HIV prevention and missed opportunities among people with recently acquired HIV infection: Α protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: Individuals who have recently acquired HIV represent a unique population because the time frame since HIV acquisition is relatively short and identification of missed HIV prevention opportunities is, therefore, closer to real time and less subject to recall bias. Identifying prevention measures used and missed opportunities for using them, can help stop further HIV transmission. OBJECTIVES: This systematic review aims to synthesise current global evidence on uptake of HIV prevention methods among people with recently acquired HIV from 2007, the year that the concept of ART as a prevention method was first introduced. METHODS AND ANALYSIS: MEDLINE/PubMed, EMBASE, PsycINFO, Cochrane and Web of Science databases, will be searched for articles published January 2007-December 2023. Eligible studies will be those that reported on HIV prevention methods among people with recently acquired HIV. Quality assessment of the studies selected will be undertaken, and reporting of the systematic review will be informed by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. RESULTS: The systematic review is expected to provide comprehensive insights into the uptake, use and adherence to HIV prevention methods among individuals with recently acquired HIV. Analysis anticipates identifying gaps in prevention coverage, missed opportunities for intervention, and variations in access to and use of prevention strategies. Sociodemographic, personal, and behavioural factors influencing prevention uptake and adherence will also be synthesised. CONCLUSIONS: The findings will be of key relevance to researchers, healthcare providers including third sector organisations/ community groups and policymakers, as they will offer insight into better understanding of missed or failed HIV prevention efforts and will help ensure future efforts meet the needs of those in need of them.
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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 | 0.126 | 0.142 |
| Meta-epidemiology (narrow) | 0.008 | 0.008 |
| Meta-epidemiology (broad) | 0.023 | 0.021 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.057 | 0.009 |
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".