Adolescent Health and Well-Being: Background and Methodology for Review of Potential Interventions
Bibliographic record
Abstract
Owing to child survival initiatives around the world in the 1970s and 1980s, a dramatic rise in the population of adolescents has been seen, especially in the developing countries. A quarter of world's population in 2012 comprised adolescents and young adults; of these, 90% lived in low- and middle-income countries. More recently, there has been a consensus on investing in adolescent health and development for the success of post-2015 developmental agenda. In this series of articles, we aimed to assess various interventions identified in our conceptual framework to evaluate their effectiveness in improving adolescent health. We took a systematic approach to consolidate the existing evidence. This article is an introductory article detailing the background, conceptual framework, and methodology used for synthesizing evidence, followed by seven articles summarizing evidence on interventions for sexual/reproductive health, nutrition, immunization, mental health, substance abuse, and accidents/injury. The concluding article of the series summarizes the findings of the all the previous articles in the series and the relevance of the evidence for action in the post-2015 Millennium Development Goals era along with evidence gaps and future research priorities.
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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 | 0.053 | 0.089 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.023 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".