ArticleNature medicine2025
Prediction of mental health risk in adolescents.
Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Understanding adverse childhood experiences within the first decade of the ABCD study: A systematic review.Developmental cognitive neuroscience · 2026Pooled it
- Digital Interventions to Facilitate Screening, Brief Interventions, and Referral to Treatment for Substance Use Among Adolescents.Child and adolescent psychiatric clinics of North America · 2026Review
- Young minds in distress: Exploring the global rise in youth mental health diagnoses.Molecular psychiatry · 2026Review
- Can weight status in the first year of life predict well-being in the first years of school?International journal of obesity (2005) · 2026Article
- Deep learning reveals a neurocomputational mechanism predicting depression risk in adolescents.Science advances · 2026Article
- Friends, family, and community influences on adolescent development: A review of impactful findings from the ABCD study®.Developmental cognitive neuroscience · 2026Article
- Associations between transdiagnostic dimensions of psychopathology and brain structure and function in youth: What have we learned from the Adolescent Brain Cognitive Development (ABCD) study?Developmental cognitive neuroscience · 2026Article
- Harnessing artificial intelligence for pediatric health: Current trends and future opportunities.iScience · 2026Review
- Elevating sleep to a global health priority: The One Sleep Health framework.Cell reports. Medicine · 2026Review
- Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.Translational psychiatry · 2026Article
- Application and effectiveness of artificial intelligence in adolescent mental health support and therapy: a scoping review.BMC psychiatry · 2026Article
- Behavioral and Psychosocial Correlates of Gender Differences in Adolescent Mental Health: A Regional Cross-Sectional Study in Northern Italy.Behavioral sciences (Basel, Switzerland) · 2026Article
- 'It is just a prediction; it's, like, not fact': youth attitudes towards risk prediction tools and personalised preventive interventions for depression and anxiety.BMJ mental health · 2026Article
- Early attention deficit hyperactivity disorder prediction from longitudinal electronic health records.Nature. Mental health · 2026Article
- What we have learned about adolescent mental health and where we are going after a decade with the Adolescent Brain Cognitive Development Study.Developmental cognitive neuroscience · 2026Review
- Neuroimaging subtypes of adolescent sleep insufficiency stratify natural short sleepers from comorbidity or environment driven insufficiency.Nature communications · 2026Article
- The augmented clinician as a framework for human-AI collaboration in mental healthcare.Frontiers in psychiatry · 2026Article
- Reciprocal relationship among perceived sleep quality, smartphone overdependence, and depression in Korean adolescents: a cross-lagged analysis using national big data.Scientific reports · 2025Article
- Shared genetic architecture between anorexia nervosa and metabolomic biomarkers suggest underlying causal pathways.medRxiv : the preprint server for health sciences · 2025Article
- A large-scale study of chronic sleep disorders in psychiatric inpatients: Prevalence, hospitalization burden, restraint use, and comorbidities.European psychiatry : the journal of the Association of European Psychiatrists · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors.
Funding
Abstract
Prospective prediction of mental health risk in adolescence can facilitate early preventive interventions. Here, using psychosocial questionnaires and neuroimaging measures from over 11,000 children in the Adolescent Brain and Cognitive Development Study, we trained neural network models to stratify general psychopathology risk. The model trained on current symptoms accurately predicted which participants would convert into the highest psychiatric illness risk group in the following year (area under the receiver operating characteristic curve = 0.84). The model trained solely on potential etiologies or disease mechanisms achieved an area under the receiver operating characteristic curve of 0.75 without relying on the child's current symptom burden. Sleep disturbances emerged as the most influential predictor of high-risk status, surpassing adverse childhood experiences and family mental health history. Including neuroimaging measures did not enhance predictive performance. These findings suggest that artificial intelligence models trained on readily available psychosocial questionnaires can effectively predict future psychiatric risk while highlighting potential targets for intervention. This is a promising step toward artificial intelligence-based mental health screening for clinical decision support systems.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.