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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: May 2, 2024
Date Accepted: Mar 22, 2025

The final, peer-reviewed published version of this preprint can be found here:

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies

Stuke H, Schlack R, Erhart M, Kaman A, Ravens-Sieberer U, Irrgang C

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies

JMIR Public Health Surveill 2025;11:e60125

DOI: 10.2196/60125

PMID: 40354649

PMCID: 12088615

Peer relationships are a direct cause of the adolescent mental health crisis: an interpretable machine learning analysis of two large cohort studies

  • Heiner Stuke; 
  • Robert Schlack; 
  • Michael Erhart; 
  • Anne Kaman; 
  • Ulrike Ravens-Sieberer; 
  • Christopher Irrgang

ABSTRACT

Background:

Converging evidence indicates an adolescent mental health crisis in Western societies that has developed and exacerbated over the past decade. Proposed driving factors of this trend include more screen time, physical inactivity and social isolation but their causal influence on mental health is insufficiently understood.

Objective:

To test whether and based on which predictor variables the development of mental health in adolescents in the last decade can be predicted and to better understand the causal chain of factors at work.

Methods:

We implemented an interpretable machine learning pipeline with repeated cross-validation to assess the development of mental health throughout adolescence in members of two longitudinal cohort studies, the British Millenium cohort (MC, n = 8599) and the German KIGGS cohort (KIGGS, n = 1212). 144 (MC) and 102 (KIGGS) predictors assessed at the age of around 13.8 years (MC) and 11.6 years (KIGGS) were used to assess mental health at an age of around 16.7 years (MC) and 16.4 years (KIGGS). Based on these predictive models, we used permutation-based feature importance analyses to identify relevant predictors and predictor domains. Moreover, we performed partial dependence analyses in a causal inference framework to determine the direct effects of physical inactivity, screen time, and peer problems on the development of mental health.

Results:

The average cross-validated Pearson correlation between predicted and true mental health in late adolescence was r = 0.641 (MC) and 0.466 (KIGGS) using gradient boosting regression models. Feature importance analyses indicated a strong impact of pre-existing mental health and weaker impacts of sex (female as a risk factor), physical health (chronic disease as a risk factor), lifestyle, socioeconomic and family factors (e.g., low parental education, income and mental health as risk factors). Causal inference analyses suggested a strong proximate impact of peer relationships, but only a small impact of physical inactivity and a very small impact of screen time.

Conclusions:

Mental health development during adolescence can be assessed by a combination of variables from early adolescence. Peer problems represent an important proximal cause of mental health development and their deterioration may contribute to the current mental health crisis.


 Citation

Please cite as:

Stuke H, Schlack R, Erhart M, Kaman A, Ravens-Sieberer U, Irrgang C

Peer Relationships Are a Direct Cause of the Adolescent Mental Health Crisis: Interpretable Machine Learning Analysis of 2 Large Cohort Studies

JMIR Public Health Surveill 2025;11:e60125

DOI: 10.2196/60125

PMID: 40354649

PMCID: 12088615

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