Determinants of HIV Preexposure Prophylaxis Adherence Among Female Sex Workers in a Demonstration Study in Cotonou, Benin: A Study of Behavioral and Demographic Factors
Bibliographic record
Abstract
BACKGROUND: HIV preexposure prophylaxis (PrEP) efficacy is closely linked to adherence, and factors associated with PrEP adherence are not well understood and may differ across populations. As PrEP demonstration projects and implementation are ongoing, it is essential to understand factors associated with adherence to oral PrEP to design effective adherence interventions and maximize the public health impact of PrEP. We thus aimed to assess demographic and behavioral factors associated with optimal PrEP adherence (100%) among female sex workers (FSWs) participating in a demonstration project in Cotonou, Benin. METHODS: Female sex workers were provided with daily Truvada and followed quarterly for 1 to 2 years. Sociodemographics, partners, and behaviors were collected through face-to-face questionnaires. Another questionnaire based on sexual the theory of planned behavior and the theory of interpersonal behavior was also administered. Generalized estimating equations were used to identify factors associated with optimal daily adherence. RESULTS: At baseline, 255 FSWs were followed up. One-year increase in age of FSWs was associated with a 3% increase in optimal adherence (prevalence ratio, 1.03; 95% confidence interval, 1.01-1.05; P for trend = 0.0003), and optimal adherence decreased by 31% for every 6 months of follow-up (prevalence ratio, 0.69; 95% confidence interval, 0.59-0.79; P for trend < 0.0001). For the participants who have completed the behavioral questionnaires, high intention to adhere to the treatment was also a predictor of optimal adherence. CONCLUSIONS: Efforts should be geared toward FSWs intending to use PrEP to help them reach adequate adherence levels for effective HIV protection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".