Indicators to Measure Adolescent Health at the Country, Regional, and Global Levels: Results of a Five-Year Selection Process by the Global Action for the Measurement of Adolescent Health
Bibliographic record
Abstract
PURPOSE: To improve adolescent health measurement, the Global Action for the Measurement of Adolescent health (GAMA) Advisory Group was formed in 2018 and published a draft list of 52 indicators across six adolescent health domains in 2022. We describe the process and results of selecting the adolescent health indicators recommended by GAMA (hereafter, "GAMA-recommended indicators"). METHODS: Each indicator in the draft list was assessed using the following inputs: (1) availability of data and stakeholders' perceptions on their relevance, acceptability, and feasibility across selected countries; (2) alignment with current measurement recommendations and practices; and (3) data in global databases. Topic-specific working groups comprised of GAMA experts and representatives of United Nations partner agencies reviewed results and provided preliminary recommendations, which were appraised by all GAMA members and finalized. RESULTS: There are 47 GAMA-recommended indicators (36 core and 11 additional) for adolescent health measurement across six domains: policies, programs, and laws (4 indicators); systems performance and interventions (4); health determinants (7); health behaviors and risks (20); subjective well-being (2); and health outcomes and conditions (10). DISCUSSION: These indicators are the result of a robust and structured five-year process to identify a priority set of indicators with relevance to adolescent health globally. This inclusive and participatory approach incorporated inputs from a broad range of stakeholders, including adolescents and young people themselves. The GAMA-recommended indicators are now ready to be used to measure adolescent health at the country, regional, and global levels.
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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 | 0.345 | 0.263 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".