The ethical, social, and cultural dimensions of screening for mental health in children and adolescents of the developing world
Bibliographic record
Abstract
Despite their burden and high prevalence, mental health disorders of children and adolescents remain neglected in many parts of the world. In developing countries, where half of the population is younger than 18 years old, one of every five children and adolescents is estimated to suffer from a mental health disorder. It is then essential to detect these conditions through screening in a timely and accurate manner. But such screening is fraught with considerable ethical, social, and cultural challenges. This study systematically identifies, for the first time, these challenges, along with potential solutions to address them. We report on the results of an international multi- and inter-disciplinary three-round Delphi survey completed by 135 mental health experts from 37 countries. We asked these experts to identify and rank the main ethical, social, and cultural challenges of screening for child and adolescent mental health problems in developing nations, and to propose solutions for each challenge. Thirty-nine significant challenges emerged around eight themes, along with 32 potential solutions organized into seven themes. There was a high degree of consensus among the experts, but a few interesting disagreements arose between members of the panel from high-income countries and those from low- and middle-income nations. The panelists overwhelmingly supported mental health screening for children and adolescents. They recommended ensuring local acceptance and support for screening prior to program initiation, along with careful and comprehensive protection of human rights; integrating screening procedures into primary care; designing and implementing culturally appropriate screening tools, programs, and follow-up; securing long-term funding; expanding capacity building; and task-shifting screening to local non-specialists. These recommendations can serve as a guide for policy and decision-making, resource allocation, and international cooperation. They also offer a novel approach to reduce the burden of these disorders by encouraging their timely and context-sensitive prevention and management.
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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 | 0.046 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".