618431

research-article2015CJBXXX10.1177/0093854815618431CRIMINAL JUSTICE AND BEHAVIORRidder et al

Empathy In Institutionalized
Adolescents With
Callous-Unemotional Traits
An Ecological Momentary Assessment Study ofEmotion Recognition
Jill De Ridder
University of Fribourg

Sandrine Pihet
University of Fribourg
University of Applied Sciences and Arts Western Switzerland

Maya Suter
University of LausanneRoberto Caldara
University of Fribourg
Callous-unemotional (CU) traits are associated with impaired distress recognition, possibly leading to suboptimal empathy
development. Evidence stems from computerized task results, having little in common with day-to-day experiences. We
assessed institutionalized adolescents’ empathic accuracy in their ability to infer staff members’ emotions, using EcologicalMomentary Assessment. A sample of 55 adolescents reported perceived levels of distress and anger in staff, 4 times per day
over the course of 8 days. CU traits were assessed with the Youth Psychopathic Traits Inventory, and data were submitted tomultilevel regression analyses. All adolescents well identified anger and distress; high CU adolescents even overestimatedboth anger and distress intensities. Our ecological data suggest that in real-life situations, cognitive empathy skills maycompensate for high CU adolescents’ distress recognition impairment. However, this compensatory process results in theperception of excessively negative emotions.
Keywords:

adolescence; callous-unemotional; empathy; emotion recognition; Ecological Momentary Assessment

A

dolescents with callous-unemotional (CU) traits are often perceived as emotionallydetached and uncaring but for themselves, showing little compassion for others andregret about their hostile actions. These characteristics may be rooted in empathy
Authors’ note: This study was funded by the Swiss National Foundation (#100014-130553). Our special
thanks goes to Cybèle Bertoni, Tamara Borovicanin, Marcello Cantarella, Margaux Clément, and Sheila Ramos
for their help during data collection, to Laura Bamert, Nathalie Grégoire, Antje Horsch, Laura Moizeau, andSébastien Urben for proof-reading of the manuscript, to the entire staff of the forensic institutions Maison d’arrêt,de detention et d’observation de Valmont at Lausanne and Time-Out at Fribourg and of the private boarding
schools Maya-Joie at La Fouly and Don Bosco at Sion, and last but not least to all participants who made thisresearch possible. Correspondence concerning this article should be addressed to Jill De Ridder, Department of
Psychology, University of Fribourg, Faucigny 2, 1700 Fribourg, Switzerland; e-mail: jill.deridder@unifr.ch.
CRIMINAL JUSTICE AND BEHAVIOR, 2016, Vol. 43, No. 5, May 2016, 653­–669.
DOI: 10.1177/0093854815618431© 2016 International Association for Correctional and Forensic Psychology

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dysfunction (Frick & White, 2008). Modeled on the affective-interpersonal dimension of
adult psychopathy, CU traits are thought to be a developmental precursor to psychopathic
traits in adulthood (Pasalich, Waschbusch, Dadds, & Hawes, 2014). Thus, in adolescents,
despite its overlap with conduct problems, CU traits are considered distinct risk-related
affective-interpersonal features (Pasalich et al., 2014). Among delinquent adolescents, CU
traits therefore identify a specific high-risk subgroup frequently involved in various typesof serious crimes and assaults, and using more proactive aggression (Frick & Moffitt, 2010).
In addition, CU traits are associated with a poor response to traditional treatment approaches(e.g., Frick & Moffitt, 2010). As a result, CU traits have been included in the fifth revisionof the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American
Psychiatric Association [APA], 2013) as a specifier (i.e., with limited prosocial emotions)
to conduct disorder (CD).
Lack of empathy is a defining feature of CU traits (Frick & Viding, 2009). Empathy isdefined as a shared emotional response resulting from comprehension and appreciation of theemotional state of others (Eisenberg, Eggum, & Di Giunta, 2010). Empathy is therefore
understood as a multidimensional phenomenon comprising both cognitive and affective components (Wai & Tiliopoulos, 2012). Affective empathy refers to the ability to feel what otherpeople feel—comparable with the construct of emotional contagion or sharing—and is characterized by visceral, automatic reactivity (Mehrabian & Epstein, 1972). Cognitive empathy
refers to the ability to understand and describe what other people feel and why they feel thatway, without necessarily experiencing emotional contagion (Wai & Tiliopoulos, 2012). The
latter ability (accurately describing or inferring the emotional state of others) is also called
empathic accuracy (Ickes, 1993). Empathic accuracy does not necessarily imply sharing theother person’s emotional state (Rauers, Blanke, & Riediger, 2013). Reduced abilities to share
and/or infer others’ emotional distress are thought to be at least in part responsible for the serious and chronic conduct problems of high CU adolescents. Such empathy dysfunction may
prevent these adolescents to access cues leading to aggressive behavior inhibition (Jolliffe &Farrington, 2004). This association between empathy deficits and CU traits has received substantial scientific attention. Several recent laboratory studies have demonstrated that adolescents with high CU traits are less affected by the emotional situation of others, but show
empathic accuracy, therefore revealing no cognitive empathy impairment (e.g., AnastassiouHadjicharalambous & Warden, 2008; Jones, Happé, Gilbert, Burnett, & Viding, 2010). Thisbody of empirical evidence has led to conceptualizing CU traits as associated with specificdeficits in affective empathy along with functional cognitive empathy (Blair, 2013).
The component of affective empathy is presumed autonomic and attributed to the amygdala (Mehrabian & Epstein, 1972). A current putative hypothesis is that high CU individuals may suffer from an amygdala dysfunction resulting in an impaired recognition of
distress-related emotions and reduced empathic responses (Blair, 2013). The accurate recognition of others’ emotions is indeed an underlying skill and as such a prerequisite for adequate inference and sharing of others’ emotional state, in other words, for empathy development(Blair, Mitchell, Peschardt, et al., 2004). Several studies in different clinical populations haveempirically demonstrated a close relation between impaired emotion recognition and empathy
deficits (e.g., Blair & Coles, 2000; Carr & Lutjemeier, 2005; Gery, Miljkovitch, Berthoz, &Soussignan, 2009). Among high CU adolescents in particular, a large body of evidence has
been gathered over the past decade. This evidence points to an impaired recognition of distress-related emotions, whereas the recognition of other emotions such as surprise or anger
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seems unaffected. Most of these studies focused on the recognition of facial expressions,some on paraverbal cues, and one on body language (for a comprehensive review, see Frick,
Ray, Thornton, & Kahn, 2014).
This bulk of evidence is largely built on experimental testing in laboratory settings using
static or dynamic computerized emotion recognition tasks (Dawel, O’Kearney, McKone, &Palermo, 2012; Wilson, Juodis, & Porter, 2011). Tasks are predominantly based on visualcues making use of unimodal faces picturing six basic emotions (anger, happiness, disgust,fear, sadness, surprise). Although some computerized stimuli were dynamic, namely, a neutral face gradually morphing through incremental stages into one of the six prototypicalexpressions (Blair, Colledge, Murray, & Mitchell, 2001), they presented only pure and context-free emotions. Such procedures are essential to maximize the internal validity. Yet,
impaired emotion recognition in the laboratory does not necessarily imply corresponding
deficits in daily life emotion inference. Visual sensory cues are just one particular aspect of
all available interpersonal information (Krueger & Funder, 2004). Inferring others’ emotions can also be affected by one’s own behavior and affective and relational experience(Gadassi, Mor, & Rafaeli, 2011). As a consequence, this line of research lacks ecologicalvalidity, questioning the transferability of those findings to everyday life interactions.
To the best of our knowledge, no study has investigated empathic accuracy in adolescents with CU traits in a daily life ecological context. Daily life studies offer a unique
opportunity to better understand emotion recognition. Indeed, a context is required in whichadolescents can infer others’ emotions making use of a wide range of interpersonal information, varying from accurately perceiving sensory cues to efficiently using acquired knowledge (Rauers et al., 2013). The aim of the present study was to start filling this gap by using
Ecological Momentary Assessment (EMA). EMA assesses actual perceptions, emotions,and behaviors as they occur in the natural settings of interest, therefore maximizing ecological validity (Fahrenberg, Myrtek, Pawlik, & Perrez, 2007).
EMA studies on adolescents are still scarce, and research on adults has focused solely on
those involved in romantic relationships. Wilhelm and Perrez (2004) were the first to introduce daily diaries into the study of empathy. They examined partners’ perception about theothers’ emotions (sad–happy, tense–relaxed, unsatisfied–satisfied) and focused primarilyon bringing research out of the laboratory into participants’ daily lives (Wilhelm & Perrez,2004). A second study on individual differences in empathic accuracy used a daily process
method assessing cohabiting partners’ feelings once a day during 3 weeks (Howland &Rafaeli, 2010) and demonstrated that momentary states versus more global patterns reflect
different types of accuracies. In a study on depression by Gadassi et al. (2011), every evening over a period of 3 weeks, participants completed diaries with questions about their own
and their partners’ negative (e.g., anger, anxiety) and positive (e.g., happiness, calmness)feelings. This study revealed, among other results, an impairment to correctly infer negative
emotions. The authors proposed that repeated experiences of rejection lead depressed individuals to develop a heightened sensitivity to negative interpersonal information (Gadassi
et al., 2011). Finally in an experience-sampling study, Rauers and collaborators (2013)
investigated younger and older couples’ empathic accuracy in daily life. Participants rated
their own and their partner’s emotions during 15 days, with six daily assessments. The study
demonstrated different skills for empathic accuracy: those associated with acquired knowledge, which remains steady throughout life, and skills associated with sensory cues, which
declines throughout life (Rauers et al., 2013).
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Regarding institutionalized adolescents, prior EMA studies had other focuses. One EMA
study was conducted on juvenile offenders (Farnworth, 2000) focusing on time use during
probation. Another EMA study was conducted on incarcerated young adults and had a nutritional focus (Eves & Gesch, 2003). Only one EMA study involved both incarcerated andjuvenile offenders and evaluated the feasibility and reliability of EMA (Pihet, De Ridder, &Suter, 2015). This last study supports feasibility and suggests that EMA allows reliable datacollection in such a challenging population (Pihet, De Ridder, et al., 2015). The present
study seems to be the first to assess everyday empathic accuracy in institutionalized adolescents with high and low CU traits.
Our primary aim was to investigate the transferability of the evidence built from laboratory studies regarding high CU adolescents’ impaired distress recognition to the complexityof everyday life situations. For this purpose, we assessed institutionalized adolescents’empathic accuracy in their ability to infer the emotions experienced by familiar adults intheir natural interactions across a wide range of real situations (Pihet, 2000). We acquired
repeated real-time parallel assessments of adolescents’ perceptions of staff members’ emotions and of staff members’ experienced emotions, while they were going about their daily
activities in their usual environment. We focused on emotions within the anger (angry, irritated) and distress (stressed/worried, destabilized) scope, as they are commonly experienced in our context of interest. The latter is not the case for fear and sadness (pilot work inteachers revealed that they nearly never experienced fear and sadness in their daily interactions with students). Thus, while there is an overlap with the construct of distress typicallyassessed in computerized emotion recognition tasks, it is important to note that both constructs are not identical. In addition, measuring anger and distress inference seems suitable
for the assessment of mixed emotions, in contrast to anger or distress in prior lab studies, as
in real life one can experience both emotions concurrently. Following the current results inthe literature, we expected high CU adolescents to show less empathic accuracy for distress-related emotions in staff members and to show normal performance in inferring otheremotions, namely, anger.
Subsequent to empathic accuracy is the affective sensitivity, measured as the estimationof the intensity of the adequately inferred emotion. Consequently, a secondary aim of ourstudy was to investigate whether high CU adolescents, in case of good empathic accuracy,
would globally underestimate distress—and not anger—intensities, compared with their
low CU counterparts, by controlling for staff members’ reported intensity. We expectedadolescents’ ability to use available distress-related sensory cues to be moderated by CU
traits. Their ability to use acquired knowledge may be less affected though, as cognitive
empathy skills seem intact for low and high CU adolescents. An additional aim was toexplore how empathic accuracy is related to adolescents’ own behavior, and own affective
and relational experience.
MethodParticipants

Seventy-one institutionalized adolescents were recruited as part of a larger study conducted in youth welfare and juvenile justice institutions in the French-speaking part of
Switzerland,1 from two forensic facilities (n = 34) and two boarding schools accommodating adolescents with behavioral and/or learning disorders (n = 37). The boarding schools
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Table 1: Sample Characteristics
Sample(N = 55)

Characteristic
Recruitment place
Boarding school
Forensic facility
Age (years)
Boys
Swiss nationals
French mother tongue
SES
High
MiddleLow
SPM score
CD diagnosis

36 (65%)29 (35%)14.8 ± 0.87
45 (82%)30 (55%)39 (81%)7 (12%)
37 (68%)11 (20%)43.15 ± 6.40
28 (51%)

Note. The figures are mean values (±SD) or frequency (and %). SES = socioeconomic status; SPM = Standard
Progressive Matrices of Raven; CD = conduct disorder.

were chosen for their mixed socioeconomic status (SES) population and their activity
schedule comparable with that of the two forensic facilities. They accommodated the adolescents from Sunday evening to Friday afternoon and offered daily sport activities.
Ninety percent of the recruited adolescents completed the study. Noncompletion resulted
from the adolescent’s refusal to participate (n = 1) or from drop-out due to lack of motivation(n = 5) or integration in an external program (n = 1). In addition, exclusion criteria were a possible intellectual disability assessed with the Standard Progressive Matrices (SPMs; n = 2) ofRaven and lack of sufficient French language skills (n = 1). Six participants (8% of completers) were excluded from analyses because of insufficient (n = 3) or invalid (n = 1) EMA
data, or insufficient staff reports (n = 2). No significant differences were observed between
completers and noncompleters on gender, nationality, or mother tongue. Compared with completers, noncompleters were however slightly older (M = 14.8, SD = 0.87 and M = 15.57, SD= 0.73 years old, respectively), U(64) = 221, p = .011, as well as more likely to have been
recruited in a forensic facility (35% and 94%, respectively), χ2(1) = 17.41, p < .001, and tocome from a low SES family (20% and 67%, respectively), χ2(2) = 11.83, p = .003.
The final sample consisted of 55 adolescents with the sample’s characteristics presented
in Table 1. Variables of interest are perceived staff anger and distress, staff-reported anger
and distress, participants’ own negative affect, misbehavior and interpersonal conflicts withstaff, and participants’ CU traits. CU traits were not confounded with any sociodemographic
characteristic, as they were not significantly associated with gender, age, nationality, mothertongue, nonverbal intelligence, or SES. CU traits were however higher in adolescents witha CD diagnosis (r = .34, p = .011), which was therefore controlled in all analyses so that all
results reflect the effect of CU traits independent of CD. Consequently, this study focusedon the participants’ affective and interpersonal style and not on the conduct problems themselves (Frick et al., 2014). Recruitment place was also significantly associated with some ofthe variables of interest (i.e., perceived anger and distress, misbehavior and interpersonal
conflicts) and was therefore equally controlled. Gender and age were not associated withany variable of interest.
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Figure 1:	EMA Items
Note. EMA items measuring the intensity of anger (two items) and distress (two items) perceived in staff members,
as well as the intensity of negative affect (10 items), misbehaviors (three items), and interpersonal conflicts (twoitems). EMA = Ecological Momentary Assessment.
a. Reversed item.

Procedure

The study procedure was approved by the local ethics committee, and agreements wereobtained from the principals of the boarding schools and directors of the forensic institutions. First, we presented the research and guaranteed the confidentiality of responses andfreedom to withdraw from the study any time without consequences. Then, written consent
was obtained from the participants and one of their parents or legal guardian.
EMA consisted of a time-sampling procedure with four measures per day (morning, noon,
afternoon, and evening) during 8 days (for the EMA items, see Figure 1). During the EMA
period, participants responded to the questions on their Personal Digital Assistant (PDA). In
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the forensic facilities, the PDAs beeped to remind participants to answer the questions assoon as possible. In the boarding schools, teachers distributed PDAs during class hours atplanned time points. Time intervals were chosen, so as to cover the complete day with minimal interference with the daily routine. The compliance was very satisfactory, with a medianof 24 valid measures (80%) of 30 possible measures (the first morning and last evening
measures were always skipped for practical reasons). This is remarkably high for an institutionalized sample. For instance, in a study of Henker, Whalen, Jamner, and Delfino (2002)
where a community sample of 13- to 16-year-olds reported on their moods, activities, social
settings, dietary intake, smoking, and alcohol use, the compliance did not exceed 80%, as iscommon in EMA studies.
Forty-seven staff members contributed to this study. Staff compliance was much lower
than expected: They provided on average only 11 valid measures (37%) of the 30 measures
expected at minimum. It was nevertheless possible to analyze momentary associations
between adolescent and staff reports.
The collection of standard demographic information, the completion of the Youth
Psychopathic Traits Inventory (YPI) and SPM, as well as the EMA training were conducted bytrained research psychologists. Assessment and EMA training occurred in individual sessions
in the forensic facilities and small group sessions in boarding schools (maximum of 10 participants for assessment and maximum of three for EMA training sessions). The Schedule for
Affective Disorders and Schizophrenia for School-Age Children–Present and Lifetime version(K-SADS-PL) interview was conducted by a qualified research psychologist in an individual
setting. All adolescents received an individualized feedback on their personal results.
Measures

EMA

Figure 1 provides an overview of EMA items and their response formats. Adolescents
reported the intensity of anger (mean of two items, Anger) and distress (mean of two items,
Distress) they perceived in staff members. They also reported the intensity of their own negative affect (mean of 10 items), misbehaviors (mean of three items), and interpersonal conflicts
with staff members (mean of two items). Questions were presented on the screen of a PDA,
on which answers were given by moving a cursor on a Visual Analogue scale, which yieldeda score between 0 and 100. The median Cronbach’s alpha was .77 for Anger and .76 forDistress. Internal consistency was good, in particular considering the small number of items.
Staff Reports

Staff members were instructed to report their own levels of anger and distress after eachperiod of at least 1 hour spent with the adolescent. They made use of identical items to thoseused for adolescents, only in a paper-and-pencil version. Scores were computed in the same
way as for adolescents. The median Cronbach alpha was .89 for anger and .87 for distress.
Internal consistency was excellent.
YPI

CU traits were assessed using the YPI (Andershed, Kerr, Stattin, & Levander, 2002), a
50-item self-report questionnaire. The YPI is specifically designed to reduce the influence of
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Criminal Justice and Behaviorsocial desirability on responses and to facilitate endorsement by describing feelings and opinions as competencies rather than deficiencies. Participants were asked to estimate the degree
to which each individual item applies to them, using a 4-point Likert-type scale ranging from1 (does not apply at all) to 4 (applies very well). The YPI measures three core dimensions of
psychopathy using its Lifestyle, Interpersonal (YPI-Int), and Affective (YPI-Aff) scales, andcaptures essential features of the emotional life. It assesses callousness or emotional insensitivity, focusing on reduced emotional contagion and the perception of emotions as weaknesses. It also assesses unemotionality or emotional impassibility, focusing on reduced fearand sadness experience (Pihet, Etter, Schmid, & Kimonis, 2015). The YPI, just as most existing measures, has therefore only partial coverage of CU traits2 as CU traits are historicallyconsidered part of the larger psychopathy construct (Frick & Ray, 2014). As users of the YPI
may rely on its scale scores separately (Pihet, Suter, Meylan, & Schmid, 2014), we opted forthis instrument focusing solely on its CU traits scales and computed a CU score by taking the
average of the YPI-Int and YPI-Aff scales. The YPI has shown good psychometric properties,
and its scores accurately predict various forms of deviant conduct (Skeem & Cauffman, 2003).
We used the French version of the YPI (D’Acremont, Van der Linden, Axelson, Flykt, &Vonèche, 2002), which has shown good psychometric properties as well (Pihet et al., 2014).
SPMs

The SPMs (Raven, Court, & Raven, 1998) were administered to provide an estimate ofnonverbal intelligence. The SPMs are made up of a series of designs with a part missing.
Participants have to select the correct part to complete the designs from a number of options
printed beneath. The SPMs have been shown to provide a valid measure of intelligence
independent of language abilities and formal schooling (Raven, 2000). A 20-min time limit
was used, for which norms are available for French adolescents (Raven et al., 1998).
Participants scoring lower than 30 (5th percentile) were excluded from the study. This
exclusion criterion was used as an estimator for possible intellectual disability.
K-SADS

The presence of CD was assessed using a validated semistructured diagnostic interview,
the K-SADS-PL (Chambers et al., 1985). This reliable interview evaluates current and past
episodes of psychopathology in children and adolescents (including CD), according to theDSM- (4th ed.; DSM-IV; APA, 1994) criteria. Due to time restrictions, we were not able toconduct the complete K-SADS-PL in all participants. The CD part was however administered systematically as CD was used as a control variable.
Data Analysis

As measurement points are nested within individuals, data were analyzed using hierarchical linear modeling (HLM), namely, a two-level model with perceived staff anger (PSAng) or
distress (PSDis) as dependent variables. The variance in PSAng or PSDis was predicted on
1.
2.

the intraindividual level (Level 1) from staff-reported anger (SRAng) or distress (SRDis),and in exploratory analyses by negative affect, misbehavior, and interpersonal conflicts withstaff, all entered as grand-mean-centered predictors.
the interindividual level (Level 2) from CU traits, entered as a grand-mean-centeredpredictor.
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Equation 1 (using anger as an example) presents the most complex model tested.
Level 1: PSAng = γ0 + γ1 SRAng + γ2 Negative Affect + γ3 Misbehavior + γ4 Conflicts +E
Level 2 : γ 0 = β00 + β01RPlace + β02 CD + β03CU Traits + R0
γ1 = β10 + β11RPlace + β12 CD + β13CU Traits + R1
γ 2 = β20 + β21RPlace + β22 CD + β23CU Traits + R2
γ 3 = β30 + β31RPlace + β32 CD + β33CU Traits + R3
γ 4 = β40 + β41RPlace + β42 CD + β43CU Traits + R4

(1)

An identical model was tested separately for distress. To increase power, the final models
were estimated including only the significant predictors. Effect sizes (r2) were estimated bycomputing the variance in the outcome variable explained by each predictor separately after
controlling for staff-reported emotions.
Level 2We always controlled for CD and recruitment place (RPlace), entered as Level 2 predictors (seeEquation 1). CD had no significant effect outside adolescents with this diagnosis had a weakerassociation between misbehavior and PSAng (β32 = −.26, p = .024). We will therefore only present
results on CU traits. We also conducted exploratory analyses with the interaction between CD and
CU traits as an additional Level 2 predictor, along with RPlace, CD, and CU. As its effect wasconsistently nonsignificant, we did not include the interaction term in the final model.
In this model, β00 reflects the average level of PSAng (higher values corresponding tohigher intensity). β10 reflects the momentary association of PSAng with SRAng (more positive values indicating better emotion recognition), β20 with negative affect (positive values
indicating that, at times where they experience more negative affect, adolescents perceive
more anger in staff members), β30 with misbehavior, and β40 with conflicts.
Level 1

Level 1 parameters were further predicted from CU traits. Predicting the intercept γ0, a
positive β01 indicates that higher CU traits are associated with higher PSAng. Predicting theslopes γ1 to γ4, a positive β13 indicates that higher CU traits are associated with a more positive momentary association between PSAng and SRAng (or negative affect for β23, misbehavior for β33, and conflicts for β43).
Results
Descriptive Results

As all variables were measured on a 0 to 100 scale, adolescents perceived staff members asquite low on anger (β00 = 29.81, SE = 2.28) and distress (β00 = 27.42, SE = 1.93), on average
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across the 8 days of EMA; a core part of the variance in these variables was found on theintraindividual level (57% for PSAng and 63% for PSDis), indicating that moment-tomoment variations were more important than interindividual differences. On average acrossthe EMA period, staff members also reported experiencing rather low levels of anger(β00 = 30.43, SE = 2.25) and distress (β00 = 25.31, SE = 2.42) toward these adolescents,
again with an important part of the variance found on the intraindividual level (71% for
SRAng and 42% for SRDis). With regard to themselves, adolescents reported a moderateintensity of negative affect (β00 = 26.75, SE = 2.99), misbehaviors (β00 = 26.75, SE = 3.14),
and interpersonal conflicts with staff members (β00 = 29.33, SE = 3.09).
Effect of CU Traits

As expected, adolescents with higher CU traits reported far more daily misbehavior (β03= 13.91, p = .003, r2 = .21) in terms of both aggression (β03 = 13.49, p = .015, r2 = .18) andrule-breaking (β03 = 14.75, p = .004, r2 = .18). They also reported significantly more interpersonal conflicts with adults (β03 = 9.66, p = .037, r2 = .09). Staff members reported experiencing significantly more distress (β03 = 14.95, p = .001, r2 = .20) toward these challenging
adolescents. After controlling for staff-reported emotions, adolescents with higher CU traits
did perceive staff members as significantly and substantially more angry (β03 = 14.22,
p < .001, r2 = .08) and distressed (β03 = 10.86, p < .027, r2 = .15).
Emotion Recognition: Correlations Between Staff Reports And Adolescents
Perceptions

Overall, adolescents showed good empathic accuracy: They inferred more anger when
staff reported more anger (β10 = .08, p = .021, r2 = .09) and more distress when staff reported
more distress (β10 = .21, p < .001, r2 = .22). Results on accuracy are presented in Table 2,
along with context variables (see below) and effect of CU traits.
Moderating Effects of CU Traits

We observed no moderation effect of CU traits on empathic accuracy, indicating that theperceptions of high CU adolescents were as strongly associated with staff reports as thoseof their low CU counterparts.
Context Variables Associated With Adolescents’ Perceptions Of Staff Emotions

All adolescents perceived more anger and distress in staff members at times where theyreported more interpersonal conflicts with them (β40 = .27, p = .001, r2 = .09; β40 = .16, p =.004, r2 = .12, respectively). Moreover, all adolescents perceived more anger in staff whenexperiencing more negative affect themselves (β20 = .43, p = .001, r2 = .15) and more distress in staff when being more disruptive (β30 = .30, p = .001, r2 = .22; see Table 2).
Moderating Effects of CU Traits

We observed no moderating effect of CU traits regarding context variables associatedwith PSDis. However, higher CU traits predicted a significantly stronger association
between PSAng and misbehavior (β33 = .23, p = .030, r2 = .08; see Figure 2 and Table 3). In
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De Ridder et al. / EMPATHY AND CU TRAITS: EMA OF EMOTION RECOGNITION 663
Table 2: Multilevel Regression Analyses of Adolescents’ PSAng and PSDis: Accuracy, Context Variables, and CU Traits
Dependent Variable
Predictor
Level 1SRAng
SRDis
Negative affectMisbehavior
Conflicts

PSAng

PSDis

.08*
.21**
.09
.30**
.16**

.43**
.07
.27**
Intercept (Controlling for SR Emotions)β03

Level 2CU

14.22**

10.86*

Note. PSAng = Perceived Staff Anger; PSDis = Perceived Staff Distress; CU = callous-unemotional; SRAng =Staff-Reported Anger; SRDis = Staff-Reported Distress.
*p < .05. **p < .01.

Figure 2:Moderating Effect of CU Traits on the Moment-to-Moment Association Between Rule-Breaking
and PSAng
Note. CU = callous-unemotional; PSAng = Perceived Staff Anger.
*p < .01.

other terms, high CU adolescents perceived more anger in staff members when they weremisbehaving, in particular when they broke the rules (β33 = .22, p = .009, r2 = .15), while theeffect did not reach significance regarding aggressive behavior (β33 = .17, p = .163, r2 = .06).
Discussion

This novel application of EMA confirmed that adolescents with high CU traits also perform in the normal range for anger recognition in ecologically valid situations. Interestingly,
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Table 3: Multilevel Regression Analyses of Adolescents’ Perceived Staff Anger: Moderating Effects of
Callous-Unemotional Trait
Level 1 Parameters
Negative affectMisbehavior
Conflicts
SRAng

Estimate

SE

T

df

Significance

−.40
.23
.14
.11

0.24
0.10
0.16
0.11

−1.65
2.23
0.92
0.99

45
45
45
45

.10
.03
.36
.33

Note. Perceived staff anger: Dependent variable; callous-unemotional traits: Level 2 predictor; SRAng = staffreported anger.

our data revealed that high CU adolescents were also unexpectedly as accurate as low CU
adolescents in inferring distress in staff members, and notably overestimated the generalintensity of both anger and distress. They specifically inferred more anger in others when
they were engaged in disruptive actions.
Our findings corroborated the normal recognition of anger (Dawel et al., 2012) observedin computerized tasks in adolescents with high CU traits, positing this expression as beinga strong signal well identified in both laboratory and ecological settings. Howland andRafaeli (2010) suggested that inferring anger accurately may involve mechanisms similar
to those used in detecting positive emotions, as anger may be strongly tied to the behavioral
activation system. In contrast, other mechanisms may be involved in studying the empathic
accuracy for negatively activated emotions, which include fear and sadness as well as stress,
worries, and destabilization (Howland & Rafaeli, 2010). This understanding supports our
choice to contrast anger and distress recognition, even when the latter only partially overlaps prior distress operationalizations. High CU adolescents’ distress recognition in everyday life interactions, in stark contrast to computerized task results, did not show the expected
impairment. According to recent neurobehavioral studies, individuals with psychopathic
traits are indeed able to display normal responses to affective information (e.g., others’ distress) but may not award it the necessary attentional resources unless the task or goal
requires it (Larson et al., 2013; Newman & Baskin-Sommers, 2011). Despite sample differences (adults with psychopathic traits vs. adolescents with CU traits), our results could beinterpreted in this light. Indeed, answering 4 times a day questions explicitly referring toothers’ emotional state may have increased the relevance of emotion identification and inturn the mobilization of attentional resources for this purpose, which might have ultimately
led to a normal perception of distress.
Another key finding of the present study is that, contrary to our expectations and in contrast to their low CU peers, high CU adolescents perceived staff members as considerably
more angry and distressed in general, and in particular inferred more anger when they weremisbehaving. This finding may reflect their (too heavy) reliance on their intact cognitive
empathy skills. In fact, high CU adolescents generally report a high level of misbehavior
and interpersonal conflicts (see the review Munoz & Frick, 2012), which may lead them tocognitively expect intense negative feelings in adults confronted to such a challenging anddisruptive behavior. This proposition is comparable with Coyne’s suggestion that repeatedexperiences of interpersonal rejection lead depressed individuals to develop a heightened
sensitivity to negative interpersonal information (Coyne, 1976). High CU adolescents’
overestimation of staff’s negative emotions, in particular during misbehavior, could also
result from an excessive reliance on their intact cognitive empathy skills, in compensation
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for their impaired affective empathy. This theoretical interpretation has been confirmed bya recent functional neuroimaging study: In a facial emotion recognition task, high CU individuals showed a reduced responsiveness of the amygdala along with an extended brain
activation in areas related to compensatory cognitive processes (Contreras-Rodríguez et al.,2014). Such compensation processes may be particularly mobilized in daily life interactions
with familiar others where contextual cues abound, in contrast to computerized emotion
recognition tasks which typically include very little context information. Evaluating affective sensitivity is complementary to examining empathic accuracy, the latter being morecomparable with prior lab studies. Whereas examining accuracy eludes the incidence ofunder- or overestimating others’ emotions, evaluating sensitivity offers these possibilities.
Another core difference between real-life interactions and computerized tasks is the predominance of the recognition of mixed sensory cues combined with interpersonal information, one’s behavior and emotions in everyday life, while computerized emotion recognition
tasks mostly use pure emotions. Mixed cues, as all ambiguous stimuli, are particularly susceptible to a confirmation bias typical of the human mind, in which the perception is distorted toward what is expected (Fisher, 1968). In high CU individuals, such common
confirmation bias may be intensified by their overselective attention, an attention deficit inwhich one only attends to restricted aspects of complex stimuli. Overselective attention was
first described in children with autism (Lovaas, Schreibman, Koegel, & Rehm, 1971) andhas also been observed in individuals with psychopathic traits (Hiatt, Schmitt, & Newman,2004). This may have increased the focus of our high CU adolescents on negative emotion
cues in staff members during misbehavior, thus contributing to their overestimation of anger
and distress. Yet, these explanations need to be confirmed in a future study using ecologicalstimuli, which would include mixed emotions and contextual cues in relevant situations.
Limitations

This novel ecological attempt to investigate the recognition of distress and anger by measuring empathic accuracy in natural situations nevertheless suffers from some limitations.
First, the small number of staff reports and their imprecise synchronization with adolescents’ reports could have restricted the power of our analyses of momentary associations
between staff emotions and adolescents’ perceptions. The present results would need to be
confirmed and refined with an EMA design ensuring optimal synchronization between staff
and adolescent data to reduce the risk of Type II error. This type of design would also enable
the assessment of causal patterns between adolescents’ perceptions, behavior, and emotions, which was not feasible in the current study given the irregular and often too lengthy
intervals between staff reports.
Second, the present study lacks objective measures of staff’s expressed emotions.
Therefore, we cannot rule out the possibility that staff members did express more intenseanger and distress when interacting with high CU adolescents but provided attenuated reportsof these emotions due to social desirability. The fact that staff members did acknowledge
feeling nonsignificantly angrier and significantly more distressed about these challenging
adolescents is not suggestive of strong social desirability effects. In addition, the only study
to date that investigated whether antisocial adolescents with high CU traits would elicit different emotional expressions compared with their low CU counterparts in their caregivers
during an emotion communication task did not find such effects (Pasalich et al., 2012). Thisabsence of effect contrasting with our observations may be due to the nonconfronting task
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used by Pasalich and colleagues (i.e., a 10-min family discussion about past shared happyand sad moments), while we focused on real-life interactions over 8 days between institutionalized adolescents and staff members, which involves regular confrontation.
Third, the type of EMA design used in the current study measured empathic accuracy but
did not explicitly measure empathy. Further research including the direct assessment of thisconstruct is therefore necessary and should moreover differentiate between its affective andcognitive components, while maximizing both internal and ecological validity. Finally, alarger sample would be required to investigate gender differences.
Conclusion

To the best of our knowledge, this is the first study examining the transferability to daily
life interactions of computerized task findings regarding the impaired distress recognitionin adolescents with high CU traits. The novelty of this study lies in using EMA to measureempathic accuracy in this particular subgroup of adolescents, with unexpected results, albeit
not necessarily contradicting the laboratory findings. When asked to repeatedly report on
staff members’ emotions, high CU adolescents were as accurate as their low CU peers in
identifying anger and distress, suggesting that the EMA procedure helped them mobilize theattentional resources necessary for empathic accuracy toward the emotions in others.
However, they substantially overestimated the intensity of negative emotions in familiar
others during everyday interactions, possibly due to their overselective attention and/or
their excessive reliance on cognitive empathy. This overestimation could undermine thedevelopment of supportive relationships and thereby contribute to maintain antisocial
behavior, particularly in sight of their reduced sensitivity to punishment and strong reward
orientation (Blair, Mitchell, Leonard, et al., 2004). These processes may also partiallyexplain the observed limited influence of parenting quality on high CU children’s behavior(Frick & Viding, 2009).
Taken together, these findings posit the overestimation of negative emotions’ intensity as a
key therapeutic target in high CU adolescents. This view is supported by recent evidence
that empathic emotion recognition training across all emotions and modalities can significantly improve affective empathy and is ultimately effective for reducing problematic
behaviors in children with high CU traits (Dadds, Cauchi, Wimalaweera, Hawes, & Brennan,2012).
Notes
1. Revisiting the role of impulsivity in conduct disorder: An ecological study of disruptive behaviors in incarcerated
adolescents supported by the Swiss National Science Foundation (#100014-130553) and conducted under the supervision of
the second author.
2. Only the Inventory of Callous-Unemotional Traits (ICU; Frick, 2004) provides a measure for CU traits. However, theUnemotional scale of the ICU, which may be particularly relevant for our study, has repeatedly shown poor internal consistency and criterion validity (Pihet et al., 2014). Correlations between the YPI-Int and YPI-Aff scales and the ICU total scoreare large (Pihet, Etter, et al., 2015).

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Jill De Ridder is a PhD student at the Department of Psychology in the University of Fribourg. Her research focuses on facial
expression recognition in juvenile offenders with callous-unemotional traits. At the Centre of Mental Health De Kempen,
Belgium, she coheads a project on the complexity of forensic psychiatric patients’ reintegration in society.
Sandrine Pihet is a full professor at the School of Health in the University of Applied Sciences and Arts Fribourg, where sheleads the mental health research group. Her research focuses on the daily life experience of individuals living with a mental
disorder and their informal caregivers, and on the impact of psychoeducative interventions on this experience.
Maya Suter is a PhD student at the Institute of Psychology in the University of Lausanne. Her research focuses on implicit
components involved in aggressive and transgressive behavior in adolescence.
Roberto Caldara is a full professor of cognitive neuroscience at the Department of Psychology in the University of Fribourg,
where he heads the Eye and Brain Mapping Laboratory` (iBMLab). His research focuses on social, affective, and visual neuroscience, with a particular emphasis on the role of eye movements in perceptual and decisional processes, as well as theircoding in the human brain.

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