P15-11. Preventive HIV vaccine acceptability: a systematic review and meta-analysis
Bibliographic record
Abstract
The effectiveness of a preventive vaccine in controlling the epidemic will be contingent on acceptability and access. The objective of this systematic review was to synthesize results from investigations of HIV vaccine acceptability to assess: 1) rates of HIV vaccine acceptability and 2) factors impacting HIV vaccine acceptability. We used a comprehensive search strategy to locate relevant articles across multiple electronic databases, including Medline, AIDSLine, CINAHIL and EMBASE, with no language or time restrictions. We included original qualitative or quantitative studies examining rates or correlates of HIV vaccine acceptability. Two authors independently assessed study quality and extracted data. We conducted meta-analysis on studies reporting correlates or predictors of HIV vaccine acceptability and calculated effect sizes for each variable. Twenty-nine original studies (n = 11,477; 17 quantitative, 12 qualitative) were included, from North America (n = 24), Africa (n = 3), Central America (n = 1) and Asia (n = 1). HIV vaccine acceptability, reported in 19 studies, ranged from 94.0 to 37.2 on a 100-point scale, with mean acceptability = 65.6 (SD = 20.5). Mean acceptability was 74.5 (SD = 9.4) at high (80–95%) versus 39.4 (SD = 21.1) at moderate (50%) efficacy (p < 0.001), reported concurrently in 10 studies. Twelve studies (n = 4,768) were included in meta-analysis. HIV vaccine acceptability was positively correlated with: efficacy (r = 0.35, p < 0.001), perceived susceptibility to HIV (r = 0.26, p < 0.001), and perceived vaccine benefits (r = 0.17, p < 0.05); and negatively associated with: cost (r = -0.33, p < 0.05), not being in a "risk group" (r = -0.32, p < 0.001), pragmatic obstacles (r = -0.29, p < 0.05), fear of vaccines (r = -0.20, p < 0.05), side effects/safety concerns (r = -0.16, p < 0.01), fear of needles (r = -0.12, p < 0.05), and African American ethnicity (r = -0.08, p < 0.05). Findings support development of tailored educational, social and structural interventions to promote uptake of partially efficacious HIV vaccines. Cost subsidies and measures to facilitate access and address vaccine fears, attitudes and low HIV risk perceptions may support roll-out of HIV vaccines.
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 | 0.013 | 0.052 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.018 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".