MétaCan
Menu
Back to cohort

Adolescent Health Interventions: Conclusions, Evidence Gaps, and Research Priorities

2016· review· en· W2521211380 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Adolescent Health · 2016
Typereview
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsSickKids FoundationCentre for Global Health ResearchHospital for Sick Children
FundersBill and Melinda Gates Foundation
KeywordsPsychological interventionMedicineAdolescent healthMental healthDisadvantagedSocioeconomic statusReproductive healthPopulationEnvironmental healthGerontologyPsychiatryNursingEconomic growth

Abstract

fetched live from OpenAlex

Adolescent health care is challenging compared to that of children and adults, due to their rapidly evolving physical, intellectual, and emotional development. This paper is the concluding paper for a series of reviews to evaluate the effectiveness of interventions for improving adolescent health and well-being. In this paper, we summarize the evidence evaluated in the previous papers and suggest areas where there is enough existing evidence to recommend implementation and areas where further research is needed to reach consensus. Potentially effective interventions for adolescent health and well-being include interventions for adolescent sexual and reproductive health, micronutrient supplementation, nutrition interventions for pregnant adolescents, interventions to improve vaccine uptake among adolescents, and interventions for substance abuse. Majority of the evidence for improving immunization coverage, substance abuse, mental health, and accidents and injury prevention comes from high-income countries. Future studies should specifically be targeted toward the low- and middle-income countries with long term follow-up and standardized and validated measurement instruments to maximize comparability of results. Assessment of effects by gender and socioeconomic status is also important as there may be differences in the effectiveness of certain interventions. It is also important to recognize ideal delivery platforms that can augment the coverage of proven adolescent health-specific interventions and provide an opportunity to reach hard-to-reach and disadvantaged population groups.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.543
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0020.001
Science and technology studies0.0040.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.010
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.606
GPT teacher head0.647
Teacher spread0.042 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it