Editorial Mental Health Policy for Children and Adolescents in Developing Countries
Bibliographic record
Abstract
About half of all lifetime mental disorders begin before the age of 14 years1,2. Worldwide prevalence rates for child and adolescent mental disorders are around 10%-20%, with similar types of disorders seen across cultures3-5. Young people have a high rate of self-harm, and suicide is a leading cause of death in young people2. An Indian study reported that suicide accounted for a quarter of deaths in boys and between half and three-quarters of deaths in girls aged 10-19 years6. Poor mental health is strongly related to other health and development concerns in young people notably lower educational achievements, substance abuse, violence, and poor reproductive and sexual health2. The suffering, functional impairment, exposure to stigma and discrimination, and enhanced risk of premature death that is associated with mental disorders in young people has obvious public-health significance. It is obvious that ‘no health is possible without mental health ’ and that mental health issues form an integral part of child development. The effectiveness of some interventions (including promotive and preventive interventions) for mental disorders in this age-group have been established, although more research is urgently needed to improve the range of affordable and feasible
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.027 | 0.026 |
| Insufficient payload (model declined to judge) | 0.034 | 0.016 |
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".