[Prevalence of Callous-Unemotional Traits in a German Adolescent Sample].

Prevalence of Callous-Unemotional Traits in a German Adolescent Sample Abstract: Background: Both the DSM-5 and ICD-11 introduced the specifier "with impaired prosocial emotions (IPE)" to more accurately diagnose Conduct Disorder (CD) in adolescents with conduct problems and elevated callous-unemotional (CU) traits. Thus, this also emphasizes the importance of these traits in predicting future maladaptive development. In the general adult population, the prevalence of CU traits is 4.5 % and varies between 2-6 % in adolescents. This study examines the applicability of the t-values developed by the LSU Developmental Psychology Lab (2023) to assess clinically relevant or critical callous-unemotional (CU) traits in adolescents in the German general population. We investigate whether these internationally calculated t-values can be used validly for the German-speaking countries without calculating own t-values or cut-off values based on the sample. Methods: The sample consists of N = 1622 adolescents (50 % female), with an average age of M = 13.63 years, whom we recruited at schools. To categorize the present data, the study utilized age- and gender-based norms (t-scores) from the 2023 Developmental Psychopathology Lab's community sample. We employed t-tests and ANOVAs to determine significant age differences (11-14 years, 15-17 years), gender, and gender-by-age interaction effect groups. Results: Our findings indicate that 91.5 % of the sample falls within the normative group, 4.3 % are at risk, and 4.2 % display clinical characteristics. We observed significant age differences, while gender differences were not prominent. The interaction effects of age and gender were significant. Posthoc analyses revealed significant differences between male adolescents and between male and female adolescents across both age groups. Conclusion: The study provides valuable insights into the prevalence of CU traits in a German school sample. Understanding the distribution of CU traits is crucial for early detection and the development of tailored interventions. In addition to educational staff, professionals in the clinical context also benefit from early identification to initiate targeted diagnostic and therapeutic measures.