Characteristics of Sexual Health Programs for Migrants, Refugees, and Asylum Seekers: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Social, cultural, and structural determinants of health for migrants, refugees, and asylum seekers can contribute towards poorer sexual health outcomes. People from migrant, refugee, and asylum seeker backgrounds usually use less mainstream sexual healthcare services and have lower levels of sexual health literacy compared with the destination countries' general population. However, there is little collated knowledge about sexual health programs that have been implemented to improve sexual health among these groups. This study aimed to describe the characteristics of programs for improving sexual health among migrants, refugees, and asylum seekers. METHODS: This study was a scoping review in which Scopus and PubMed were searched for peer-reviewed articles published in English since 2010 from countries similar to and including Australia such as New Zealand, the United States of America, Canada, the United Kingdom, and European Union countries). The final search of databases was performed on 26 June 2023, and resultant studies were inputted into Endnote and Covidence systematic review software to remove duplicates before screening. The study utilised a qualitative approach using inductive thematic analysis of the content of the studies to extract and categorise the characteristics of the program. RESULTS: A total of 3044 articles were screened and 20 were included for data extraction. The included studies were conducted in six countries (the United States of America, Australia, France, Italy, Denmark, and Belgium). The key characteristics of sexual health programs identified included consumer consultation and engagement, cultural appropriateness, language support, peer education, self-directed learning, group learning, financial support, and outreach services. the programs had a combination of these characteristics to ensure that they can improve target population engagement with educational materials and decrease barriers to accessing sexual healthcare. CONCLUSION: Consideration of migrants, refugees, and asylum seekers' culture, language, socioeconomic characteristics, and access to information and services in the design of the sexual health programs may improve sexual health outcomes among these groups. However, further research is needed to assess the importance and implementation feasibility of the identified characteristics for sexual health programs in specific context.
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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 | 0.019 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.025 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".