Integrated Theory-Based Health and Development Interventions for Young People: A Global Scoping Review
Bibliographic record
Abstract
BackgroundMost health and developmental issues affecting young people are interrelated. However, few interventions address multiple behavioral domains simultaneously or are based on theories that encompass a holistic perspective of youth development.AimThe purpose of this scoping review was to identify and describe the range of theory-based, multibehavioral health interventions aimed at improving two or more of the following behavioral youth outcomes: (1) sexual and reproductive health; (2) education and employment; (3) violence; and (4) substance use.MethodsInterventions conducted worldwide and published in English or Spanish between January 2000 and July 2020 were identified using four databases: PubMed, PsycINFO, LILACS, and SciELO.ResultsA total of 11,084 articles were identified, of which 477 were retrieved and assessed for eligibility. Twenty-three articles (evaluating 21 interventions) ultimately met the inclusion criteria. Most interventions were conducted in the United States and addressed two behavioral domains of interest, although seven interventions incorporated three domains, and one incorporated all four. Substance use was the most common domain (16 interventions) but only in the United States/Canada, followed by sexual and reproductive health (14 interventions). All produced significant improvement in at least one outcome or for at least one subgroup of youth. The most common theoretical foundations were positive youth development and social learning theory.ConclusionIntegrated interventions that are theory based and evidence informed can support positive development and empower youth to make healthy decisions. Further efforts are needed to address structural and policy issues that affect young people’s developmental opportunities and health outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.029 | 0.021 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".