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Record W3200216158 · doi:10.3390/adolescents1030028

Interventions and Strategies to Improve Sexual and Reproductive Health Outcomes among Adolescents Living in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis

2021· review· en· W3200216158 on OpenAlexaff
Salima Meherali, Mehnaz Rehmani, Sonam Ali, Zohra S Lassi

Bibliographic record

VenueAdolescents · 2021
Typereview
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsReproductive healthPsychological interventionAbortionMedicineFamily planningIncentiveReproductive rightsMeta-analysisEnvironmental healthPsychologyPsychiatryPopulationPregnancy

Abstract

fetched live from OpenAlex

Adolescent access to quality sexual and reproductive health and rights has been a major issue in most low- to middle-income countries (LMICs). This systematic review aims to identify the relevant community and school-based interventions that can be implemented in LMICs to promote adolescents’ sexual and reproductive health and rights. We identified 54 studies, and our review findings suggested that educational interventions, financial incentives, and comprehensive post-abortion family planning services were effective in increasing their knowledge and use of Adolescent Sexual and Reproductive Health and Rights (ASRHR) services, such as contraception, which led to a decrease in unwanted pregnancies. However, we found inconclusive and limited evidence on the effectiveness of interventions for improved violence prevention and adolescent behavior towards safe sexual practices. More rigorous studies with long-term follow-ups are needed to assess the effectiveness of such interventions.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.020
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.181
GPT teacher head0.481
Teacher spread0.300 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations35
Published2021
Admission routes1
Has abstractyes

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