Identifying adolescents at risk for depression: Assessment of a global prediction model in the Great Smoky Mountains Study

Arthur Caye, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Lauro E. Marchionatti, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Rivka Pereira, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Helen L. Fisher, King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom; ESRC Centre for Society and Mental Health, King's College London, London, United Kingdom.
Brandon A. Kohrt, Division of Global Mental Health, Department of Psychiatry, School of Medicine and Health Sciences, The George Washington University, Washington, DC, United States.
Valeria Mondelli, King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, United Kingdom; National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, United Kingdom.
Ellen McGinnis, University of Vermont, Burlington, VT, United States.
William E. Copeland, University of Vermont, Burlington, VT, United States.
Christian Kieling, Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Child and Adolescent Psychiatry Division, Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil. Electronic address: ckieling@ufrgs.br.

Document Type

Journal Article

Publication Date

8-20-2022

Journal

Journal of psychiatric research

Volume

155

DOI

10.1016/j.jpsychires.2022.08.017

Keywords

Adolescence; Depression; Prediction; Prevention; Risk score; Young adult

Abstract

The Identifying Depression Early in Adolescence Risk Score (IDEA-RS) has been externally assessed in samples from four continents, but North America is lacking. Our aim here was to evaluate the performance of the IDEA-RS in predicting future onset of Major Depressive Disorder (MDD) in an adolescent population-based sample in the United States of America - the Great Smoky Mountains Study (GSMS). We applied the intercept and weights of the original IDEA-RS model developed in Brazil to generate individual probabilities for each participant of the GSMS at age 15 (N = 1029). We then evaluated the performance of such predictions against the diagnosis of MDD at age 19 using simple, case-mix corrected and refitted models. Furthermore, we compared how prioritizing the information provided by parents or by adolescents affected performance. The IDEA-RS exhibited a C-statistic of 0.63 (95% CI 0.53-0.74) to predict MDD in the GSMS when applying uncorrected weights. Case-mix corrected and refitted models enhanced performance to 0.69 and 0.67, respectively. No significant difference was found in performance by prioritizing the reports of adolescents or their parents. The IDEA-RS was able to parse out adolescents at risk for a later onset of depression in the GSMS cohort with above chance discrimination. The IDEA-RS has now showed above-chance performance in five continents.

Department

Psychiatry and Behavioral Sciences

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