predictor ofsociomoral reasoning score; the model explained 6% of the vari-ance. In Model 3, with the inclusion of IQ, the diagnostic group pre-dictive value was substantially reduced with only WASI FSIQ scoreremaining a significant predictor of sociomoral reasoning, contrib-uting 7% to the variance in moral reasoning.

PD Mean (SD) t-Value Cohen’s d

303.0 (54.0) �2.80* 0.5623.4 (6.0) 2.75* 0.55101.8 (14.1) �3.13* 0.60

6.68 (3.79) 0.59 .124.10 (3.76) �0.35 .0710.78 (6.11) 0.14 .03

73.26 (27.93) n = 39 �1.02 0.35

978 E.J. Goodwin et al. / Personality and Individual Differences 53 (2012) 974–979

4. Discussion

This study investigated the relationship between antisocial per-sonality traits, psychiatric diagnosis, intelligence, and sociomoralreasoning in mentally disordered offenders. The hypothesis of asignificant negative correlation between sociomoral reasoningand antisocial personality traits (H1) was not supported. A signifi-cant positive correlation between sociomoral reasoning andintelligence was found for the SMI patients but not for the PD pa-tients, partially supporting (H2). Contrary to (H3), patients in thePD group obtained higher sociomoral scores than those with SMI.The PD patients also had significantly higher IQ estimates thanthe SMI patients and the hierarchical multiple regression indicatedthat, when controlling for age, psychiatric diagnosis and ethnicity,social desirability and antisocial personality, IQ was the singlemost powerful predictor of sociomoral reasoning.

The non-significant correlation between antisocial personalitytraits and sociomoral reasoning might appear at first sight coun-ter-intuitive, particularly given the significant group differencesindicating that those with PD exhibited both significantly moreantisocial traits and scored significantly better on the sociomoralreasoning measure. This supports previous research reporting thatadult offenders are generally able to reason at a mature sociomorallevel and their antisocial traits may not necessarily relate to lowerlevel sociomoral reasoning (Stevenson et al., 2003). This, togetherwith the present study findings that most participants reasonedat middle to higher levels (i.e. at sociomoral Stage 3), indicates apossible disconnect between cognition and behaviour wherebyoffenders of average intelligence may reason one thing but actquite differently, as noted by Cima et al. (2010).

However, it seems that whilst diagnosis in this study may ap-pear to be a predictor of sociomoral reasoning, intellect is animportant mediator of the process and m.ay, in part, account forthe apparent disconnect between sociomoral cognitions and illegalbehaviour. This could be tested further in future research byincluding samples with offending histories and intellectual impair-ments (Langdon et al., 2011). However, intellectual functioningonly accounted for a small amount of incremental variance in Mod-el 3 and other cognitive factors could be important to include, forexample executive functioning tasks to assess cognitive flexibility,verbal reasoning and fluency.

4.1. Strengths, limitations and future research

There are some possible confounding variables that must beacknowledged, which were not controlled in the current study.Firstly, in relation to those participants with severe mental illness,information was not obtained about medication status, which mayhave implications on results (e.g. cognitive ability). This cannot beanalysed further as information regarding premorbid levels of cog-nitive functioning was not available. Related to this is the possibil-ity that the ultimately small percentage of variance explained byWASI FSIQ belies a more specific neurocognitive explanation, forexample executive functioning is reported to be a particular deficitamong individuals with schizophrenia and a history of violence(Barkataki et al., 2005). This was not assessed here and would war-rant further investigation.

Reliance on self-report methods also limits this study and, com-bined with the sample characteristics, is likely to be implicated inthe small effect sizes. It remains possible that antisocial traits and/or sociomoral responses may be underestimated, although therewas no difference between diagnostic groups with respect to socialdesirability. Finally, a number of potential participants declined toparticipate. As they were non-consenting, demographic data couldnot be collected and so comparisons including this group were not

possible, therefore caution should be taken when generalising tothe wider hospital population.

A strength of the study is the use of a sociomoral measure thatwas independently scored according to specified criteria, and forwhich good inter-rater reliability was established. Nevertheless,Langdon et al. (2011) have suggested that recognition measuresof sociomoral reasoning may be more appropriate for those withpoorer verbal language skills, and thus lower sociomoral scoresobtained by SMI participants in this study may be an artefact ofthe ‘open-ended’ style adopted by the SRM-SF measure requiringverbally articulated or written responses. This warrants furtherinvestigation through the comparison of sociomoral scores usingdifferent methods of assessment.

Understanding sociomoral reasoning, and the factors that relateto it, has important clinical implications for offender treatment tar-gets. Whilst some MDOs may require cognitive interventions toimprove critical thinking and social perspective taking, these needto be complemented by behavioural interventions that bridge cog-nitive reasoning skills and behaviour by making explicit the asso-ciation between sociomoral reasoning and prosocial competence.

Acknowledgements

We acknowledge the support of the National Institute forHealth Research, through the Mental Health Research Network, ref-erence RC-PG-0308-10215. We also thank Deborah Olaniyan forsecond-rating the 20 SRM-SF questionnaires.

References

Barkataki, I., Kumari, V., Das, M., Hill, M., Morris, R., O’Connell, P., et al. (2005). Aneuropsychological investigation into violence and mental illness. SchizophreniaResearch, 74(1), 1–13.

Basinger, K. S., Gibbs, J. C., & Fuller, D. (1995). Context and the measurement ofmoral judgment. International Journal of Behavioral Development, 18, 537–556.

Blair, R. J. (1995). A cognitive developmental approach to morality: Investigatingthe psychopath. Cognition, 57, 1–29.

Cima, M., Tonnaer, F., & Hauser, M. D. (2010). Psychopaths know right from wrongbut don’t care. Social Cognitive and Affective Neuroscience, 5(1), 59–67.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155–159.Gibbs, J. C., Basinger, K. S., & Fuller, D. (1992). Moral maturity: Measuring the

development of sociomoral reflection. Hillsdale, NJ: Lawrence Erlbaum.Gibbs, J. C., Basinger, K. S., Grime, R. L., & Snarey, J. R. (2007). Moral judgement

development across cultures: Revisiting Kohlberg’s universality claims.Developmental Review, 27, 443–500.

Gibbs, J. C., Potter, G. B., & Goldstein, A. P. (1995). The EQUIP Program: Teaching youthto think and act responsibly through a peer-helping approach. Champaign, IL:Research Press.

Gough, H. G. (1960). Theory and measurement of socialization. Journal of Consultingand Clinical Psychology, 24, 23–30.

Greene, J. D., Sommerville, R. B., Nystrom, L. E., Darley, J. M., & Cohen, J. D. (2001). AnFMRI investigation of emotional engagement in moral judgment. Science, 293,2105–2108.

Gudjonsson, G. H., Einarsson, E., Bragason, O. O., & Sigurdsson, J. F. (2006).Personality predictors of self-reported offending in Icelandic students.Psychology, Crime and Law, 47, 361–368.

Gudjonsson, G. H., & Young, S. (2010). Personality and deception. Are suggestibility,compliance and acquiescence related to socially desirable responding?Personality and Individual Differences, 50, 192–195.

Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionistapproach to moral judgment. Psychological Review, 108(4), 814–834.

Hare, R. D. (2003). Hare Psychopathy Checklist-Revised (PCL-R) (2nd ed.). Toronto,Ontario, Canada: Multi-Health Systems.

Hart, S. D., Cox, D. N., & Hare, R. D. (1995). The Hare Psychopathy Checklist: ScreeningVersion (PCL:SV). Toronto, Ontario, Canada: Multi-Health Systems.

Kohlberg, L. (1969). Stage and sequence. The cognitive-development approach tosocialization. In D. A. Goslin (Ed.), Handbook of socialization theory and research(pp. 347–480). Chicago, IL: Rand McNally.

Langdon, P. E., Clare, I. C. H., & Murphy, G. H. (2011). Moral reasoning theory andillegal behaviour by adults with intellectual disabilities. Psychology, Crime andLaw, 17(2), 101–115.

Langdon, P. E., Murphy, G. H., Clare, I. C. H., & Palmer, E. J. (2010). The psychometricproperties of the Sociomoral Reflection Measure – Short Form and the MoralTheme Inventory for men with and without intellectual disabilities. Research inDevelopmental Disabilities, 31, 1204–1215.

O’Kane, A., Fawcett, A., & Blackburn, R. (1996). Psychopathy and moral reasoning:Comparison of two classifications. Personality and Individual Differences, 20,505–514.

E.J. Goodwin et al. / Personality and Individual Differences 53 (2012) 974–979 979

Palmer, E. J. (2003). Offending behaviour: Moral reasoning, criminal conduct and therehabilitation of offenders. Cullompton, UK: Willan.

Paulhus, D. L. (2006). Paulhus Deception Scales. Newbury, Berkshire: Multi-HealthSystems.

Piaget, J. (1932). The moral judgement of the child. London: Routledge and KeganPaul.

Stams, G. J., Brugman, D., Dekovíc, M., van Rosmalen, L., van der Laan, P., & Gibbs, J.C. (2006). The moral judgement of juvenile delinquents: A meta-analysis.Journal of Abnormal Child Psychology, 34, 697–713.

Stevenson, S. F., Hall, G., & Innes, J. M. (2003). Sociomoral reasoning and criminalsentiments in Australian men and women violent offenders and non-offenders. International Journal of Forensic Psychology, 1(1),111–119.

Watt, M. C., Frausin, S., Dixon, J., & Nimmo, S. (2000). Moral intelligence in asample of incarcerated females. Criminal Justice and Behavior, 27,330–335.

Wechsler, D. (1999). Wechsler Abbreviated Scale of Intelligence (WASI). New York: ThePsychological Corporation.