Emotion Recognition Deficits in Children and Adolescents with Psychopathic Traits: A Systematic Review

Vol.:(0123456789) Clinical Child and Family Psychology Review (2024) 27:165–219 https://doi.org/10.1007/s10567-023-00466-z Emotion Recognition Deficits inChildren andAdolescents withPsychopathic Traits: ASystematic Review BeatrizDíaz‑Vázquez1 · LauraLópez‑Romero1 · EstrellaRomero1 Accepted: 3 December 2023 / Published online: 19 January 2024 © The Author(s) 2024 Abstract Children and adolescents with psychopathic traits show deficits in emotion recognition, but there is no consensus as to the extent of their generalizability or about the variables that may be moderating the process. The present Systematic Review brings together the existing scientific corpus on the subject and attempts to answer these questions through an exhaustive review of the existing literature according to PRISMA 2020 statement. Results confirmed the existence of pervasive deficits in emotion recognition and, more specifically, on distress emotions (e.g., fear), a deficit that transcends all modalities of emotion presentation and all emotional stimuli used. Moreover, they supported the key role of attention to relevant areas that provide emotional cues (e.g., eye-region) and point out differences according to the presence of disruptive behavior and based on the psychopathy dimension examined. This evidence could advance the current knowledge on developmental models of psychopathic traits. Yet, homogenization of the conditions of research in this area should be prioritized to be able to draw more robust and generalizable conclusions. Keywords Emotion recognition· Psychopathic traits· Childhood· Adolescence· Attention bias Introduction Psychopathic personality, defined as a constellation of interpersonal (e.g., superficial charm, grandiosity), affective (lack of remorse, callousness) behavioral/lifestyle (e.g., irresponsibility, impulsivity) and arguably antisocial traits (e.g., poor behavioral control, early behavioral problems) (Hare & Neumann, 2008), constitute one the best predictors of severe, chronic and difficult-to-treat antisocial behavior, with an important economic and social burden (Reidy etal., 2015). In an effort to gain deeper insights into the emergence of the most serious, aggressive and persistent pattern of child and youth conduct problems (CP), the study of psychopathic personality has been downward extended to early developmental stages. This line of research has allowed to collect extensive evidence on usefulness and viability of psychopathic traits across early childhood (i.e., preschool years; e.g., Waller & Hyde, 2018), middle childhood (i.e., elementary school years; e.g., Gorin etal., 2019) and adolescence (e.g., Lynam etal., 2009). Previous research conducted in young samples was mainly focused on the affective dimensions of psychopathic traits (i.e., CU traits), largely examined as a putative precursor of adult psychopathy (Hyde & Dotterer, 2022). In this regard, an extensive line of research has supported CU traits as a potential identifier of an etiological and clinically distinctive subgroup of problematic children1 (see Frick etal., 2014). As a result, a new specifier, largely based on the CU conceptualization, has been added for CD in the latest edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association—APA, 2013; i.e., “with limited prosocial emotions”), and the International Classification of Diseases (ICD-11; World Health Organization—WHO, 2019; i.e., “limited vs. prosocial emotions”). * Laura López-Romero [email protected] Beatriz Díaz-Vázquez [email protected] Estrella Romero estrella.romer[email protected] 1 Department ofClinical Psychology andPsychobiology, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Campus Vida, SantiagodeCompostela, Spain 1 When no other clarification is made, the terms “children” or “childhood” overall refer to both early (i.e., preschool) and middle childhood (i.e., elementary school), including children up to age 12. 166 Clinical Child and Family Psychology Review (2024) 27:165–219 Regardless the advances achieved from the CU conceptualization, the study of psychopathic personality in childhood and adolescence has been enriched from a multidimensional perspective, involving a constellation of interpersonal [grandiose-manipulative (GM)], affective (CU) and behavioral traits [impulsive-need of stimulation (INS)]. So far, compelling evidence on early identification, relative stability and predictive value of the psychopathic constellation has been consistently provided (Salekin etal., 2018). Beyond old and current debates about which dimension(s) should be considered in developmental models of CP (see Frick, 2022; Salekin, 2022), additional support for considering interpersonal (GM) and behavioral traits (INS)2 when defining and studying psychopathic personality has been increasingly collected (see Salekin, 2017, 2022). Hence, some recent studies have reinforced psychopathic traits, conceptualized as a multidimensional construct, as a relevant predictor in the development of serious CP and other forms of child and adolescent maladjustment (e.g., Bergstrøm & Farrington, 2022; Burke etal., 2022; Colins etal., 2022; Fanti etal., 2018; López-Romero etal., 2021, 2022). A critical question in the field is, therefore, whether including other dimensions of psychopathy may increase our knowledge about the construct, particularly clarifying how all affective, interpersonal, and behavioral dimensions develop, and which etiological processes might be underlying. If psychopathic personality indeed identifies a subgroup of children and adolescents with more serious and persistent CP, disentangling its potential distinctive etiological pathways will enrich developmental models of both psychopathic traits and disruptive behavior. Unraveling theDevelopmental Basis ofPsychopathic Traits: The Role ofEmotion Recognition Probably due to the prominence of the affective traits in the conceptualization and manifestation of psychopathic personality, affective impairments have been largely researched in relation to psychopathic traits at the neurobiological, cognitive, emotional and behavioral levels (Blair, 2013). Developmental models of psychopathy have commonly pointed to an amygdala dysfunction (e.g., Blair, 2003a), which is involved in emotion recognition (Phelps & LeDoux, 2005), a process that also seems to be affected in individuals high on psychopathic traits (Dawel etal., 2012). Emotion recognition refers to the ability to attribute emotional states in others, based on the identification of emotional cues relevant for socialization. Accurately processing emotional expressions, particularly facial expressions, is critical for everyday functioning as it facilitates appropriate interpersonal communication (Marsh & Blair, 2008), promotes shared affective experience (Hinnant & O’Brien, 2007), and motivates prosocial behavior (Marshall & Marshall, 2011). Conversely, deficits in emotion recognition may lead to dysfunctional interpersonal relationships and social adjustment (Kyranides etal., 2020), particularly when deficits in recognition affect distress emotions (e.g., fear, sadness). Hence, failing to recognize others’ distress may hinder the development of empathic concern through a process that would imply the absence of discomfort that typically follows wrong behaviors (e.g., guilt). This, in turn, would restrain the inhibition of those behaviors that may cause distress in others (e.g., Kochanska etal., 2010). Accordingly, deficits in emotion recognition have been suggested as a potential link between psychopathic traits and different forms of behavioral maladjustment (e.g., CP, antisocial behavior) commonly observed in high psychopathic individuals (Frick etal., 2014; Salekin, 2017). Whether emotion recognition deficits are specific to distress emotions or reflect a more pervasive emotional impairment has been a question over debate. From one perspective, Blair (1995, 2006) suggested that psychopathy would be marked by specific deficits in the recognition of both fear and sadness. This would result in the no-experience of aversion after a behavior that may cause distress in others, allowing individuals with psychopathic traits to behave in a self-gratifying and goal-directed manner, without the negative consequence of feeling guilty and bad. Overall, these deficits would partially explain the callous, unremorseful and deceitful behavior in psychopathic personality. From an alternative approach, Dadds etal. (e.g., Dadds etal., 2006, 2008) have proposed a dysfunction on attentional mechanisms that would underlie emotion recognition deficits. More specifically, attentional deficits to socially relevant cues (i.e., the eyes, with some new evidence also for the mouth; Demetriou & Fanti, 2022), would serve as the basis for the emotion recognition deficits observed in high psychopathic individuals (Dadds etal., 2011, 2014). From this perspective, impairments in emotion recognition would be more pervasive rather than specific and would derive a more generalized deficit in socio-emotional functioning (Dawel etal., 2012). Both theoretical approaches found support in previous meta-analytic studies, which mainly examined results from adult populations. The first documented meta-analysis on the topic provided support for a specific deficit in recognizing fear and, to a lesser extent, sadness from facial expressions 2 These dimensions, particularly the interpersonal and behavioral, have been differently labelled in previous literature as it is the case of “grandiose-deceitful” for the interpersonal (Andershed, etal., 2002; Colins etal., 2014) or “daring-impulsive” (Salekin & Hare, 2016), “impulsive-irresponsible” (Andershed etal., 2002) for the behavioral dimensions. To be consistent across the study, we have assumed GM, CU and INS acronyms, as defined in the main text, to refer to interpersonal, affective and behavioral psychopathic traits respectively. 167Clinical Child and Family Psychology Review (2024) 27:165–219 in antisocial individuals, with no moderation of psychopathic traits (Marsh & Blair, 2008). Later studies reported a more pervasive deficit, with impairments in the recognition of multiple emotions (Wilson etal., 2011), also when more than facial cues (i.e., vocal, postural) were examined (Dawel etal., 2012). From these meta-analytic studies, only Dawel etal. (2012) distinguished between adult and young samples—including both middle-school children and adolescents, who showed deficits for all emotions, and particularly anger, fear and sadness, with greater effects for fear. Yet, most analyses were conducted for the total sample, with most adults from the forensic setting, and most children/adolescents from community or clinical settings. No additional distinction was made between child and adolescent samples, and no other relevant moderators (e.g., gender, age, sample type, the presence -or notof concurrent disruptive behavior) were examined. Emotion Recognition andPsychopathic Traits inChildhood andAdolescence The multiple studies published so far in child and adolescent samples have yielded, to date, mixed results, probably due to a variety of designs, sampling procedures and methods that makes it difficult to extract firm conclusions (Northam & Dadds, 2020). Mirroring results from adult samples (e.g., Brislin & Patrick, 2019; Demetrioff etal., 2017; Kyranides etal., 2020), some studies provided additional evidence for the specific deficit in the recognition of fear (e.g., Fairchild etal., 2009), and other distress emotions, including anger or sadness (e.g., Muñoz, 2009; Powell etal., 2023). Others, in contrast, have found more pervasive deficits across different emotions including disgust or happiness (e.g., Kahn etal., 2017). There is also opposite evidence, with some studies showing increased recognition for distress emotions (e.g., Schwenck etal., 2014), or even no association between psychopathic traits and emotion recognition (e.g., MartinKey etal., 2020). Understanding the diversity of results, and their potential causes and explanations, is of uttermost importance to clarify how psychopathic traits develop, and which mechanisms may boost or restrain their negative consequences. In this regard, applied implications from this knowledge may differ depending on whether emotion recognition deficits indeed exist, whether they are specific to one or two emotions (e.g., fear or sadness), or whether they reflect a more pervasive impairment in socioemotional functioning and the interpretation of others emotional states. Related with this last hypothesis, studies examining attention deficits related to emotion recognition also yielded mixed results, particularly when using eye-tracker methodologies (Demetriou & Fanti, 2022). Thus, even though there was evidence of reduced attention to other’s eyes in children and adolescents high on CU traits (e.g., Dadds etal., 2006, 2008; Martin-Key etal., 2018), some studies also revealed no association between CU traits and attention to the eyes (e.g., Bedford etal., 2017; Muñoz etal., 2021). In addition, the inclusion of other relevant face areas, such as the mouth, has made these results even more complex, with some studies suggesting that the deficits are more specific to the eyeregion (e.g., Demetriou & Fanti, 2022) whilst others suggest that emotions linked to eye-region deficits (i.e., fear and anger) could differ from those observed in the mouth-region (i.e., sadness) (Hartmann & Schwenck, 2020). The Present Study The pattern of mixed results obtained in previous research raises the need to systematically organize the current knowledge, providing compelling evidence about well-established findings, and identifying the gaps and inconsistencies that should be addressed in future research. This systematic review is devoted to accurately examining the association between psychopathic traits, addressing all its dimensions, and emotion recognition deficits in young samples, including early childhood, middle-childhood, and adolescence (mean age up to 18years old). As it might be expected, CU traits have derived most of the research aimed at understanding the aforementioned impairments in emotion recognition and processing (see Northam & Dadds, 2020). However, as evidence has been collected on the multidimensionality of the construct (Salekin, 2017, 2022) studies addressing other psychopathy dimensions would be also considered. This may shed new light on the nature of emotion recognition deficits in psychopathic personality, leading to disentangle some of its mechanistic trends. It would also help to clarify whether previous findings on CU traits can be extrapolated to other psychopathy dimensions, whether there might be specific deficits for specific dimensions or whether a combination of high interpersonal, affective, and behavioral psychopathic traits may identify a distinctive etiological subgroup. All studies published to date have been taken into account, with no time restrictions imposed. Even though there are some previous meta-analyses on this topic, they have been published more than 10years ago, two of them considered together young and adult samples (Marsh & Blair, 2008; Wilson etal., 2011), and one distinguished between midchild/adolescents and adult samples (Dawel etal., 2012). However, the study from Dawel etal. (2012) did not cover any study in preschool samples, did not distinguish between children and adolescents, and did not account for any other potential variables relevant to understand the association between emotion recognition and psychopathic traits in youngsters, such as the sample type or the co-occurrence of CP (Dawel etal., 2012). Therefore, all studies published up to 2022 were examined, and several methodological variables and sample characteristics of studies were compared in 168 Clinical Child and Family Psychology Review (2024) 27:165–219 an attempt to account for the discrepancies observed in previous research. Due to the importance that attention deficits may have in the emotion recognition impairments observed in individuals high on psychopathic traits (Dadds etal., 2006), and with the aim to provide additional clarification in the aforementioned theoretical approaches, studies examining attention biases in the context of emotion recognition and psychopathic personality were also included. More specifically, the present systematic review aims to respond to the following questions: 1. Are there emotion recognition deficits in children and adolescents with different levels of psychopathic traits? 2. Are emotion recognition deficits related to specific emotions (e.g., fear, sadness) or do they respond to a more pervasive emotional impairment? 3. Are there specific deficits associated to different psychopathy dimensions? 4. Are emotion recognition deficits specifically related with attention biases to relevant areas showing emotional and/ or distress cues? (e.g., eye region, mouth region) 5. Are there specific differences according to age (i.e., childhood versus adolescence), gender (i.e., boys, girls), sample type (i.e., community-based, forensic, clinicalreferred) and the co-occurrence of different forms of disruptive behavior including CP, conduct disorder (CD) and oppositional defiant disorder (ODD)? In accordance with previous literature, we anticipate (a) an association between emotion recognition and psychopathic traits; (b) the presence of more pervasive rather than specific deficits; (c) the influence of the different dimensions of psychopathy, (d) a relevant role of attention biases in emotion recognition deficits; and (e) the moderating role of socio-demographic variables, including sex and age, as well as the existence of clinical diagnoses (CD, ODD) or subclinical symptoms (CP). In sum, this review is aimed to organize the available evidence in this field, by providing a comprehensive guide of studies and by addressing multiple sources of variability. Ultimately, this review is expected to identify shared conclusions across studies, and to delineate some guidelines to homogenize future protocols and favor additional replication. Method Systematic Search Strategy The present review was performed according to the actualized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page etal., 2021). The PRISMA Checklist is provided in TableS1, available online. A protocol for this study was developed and registered on PROSPERO (Registration number: CRD42021276769). A search strategy (available on Prospero and Supplement X) was developed to cover the key elements of this systematic review, including (1) psychopathic traits (callous* unemotion* or CU or psychopathy or psychopathic), (2) emotion recognition (emotion* recognition or emotion* process* or emotion* identification or eye gaze or eye track* or eye fix* or facial emotion* or emotion* attent*), and (3) the developmental period (child* or adolesc*). Note that emotion processing was also included in the search strategy since some studies used indistinctively emotion recognition and processing to examine specific deficits in the recognition of basic emotions. The search to identify relevant literature was conducted on September 22nd, 2021 on PsycInfo, Scopus, PubMed and Web of Science (WOS) databases. An update of the systematic search was conducted on December 23, 2022 in order to include all published studies up to 2022. The same search terms were applied across all databases with adjustments made to accommodate the specific requirements of the search sites (see Table1). We did not impose a start data as most studies in this area have been published in the past 20years, and it was our intention to provide a complete picture of the state of the art. Publications were restricted to peer review journal articles to ensure a minimum threshold for quality. In addition to the electronic search, the reference lists of the included studies were also checked to identify other potentially eligible studies. Eligibility Criteria This review aimed to include all published studies, in English or Spanish, that examined the relationship between psychopathic traits and emotion recognition in children and adolescents (mean age up to 18). Studies including participants aged ≥ 18 were included as long as they were based on a well-established adolescent sample (e.g., high-school students; forensic juvenile samples that in some contexts may involve participants up to age 21). The review included cross-sectional and longitudinal studies, with both correlational and/or between-groups designs. Specific inclusion criteria for studies in this review were: 1. Studies should include a validated measure of psychopathic traits, as well as a valid recognition measure (lab task), with normed or validated stimuli (i.e., facial, vocal, postural expression) for at least one or more basic emotions (e.g., anger, disgust, fear, happiness, sadness and surprise; Ekman, 1992). 2. Samples might be community, at risk, forensic or clinical, or any combination thereof. Forensic samples are 169Clinical Child and Family Psychology Review (2024) 27:165–219 defined as populations that have been in contact with the juvenile justice system; clinical samples include participants that have been diagnosed with some mental disorder, particularly CD or ODD; at risk samples include participants from disadvantaged environments, as well as those with high levels of CP that have not yet been in contact with juvenile justice systems not either have received a mental disorder diagnosis, and community samples include participants who do not meet criteria for forensic, clinical or at risk samples. 3. Studies defining psychopathic traits as a dichotomous variable (e.g., high CU traits), should also include a control group. The control group may be a community or a matched forensic, at risk or clinical sample with distinctive levels of psychopathic traits (e.g., low CU traits). 4. Studies must be full-text papers published in peerreviewed journals in both Spanish and English. Studies were excluded if they were based on adult samples (mean age < 18), or whether they explicitly included participants with known cognitive impairments that are likely to influence emotion recognition, including brain injuries, neurodevelopmental disorders (e.g., autism spectrum disorder; ASD) or current substance abuse. Studies including between-groups designs with participants meeting criteria for one or more of the aforementioned impairments were retained as long as it was possible to extract specific data for participants with psychopathic traits who do not meet criteria for those impairments. Studies exclusively based on populations with an attention deficit hyperactivity disorder (ADHD) diagnosis were also excluded. Yet, considering the high co-occurrence rates between CP and ADHD (Hudec & Mikami, 2017), studies were retained if they were based on populations with CP, who may also meet criteria for CD or ODD, even though they reported the inclusion of participants with comorbid ADHD (k = 17). To gain clarity about the potential influence of ADHD symptoms in emotion recognition deficits related to psychopathic traits, the percentage of participants with ADHD will be extracted, and information about control analysis (or the absence of) will be explicitly provided. Study Identification andSelection Title and abstract were screened by two researchers, and excluded if they did not meet the inclusion criteria. Both researchers were blinded to each other’s decisions and the first study selection was put in common once the study selection phase was finished. RefWorks was independently used by both researchers as a reference manager tool. Of the 3215 abstracts screened, 74 were included for full-text review, which was also performed by two researchers who worked independently. If studies met the inclusion criteria, they were finally included in the review. If they violated some of the eligibility assumptions, they were classified based on the reason of exclusion (e.g., adult samples, emotion processing instead of emotion recognition, no measures of psychopathic traits, no lab task for emotion recognition, participants with neurodevelopmental disabilities). At the full-text level, articles were excluded if they: Included participants with a mean age that exceed the 18years of age (k = 3), measured emotion recognition through questionnaires or scenarios with additional contextual cues that require emotional inferences (k = 3), examined complex instead of basic emotions (k = 1), emotion recognition was computed as a function of a global measure (e.g., moral reasoning, emotional understanding) (k = 5), or it was restricted to inform about owns’ emotional state in response to emotional content (e.g., emotional responsiveness) (k = 2), emotion recognition deficits were not (exclusively) linked to psychopathic traits (k = 4), assessed emotional processing instead of emotion recognition (k = 4), and there was evidence of substance abuse Table 1 Systematic search strategy a #= AND b Results based on the updated systematic search, conducted on December 23, 2022 Database PsycInfo Scopus Pubmed WOS Keywords L1. (callous* unemotion* or CU or psychopathy or psychopathic) #a L2. (emotion* recognition or emotion* process* or emotion* identification or eye gaze or eye track* or eye fix* or facial emotion* or emotion* attent*) # L3. (child* or adolesc*) Fields Any field (ALL) TITLE-ABS-KEY All fields All fields Resultsb939 321 1044 1273 Filters 1. Language: English, Spanish 2. Age: 0–18 3. Peer Review 4. Humans (male, female, inpatient, outpatient) 1. Language: English 1. Language: English, Spanish 2. Humans 3. Age: 0–18 1. Language: English, Spanish 170 Clinical Child and Family Psychology Review (2024) 27:165–219 (k = 2). If the studies met the inclusion criteria but sufficient data was not available to extract the main results, data were directly requested from the authors by email. At all stages of the review process, disagreements were solved by discussion and consensus and, when needed, a third researcher settled the unresolved disagreements. The inter-rater agreement Cohen’s kappa was used to compare agreement between the researchers regarding the decision to include or exclude the eligible studies, and interpreted as ≤ 0, no agreement, 0.01–0.20, none to slight, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 substantial, 0.81—1.00 almost perfect agreement (McHugh, 2012). Quality Assessment Two independent reviewers assessed the quality of included studies using the Appraisal Tool for Cross-Sectional Studies (AXIS) (Downes etal., 2016), which contains 20 questions regarding introduction, methods, results and discussion of each study. Each question could be answered with “yes” (1 point) or “no”/“don’t know” (0 points). Longitudinal studies were assessed via the Critical Appraisal Skills Program (CASP), a 12-question checklist that addresses different aspects concerning the objectives, sample recruitment, measurement, attrition, results and implications. Disagreements on studies’ quality assessment were solved by consensus. Data Extraction andSynthesis Relevant data for each included article were added to an extraction sheet developed for this review and refined when necessary. Data extraction included participants characteristics (N [females], sample type and age range [mean age]), psychopathic and/or CU traits measure and informant, emotion recognition task specificities (i.e., type of stimuli, emotions assessed and measurement outcome), and main results specifically related with the objectives of this review. For correlational studies we extracted results focused on the relationship between psychopathic traits and emotion recognition, whilst in between-group designs we focused on results obtained in comparisons between the high psychopathic and the comparison groups. Between-group designs where psychopathic traits were examined as potential covariates were also considered as long as it was possible to extract specific data on the effect of psychopathic traits on emotion recognition. For studies assessing attention biases, information about the Areas of interest (AOI) and the measurement outcome was also extracted. Studies were organized by their focus on specific CU traits (k = 26) (Table2) or multidimensional psychopathic traits (Table3), and the inclusion of attention biases measurement (Table4). Additional information about main study characteristics was also collected, including: the main purpose of the study, the study design, sample definition, percentage (%) of males, location and ethnicity, psychopathy dimension, emotion recognition task specificities (i.e., stimuli, exposure duration, number of blocks and trials, and response format), and the inclusion (or not) of attention biases analyses including, when available, the type of measure and/or the measurement device (TableS3). A narrative approach was used to synthesize the findings for each study, obtained by compiling the information from the extraction sheet form. A minimum of five studies reporting similar results was used as a criterion to extract firm conclusions. Nevertheless, inconsistent findings or descriptive results based on a smaller number of studies were also reported as they may provide relevant information to establish new ways of discussion and analysis in future research. Results Study Selection The systematic search was conducted in two different time points; the first one provided 1631 titles from the electronic database search, and two additional references located via reference-list searches. The second one (update) provided 3577 titles. After excluding duplicates, 4679 studies were screened based on titles and abstracts. A total of 76 articles were selected for full-text assessment of eligibility, and the remaining articles were excluded for being off-topic and because they failed to meet the minimum inclusion criteria for this systematic review. After the full text assessment, 50 articles were finally included in the review. The excluded articles and the reasons for their exclusion are available in Supplementary Material (TableS5). The entire selection process is represented in the flowchart of Fig.1. The inter-rater agreement Cohen’s Kappa revealed an almost perfect agreement (K = 0.89) between the researchers regarding the decisions to include or exclude the eligible studies. Study Characteristics TableS3, available online, provides a summary of the main characteristics of each included study. The 50 included studies were published between 2000 and 2022 and provide data from 12,139 children and adolescents (40.84% females [N = 4958]; M age = 12.27) belonging to clinical (k = 10), forensic (k = 6), community (k = 9), at-risk (k = 9) and combined (k = 16) samples. Depending on age, we can distinguish between samples of children (i.e., up to 12years old; k = 13), samples of adolescents (i.e., from 12years old; k = 16), and mixed samples of children and adolescents 171Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 Studies examining emotion recognition in relation to CU traits Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Aghajani etal. (2021) n = 81 (–) CD/LPE+ = 19 CD/LPE- = 31 *22% comorbid ADHD CG = 31 Forensic Community 15–19 (M CD/ LPE ± = 16.84 M HC = 17.02) LPE proxy from the Remorseless, Callousness and Unemotionality subscales of the YPI (SR) CD/LPE+ = two or more items > 5 Facial Fear Sad RT and accuracy (% of correct attribution) Controlling for age and IQ, but not ADHD: 1. There were no significant differences across groups in ER as measured by RT and % of correct attribution of other’s emotions Bennett and Kerig (2014) n = 417 (111) Primary CU (1) = 55 Secondary CU (2) = 76 Low CU (3) = 279 Forensic 12–18 (16.5) (M1 = 15.85 M2 = 16.06 M3 = 16.26) ICU Total score (SR) CU > 26 CG < 26 Facial Fear Anger Sad Shame Disgust Accuracy (% of correct responses) 1. The acquired (secondary) CU group were more accurate in recognizing others disgust 2. Membership in the primary CU group was less than the acquired group as accuracy increased for recognition of disgust, but was more likely as accuracy increased for shame 3. In relation to the Low CU group, the primary CU were more accurate in the recognition of anger. There were no differences with the acquired CU group 172 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Dadds etal. (2018)n = 364 (102) *53% ODD/CD; 35.6% ADHD Clinical 3–16 (8.93) APSD/SDQ CU derived measure (Combined PR, TR, SR) Facial Happy Sad Anger Fear Disgust Neutral Accuracy (Total score) Controlling for the effects of ADHD medication: 1. Low CU traits were related with more accurate ER 2. The relationship between CU traits and ER differed according to maltreatment history; CU traits were associated with poorer recognition of those with zero or negligible history of maltreatment 3. Patterns of moderation effects of maltreatment were inconsistent across subgroups. For the group who self-reported maltreatment, CU traits were related with poor ER in those with lower anxiety 4. Both direct and moderated effects of CU on ER were not limited to fear or sadness. Negative correlations were to some extent evident for all the analyzed emotions, except happiness De Ridder etal. (2016) n = 55 (10) Forensic NR (14.8) YPI CU subscale (SR) Ecological Anger Distress Accuracy (Total score) 1. High CU adolescents were as accurate as low CU adolescents in inferring distress and anger in staff members 2. High CU adolescents notably overestimated the general intensity of both anger and distress 3. High CU adolescents perceived more anger in staff members when they were misbehaving, particularly breaking the rules 173Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Ezpeleta etal. (2017) n = 320 (155) CU+ /ODD+ = 51 CU+/ODD− = 24 CU−/ODD+ = 38 CU−/ODD− = 207 *8.7% comorbid ADHD (CG) = 207 Community 8 (–) ICU Total score (TR) Emoticons Happy Sad Anger Fear Neutral Accuracy RT Controlling for sex, SES and comorbidities: 1. Children within the CU−/ ODD+ and the CU+/ ODD+ were less accurate than the CG in processing the information, specifically when the stimuli expressed happiness, fear or neutral 2. Children high on CU traits but low on ODD performed similarly to the CG with respect to both accuracy and RT with one exception: children high on CU traits responded faster to fear 3. Children within the CU+/ ODD+ group differed in accuracy but not in RT in relation to the CG Kahn etal. (2017) 112 (–) Forensic 12–20 (15.5) ICU Total score (SR) Facial Happy Sad Anger Disgust Fear Neutral Accuracy 1. There were no significant main effects for CU traits or interactions with anxiety in predicting overall accuracy in the affective facial recognition task When predicting accuracy for independently identify the 6 analyzed emotions: 2. CU traits were positively associated with fear recognition accuracy at lower levels of anxiety 3. CU traits were related with poorer results in the recognition of disgust, with a trend suggesting that this relationship tend to occur at high levels of anxiety 180 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Peticlerc etal. (2019) n = 1005 (–) (504 twin pairs, 209 MZ, 295 DZ) Community 6–7 Four items ad hoc 1. “he/she didn’t seem to feel guilty after misbehaving” 2.” he/she has been insensitive to others' feelings” 3.” his/her emotions appear superficial” 4.” has not kept his/ her promises” Facial Happy Sad Anger Fear Accuracy Controlling for other problems (physical aggression, ADHD and depressive symptoms), and for the recognition of other emotions: 1.There was a relationship between CU traits, measured in kindergarten and first grade, and poor emotional recognition of fear, measured in first grade 2. The relationship between CU traits and deficits in fear recognition was genetically influenced 3. The relationship between CU traits and deficits in the recognition of sadness did not hold after controlling for other problems and the recognition of other emotions. No genetic influence was reflected in this relationship, although evidence was provided for the influence of the non-shared environment 181Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Rehder etal. (2017)n = 761 (657) EA = 446 CP+ CU = 20 CG = 442 AA = 315 CP+ CU = 16 CG = 291 Community at risk 6–7 ICU Empathicprosocial and callous subscales (PR) Facial Anger Sad Happy Fear Accuracy (overall and specific emotions) Controlling for primary caregivers’ years of education and children’s age: 1.Differences among typical children (CG), children with CP-only and children with CP + CU were moderated by child race and family income for overall emotion recognition, and by child race for specific emotion recognition 2. Only among EA children, and children within families with higher income-toneeds ratio (i.e., no extreme poverty), CG showed better accuracy for overall emotion recognition than children in the CP only and CP + CU groups 3. Only among EA children, CG showed better recognition for happy faces than children in the CP only and CP + CU group 4. Children in the CP only and CP + CU groups often did not perform differently on emotion recognition accuracy Schwenck etal. (2011) n = 192 (–) ASD = 55 CD = 70 (CD/CU+ = 36 CD/CU− = 34) *44.8% comorbid ADHD CG = 67 Clinical 6–17 (12.3) ICU Total score (PR) CD/CU+ ≥ 32 (median split) CD/CU− < 32 Facial morphed Anger Happy Sad Fear Disgust Accuracy RT 1. There were no significant differences between CD groups (CU+/CU−) in emotion recognition based on RT and the number of correctly identified emotions 2. Removing ADHD children receiving medical treatment did not change the pattern of results 182 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Schwenck etal. (2014) n = (64) CP = 32 (CP/CU+ = 16; CP/CU− = 16) *62.6% comorbid ADHD CG = 32 Clinical 8–16 (13.23) ICU Total score (PR) CP/CU+ > 35.5 (median split) CP/CU− < 35.5 Facial morphed Anger Happy Sad Fear Disgust Accuracy RT There were no significant differences in the analyzed variables between children with and without comorbid ADHD Regarding RT: 1. Girls with CP/CU− reacted more slowly than CG to faces developing happy, sad, and fearful expressions 2. Girls with CP/CU+ did not differ from CP/CU− and CG Regarding accuracy: 3. Girls with CP/CU+ recognized fearful expressions better than the other two groups 4. Girls with CP/CU− recognized sad expressions less often than CG 5. Girls with CP/CU+ mistook sad faces more commonly as disgusted faces than CG; whilst girls with CP/CU− identified fearful faces as disgusted more often than the CP/ CU+ group 183Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement White etal. (2016)n = 337 (185) (High LC = 107; Low LC- = 230; High PI = 96; Low PI = 241) At-risk 3–7 (4.82) MAP-DB Low Concern, Punishment Insensitivity (PR) High/Low groups ≥ /≤ 80th percentile Facial Fear Happy Anger Neutral Accuracy Latency (mean RT) Controlling for age, sex, temper loss, aggression, impulsivity, and the control block In terms of Accuracy: 1. The High LC group was less accurate in identifying fearful faces than the low LC; the accuracy rates did not differ for angry or happy faces 2. There were no differences between High and Low PI groups 3. Female were more accurately to emotional facial expressions than males In terms of Latency: 3. No significant differences were observed between High/Low LC and PI groups Wolf and Muñoz (2014) n = 50 (–) At-risk 11–16 (14.3) YPI CU subscale ICU Total score (SR) Facial and Body postures Dynamic Fear Anger Happy Disgust Sad Pain Accuracy Controlling for age and violent delinquency: 1. Fearful facial and bodily expressions were unrelated with CU traits 2. For the YPI-CU, there were deficits in the recognition of pain in faces, often misidentified as sadness and disgust, and anger in postures, often misidentified as happiness and disgust 3. For the ICU, results showed a significant enhancement in the recognition of anger in faces and disgust in postures 184 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 2 (continued) Study Participants CU measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Woodworth and Waschbusch (2007) n = 73 (14) CP = 32 CP/CU = 24 CG = 18 *84.9% comorbid ADHD Clinical Community 7–12.78 (9.81) APSD CU (Combined PR, TR) CU+ ≥ 67 (median split) CU− ≤ 63 Facial Anger Disgust Fear Happy Sad Surprise Accuracy Controlling age, sex, IQ and ADHD 1. Children with higher CU scores were less accurate in labelling sad affect than children with lower CU scores 2. Children with higher CU scores were more accurate in labelling fear than children with lower CU scores, but this main effect was qualified by the CP-CU interaction trend 3. Children with high CP but low CU traits were less accurate than other children in interpreting fearful facial emotions AA African American, ADHD attention deficit hyperactivity disorder, APSD antisocial process screening device, ASD autism spectrum disorder, CD conduct disorder, CG comparison group, CP conduct problems, CU callous-unemotional, DZ dizygotic, EA European American, ER emotion recognition, GM grandiose-manipulative, HC healthy control, ICU inventory of callousunemotional traits, INS impulsive-need of stimulation, IQ intelligence quotient, LC low concern, LPE limited prosocial emotions, M media, MAP-DB multidimensional assessment profile of disruptive behavior, MZ monozygotic, NR not reported, ODD oppositional defiant disorder, PI punishment insensitivity, PR parent-reported, RT reaction time, SES socioeconomic status, SDQ strengths and difficulties questionnaire, SR self-reported, TR teacher-reported, UBHR unbiased hit rate, UNSW University of New South Wales, YPI youth psychopathic traits inventory 185Clinical Child and Family Psychology Review (2024) 27:165–219 Table 3 Studies examining emotion recognition in relation to overall psychopathic traits Study Participants Psychopathy measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Blair and Coles (2000) n = 55 (24) PSD = 11 CG = 10 Community 11–14 (12.4) PSD Total score (TR) Facial Happy Surprise Fear Sad Disgust Anger Accuracy (Total correct answers) 1. Higher scores in psychopathic traits were related with lower emotional recognition, as well as with an increased impairment in the recognition of anger, sadness and fearful expressions 2. At the dimensional level, Factor 1 (GM/CU) was inversely correlated with the ability to recognize sadness and fear. Factor 2 (INS) was inversely correlated with the ability to recognize fearful expressions 3. When comparing children high and low in psychopathic traits, results revealed a poorer recognition of sadness in the high group, controlling for mental age and sex Blair etal. (2001)n = 51 (-) PP = 20 CG = 31 At-risk 9–17 (MPP = 12.93) (MCG = 12.84) PSD Total score (TR) PP > 28 CG < 20 Facial (morphed) Happy Sad Surprise Fear Disgust Anger Sensitivity (nº of stages needed to correctly identify the expression) Accuracy (% of errors) 1.Children with psychopathic tendencies needed significantly more stages before they could successfully recognize sad expressions 2.Children with psychopathic tendencies made more errors when processing fearful expressions, being more likely to misclassify fear as one of the other five basic emotions 3. There were no group differences for the recognition of happy, anger, disgust and surprise 186 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 3 (continued) Study Participants Psychopathy measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Blair etal. (2005)n = 43 (–) PP = 22 CG = 21 At-risk 11.8–15.5 (MPP = 13.5) (MCG = 12.87) APSD Total score (TR) PP > 25 CG < 25 Vocal Happy Disgust Anger Sad Fear Accuracy (% errors) 1. Boys within the PP group overall made more errors than the CG 2. Boys with PP presented a selective impairment for the recognition of fearful vocal affect 3. Boys PP group did not show significant impairment in the recognition of sad vocal affect 4. When making errors on angry or disgusted expressions, children within the PP group were more likely to mistake these expressions for fearful expression 5. Within the PP group, the covariate age had a significant positive effect in the recognition of fearful affect, and the IQ had a significant effect in the recognition of fearful and disgusted vocal affects 6. At the dimensional level, there were a positive correlation between CU traits and the number of fearful and happy vocal affect recognition errors, and between GM traits and the number of fearful recognition errors. There were no significant correlations with INS Bowen etal. (2014)n = 100 (–) Offenders = 63 CG = 37 Forensic Community 13–17 (Moff = 15.79) (MCG = 15.41) YPI Total score and CU subscale (SR) High > 2.5 Low < 2.5 Facial (morphed) Happy Sad Fear Anger Disgust Surprise Accuracy (% correct recognition scores at each intensity) 1.Young offenders with high psychopathic traits were significantly worse at detecting 50% and 75% intensity of disgusted faces 2. Having high levels of psychopathic traits explained enhanced, rather than diminished, recognition of sad expressions 3. There was a positive correlation between CU traits and 25% and 100% anger recognition 187Clinical Child and Family Psychology Review (2024) 27:165–219 Table 3 (continued) Study Participants Psychopathy measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Dadds etal. (2006)Study 1 = 33 (–) Study 2 = 65 (–) Community Study 1 = 8–15 (12.07) Study 2 = 9–17 (13.2) APSD/SDQ CU and AB (GM/INS) subscales (Combined PR-SR) Facial Happy Sad Anger Disgust Fear Neutral Accuracy 1. AB (GM-INS) and CU traits were associated with different ER problems in young males 2. AB was uniquely associated with a tendency to over-interpret hostility in neutral faces 3. CU traits were uniquely related to poor recognition of fearful expressions, which are in part owing to visual neglect of the eye region of other people’s eyes 4. This deficit improved in the eye gaze condition, but returned in the mouth gaze condition Fairchild etal. (2009)n = 121 (–) EO-CD = 42 AO-CD = 39 *21% comorbid ADHD CG = 40 Community At-risk 14–18 (EO-CD = 15.8) (AO-CD = 15.5) (CG = 15.8) YPI Total score (SR) High > 2.5 Facial (morphed) Anger Disgust Fear Happy Sad Surprise Accuracy (Total score) 1. Relative to CG, recognition of anger, fear, disgust, and happiness was impaired in participants with EO-CD. Also, recognition of fear was impaired in participants with AO-CD. These results were replicated when removing participants with ADHD 2. Participants with CD who were high on psychopathic traits showed impaired fear, sadness and surprise recognition, as compared to those low in psychopathic traits Fairchild etal. (2010)n = (55) CD = 25 *20% comorbid ADHD CG = 30 Community At-risk 14–18 YPI Total score and CU (SR) High > 2.5 in Total score Facial (morphed) Anger Disgust Fear Happy Sad Surprise Accuracy (Total score) 1. Girls with CD showed impaired recognition of anger and disgust. These results were replicated when removing participants with ADHD 2. Participants with CD and high on psychopathic traits showed impaired recognition of sadness, as compared to those lower in psychopathic traits 188 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 3 (continued) Study Participants Psychopathy measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Gillen etal. (2018)n = 144 (49) Forensic 11–18 (15.24) PCL: YV subscales Facial Vocal tone Happy Sad Anger Fear Accuracy (Total score) 1. The PCL: YV Total score was related to lower accuracy of happy and sad faces 2. Interpersonal (GM) traits were positively related to fearful and angry facial emotion recognition accuracy, when controlling for the other two psychopathic factors 3. Affective (CU) traits were associated with poorer accuracy in identifying happy faces and sad, angry and fearful voices 4. Behavioral (INS) traits were not related to accuracy in recognizing emotional facial or vocal tones Kahn etal. (2016)n = 141 (23) Forensic 14–18 (17.03) PCL: YV ICU SR APSD SR CPS SR YPI SR All subscales Facial Happy Fear Surprise Disgust Excitement Accuracy 1. Controlling for IQ, there is no evidence of significant associations between psychopathic traits, measured by the PCL: YV, and Experiential EI 2. For self-reported measures, there was a negative association between the Callous-Disinhibited scale from the CPS and the experiential area, but it did not hold when controlling for multiple comparisons. The association was negative with the GM factor Lemos Vasconcellos etal. (2014) n = 41 (–) (High PP = 20 Low PP = 21) Forensic 13–19 (M High PP = 16.3; M Low PP = 16.7) PCL-YV Total score High PP ≥ 30 Low PP ≤ 20 Facial Fear Sad Happy Disgust Surprise Anger Accuracy 1. The High PP group was significantly poorer than the Low PP group in the recognition of fear in faces presented for 200ms 2. No other differences between groups reached statistical significance; yet, effect sizes also demonstrated a moderate difference for fear recognition at 500ms and 1s, with worse performance for the High PP group, and small-tomoderate difference for sadness and surprise at 500ms, with worse performance for the Low PP group 189Clinical Child and Family Psychology Review (2024) 27:165–219 Table 3 (continued) Study Participants Psychopathy measure (informant) Emotion recognition Main outcome specific to emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotions Measurement Sharp etal. (2014)n = 417 (187) Community 10–12 (11.33) YPI subscales (SR) Facial (eye region) Happy Sad Anger Fear Disgust Surprise Accuracy 1. GM, CU and INS significantly (and inversely) correlated with emotion recognition 2. When the three dimensions were modeled together in a regression framework, only CU traits significantly predicted emotion recognition, but only in relation to complex emotions 3. No psychopathy dimension were predictive of basic emotion recognition Stevens etal. (2001)n = 18 (–) (PSD+ = 9; PSD− = 9) At-risk 9–15 (11.7) PSD Total score (TR) PSD+ > 25 PSD− < 20 Facial Auditory Happy Sad Anger Fear Accuracy 1. The PSD+ group was less likely to name the facial or vocal affect correctly than the PSDgroup 2. Both groups were significantly more likely to name the facial expressions than the vocal affects 3. The PSD+ group showed selective impairments in the recognition of both sad and fearful facial expressions and sad vocal tone 4. The two groups did not differ in their recognition of happy of angry facial expressions, and fearful, happy and angry vocal tones 196 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 4 (continued) Study Participants CU/psychopathy measure (informant) Emotion Recognition Attention biases Main outcome specific to attention biases and emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotion Measurement AOI Measurement Levantini etal., (2022a) n = 116 (–) ODD = 94 CD = 22 *48.28% comorbid ADHD Clinical 7 –12 (9.0) APSD subscales (Combined PR, TR) Facial Happy Sadness Anger Disgust Fear Neutral Accuracy Face Eyes Mouth Number of fixations (FC), Average length of each fixation (FD), Length of first fixation (FFD) Controlling for age, IQ, externalizing problems and SES: 1. CU traits were significantly and negatively associated with sadness recognition and narcissism was negatively associated with disgust recognition 2.Regarding gaze pattern, CU traits were negatively associated with length or first fixation to the mouth of angry faces, number of fixations to the eyes of sad faces and length of first fixation to the eyes of disgusted faces 3. Impulsivity (INS) was positively associated with the number of fixations and average length of each fixation to the eyes of angry faces and number of fixations to the eyes of fearful faces 4. Narcissism (GM) was negatively associated with the number of fixations to the eyes of angry faces, and positively associated with the number of fixations to the mouth of angry faces 197Clinical Child and Family Psychology Review (2024) 27:165–219 Table 4 (continued) Study Participants CU/psychopathy measure (informant) Emotion Recognition Attention biases Main outcome specific to attention biases and emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotion Measurement AOI Measurement Martin-Key etal. (2018) n = 101 (49) CD = 50 (24) *34% comorbid ADHD CG = 51 (25) Forensic Community 13–18 MCDmale = 15.94) MCDfemale = 16.21) MCGmale = 16.22) MCGfemale = 16.40) ICU Total score (SR) Facial static and dynamic Anger Sad Fear Happy Surprise Disgust Neutral Accuracy Eyes Mouth Initial eye preference Total eye preference Controlling for subject, comorbidity and age: 1. Higher levels of CU traits were associated with poorer fear recognition across the whole sample 2. Within the CD group, those high on CU traits showed better fear recognition, and reduced attention to the eyes for surprise faces 3. CU and emotional intensity interacted to predict initial eye preference for surprise, which increased with emotional intensity and was larger for high CU participants 4.With exception of disgust, females showed greater total eye preferences than male for all emotions 198 Clinical Child and Family Psychology Review (2024) 27:165–219 Table 4 (continued) Study Participants CU/psychopathy measure (informant) Emotion Recognition Attention biases Main outcome specific to attention biases and emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotion Measurement AOI Measurement Martin-Key etal. (2021) n = 96 (48) CD = 45 (23) *20% comorbid ADHD CG = 51 (25) Forensic Community 13–18 MCDmale = 15.80) MCDfemale = 16.36) MCGmale = 16.22) MCGfemale = 16.40) ICU Total score (SR) Body postures (dynamic and static) Anger Fear Neutral Accuracy Arms Arm preference score (% of time fixation) Controlling for subject, age and psychiatric comorbidity: 1. There were no effects of CU traits on body posture recognition 2. The effects of CU traits varied according to CD status and sex, with CD males with lower levels of CU traits showing the most atypical fixation behavior More specifically: 3. Higher levels of CU traits predicted higher arm preference score across the entire sample, yet, CU traits were negatively associated with arm preference scores in females, but positively associated in males 4. For fearful and neutral body postures, CU traits were related with arm preference scores in the CD group. These association were negative for females, but positive for males (in the total sample) 5. This atypical fixation behavior did not explain the body posture recognition deficits observed in CD 199Clinical Child and Family Psychology Review (2024) 27:165–219 Table 4 (continued) Study Participants CU/psychopathy measure (informant) Emotion Recognition Attention biases Main outcome specific to attention biases and emotion recognition N (female) Sample type Age range (M) Type of stimuli Emotion Measurement AOI Measurement Muñoz etal. (2021) n = 73 (12) *52% ADHD Clinical 11–16 (14.0) ICU Total score and subscales APSD I/CP score (SR) Facial Fear Anger Happy Neutral Accuracy Eyes Mouth Reflexive attentional orienting (number, direction and velocity of saccades) 1.Children high on CU traits did not show a significant deficit in reflexive gaze to the eye region of fearful faces 2. Similar non-significant effects were observed for the other emotions 3. Children high on CU traits performed more poorly in labelling fearful faces accurately, only when the mouth region and not the eye region of the face was primed. Yet, there were no significant differences regarding the association between ICU scores and fear recognition across the mouth-fixation and the eyefixation condition 4. Youths high on I/CP who are also high on CU traits shifted their gaze less toward fearful eyes when initially focused on the mouth. Only the Callousness facet was significantly associated with decreased gaze shift AB antisocial behavior, ADHD attention deficit hyperactivity disorder, AOI area of interest, APSD antisocial process screening device, ASD autism spectrum disorder, CD conduct disorder, CG comparison group, CP conduct problem, CU callous-unemotional, CPTI child problematic traits inventory, DBD disruptive behavior disorder, ER emotion recognition, FC fixation count, FD fixation durations, FFD first fixation duration, GM grandiose-manipulative, HC healthy control, I/CP impulsivity/conduct problems, ICU inventory of callous-unemotional traits, INS impulsiveneed of stimulation, NR not reported, M media, ODD oppositional defiant disorder, PR parent-reported, RT reaction time, SD statistic deviation, SDQ strengths and difficulties questionnaire, SR self-reported, TR teachers-reported 200 Clinical Child and Family Psychology Review (2024) 27:165–219 (k = 20). Within children’s samples, the majority of the analyzed articles have focused on middle childhood (k = 9). A few articles included combined samples from early and middle childhood (k = 3). Only one study examined emotion recognition deficits in preschoolers (Kimonis etal., 2016). Most of the population analyzed came from European samples (k = 26; 11 UK; 3 Germany; 3 Netherlands; 2 Cyprus; 2 Italy; 1 Spain; 1 Switzerland and five with no region specified). The next most frequent location was USA (k = 9), Australia (k = 4), Canada (k = 2) and Brazil (only 1 study). Ethnicity was reported in 27 studies being White/ Caucasian (k = 19) and African American (k = 7) the most analyzed ethnic groups. The most common diagnosis notified was CD (k = 16), followed by ODD (k = 7) and CP (k = 3). In some cases, the clinical sample was classified according to the level of CU traits (Bennet & Kerig, 2014; Demetriu & Fanti, 2022), the specifier with Limited Prosocial Emotions (LPE), under the label “offenders” (Bowen etal., 2014), based on levels of Low concern (LC) and punishment insensitivity (PI) (White etal., 2016), or based on the presence/absence of “psychopathic personality” (Blair etal., 2001, 2005; Lemos Vasconcellos etal., 2014). Regarding the clinical samples (i.e., children and adolescents with (sub)clinical levels of CP, ODD and CD) (n = 2724; 22.44% of total sample), some articles reported the number of comorbid ADHD (n = 2724; 24.63% of clinical samples). Also, despite not being considered in this review, in three cases ASD was notified (Bours etal., 2018; Klapwijk etal., 2016; Schwenck etal., 2011). All this information was added to the descriptive sample section, in all results tables (see Tables2, 3, 4). The presence and intensity of psychopathic traits have been assessed with various instruments, including the Youth Psychopathic Traits Inventory (YPI; Andershed etal., 2002) (k = 9), the Inventory of Callous Unemotional Traits (ICU; Frick, 2004) (k = 24; 48%), the Antisocial Process Screening Device (APSD; Frick y Hare, 2002) (k = 12), the Psychopathy Screening Device (PSD; Frick etal., 1994) (k = 3), the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997) (k = 4), the Child Problematic Traits Inventory (CPTI; Colins etal., 2014) (k = 1), the Psychopathy Checklist: Youth Version (PCL: YV; Forth etal., 2003) (k = 3), Items ad hoc (k = 1) and the Multidimensional Assessment Profile of Disruptive Behaviour (MAP-DB; Wakschlag etal., 2012) (k = 1). Sometimes cut-off points were used to determine the presence or absence of psychopathic traits (especially CU traits), which have been arbitrarily chosen according to different studies. Regarding CU traits, sometimes the subdivision in three dimensions (i.e., callouness, uncaring, and unemotional) was also considered. The affective factor of psychopathy (i.e., CU traits) has been the most evaluated psychopathy dimension (k = 33; 66%). Studies that just focused on CU traits are described in Table2. These traits can be found in different degrees of intensity (high/low) or can be conceptualized dichotomously (presence/absence). Also, 17 studies considered psychopathic traits as a multidimensional construct. Most of them (k = 9) considered psychopathic personality as a composite total score, with 3 also providing data on specific CU traits (Bours etal., 2018; Bowen etal., 2014; Fairchild Records identified from Databases (n= 1631): PsycInfo (n = 436) Scopus (n = 152) Pubmed (n = 465) WOS (n = 578) Records removed before screening: Duplicate records removed by Refworks (n = 529) Records screened (n = 1102) Records excluded based on tittle and abstract: ( n = 1039 ) Reports assessed for eligibility ( n = 63 ) Reports excluded (n = 17) See Reasons in Appendix X Records identified from: Citation searching (n = 2) Studies included in first search (n = 46) Identification of studies via databases and re g isters ( first search ) Identification of studies via other methods Identification Screenin g Included New studies ( u p date ) Records identified from Databases (n= 3577): PsycInfo (n = 939) Scopus (n = 321) Pubmed (n = 1044) WOS (n = 1273) Records removed before screening: Duplicate records removed (n = 12) Duplicate records removed by Refworks (n = 1432) Records screened (n = 2113) Records excluded based on tittle and abstract: ( n = 2104 ) Reports assessed for eligibility ( n = 9 ) Reports excluded (n = 7) See the reasons for the articles indicated with (*) in Appendix X Studies included in update (n = 2) Total studies included in review (n = 50) Fig. 1 Flowchart for systematic review process. Adapted from the flow diagram of PRISMA (Page etal., 2021) 201Clinical Child and Family Psychology Review (2024) 27:165–219 etal., 2010). The remaining studies focused on different subdimensions (i.e., GM, CU, INS) (k = 5), or used alternative combinations (e.g., GM-INS, CU) (Dadds etal., 2006, 2008, 2011). Articles assessing psychopathic traits from a multidimensional perspective are reported in Table3. Considering design, 24 studies compared performance in emotion recognition across the whole sample using a correlational design. In the remaining (k = 26), a betweengroup design was used. To determine membership of the comparison group, one of the following criteria was considered: CU levels (high vs. low), cut-off points based on psychopathy assessment instruments, no clinical disorders and not being an offender. Most studies were cross-sectional (k = 45; 90%), whilst just five studies provided longitudinal results (Bedford etal., 2017; De Ridder etal., 2016; Peticlerc etal., 2019; Rehder etal., 2017). All studies included in the present review employed an emotional recognition task. Most of the articles examined the recognition of basic emotions (Ekman, 1992). However, the most repeated emotions were distress emotions (fear and sadness). Fear was analyzed in all articles except 1 (98%) (Milone etal., 2019), whilst sadness was considered in 44 articles (88%). Some articles assessed more emotions than the basic ones (i.e., excitement, shame, pain, mad, scared) (Bedford etal., 2017; Bennett & Kerig, 2014; Kimonis etal., 2016), but these results were not considered for the purpose of the current review. The most frequent emotion recognition tasks used were UNSW Facial Emotion Task (k = 6), The Emotion Hexagon Task (k = 5), NimStim Set of Facial Expressions (k = 4), Facial Emotion Recognition Task (k = 3), RaFD (k = 3), DANVA-II (k = 2) y CET (k = 2). Both accuracy and reaction time were the most used measures for emotion recognition. The emotion recognition task was sometimes complemented by another task to assess attentional bias (k = 11). The characteristics of the attentional tasks, with their specific results, are presented in Table4. Only two of these articles examined attentional bias by assessing gaze direction between mothers and children (Bedford etal., 2017; Dadds etal., 2011). In the others, eye tracker devices were used. To assess the attentional pattern, AOI were established: eyes and mouth (k = 8), only the face (Bedford etal., 2017), eyes (Dadds etal., 2011) or arms (Martin-Key etal., 2021). The analysis of the response considered accuracy, reaction time (RT), number and duration of fixations. The most analyzed stimulus type was facial and human (k = 43; 86%). Bodily stimuli (Martin-Key etal., 2021; Muñoz, 2009; Wolf & Muñoz, 2014) and vocal tones were also examined (Blair etal., 2005; Gillen etal., 2018; Stevens etal., 2001), as well as non-human stimuli, including doll faces (O’Kearney etal., 2017, 2020) and emoticons (Ezpeleta etal., 2017). Stimuli presentation time ranged from 200ms (Lemos Vasconcellos etal., 2014) to 6s for static images (Bours etal., 2018), and from 1s (Kimonis etal., 2016; Martin-Key etal., 2018) to 9s (Schwenck etal., 2011, 2014) for dynamic emotional stimuli. In the case of video clips, the presentation ranged between 3s (Martin-Key etal., 2021) and 144s (Martin-Key etal., 2017, 2020). Risk ofBias inStudies The evaluation made from AXIS and CASP suggests overall a low to moderate level of bias among the eligible studies (see TablesS4, S5, available online). Most of the included studies provided good indicators of quality, suggesting a low risk of bias. Exceptionally, some articles that did not provide sufficient information for replicability (Milone etal., 2019) or used subjective measures that may introduce considerable bias into the study (De Ridder etal., 2016). Results ofIndividual Studies The main results obtained in the articles included in this systematic review are reported in Tables2, 3 and 4. The first two analyze those studies that consider CU traits (Table2) and all psychopathic traits (Table3) respectively. The third one (Table4), groups together all those articles that evaluated attentional bias in addition to emotion recognition. Emotion Recognition andPsychopathic Traits CU Traits CU traits was the most studied dimension (k = 33). Evidence was found on the relationship between high levels of CU traits and a deficit in general emotion recognition (Bedford etal., 2017; Demetriou & Fanti, 2022; Hartmann & Schwenck, 2020; Lui etal., 2016). In addition, this impairment also affected the recognition of some specific emotions. Hence, Woodworth and Waschbusch (2007) found that children high on CU traits were less accurate in labelling sadness. Fear recognition has also been affected both in isolation (Dadds etal., 2008; Martin-Key etal., 2018; Muñoz, 2009; Peticlerc et al., 2019; White et al., 2016) and in combination with other distress emotions, including anger (Muñoz, 2009), disgust (Sylvers etal., 2011) and sadness (Billeci etal., 2019). It seems that emotional complexity may play a role in emotion recognition, as postulated by some authors (Adolphs & Tranel, 2004). In this sense, Sharp etal. (2014) found that CU traits might imply a difficulty in the recognition of complex emotions as opposed to simple emotions. Moreover, this deficit seems to affect all modalities: bodily (Muñoz, 2009), vocal (fear and happy; Blair etal., 2005; sad, angry and fear; Gillen etal., 2018) and facial (all other studies reviewed in this section). Evidence was also found 202 Clinical Child and Family Psychology Review (2024) 27:165–219 in regards emotional processing, measured as reaction time, with children high on CU traits recognizing the emotions of anger, sadness and fear more slowly (Hartmann & Schwenck, 2020). In some cases, no significant differences according to the level of CU traits were found in the accuracy of recognizing distress emotions, including angry, sad and fearful faces (Hartmann & Schwenck, 2020), also in ecological environments (De Ridder etal., 2016). In this ecological assessment, conducted in a forensic sample, CU participants seemed to overestimate the intensity of distress and anger in staff members, particularly when they were misbehaving (De Ridder etal., 2016). In regular task conditions, the lack of relationship between CU traits and recognition of fearful faces and body postures varied depending on the assessment instrument used (Wolf & Muñoz, 2014). A similar result was also found in Bowen etal. (2014), with a positive correlation between CU traits and 25% and 100% anger intensity recognition. In sum, there was a broad trend to relate CU traits with moderate pervasive emotion recognition (Lui etal., 2016) as well as a specific deficit for fear, with effect sizes ranging from moderate (Martin-Key etal., 2017) to large (De Ridder etal., 2016; Woodworth & Waschbusch, 2007). Moderate (Martin-Key etal., 2017) and large effects were also found for sadness (De Ridder etal., 2016). These deficits transcended modality and type of stimulus presented. Emotion processing was also strongly impaired, with longer time required for emotional recognition in children and adolescents high on CU traits. CU Subdimensions Two studies considered the role of subdimensions of CU traits, with some mixed results even in effect sizes, which have consistently been small for the different subdimensions (Kimonis etal., 2016; Moore etal., 2019) and have ranged from small (Moore etal., 2019) to moderate for the total ICU score (Kimonis etal., 2016). On the one hand, Kimonis etal. (2016) found that scoring high on the ICU total score was associated with lower accuracy in recognizing fear, anger, happiness and sadness. Regarding subdimensions, callousness was only associated with poor fear and sadness recognition but not after controlling for uncaring. Moreover, uncaring remained significantly associated with anger, happy and sad recognition after controlling for callousness. On the other hand, Moore et al. (2019) found that the ICU total score was significantly associated with impaired sadness recognition. Furthermore, the uncaring/callousness subdimension was significantly associated with impaired recognition of happiness, sadness, fear, surprise and disgust. For all these emotions, the relationship between uncaring/callousness and the recognition of distress emotions was entirely accounted by shared genetic influences. An opposite pattern of results was observed for the unemotional subdimension, which was significantly associated with improved recognition of surprise and disgust. CU Variants Some scholars pointed to the existence of two CU variants. Primary callousness arises as a function of a genetically based deficit in emotion processing mainly characterized by a lack of emotional distress and anxiety (Blair etal., 2006). In contrast, acquired callousness proposes that CU might arise trough the result of environmental factors, with anxiety playing a central role in the definition of the secondary variant (Kerig & Becker, 2010). Following these premises, Bennett and Kerig (2014) investigated the importance of these two variants in emotion recognition, finding differences depending on the type of CU variant. Thus, the acquired or secondary group were more accurate in recognizing others disgust whilst primary CU were more accurate in the recognition of anger compared with the low CU group. For both primary and secondary variants, the relations with emotion recognition were strong. In addition, the ability to recognize certain emotions determined the classification of the adolescents into the primary (more accuracy for shame) or secondary group (more accuracy for disgust). Psychopathic Traits (GM, CU, INS) Higher scores in psychopathic traits, measured as a multidimensional construct, were related with lower facial emotional recognition (Blair & Coles, 2000; Dadds etal., 2006; Sharp etal., 2014; Stevens etal., 2001), as well as with an increased impairment in the recognition of happy (Gillen etal., 2018) anger (Blair & Coles, 2000), sadness (Blair & Coles, 2000; Gillen etal., 2018; Stevens etal., 2001) and fearful expressions (Blair & Coles, 2000; Lemos Vasconcellos etal., 2014; Stevens etal., 2001). Moreover, when comparing groups with high and low levels of psychopathic traits, results revealed a poorer recognition of sadness in the high psychopathic traits (PP) group. Processing (RT) and recognition (accuracy) were also impaired for distress emotions (i.e., sadness and fear), with children with psychopathic traits, who need more stages (i.e., emotional complexity) to recognize disgust (Bowen etal., 2014) and sad expressions (Blair etal., 2001). Also, they made more errors with fear expressions, being more likely to misclassify fear as one of the other five basic emotions (Blair etal., 2001), and more specifically with angry expressions (Blair etal., 2005). These deficits were seen in the same direction when vocal stimuli were considered (Blair etal., 2005; Stevens etal., 2001). In this sense, boys with psychopathic traits presented a selective impairment for the recognition of fearful vocal affect (Blair etal., 2005) or were less accurate to correctly identify the sad vocal affect (Stevens etal., 2001). One of the included studies examined emotion recognition as part 203Clinical Child and Family Psychology Review (2024) 27:165–219 of emotional intelligence and found no relationship between experiential emotional intelligence, measured as a proxy of emotion recognition through facial emotion assessment, and the combination of the three psychopathy dimensions (Kahn etal., 2016). Overall, as was observed for CU traits, the presence of psychopathic traits entailed a lower facial and vocal emotion recognition focused on distress emotions (fear and sadness), with effect sizes ranging from moderate (Gillen etal., 2018; Lemos Vasconcellos etal., 2014) to large (Blair & Coles, 2000) for both emotions and modalities. Moreover, processing was also significantly impaired, needing more time to react or more stages of each morphed emotion to reach an accurate identification. Other Combinations ofPsychopathic Traits At the dimensional level, GM/CU traits, representing the Factor 1 of psychopathic personality, were moderately inversely correlated with the ability to recognize sadness and fear (Blair & Coles, 2000). Yet, in Blair etal. (2005) no significant correlation was found. GMINS were associated with different emotion recognition problems (Dadds etal., 2006). Considering psychopathic traits separately, INS was inversely correlated with the ability to recognize fearful expressions (Blair & Coles, 2000) or not related to accuracy in recognizing emotional facial or vocal tones (Gillen etal., 2018). In other studies, INS interacted with CU traits in predicting preattentive fear-recognition deficits (Sylvers etal., 2011). In the case of GM, this psychopathic dimension affects the number of fearful recognition errors (Blair etal., 2005; Gillen etal., 2018) and the accuracy to identify angry facial emotions (Gillen etal., 2018). Measurement ofPsychopathic Traits Several different assessment instruments have been used for the measurement of psychopathic traits (see “Study Characteristics” section). Particularly noticeable is the variability when considering the informant [parent-report (PR), teacher-report (TR) and self-report (SR)], the focus on different subscales (e.g., total scores, CU traits), the dimensional versus categorical conceptualization of the variables, and the cut-off points employed to define high/low scores on the intended measures, even when using the same instrument. This heterogeneity can be observed in Tables2, 3, 4, included in the text. The Inventory of Callous Unemotional Traits (ICU; Frick, 2004) (k = 24; 48%) was the most widely used. When the informant was the child/ adolescent (i.e., SR) and the total score of the instrument was considered, most of the reviewed studies did not find deficits associated with CU traits and emotion recognition (Klapwijk etal., 2016) or attention biases (Bours etal., 2018; Martin-Key etal., 2021; Muñoz etal., 2021), even when CU traits were treated dimensionally (Martin-Key etal., 2017, 2020). When deficits in emotion recognition were reported, they tended to be more pervasive (e.g., Pauli etal., 2021) rather than specific (e.g., fear; Muñoz, 2009), and particularly in at risk samples (Lui etal., 2016). These deficits were typically associated with other variables examined in the study, including CU variants or anxiety (Bennett & Kerig, 2014; Kahn etal., 2017), or were linked to sample characteristics (e.g., clinical groups; Martin-Key etal., 2018). If we consider external informants (i.e. parents and teachers), the variability of the results continues to be maintained, with a certain tendency towards an appreciation of deficits in the recognition of sadness (Hartmann & Schwenck, 2020; Moore etal., 2019; Schwenck etal., 2014), mixed emotions (O’Kearney etal., 2020), and happy, fearful, neutral and angry facial expression (Ezpeleta etal., 2017; Hartmann & Schwenck, 2020). Also, a relation between poorer emotion recognition and high CU was found (Bedford etal., 2017). Only two studies found no relationship between CU traits and emotional perception (O’Kearney etal., 2017) or recognition (Schwenck etal., 2011), when using parent’s or teacher’s reports. When multiple subscales were used (i.e., Callousness, Uncaring, Unemotional), both impaired and enhanced emotion recognition were found (Kimonis etal., 2016; Moore etal., 2019; Rehder etal., 2017). As is the case of the self-reported measures, the outcomes sometimes depended on the moderator variables, including sex (Schwenck etal., 2014) and ethnicity (Rehder etal., 2017). When using the Antisocial Process Screening Device (APSD; Frick y Hare, 2002) (k = 12) all but one study (Muñoz etal., 2021), showed deficits in emotion recognition, especially for fear (Woodworth & Waschbusch, 2007) and sadness (Dadds etal., 2006, 2008), as well as an aberrant pattern in attention, especially to the eyes (Billeci etal., 2019; Dadds etal., 2008, 2011). It is important to note that deficits in emotion recognition were mostly observed with the APSD total score, considering all the psychopathy dimensions, irrespectively of the informant (Blair & Coles, 2000; Blair etal., 2001, 2005; Dadds etal., 2006, 2008; Levantini etal., 2022a; Sylvers etal., 2011). For The Youth Psychopathic Traits Inventory (YPI; Andershed etal., 2002) (k = 9), which is a self-reported measure, all studies found deficits in multiple emotions, i.e., disgust (Bowen etal., 2014), sadness (Fairchild etal., 2009, 2010) and complex emotions (Sharp etal., 2014), across all psychopathy dimensions. Again, results differed in relation to potential moderators, as sample type (e.g., offenders; Bowen etal., 2014) or the use of specific subscales (e.g., YPI CU; De Ridder etal., 2016). In some cases, various instruments were simultaneously used to measure psychopathic traits. Separate results for the measurements employed were sometimes not provided 204 Clinical Child and Family Psychology Review (2024) 27:165–219 (Bours etal., 2018; Dadds etal., 2008, 2011, 2018; Kahn etal., 2016; Kohls etal., 2020a). In other cases, studies reported different results according to the instrument (Kahn etal., 2016; Wolf & Muñoz, 2014). As an example, Wolf and Muñoz (2014) showed that CU traits measured through the ICU were related with a significant enhancement in the recognition of anger faces and disgusted body postures, a result that did not replicate when using the CU measure of the YPI. Finally, some studies showed differences across instruments that seemed more related with the dimension assessed (e.g., ICU total versus callousness) rather than the instrument itself (Kimonis etal., 2016; Muñoz etal., 2021). In sum, as previously observed, variability in the results is the dominant trend for both accuracy and attention. Nevertheless, we can identify certain patterns. Potential moderator variables examined in the review (e.g., age, gender, sample type) seemed to play a significant role in determining deficits in emotion recognition. In the case of CU traits measured with the ICU, more specific deficits were observed when data was reported by parents and/or teachers rather than self-reports. Finally, the use of different subscales, combining various assessment instruments, and employing different cut-off points could have affected the results, increasing their variability. (Sub)Clinical Groups: The Role ofDisruptive Behavior Expectedly, higher levels of psychopathic traits were reported within the groups of children and adolescents with CP, or with the clinical groups (CD/ODD) (Kohls etal., 2020a; Martin-Key etal., 2018, 2020). CD was the clinical condition most studied (k = 13). Within this group, when we consider high levels of psychopathic traits, results showed deficits in fear, sadness and surprise emotions (Fairchild etal., 2009), as well as a unique deficit in recognizing sadness (Fairchild etal., 2010) in both male and female samples respectively. However, results vary when we only analyze CU traits. Thus, even though one study showed that elevated CU traits within the CD group were associated with overall emotion recognition impairments, rather than deficits in particular emotions (Kohls etal., 2020a), in most of the examined studies no significant differences were found, regardless of the type of stimulus used, as a function of CU traits (Aghajani etal., 2021; Kohls etal., 2020a; Kohls etal., 2020b; Klapwijk etal., 2016; Martin-Key etal., 2017, 2020, 2021; Milone etal., 2019; Schwenck etal., 2011). Indeed, in all of the aforementioned studies but two (Aghajani etal., 2021; Martin-Key etal., 2020) deficits in emotion recognition were uniquely related with the presence of CD. In addition to this finding, some authors pointed out that this group (CD/CU+) would not benefit from increasing the emotional intensity of the stimuli to enhance recognition (Pauli etal., 2021). Regarding processing, higher levels of CU traits indicated faster processing speed, requiring less time to recognize emotions in general (Klapwijk etal., 2016) and fear in particular (Martin-Key etal., 2018). This pattern of mixed results was also replicated if we analyze the clinical condition constituted by ODD (k = 3). In this regard, it was found that (a) high or low levels of CU traits did not affect emotional recognition (Ezpeleta etal., 2017; O’Kearney etal., 2017), (b) only affected the recognition of mixed emotions (O’Kearney etal., 2020), or (c) even higher levels of CU traits were associated with better recognition of fear (Ezpeleta etal., 2017). Within the group of CP (k = 2), results confirmed that higher levels of CU traits involved a better recognition of fear (Schwenck etal., 2014; Woodworth & Waschbusch, 2007). Also, CU levels did not affect emotional processing (Schwenck etal., 2014), and lower levels of CU traits implied lower recognition of sadness as compared to healthy controls (Schwenck etal., 2014). Moreover, it was the intensity of CP and not the intensity of CU traits what seemed to determine poorer fear recognition (Woodworth & Waschbusch, 2007). Other combinations yielded similar results. In groups with CD/ODD, emotional affect was given by high or low levels of ODD, so that at high levels of CU in both conditions, there was poorer recognition of fear in the ODD− group and worse recognition of anger in ODD+ (Hartmann & Schwenck, 2020). In other cases, it was the presence of several dimensions of psychopathy that was associated with the observed deficits; in this regard, CU traits determined worse recognition of sadness and high GM implied worse recognition of disgust (Levantini etal., 2022a). Despite the few studies that looked at psychopathic personality as a whole, it seems to be this combination (e.g., CP + PP), and not exclusively CU traits, which seems to show more deficits in emotional recognition within clinical groups. In fact, when looking only at CU traits, it seems that the intensity of disruptive behavioral disorders could make the difference in emotion recognition, rather than the presence of CU traits. Thus, CU traits would be more associated within the (sub)clinical groups with better and faster fear recognition, with effects ranging from moderate (Ezpeleta etal., 2017) to large (Martin-Key etal., 2018). Comorbid ADHD Co-occurrence rates between CP and ADHD are particularly high (Hudec & Mikami, 2017). That is the reason why data concerning comorbidity of ADHD were reported when available for some clinical groups (k = 20). Two studies did not report any test or control analysis for comorbid ADHD (Martin-Key etal., 2020; O’Kearney etal., 2017), and some others did not control for comorbid ADHD (Aghajani etal., 2021; Klapwijk etal., 2016; Levantini etal., 2022a; Muñoz etal., 2021). Yet, in most of the included studies that reported comorbid lev- 205Clinical Child and Family Psychology Review (2024) 27:165–219 els of ADHD, its potential effect was tested or controlled for (Ezpeleta etal., 2017; Hartmann & Schwenck, 2020; Kohls etal., 2020a; Martin-Key etal., 2017, 2018, 2021; Peticlerc etal., 2019; Schwenck etal., 2014; Woodworth & Waschbusch, 2007), as it was the effect of ADHD medication (Bours etal., 2018; Dadds etal., 2018; Schwenck etal., 2011). When ADHD was considered, there were no significant differences in the analyzed variables between children with and without comorbid ADHD, or results were replicated in the same direction when ADHD or hyperactivity was removed or controlled for (Dadds etal., 2011; Fairchild etal., 2009, 2010; Schwenck etal., 2011), even in community samples (Peticlerc etal., 2019). Additional studies also reported that ADHD medication did not influence the observed results (Bours etal., 2018; Dadds etal., 2018; Schwenck etal., 2011). Emotional Stimuli Presented Type ofStimulus Presented (Facial, Vocal orBodily) Most of the studies included in this review addressed emotional recognition and/or processing using human facial stimuli (k = 46). Of these, only 7 have found no deficits associated with the presence of psychopathic traits, either conceptualized as specific dimensions or as a whole (Aghajani etal., 2021; Kahn etal., 2016; Kohls etal., 2020b; Martin-Key etal., 2020; Milone etal., 2019; O’Kearney etal., 2017; Schwenck et al., 2011). Milone et al. (2019) and Sharp etal. (2014) focused the analysis on a specific facial region, i.e., the eyes, finding mixed results (against and supporting respectively), regarding the impairment of emotional recognition in the presence of psychopathic traits. Emotional recognition of human bodily postures was also explored (Muñoz, 2009; Martin-Key etal., 2021; Wolf & Muñoz, 2014). Except Martin-Key etal. (2021), which only found an atypical fixation behavior (i.e., arm preference) in high CD males, the remaining studies found deficits in emotion recognition in the presence of psychopathic traits. Deficits were also replicated for vocal stimuli. Deficits in the vocal recognition of sadness were the most common (Gillen etal., 2018; Stevens etal., 2001), but there were also deficits in the recognition of the vocal affect of anger and fear in relation to CU traits (Gillen etal., 2018), and fear in the presence of psychopathic traits (Blair etal., 2005). De Ridder etal. (2016) deserves special mention for locating the assessment of emotional recognition in a valid ecological environment. Results showed the same accuracy levels for distress emotions between low and high CU groups, but results revealed differences in overestimating intensity of anger and distress emotions in the staff, especially when participants were misbehaving. Finally, it should be noted the use of non-human stimuli in some studies. Emoticons were used in Ezpeleta etal. (2017) and dolls with detachable faces in O’Kearney etal. (2017, 2020). Except for O’Kearney etal. (2017), deficits were found in accuracy and reaction time for mixed (e.g., happy-sad) and simple emotions in clinical ODD groups. By synthesizing, the relationship between the presence of psychopathic traits and deficits in emotional recognition was found in all types of emotional stimuli studied. Intensity andDuration ofStimuli Regarding intensity, there was no agreement in the results found across the analyzed studies. Hence, in non-clinical groups, some authors found that higher levels of psychopathic traits require a clearer emotional stimulus to be recognized (Blair et al., 2001). However, Bowen etal. (2014) found that the presence of psychopathic traits determined a worse recognition of disgust at medium to high intensities. Furthermore, when considering only CU traits, participants recognized anger rated with very low and very high intensity better. In the case of clinical groups, the results overall indicated that recognition accuracy was better for high intensity stimuli at both high and low CU levels. However, CD/ CU+ groups benefited less from the increased intensity of emotional expressions (Pauli etal., 2021). In some cases, CU and emotional intensity interacted to predict initial eye preference for surprise, which increased with emotional intensity and was larger for high CU participants (MartinKey etal., 2018). The effects of duration were only analyzed in Lemos Vasconcellos etal. (2014), who found that the duration of the stimuli presentation affected fear recognition in those groups that scored high on psychopathic traits, with moderate effect sizes. Fear recognition was worse in the shortest experimental condition (200ms) compared to the other conditions. No other differences between groups reached statistical significance; yet effect sizes also demonstrated a moderate difference for fear recognition at 500ms and 1s, with worse performance for the High PP group, and small-to-moderate difference for sadness and surprise at 500ms, with worse performance for the Low PP group. The Role ofAttention The pattern of attention and eye fixation to regions of the face or body as a mediating factor of emotional recognition has been a factor studied in some articles of the present review (k = 11). Within the non-clinical groups, results tend to indicate that at higher levels of CU traits, an aberrant attentional pattern towards the eye region is observed in the number of fixations (Dadds etal., 2008; Demetriou & Fanti, 2022), and in the duration of eye interactions and on the first attentional focus to the eye region (Dadds etal., 2008), which could determine a deficit in the recognition of fear (Dadds etal., 2008) or for all emotions in general 212 Clinical Child and Family Psychology Review (2024) 27:165–219 be assessed in the light of some important limitations. The most remarkable concerns the high heterogeneity found in the different studies. It is hard to identify a unique source for this variability, but there are some possible factors that might be of influence. Multiple emotions were presented, but not the same across all studies. Most of them considered the basic emotions (Ekman, 1992), but at times, the emotions chosen were in response to the researcher's objectives (e.g., distress emotions, complex emotions). Intensity at presentation, complexity and exposure times were variable too, both being characteristics relevant for emotion recognition. Also, occasionally, emotional stimuli were presented several times, so the learning effect cannot be dismissed. The environmental conditions (e.g., light, noise, spaces) of the experimental setup and the way information is collected (e.g., self-registration, third part collection) can lead to differences in the results. The wide range of different instruments used to assess psychopathic traits, with different informants (i.e., teachers, parents, self-report), the consideration of psychopathic traits from a dimensional versus a categorical perspective, or the arbitrary cut-off point used to determine the presence/absence of psychopathic traits, may also lead to inconsistencies in the results. As a result of this variability, at times, the shortage of studies made it challenging to extract robust results and draw generalizable conclusions. In addition, some studies did not provide enough information for replication. In this regard, while certain recognition deficits were replicated across stimuli and presentation modalities, which is relevant to generalization, future research would benefit from homogenizing experimental conditions and promoting replication studies across diverse samples, contexts, and settings. Other factors that affect the variability in results include the limited sample size in some of the included studies and the non-differentiation of the sample with respect to sex. A better understanding of this phenomenon inevitably requires the establishment of differentiated samples between boys and girls and the recruitment of a sufficient sample size to be able to draw reliable conclusions, particularly when between-groups designs are considered. Also important is to continue examining the longitudinal association between emotion recognition and psychopathic traits, as most of the studies included in this review were cross-sectional and hindered the possibility to interpret the directionality of the effects. New longitudinal research will help to disentangle the potential causal mechanisms, addressing linked deficits in other relevant brain structures and functional areas. Hence, complementary measures of emotional processing, including psychophysiological recordings (i.e., heart rate, skin conductance), are particularly needed to provide further evidence on underlying mechanisms that might be influencing the relationship between psychopathic traits and emotion recognition. Future research would also benefit from including preschool samples, as the available results are scarce in this developmental period. This would help to elucidate whether deficits in emotion recognition in early childhood could be somehow explained by the presence of psychopathic traits beyond age-related reasons (i.e., increased ability to recognize different emotions as children grow up). Finally, additional suggestions for future research would include stimuli with different emotional intensities. Limiting the recognition methodology only to images of high emotional intensity may not provide a clear picture of emotional recognition difficulties, whilst contemplation of various emotional intensities may be best suited to reveal sensitivity and more subtle differences in recognition (Adolphs & Tranel, 2004). More attention should be also paid to other modalities such as vocal affect, as they represent a great complement to facial and bodily stimuli in socialization processes. Lastly, promotion of cross-national and crosscultural studies with the aim of outlining cultural differences in emotional recognition should be also encouraged. Some other limitations concerning this study should also be outlined. It covers a wide period of time (i.e., more than 20years), and two distinctive developmental periods (i.e., childhood and adolescence), which results in an appreciable number of studies, with multiple results to be extracted. This fact, along with the inclusion of mixed samples, makes complex to provide a finer-grained extraction, with studies specifically examined by age, sex or sample type. Relatedly, to address all the intended objectives, an extensive search equation was used, providing a great number of results to be screened. The great number of eligible studies required an organized extraction. For the current study, and based on our objectives, results were organized based on the psychopathy dimension analyzed, and the assessment of attention deficits, but other forms or organization could be possible, including the sample type, or the developmental period. However, because some studies included mixed samples, these alternative forms of organization were finally discarded. The inclusion of adolescent samples led to include some participants older than 18, resulting in a wide age range. Yet, their inclusion was justifiable as they were part of well-defined adolescent samples (e.g., high school, samples within juvenile forensic systems that include participants up to 21years old). Finally, restricting the search to published studies (i.e., excluding grey literature) may raise the likelihood of publication biases due to the file drawer effect. The inclusion of multiple results, in different directions, could have attenuated this effect but the potential influence of this kind of biases cannot be diminished when interpreting the results. 213Clinical Child and Family Psychology Review (2024) 27:165–219 Theoretical andPractical Implications Emotion recognition of facial expressions represents a crucial component of human social interaction, allowing the observer to infer another's emotional state and adjust their behavior (Blair, 2003b). This review provides important clinical, social and scientific implications. On a clinical and scientific level, it raises the need to attend to this problem at an early age, as we already know that psychopathic traits can be reliable identified early in development (Colins etal., 2014; López-Romero etal., 2019) and, what is even more important, that these traits could be more malleable at childhood when behavioral patterns are not firmly established. Disentangling the mechanisms underlying the development of psychopathic traits will provide additional insight about a construct that has proved its value for child and youth CP. This, in turn, will help to improve the development of more tailored preventive and intervention approaches, aimed at restraining high-risk patterns of behavioral maladjustment, with related benefits in the policy and social fields. However, more research is needed to clarify how preventive interventions could be improved from research in emotion recognition, particularly in early childhood. In (sub)clinical samples, parent training seems to be the option that works best to reduce conduct problems (Romero etal., 2023). Recently, attempts have been made to improve behavioral parent training interventions to increase efficacy for children with CP + CU (Dadds etal., 2019; Kimonis etal., 2019; Waschbusch etal., 2019) with some promising results for high CU children evidenced in a recent metaanalysis (Perlstein etal., 2023). Based on previous research on the association between parenting practices and psychopathic traits (e.g., Waller etal., 2018), these tailored programs emphasized the importance of improving the quality of parent–child relationships by increasing sensitive and receptive parenting interactions (Kimonis etal., 2019). Aligning with prior recommendations of translating emotion-related evidence to prevention (e.g., Izard, 2002), some recent interventions have also incorporated an element of distress cue and emotion recognition training, with the goal of increasing socioemotional skills (e.g., empathy) in children with high CU traits. Interestingly, promising results have been reported in this regard (Fleming etal., 2022), even when considering attention deficits as the target of the intervention (Muñoz etal., 2021). Because previous research has suggested that parenting practices could be moderating the association between psychopathic traits and emotion recognition deficits (Levantini etal., 2022b), additional knowledge on these interactions would serve to continue refining parenting programs with socioemotional components specifically tailored to children and adolescents with psychopathic traits. Yet, these promising implications at the practical level should also be interpreted with caution. Hence, some studies included in this review showed no deficits (e.g., Martin-Key etal., 2020), or even better recognition (e.g., Ezpeleta etal., 2017) in relation to psychopathic traits. This is particularly important within the (sub)clinical groups, with psychopathic traits, and not just CU, being linked with impairments in emotion recognition. However, high CU individuals tend to be the target of the current interventions intended to reduce child CP (Perlstein etal., 2023), whilst other psychopathic dimensions have been overlooked in intervention. Also, if psychopathic individuals show enhanced abilities for emotion recognition, as revealed but some studies in this review (e.g., Ezpeleta etal., 2017; Klapwijk etal., 2016; MartinKey etal., 2018), this kind of interventions may come with some iatrogenic results. Improving the current knowledge on emotion recognition in relation to psychopathic personality, accounting for all its dimensions and potential moderators, would be decisive to keep moving forward at the practical level, with refinements in evidence-based programs that really account for deficits in this population. Homogenizing research conditions and favoring replication studies could help in this purpose, allowing the establishment of more robust and clearer conclusions on the association between emotion recognition and psychopathic traits and, in turn, on the transfer of those results to the applied context. Conclusions This is the first systematic review specifically focused on the association between psychopathic traits, accounting for all its dimensions, and emotion recognition deficits in children and adolescents. Results overall showed impairments in emotion recognition in relation to psychopathic traits. These results revealed pervasive deficits across emotions, although they were more marked for distress emotions, including fear or sadness, with deficits being replicated across all modalities of emotion presentation and all stimuli used. Importantly, when disruptive behavior is present, overall psychopathic traits, beyond CU, seem to account for emotion recognition deficits. Attentional patterns seemed biased in children and adolescents high on psychopathic traits and involve different patterns regarding the areas of interest analyzed, including the eyes or the mouth. Notwithstanding these results, the present review is characterized by a great heterogeneity in study designs and task conditions, hampering the establishment of firm conclusions. Considering the importance of this research for developmental models of psychopathic traits, replication studies, based on more standardized study characteristics, are particularly encouraged. 214 Clinical Child and Family Psychology Review (2024) 27:165–219 Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1056702300466-z. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study was supported by the Projects PID2019-107897RB-I00/ funded by MCIN/AEI/https://doi. org/10.13039/501100011033, and TED2021-130824B-C22, funded by MCIN/AEI/https://doi.org/10.13039/501100011033and the European Union (EU) “NextGenerationEU”/PRTR. B. Díaz-Vázquez’s was supported by a predoctoral contract funded by bank Santander and the University of Santiago de Compostela L. López-Romero’s contribution was supported by the grant RYC2021-032890-I, funded by MCIN/AEI/https://doi.org/10.13039/501100011033and the EU “NextGenerationEU”/PRTR. Data Availability The materials that support the findings of this study are available from the corresponding author, LLR, upon request. Declarations Conflict of interest The authors declare no conflicts of interest. Ethical approval All these funded research lines were approved by the Bioethical Committee at the University of Santiago de Compostela. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 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