Callous-Unemotional Traits in Individuals ReceivingAccommodations in University

Franklynn E. Bartol & Carlin J. Miller

# Springer Science+Business Media New York 2014

Abstract Research with antisocial individuals suggests thatcallous-unemotional (CU) traits, a dimension of psychopathy,consistently predict severe antisocial behaviours and correlatewith deficits in recognizing negative emotions, especiallyfearful facial expressions. However, the generalizability ofthese findings to non-antisocial populations remains uncertainand largely unexplored. This small, exploratory study aimedto extend this research by measuring CU traits and facialemotion recognition in university students with Attention-Deficit Hyperactivity Disorder (ADHD), learning disabilities,other psychiatric disorders, and comparison participants withphysical/sensory disabilities. As the clinical groups can ex-hibit deficits in emotion recognition, this study sought to shedlight on the candidacy of CU traits as a factor in emotionrecognition. Results suggested that individuals in the diagnos-tic groups possess similar levels of CU traits to the comparisongroup and that the relationship between CU traits and emotionrecognition deficits previously seen in antisocial populationsis not present in this sample. Contrary to the hypothesis, thosein the diagnostic groups displayed similar levels of accuracyon an emotion recognition task as the comparison group.Recommendations are made for future research to use morespecific and representative diagnostic populations to furtherassess the relationships between CU traits and emotion recog-nition in non-antisocial populations.

Keywords Callous-unemotional traits . Emotionrecognition . Attention-Deficit Hyperactivity Disorder .

LearningDisability

Many factors have been found to contribute to everyday socialfunctioning, not the least of which is personality (Hopwoodet al. 2009). Callous-unemotional traits are among the latestpersonality traits to be examined, and they seem to have strongimplications for how we relate to others. Callous-unemotional(CU) traits describe an interpersonal style that includes anabsence of empathy, callous use of others, lack of guilt, anda general lack of affect. These traits have been commonlyincluded in definitions (Cleckey 1976; Hare 1999) and mea-sures (Hare 2003; Lilienfeld and Widows 2005) of psychop-athy in adults. They are often under the “affective dimension”of psychopathy, along with other narcissistic and antisocialpersonality traits and a socially deviant lifestyle (Hare 2003;Lilienfeld and Widows 2005). While measures of psychopa-thy are primarily research tools, as ‘psychopath’ is not arecognized diagnostic category, but these personality traitsare related to clinical diagnoses based on antisocial behav-iours, such as Antisocial Personality Disorder in adults andConduct Disorder in youth. These traits have also been notedas normally distributed in the population are not strictly lim-ited to psychopathy or to individuals with aberrant behaviours(Herpers et al. 2012). The present study will specificallymeasure CU traits in order to explore their unique presenceand function in several diagnoses.

A recent increased interest in antisocial youth has revealedstrong links between CU traits and negative outcomes, such ashigher rates of antisocial behaviour (Dadds et al. 2005) andlower responsiveness to behavioural intervention (Hawes andDadds 2005; Waschbusch et al. 2007), although more recentresearch has suggested that these characteristics are not unal-terable especially in youth (Salekin et al. 2010). CU traits havebeen shown to identify a subgroup of antisocial youth whoexhibit more severe violent and aggressive behaviour(Enebrink et al. 2005; Frick et al. 2003; Lawing et al. 2010).Youth high in CU traits may show a lack of responsiveness topunishment (Dadds and Rhodes 2008; Hawes and Dadds

F. E. Bartol :C. J. Miller (*)Department of Psychology, University of Windsor, 401 SunsetAvenue, Windsor, ON N9B 3P4, Canadae-mail: cjmiller@uwindsor.ca

J Psychopathol Behav AssessDOI 10.1007/s10862-014-9417-2

2005; Pardini 2006) and reward (Blair et al. 2006; Marini andStickle 2010), rendering most behavioural modification tech-niques unsuccessful in this population (Hawes and Dadds2005; Waschbusch et al. 2007). Following such evidence,several researchers have supported the new Diagnostic andStatistical Manual of Mental Disorders (5th ed.; DSM–5;American Psychiatric Association [APA] 2013) incorporationof CU traits into the diagnosis of Conduct Disorder (CD) inorder to identify a subgroup at greater risk for persistent andsevere delinquency (Frick and Moffitt 2010; Pardini and Fite2010).

The specific emotional and social characteristics of antiso-cial samples with CU traits have been a topic of increasedinterest recently. Specifically, deficits in processing fearful andsometimes sad facial expressions have been well documented(Blair et al. 2001; Dadds et al. 2006; Leist and Dadds 2009).White et al. (2012) found that a reduced amygdala responsecorrelated with deficits in recognizing fear, and that this oc-curred independent of attentional load. This finding suggestsan emotional deficit and goes against the previous suggestionthat a heightened top-down attentional response to non-emotional stimuli decreased this population’s ability to recog-nize distressing emotions (Blair and Mitchell 2009). Problemsin fear processing extend beyond faces to body postures(Muńoz 2009), suggesting a general deficit in recognizingfear in others. Although the majority of studies support aspecific difficulty in recognizing fear and sadness, there issome conflicting evidence. A recent study found that thosehigh in CU traits can recognize negative emotions (fear, anger,sadness) just as well as those low on these traits, but exhibitlower emotional reactivity to these expressions (Linick 2012).Another study found that children with high levels of CU traitsand CD showed deficits in recognizing sad faces but wereactually better at recognizing fearful faces than those with lowCU traits (Woodworth and Waschbusch 2008). This conflict-ing finding may be explained by an examination of the con-tribution of CU traits apart from CD. Leist and Dadds (2009)found that CU traits were uniquely associated with deficits infear recognition in a sample of high-risk youth, while antiso-cial behaviour was associated with an increase in fear recog-nition. Therefore, it is possible that antisocial behaviour, CD,and CU traits have unique and interacting associations when itcomes to fear recognition.

Most research has examined CU traits in incarcerated indi-viduals or in youth with significant conduct problems. Thefew studies that have used non-clinical samples representativeof the general population have shown similar CU trait predic-tions and correlations to those found in antisocial populations(Chabrol et al. 2012; Moran et al. 2008; Moran et al. 2009;Stellwagen and Kerig 2012). These studies highlight that CUtraits are one characteristic on a spectrum of personality di-mensions and not simply a qualitative category for use only indelinquent or antisocial populations. The predictive utility and

characteristic associations of CU traits could possibly extendto other populations.

Attention-Deficit Hyperactivity Disorder (ADHD) hasbeen included in the CU literature, but usually in associationwith other disorders. Although psychopathic characteristicsare not seen in all individuals with ADHD, a significantnumber of individuals evidence comorbid ADHD and antiso-cial personality disorder/psychopathy by young adulthood(Fowler et al. 2009; Miller et al. 2008). Therefore, the uniquepresence of CU traits in ADHD is of particular interest.Because many children with CD meet diagnostic criteria forADHD (Loeber et al. 1995), studies tend to assess CU traits insamples exhibiting ADHD and conduct problems or CDconcurrently. This has made it difficult to ascertain the uniquerole of CU traits in ADHD. However, some research hasstarted to address this problem. Research by Enebrink andcolleagues (2005) showed that CU traits predicted worseoutcomes in boys with conduct problems, but that this wasindependent of ADHD comorbidity. Other studies examiningassociations between conduct problems/CU and various out-comes—global impairment, level of conduct problems, ag-gression—suggest that the presence of CU traits is moredetrimental at low levels of ADHD (Brammer and Lee2012; Frick et al. 2003; Waschbusch and Willoughby 2008).

One point of similarity between ADHD-only populationsand antisocial CU populations are their deficits in emotionrecognition. Studies have found that individuals with ADHDhave greater difficulty with recognizing emotional facial ex-pressions than comparison groups (Miller et al. 2011;Norvilitis et al. 2000; Singh et al. 1998). Although one studydid find a particular difficulty in recognizing fear (Singh et al.1998), others found a general deficit across emotions.Therefore, ADHD-related deficits in emotion recognitionmight not be homologous to those associated with CU traits.Marsh and colleagues (2008) found that the reduced amygdalaresponse to fearful faces that is characteristic of high CUsamples (Jones et al. 2009; Marsh et al. 2008; White et al.2012) was absent in those with ADHD and low levels of CUtraits. The same study also revealed greater connectivity be-tween the ventromedial prefrontal cortex and amygdala inADHD individuals, but reduced connectivity for those highin CU traits. These findings suggest that the neural mecha-nisms underlying CU individuals’ difficulties with emotionrecognition are not responsible for the same difficulties seen inADHD. The present study will help reveal whether CU traitsare associated with emotion recognition deficits in ADHD. Ifno association is found, then other factors, like the manyexecutive dysfunctions associated with ADHD, may underlieinaccurate identification of emotions.

Although CU traits have not been assessed in individualswith Learning Disabilities (LD), emotional processing in LDhas been of great interest in past research. Following a litanyof results showing significant social skill deficits in those with

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LD (see Swanson and Sharon 1992 for a review), deficits insocial functioning are now recognized bymany agencies, suchas the National Joint Committee on Learning Disabilities(1989), as a common symptom of LD. One difficulty lies inprocessing and understanding social information (Baumingerand Kimhi-Kind 2008; Most and Greenbank 2000; Sisterhenand Gerber 1989). Specifically, individuals with LD haveshown a general difficulty labeling emotional facial expres-sions compared to those without LD (Holder and Kirkpatrick1991; Petti et al. 2003; Yuehua and Shanggui 2008). Thequestion that remains is whether these difficulties recognizingemotion in others stem from a callous, uncaring attitude (theydo not care about what another person is feeling), an inabilityto empathize (they cannot understand what another person isfeeling), or simply a difficulty in learning this social skill (theytry to understand the emotions of others but come to inaccu-rate conclusions more often than is typical). It seems plausiblethat a more general difficulty in learning to interpret socialinformation is responsible, as those with LD who have troubleinterpreting text-based information tend to have troubleinterpreting social cues (Cobb-Morocco et al. 2001).Children with LD also tend to have smaller vocabulary offeeling words (Elias 2004), which would make it hard to labelemotions accurately. A difficulty with social cues may resultfrom these more general difficulties with interpretation andlabeling. The present study will help elucidate the mecha-nisms behind emotion recognition difficulty in LD by com-paring performance on an emotion recognition task to levelsof CU traits.

The relationship between CU traits and psychiatric disor-ders in general is unclear. There is some evidence that highCU populations with conduct problems are at higher risk ofexhibiting mood-related symptoms (Enebrink et al. 2005;Fink 2011). However, the level of CU traits in individualswith psychiatric difficulties but not conduct problems is stillunclear. A review by Herpers and colleagues (2012) foundmixed findings regarding a relationship between CU traits andspecific psychiatric diagnoses. None of the studies reviewedlooked for a relationship between CU traits and emotionrecognition. Therefore, although many psychiatric disorders,such as mood disorders (Derntl et al. 2012), obsessive-compulsive disorder (Corcoran et al. 2008), and panic disor-der (Cai et al. 2012), are associated with emotion-recognitiondeficits, it is still unclear whether level of CU traits is acontributing factor. The present study will help identifywhether the relationship between high CU traits and emotionrecognition deficits, particularly a deficit in recognizing fear,normally seen in antisocial populations with conduct prob-lems, is relevant to psychiatric diagnoses in general.

Although CU traits have proven predictive and discrimina-tive value in the antisocial domain, the value of these traits inother populations remains to be seen. If the significance of CUtraits extends to other disorders and disabilities, this

information may guide diagnosis and treatment in non-antisocial populations. The present study aims to measureCU traits and emotion recognition in a sample of universitystudents receiving services through the Office of StudentDisability Services. Specially, the groups of interest werethose diagnosed with ADHD, LD, and psychiatric disorders,as well as a comparison sample of students with physical/sensory disabilities. Although it is not expected that thesepopulations will exhibit high levels of an antisocial character-istic like CU traits, previous research has not tested for this.Therefore, this investigation will act as an exploratory studyinto the levels of CU traits in diagnoses beyond the well-studied disruptive behaviour disorders. This study will alsotest that the relationship between CU traits and emotion rec-ognition holds true in non-antisocial populations Based on thefindings from previous research mentioned above, it is ex-pected that individuals with ADHD, LD, and psychiatricdisorders will exhibit greater difficulties in recognizing allemotions than the comparison (physical/sensory disabilities)group. As shown in previous research, higher levels of CUtraits should specifically correlate with deficits in identifyingfear.

Methods

Participants

The sample consisted of 39 students (5 males, 33 females, 1‘prefer not to answer’) who ranged in age from 18 to 30 (M=22.03, SD=3.31, one did not answer). The majority of partic-ipants were Non-Hispanic White or Caucasian (66.67 %),with the remainder being Non-Hispanic Black or AfricanDescent (7.69 %), Hispanic/Latino (5.13 %), Asian or AsianDescent (5.13 %), and Other/Mixed (15.38 %). All partici-pants were enrolled in a university in Southwestern Ontarioand were currently registered with the university’s StudentDisabilities Services as having a learning disability (N=9),ADHD (N=8), a non-ADHD psychiatric disorder (N=14), ora disability that did not include a learning disability or apsychiatric disorder, such as a physical disability or sensoryimpairment (N=8). The last group was used to comparison forthe effects related to needing services of any kind in a univer-sity. Physical and sensory impairments that might emotionrecognition were excluded (i.e. disabilities resulting fromtraumatic brain injury or illness that might affect neuropsy-chological functioning). See Appendix, Table 1 for demo-graphic information by group. The researcher actively recruit-ed participants by hanging posters throughout the campus andin the Student Disabilities Office. The researcher also request-ed that Student Disabilities Services send a brief email aboutthe project to students currently receiving services.Participants were entered into a draw for one of three

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twenty-five dollar gift certificates to the local shoppingmall ascompensation.

Measures

Callous-Unemotional Traits The 24-item self-report versionof the Inventory of Callous-Unemotional Traits was used(ICU; Frick 2004). The survey asks participants to rate thetruth of statements in regards to themselves using a four-pointscale ranging from 0 to 3 (0 = “not at all true”, 1 = “somewhattrue”, 2 = “very true”, 3 = “definitely true”). Some items areworded positively and must be scored conversely beforescores are calculated. Possible scores range from 0 to 72, withhigher scores representing a higher level of CU traits. Thedistribution of ICU scores for the full sample approximatednormality (M=17.35, SD=7.22) with a range of 6 to 39.

Previous studies have shown adequate internal consistency(Cronbach’s α=0.77, Essau et al. 2006; Cronbach’s α=0.88,Feilhauer et al. 2012) and moderate to good test-retest reli-ability (r=0.72, p<.001; Feilhauer et al. 2012) for this mea-sure. Criterion and convergent validity (Essau et al. 2006;Feilhauer et al. 2012) as well as discriminative validity(Roose et al. 2010) have also been supported for the ICU.The use of this measure in university samples has also beenvalidated (Kimonis et al. 2012). Internal consistency for thepresent study was adequate (α=0.764).

Emotional Processing Task The emotional processing taskwas administered using the DirectRT computer program. Weused pictures of emotional facial expressions of a young maleand female taken from the Montreal Set of Facial Displays ofEmotion (MSFDE; Beaupré and Hess 2005). To keep partic-ipation time at a minimum, only the Caucasian faces from theMSFDE were used. Previous research using the MSFDE in adiverse Canadian sample found that cultural minority groupscould recognize emotional facial expressions of Caucasianfaces and those of their own cultural group equally well(Beaupré and Hess 2005). Therefore, using only Caucasianfaces from the MSFDE should not have put non-Caucasianparticipants at a disadvantage.

The MSFDE includes morphed versions of the pictures toshow five different intensities of each emotion. The pictureswere validated by two certified coders using the Facial ActionCoding System (Ekman and Friesen 1978). Participants werepresented with a picture of a face and had to try to identify theemotion displayed (See Appendix, Fig. 1). They were told toanswer as quickly and accurately as possible by selecting thecorresponding number key on a keyboard from a list of 8choices: neutral, sadness, joy, shame, fear, disgust, anger, and‘don’t know’. In the first trial, pictures of faces were presentedin order of increasing intensity for each emotion (neutral,20 %, 40 %, 60 %, 80 %, and 100 %), with gender of the facebeing held constant from neutral to 100 %. The second trial

presented emotion, intensity, and gender in a randomizedorder. Consistent with past studies (Ali 2007), answers werescored as 1 if the participant responded with the correctemotion and 0 if any other response was given. No validitychecks were conducted for this task, although it is a commonresearch paradigm.

Procedure

The study was approved by the university’s Research EthicsBoard. The study took place in a quiet university computerlab. Participants attended a single scheduled session, at thebeginning of which they were given a consent form to signindicating their willingness to participate in the study.Participants were encouraged to take their time reading theform and to ask questions if needed. Only after the participanthad given written consent did the research portion of thesession begin.

The researcher explained the procedure for completing theICU. Participants were asked to carefully review the instruc-tions before filling out the survey. After participants complet-ed the survey, the researcher explained the procedure forcompleting the emotion recognition task on a computer.There were also written instructions for the participant tocarefully review before starting the task. Throughout thestudy, participants were sitting at an individual desksurrounded by cardboard dividers to create a private booth.The researcher was available nearby for the duration of thestudy to answer any questions or concerns the participant had.At the end of the session, participants were given a copy of theconsent form to keep.

Results

In order to compare the four diagnostic groups (ADHD, LD,psychiatric disability, physical/sensory disability) in terms ofICU scores a one-way ANOVAwas conducted. Results showa marginal main effect of diagnostic group on ICU scores witha large effect size, F(3, 35)=2.45, p=0.080, ηp

2=0.174. Therewere no significant differences between individual diagnosisgroups regarding ICU scores. See Appendix, Table 1 for ICUscores by diagnostic group.

For the emotion recognition tasks, an independent mea-sures t-test was conducted to compare the means of the or-dered and randomized trials. On average, participants correct-ly identified emotions more often on the randomized trial (M=68.98 %, SD=10.57) than on the ordered trial (M=64.42 %,SD=11.13). This difference was statistically significant,t(38)=3.459, p<.05. It is important to note that theincrease in accuracy of 4.56 % between the first trial(ordered) and the second trial (randomized) could bedue to practice effects. Considering the relatively small

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difference in mean percentage score and the possibility thateffects were due to practice rather than stimulus order, scoresfrom the two trials were combined in all further analyses.

In order to compare the four diagnostic groups (ADHD,LD, psychiatric disability, physical/sensory disability) interms of emotion recognition, a one-way ANCOVAwas con-ducted. Participants’ ICU scores were used as the covariate.The test revealed a non-significant main effect of diagnosisbut a medium effect size, F(3, 34)=0.755, p=0.527, ηp

2=0.062. Total ICU score also had a non-significant main effectwith a medium effect size, F(1, 34)=2.577, p=0.118, ηp

2=0.070. Contrary to the hypothesis, there were no significantdifferences between diagnoses regarding the mean percentageof correct responses to identifying emotions (ADHD=67.3%,LD=64.1 %, psychiatric disorders=69.2 %, physical disabil-ities=63.5 %). Overall emotion recognition scores changedvery little when controlling for the ICU scores (ADHD=from68.49 to 67.3 %, LD=from 62.50 to 64.1 %, psychiatricdisorders = from 68.55 to 69.2 %, physical disabilities = from64.83 to 63.5 %).

A repeated measures ANCOVAwas conducted to examinethe effect of diagnostic group on specific emotion recognition.Participants’ ICU scores were again used as the covariate.Mauchly’s Test of Sphericity was significant, soGreenhouse-Geisser adjustments were used. There was a sig-nificant main effect of emotion with a medium to large effectsize, F(4.4, 149.2)=4.658 p<.05, ηp

2=0.12. Pairwise compar-isons assessed at p<0.05 revealed that participants scoredsignificantly higher in recognizing anger (68.5 %), joy(75.9 %), sadness (69.9 %), disgust (65.6 %), and neutral(78.3 %) compared to fear (50.5 %). Sadness, joy, and neutralwere each identified significantly more often than shame(57.1 %). Joy and neutral were each identified significantlymore often than disgust. The interaction between emotion andtotal ICU score was non-significant with a small to mediumeffect size, F(4.39, 149.19)=1.78, p=0.13, ηp

2=0.049. Theinteraction between emotion and diagnosis was also non-significant with a small to medium effect size, F(13.16,149.19)=0.485, p=0.93, ηp

2=0.041. Tests of between-subject effects revealed a non-significant main effect of ICUscore with a medium to large effect size, F(1, 34)=3.078, p=0.088, ηp

2=0.083. The main effect of diagnosis was non-significant with a medium effect size, F(3, 34)=0.726,p=0.543, ηp

2=0.083.

Fear Recognition As fear is the emotion of greatest interest inthe extant literature, a one-way ANCOVA was conducted tocompare the four diagnostic groups in regard to fear recogni-tion. Contrary to expectation, the main effect of ICU score wasnon-significant with a very small to insignificant effect size,F(1, 34)=0.196, p=0.661, ηp

2=0.006. The main effect ofdiagnostic grouping was non-significant with a smalleffect size, F(3, 34)=0.808, p=0.498, ηp

2=0.067.

There was a non-significant effect of each diagnosis with smalleffects, except for the psychiatric disorder group, which wasnon-significant but with a medium effect size, ηp

2=0.066.

Discussion

This study assessed the level of CU traits, as well as therelationship between CU traits and emotion recognition, inindividuals receiving services through the Office of StudentDisabilities on a university campus. Results suggest that thesediagnostic groups exhibit similar levels of CU traits whencompared with the comparison group and that the relationshipbetween CU traits and emotion recognition deficits previouslyseen in antisocial populations is not present in this sample.Contrary to the hypothesis, these diagnostic groups displayedsimilar levels of accuracy on the emotion recognition task asthe comparison group.

The theoretical range of total scores for the ICU is 0–72.No guidelines exist for the interpretation of ICU scores.However, the mean score for the present study (M=17.35,SD=7.22) was significantly lower than that found in a largecommunity sample of 14 to 21 year olds (M=24.05, SD=9.17;Roose et al. 2010), t(492)=4.45, p<0.0001, and significantlylower than that found in a healthy control group of male 8 to17 year olds (M=24; Feilhauer et al. 2012), t(209)=4.35,p<0.0001. One explanation for this low mean score may bethe large imbalance of females to males in the present study, astypically females score lower on the ICU than males (Essauet al. 2006). A small university sample, which is unlikely to besignificantly antisocial, may also score lower than the rest ofthe population, as very few individuals score high on CU traitsbut low on antisocial behavior (Frick et al. 2000).

Although this study found a non-significant main effect ofdiagnosis on ICU scores, this effect is significant at the 10 %level and has a large effect size. This suggests that with a largersample size, a significant effect of diagnosis on ICU scoresmight be seen. Individual group means suggest that, with largergroup sample sizes, the higher LD (M=21.38, SD=7.84) andpsychiatric group (M=18.96, SD=6.57) scores may provesignificantly different from the lower physical/sensory disabil-ity group scores. In comparison, past findings in offendingpopulations show slightly higher ICU scores; a 13–20 year-old male and female sample scored between 27 and 29 on theICU (Feilhauer et al. 2012) and a 12–18 year-old female grouphad an average score of 23.80 (SD=9.30) (Kunimatsu et al.2012). The fairly close proximity of scores between the femaleoffending group and the current study’s predominantly femaleLD sample raises the question of whether CU traits may be ofclinical significance in those with LD.

The mean ICU score of the ADHD group (M=14.22, SD=6.46) was very close to the mean score for the comparison

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group (M=14.00, SD=6.70). This suggests that a diagnosis ofADHD alone (not co-morbid with a disruptive behaviourdisorder) is not correlated with CU traits. This result agreeswith the findings of Fowler et al. (2009) that suggest theassociation between ADHD and psychopathy scores existsonly due to a shared link with conduct disorder, and not dueto a unique link between ADHD symptoms and psychopathictraits (which would include CU traits). Several other studieshave specifically found no support for a link between ADHDand high levels of CU traits (Barry et al. 2000; Fowler et al.2009; Waschbusch and Willoughby 2008).

Emotion recognition did not differ significantly betweengroups. This was unexpected, given past findings that thosewith LD (Dickinson 2000; Dimitrovsky et al. 1998; Holderand Kirkpatrick 1991; Petti et al. 2003; Yuehua and Shanggui2008) and ADHD (Miller et al. 2011; Norvilitis et al. 2000;Singh et al. 1998) have greater difficulty recognizing emo-tional facial expressions compared to control groups. Thenature of this study’s sample may explain this unexpectedfinding, as university students would likely represent thehigher-functioning individuals in each diagnostic populationand may, therefore, have less impaired emotion-recognitionskills. This study was also not able to control for the possibleeffects of treatment or medication. Considering the mediumeffect size of diagnosis in overall, across-emotions, and fearrecognition, a larger and more representative sample mightreveal significant differences in emotion recognition.

As expected, the specific emotion to be recognized signif-icantly affected performance on the emotion recognition task.Past research has found that the general population has greaterdifficulty in recognizing negative emotions, especially fearand disgust, but relative ease in identifying joy (Elfenbeinand Ambady 2002; Matsumoto 1992). In agreement with this,fear was significantly harder for participants to recognizecompared to most other emotions, followed by shame anddisgust, while joy and neutral were easiest to identify.

Inventory of Callous-Unemotional Traits score did not havea significant effect on emotion recognition, although mediumto large effect sizes were found. The interaction betweenemotion and ICU score was also non-significant. Most sur-prisingly, an effect of ICU score on fear recognition was notfound. This disagrees with past research on antisocial popula-tions that found a link between high CU traits and decreasedfear recognition (Blair et al. 2001; Dadds et al. 2008, 2006;Leist and Dadds 2009; Stevens et al. 2001). This suggests thatin non-antisocial populations, CU traits do not affect emotionrecognition in general or fear recognition specifically.However, the average level of CU traits in this sample waslower than those found in community samples, possibly indi-cating that the small and predominantly female sample did notcapture those with high CU traits. Therefore, an effect ofhigher levels of CU traits on emotion recognition in thesepopulations cannot be ruled out. It is also possible that in

antisocial populations, there is another variable at play—re-duced amygdala response to fearful facial expressions (Whiteet al. 2012), reduced empathic sadness (De Wied et al. 2011),etc.— affecting the relationship between CU traits and emo-tion recognition that is absent in non-antisocial populations.Such possible third variables should be explored in futurestudies comparing antisocial and non-antisocial samples.

Diagnosis did not predict emotion recognition skills acrossdifferent emotional facial expressions. This agrees with pastliterature that has found generalized emotion recognition defi-cits (not specific to any one emotion) in those with ADHD(Miller et al. 2011; Norvilitis et al. 2000; Singh et al. 1998) andthose with LD (Dickinson 2000; Dimitrovsky et al. 1998;Holder and Kirkpatrick 1991; Petti et al. 2003; Yuehua andShanggui 2008). In terms of psychiatric disorders, mood andlevel of symptoms at the time of testing can affect specificity ofemotion recognition deficits (Corcoran et al. 2008; Csukly et al.2008). The absence of specific emotion recognition deficits inthese results suggests that mood and symptom level wererelatively stable in the individuals tested. However, as this studydid not assess symptoms, or even specific psychiatric diagno-ses, it is difficult to draw specific conclusions about the perfor-mance of the psychiatric group on the emotion recognition test.

Conclusions and Future Directions

This study sought to address the current lack of understandingregarding the effects of CU traits on emotion recognition innon-antisocial disordered populations. Results suggest that, inthose with ADHD, LD, and psychiatric disorders, CU traitsare unrelated to emotion recognition. The clinical groups didnot differ from comparisons in ICU score, although this non-significance may have been due to the small sample sizes.Additionally, these samples scored lower in CU traits thancommunity samples and healthy comparisons in past studies.

Future research should assess antisocial characteristics con-currently with CU traits so that the unique and interactiveeffects of these two personality dimensions can be betterassessed. Non-antisocial diagnosis populations, such as theones examined in this study, should specifically be studied inorder to assess the cross-disorder utility of CU traits. With CUtraits added as an identifier to disruptive behaviour disorderdiagnoses in the new DSM-5 (APA 2013) , it is more impor-tant than ever to assess whether or not this personality trait caneventually be used to help identify and treat other disorders.

While this study provided a good baseline for the cross-disorder examination of the relationship between CU traitsand emotion recognition, it is important that further researchexamine this relationship at different levels of symptoms andin more specific diagnoses. Due to sample size restrictions,this study assessed general groupings of LD, ADHD, andpsychiatric disorders. Specific psychiatric diagnoses, non-verbal versus verbal LD, and different sub-types of ADHD

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should be examined in future research, as these could repre-sent important distinctions in emotion recognition and CUtraits. Larger sample sizes that are more representative of thefull range of functioning and symptoms in each diagnosticgroup (equal gender make-up, non-university sample) areneeded to assess the presence and effects of CU traits in thesenon-antisocial populations. This study did not measure dis-ruptive behavior disorder symptoms, as it was assumed thesewould be low in a university population. However, futurestudies should add such a measure in order to more specifi-cally assess the possible role of antisocial behaviours in therelationship between CU traits and emotion recognition.

To date, the vast majority of research on CU traits hasexamined individuals with severe conduct problems and thosediagnosed with disruptive behaviour disorders. A recent meta-analysis of the current CU traits literature concluded that highCU traits are present in other disorders, but, due to a lack ofresearch in this area, their clinical significance beyond disrup-tive behaviour disorders is not well understood (Herpers et al.2012). The present study provided an important step towardsaddressing this lack of understanding. It will provide a basisfor more specific examinations of the relationship betweenCU traits and emotion recognition.

Acknowledgments The authors wish to thank Daniel Edelstein at theAcademic Data Centre within the Leddy Library at the University ofWindsor for his assistance with the statistical analyses and the participantsfor their willingness to be part of the project.

Conflict of Interest Franklynn E. Bartol declares no conflict of interest;Carlin J. Miller declares no conflict of interest.

Experiment Participants The full research protocol was reviewed bythe University’s Research Ethics Board. Participants gave full consentprior to participation in the study.

Appendix

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Table 1 Descriptive statistics

N %Female

MeanAgeM(SD)

%Caucasian

ICU ScoreM(SD)

Total 39 86.8 22.03(3.31) 66.67 17.35(7.22)

ADHD 8 88.9 22.00(2.27) 62.50 14.22(6.46)

LD 9 77.8 20.00(1.50) 77.78 21.38(7.84)

Psychiatric Disorder 14 42.9 22.07(2.47) 100.00 18.96(6.57)

Physical Disability/Sensory Impairment

8 50.0 24.00(5.29) 100.00 14.00(6.70)

There is one missing age and one ‘prefer not to answer’ gender. Bothinstances are from subjects in the ADHD group

Fig. 1 Example from the emotional processing task. The female modelhere is displaying a neutral facial expression. Emotion answer choices aredisplayed along the right, with the corresponding number key that theparticipant presses to answer on the keyboard

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