Acceptability and adherence of a candidate microbicide gel among high-risk women in Africa and India
Bibliographic record
Abstract
Vaginal microbicides currently under development are substances that may prevent the transmission of HIV. Qualitative, in-depth post-trial interview data from a Phase III clinical trial of 6% Cellulose Sulfate microbicide gel in two sites in Africa (Uganda and Benin) and two in India (Chennai and Bagalkot) were examined in order to better understand factors that influence microbicide acceptability and adherence in a clinical trial setting. Women found the gel relatively easy to use with partners with whom there were no expectations of fidelity, in situations where they had access to private space and at times when they were expecting to engage in sexual intercourse. Adherence to gel seemed significantly more difficult with primary partners due to decreased perceptions of risk, inconvenience or fear of partner disapproval. Findings suggest that women in a variety of settings may find a microbicide gel to be highly acceptable for its lubricant qualities and protective benefits but that adherence and consistent use may depend greatly on contextual and partner-related factors. These findings have important implications for future trial designs, predicting determinants of microbicide use and acceptability and marketing and educational efforts should a safe and efficacious microbicide be found.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".