Self-care strategies that support PrEP adherence: a qualitative study with female sex workers in rural Uganda
Bibliographic record
Abstract
The World Health Organization (WHO) recently released revised guidelines on self-care interventions for health and well-being, which, in 2022, included recommendations supporting equitable access to information about and availability of pre-exposure prophylaxis (PrEP) as a self-care strategy. Successful implementation of PrEP as an HIV prevention strategy extends beyond providing access to medication. It hinges on individuals adopting self-care strategies to ensure adherence to PrEP in their daily lives. This paper aims to explore self-care strategies that bolster adherence to oral PrEP among female sex workers in two rural Ugandan settings. Through in-depth interviews with 20 female sex workers residing in fishing communities or Trans-Africa highway towns, we used deductive thematic analysis to explore people-centred and health system-centred perspectives on women's PrEP-related self-care strategies. A people-centred perspective on self-care illustrated a range of self-care strategies to support PrEP adherence conducted by women individually (medication reminders; pairing PrEP with daily habits), and with support from others in familial and social networks (verbal reminders to take tablets; information sharing; shared clinic visits; shared pill-taking routines). A health system-centred perspective illustrated the importance of support from health services and professionals. Examples included information provision; NGO clinics as friendly, safe, non-judgemental spaces; PrEP distribution through home-based care outreach strategies; in-bulk PrEP provision for work-related travel periods; formal integration of female sex workers into the system as peer health workers. By considering both person-centred and health system-centred perspectives on self-care, we can pinpoint strategies for health systems to assist female sex workers and their communities in preventing the acquisition and transmission of HIV.
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 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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".