Determinants of Willingness to Use Oral HIV Pre-Exposure Prophylaxis Among Transgender Women in Colombia
Bibliographic record
Abstract
Purpose: This study examined the willingness of transgender women (TGW) to use oral HIV pre-exposure prophylaxis (PrEP) to prevent HIV. Using the information-motivation-behavioral skills (IMB) model, the study considered both social (e.g., unstable housing) and psychosocial (e.g., depressive symptoms) influences on this willingness. Methods: We conducted a cross-sectional study of TGW from October 2020 to February 2021, collaborating with community-based organizations to administer face-to-face surveys. We used logistic regression to identify the determinants of willingness to use PrEP and test the mediating effect of PrEP self-efficacy on the relationship between information/motivation and the willingness to use PrEP, as well as the effects of social and psychosocial factors on the IMB model. Results: A total of 68% of participants, with an average age of 32, were willing to use PrEP within 12 months. Willingness was higher among those who were younger, had lower socioeconomic status, lacked stable housing, or held positive attitudes toward PrEP. Information factors were not related to willingness. Motivational factors such as positive social norms and high self-efficacy increased willingness, whereas depressive symptoms and PrEP-related stigma reduced it. Motivational factors mediated the relationship between depressive symptoms and willingness to use PrEP. Conclusions: The IMB model effectively explained the main determinants of willingness to use PrEP in the studied population. Interventions addressing motivations, reducing PrEP-related stigma, and managing depressive symptoms are crucial for TGW. Future research and interventions should focus on younger and more socially vulnerable TGW who are willing to use oral PrEP.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".