Global research priorities for youth mental health
Bibliographic record
Abstract
AIM: Over the past two decades, the youth mental health field has expanded and advanced considerably. Yet, mental disorders continue to disproportionately affect adolescents and young adults. Their prevalence and associated morbidity and mortality in young people have not substantially reduced, with high levels of unmet need and poor access to evidence-based treatments even in high-income countries. Despite the potential return on investment, youth mental disorders receive insufficient funding. Motivated by these continual disparities, we propose a strategic agenda for youth mental health research. METHOD: Youth mental health experts and funders convened to develop youth mental health research priorities, via thematic roundtable discussions, that address critical evidence-based gaps. RESULTS: Twenty-one global youth mental health research priorities were developed, including population health, neuroscience, clinical staging, novel interventions, technology, socio-cultural factors, service delivery, translation and implementation. CONCLUSIONS: These priorities will focus attention on, and provide a basis for, a systematic and collaborative strategy to globally improve youth mental health outcomes.
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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 | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.014 | 0.024 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".