Transdiagnostic profiles of socio-affective functioning in adolescents at-risk of poor mental health.

Abstract

Background: Adolescence is a developmental period during which many mental health problems emerge or worsen. Recently, there has been a shift towards identifying risk factors that predict psychopathology across a range of diagnostic boundaries-known as 'transdiagnostic' approaches. There are several social and emotional risk factors for specific mental health diagnoses that have been well-characterised. Yet, there is limited understanding about how these socio-affective risk factors map onto transdiagnostic symptoms. We identified profiles of socio-affective functioning in early adolescence and how these profiles are associated with transdiagnostic symptoms of mental health problems.

Methods: Adolescents at heightened risk of general psychopathology aged 12-14 (N = 559, M _age = 13.26, SD_age = 0.72, 58.14% female) were recruited as part of a mental health trial. Participants completed questionnaire and task-based measures assessing emotion functioning (emotion perception, emotion regulation, and interoception), social relationships (with peers and family members), and mental health. Using a simple artificial neural network that projects a high-dimensional input to a 2D topology we were able to map differences in questionnaire- and task-based socio-affective profiles. Clustering was then used to identify zones within that 2D topology, indicating relatively homogenous profiles. Associations between these zones and transdiagnostic mental health symptoms were examined.

Results: We identified three reliable clusters of socio-affective functioning from the questionnaire measures and four clusters from the task-based measures. There were significant differences between questionnaire clusters on general psychopathology and p-free internalising symptoms, whereas there were only significant differences between task clusters on general psychopathology.

Conclusion: This study demonstrated the potential of data-driven methods to derive profiles of socio-affective functioning that are associated with transdiagnostic mental health problems. Through identifying socio-affective mechanisms that characterise these clusters, these findings can be used to identify active ingredients for future intervention development to prevent the onset and worsening of mental health problems in adolescence.