| Literature DB >> 34792650 |
Jan Stochl1,2,3, Hannah Jones4, Emma Soneson5, Adam P Wagner6,7, Golam M Khandaker5,8, Stanley Zammit4,9, Jon Heron4, Gemma Hammerton4, Edward T Bullmore5, Ray Dolan10, Peter Fonagy11, Ian M Goodyer5, J Perez5,6,7,8,12, Peter B Jones5,6,8.
Abstract
Characterizing patterns of mental phenomena in epidemiological studies of adolescents can provide insight into the latent organization of psychiatric disorders. This avoids the biases of chronicity and selection inherent in clinical samples, guides models of shared aetiology within psychiatric disorders and informs the development and implementation of interventions. We applied Gaussian mixture modelling to measures of mental phenomena from two general population cohorts: the Avon Longitudinal Study of Parents and Children (ALSPAC, n = 3018) and the Neuroscience in Psychiatry Network (NSPN, n = 2023). We defined classes according to their patterns of both positive (e.g. wellbeing and self-esteem) and negative (e.g. depression, anxiety, and psychotic experiences) phenomena. Subsequently, we characterized classes by considering the distribution of diagnoses and sex split across classes. Four well-separated classes were identified within each cohort. Classes primarily differed by overall severity of transdiagnostic distress rather than particular patterns of phenomena akin to diagnoses. Further, as overall severity of distress increased, so did within-class variability, the proportion of individuals with operational psychiatric diagnoses. These results suggest that classes of mental phenomena in the general population of adolescents may not be the same as those found in clinical samples. Classes differentiated only by overall severity support the existence of a general, transdiagnostic mental distress factor and have important implications for intervention.Entities:
Keywords: Adolescence; Classification; Psychopathology; Transdiagnostic approach
Year: 2021 PMID: 34792650 DOI: 10.1007/s00787-021-01909-0
Source DB: PubMed Journal: Eur Child Adolesc Psychiatry ISSN: 1018-8827 Impact factor: 4.785