HIV Risk Perceptions and the Distribution of HIV Risk among African, Caribbean and Other Black People: Mixed-Methods Results from the BLACCH Study
Bibliographic record
Abstract
BACKGROUND: African, Caribbean and other Black people (ACBP) are a priority group for HIV prevention efforts in Canada. ACBP and service providers’ (SP) perceptions about HIV risk impact the uptake and delivery of prevention messages. These perceptions may not reflect actual risk among ACBP, so it is important to assess them and identify groups for which they may be valid. Emerging evidence from Sub-Saharan Africa shows that social determinants of health (SDOH) impact the distribution of HIV risk. However, SDOH are context-specific, and to date, virtually no research has explored their impact on HIV risk among ACBP in North America. OBJECTIVE: Compare ACBP’s and SP’s perceptions about HIV risk among ACBP to a corresponding quantitative risk profile. METHODS: Using a community-based approach, a purposive sample of eight SPs and 22 ACBP were recruited for qualitative interviews. They were asked questions about HIV, and their responses are being analyzed using qualitative content analysis to identify themes. Following the interviews, a convenience sample of 188 ACBP completed a quantitative questionnaire covering HIV-related risk behaviours. Quantitative data were analyzed to describe the distribution of HIV risk behaviours according to the following SDOH: gender, poverty status, educational attainment, immigration experience, ethnicity and employment status. Qualitative and quantitative data were compared using concurrent triangulation. RESULTS: Interview participants mainly discussed sexual behaviours related to HIV risk, and the survey results showed that much of the community’s risk is sexual in nature. Risk behaviours acknowledged by ACBP and SP that showed statistically significant variation according to the SDOH include: forced sex, condom use, sex while drunk or high, and abstinence. It appears as though individuals with higher social status (based on SDOH) are at higher risk than those of lower social status. DISCUSSION: Further analyses including statistical weights need to be performed before these results can be finalized.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".