Effectiveness of peer-led health behaviour interventions on adolescent’s mental health and wellbeing: a systematic review and meta-analysis
Bibliographic record
Abstract
Mental health disorders affect 15% of youth aged 10-19 years globally, typically emerging before age 15. While school-based peer-led programs show promise in improving physical health behaviours by leveraging existing social networks, reducing stigma, and demonstrating high implementation feasibility, their effectiveness for mental health outcomes remains unclear. This systematic review examined controlled trials of school-based, peer-led lifestyle interventions (physical activity, diet, or sleep) reporting mental health outcomes in adolescents aged 10-19 years. Six electronic databases were searched up to March 28, 2024. Seven studies met inclusion criteria, encompassing 7,060 adolescents from 151 schools across the UK, USA, Canada, and Norway. Interventions varied in frequency and duration, with six focusing on physical activity and one on diet. Meta-analyses revealed no significant effects for psychological difficulties (MD = 0.60, 95% CI -3.52 to 4.72; p = 0.32, k = 2), self-efficacy for physical activity (SMD = 0.18, 95% CI -3.08 to 3.44; p = 0.61, k = 2), or wellbeing (SMD = 0.0, 95% CI -2.94 to 2.94; p = 1.0, k = 2). These findings, while requiring cautious interpretation, highlight the pressing need for more comprehensive and rigorous research to better understand the impact of peer-led interventions on mental health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".