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Record W4416947080 · doi:10.1093/her/cyaf056

Sexual health literacy and education programs for culturally and linguistically diverse young people living in Australia, Canada, New Zealand, and the United Kingdom: a scoping review of content evaluations

2025· review· en· W4416947080 on OpenAlexaboutno aff
Ruth Wagstaff, Kirstie Daken, Amy B. Mullens, Claire Moran, Zhihong Gu, Yibeltal Alemu, Judith A. Dean

Bibliographic record

VenueHealth Education Research · 2025
Typereview
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
FundersQueensland Health
KeywordsGrey literatureReproductive healthGovernment (linguistics)LiteracyProgram evaluationImmigrationContent analysisCultural competenceSocioeconomic status

Abstract

fetched live from OpenAlex

Young people from key priority communities, represent an important focus for enhancing sexual and reproductive health (SRH). There is an abundance of literature indicating that sexual health programs designed to improve sexual health literacy (SHL) for young people from culturally and linguistically diverse (CALD) backgrounds are often developed using established health behaviour models and community involvement models. However, little evidence exists on the processes or standards used to evaluate program effectiveness or update content to remain relevant and appealing. This scoping review of academic literature, and government and not-for-profit organizations reports in Australia, Canada, New Zealand, and the United Kingdom (countries with similar healthcare systems, immigration patterns and socioeconomic status), was conducted to determine if and how program content was reviewed and evaluated for currency and effectiveness. No academic or grey literature reports were identified that described the assessment of SHL program content or resources targeting young people from CALD backgrounds. Organizations and authors were contacted for further details of program content assessment with little success. This suggests a gap in the literature and lack of program evaluation or processes for updating of program content. This review highlights recommendations regarding advancing future research and enhancing program content evaluation.

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)0.014
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.534
GPT teacher head0.639
Teacher spread0.105 · 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 designSystematic review
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

Citations0
Published2025
Admission routes1
Has abstractyes

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