Risk Compensation in the Context of Sexually Transmitted Infections in Women Using the Dapivirine Vaginal Ring in Africa: A Scoping Review
Bibliographic record
Abstract
Background: Sexually transmitted infections (STIs) remain a critical public health challenge globally, with Africa facing the highest incidence and mortality rates. The Dapivirine Vaginal Ring (DVR) is a discreet HIV prevention tool for women but does not protect against other non-HIV STIs. Like any other HIV biomedical prevention tool, DVR might lead to increased STI prevalence. Thus, this scoping review assessed the prevalence of STIs and the sociocultural, economic, and demographic factors influencing STI risk among African women using DVR in Africa. The review also examined current policies and interventions to reduce STI risk. Method: We searched electronic databases such as the Ovid platform, MEDLINE, Embase, Global Health, CINAHL, Web of Science, Cochrane Library databases, Social Sciences Citation Index, and Gray literature from January 2014 to July 2024. The Rayyan tool was used to screen the title and abstract, whereas DistillerSR Version 2 was used for the full text screening. The qualitative data were analyzed for themes using QDA Miner Lite, while the numeric data was analyzed using the Microsoft Excel Package. This scoping review followed the PRISMA-ScR guidelines. Result: (9.38%), and syphilis (0.90%). Sociocultural, economic, and demographic factors, including poverty, patriarchy, location, knowledge, and age, were found to influence STI risk among women using DVR. Suggested policies include routine STI screening, education, targeted interventions, and partner treatment frameworks to effectively control STIs. Conclusion: Our findings reveal no evidence of risk compensation with DVR use. Holistic sexual health services are needed to support the use of DVR and prevent other STIs. Further research on biomedical tools that prevent both HIV and other STIs is crucial to address this gap.
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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".