Health and well-being of refugee women in sex work: A systematic literature review
Bibliographic record
Abstract
Introduction: Refugees face many barriers when arriving in a new country, and these barriers are especially felt by women, who often travel alone or with children. These barriers create a situation where some women turn to sex work, either voluntarily or involuntarily. Both refugees and sex workers face adversities related to their mental health and well-being, however little research has examined the intersections between both identities outside of STI incidence and violence. Objective: This systematic literature review aimed to explore mental health and overall well-being of women refugees who engage in sex work. Themes were extracted to better understand experiences to inform clinical and community practice. Methods: A systematic literature review was conducted using PsycInfo, CINAHL, Scopus, Web of Science, PubMed, Google Scholar, ProQuest, and Medline, as well as grey literature for articles published between 2013 and 2023. The JBI Critical Appraisal Checklist for Qualitative Research was used to evaluate the quality of the primary research articles. 11 articles were included in the final synthesis. Results: The five themes included Fear, Mental/Psychological Health, Social Well-being, Economic/Financial Well-being, and Spiritual Struggles. These themes were interconnected to shape the experiences of these women within their circumstances. Engaging in sex work as a refugee, particularly in instances of sex trafficking, created significant challenges in all aspects of well-being, and the circumstances related to being a refugee often increased vulnerabilities to become involved in sex work for survival. Conclusion: These results suggest the need for policies, community programs, and clinical practice protocols to address the unique needs of women refugees to mitigate factors drawing them to sex work, and better support those who are currently involved in it.
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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 | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.018 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 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".