Uptake of Community-Based Peer Administered HIV Point-of-Care Testing: Findings from the PROUD Study
Bibliographic record
Abstract
OBJECTIVES: HIV prevalence among people who inject drugs (PWID) in Ottawa is estimated at about 10%. The successful integration of peers into outreach efforts and wider access to HIV point-of-care testing (POCT) create opportunities to explore the role of peers in providing HIV testing. The PROUD study, in partnership with Ottawa Public Health (OPH), sought to develop a model for community-based peer-administered HIV POCT. METHODS: PROUD draws on community-based participatory research methods to better understand the HIV risk environment of people who use drugs in Ottawa. From March-October 2013, 593 people who reported injecting drugs or smoking crack cocaine were enrolled through street-based recruitment. Trained peer or medical student researchers administered a quantitative survey and offered an HIV POCT (bioLytical INSTI test) to participants who did not self-report as HIV positive. RESULTS: 550 (92.7%) of the 593 participants were offered a POCT, of which 458 (83.3%) consented to testing. Of those participants, 74 (16.2%) had never been tested for HIV. There was no difference in uptake between testing offered by a peer versus a non-peer interviewer (OR = 1.05; 95% CI = 0.67-1.66). Despite testing those at high risk for HIV, only one new reactive test was identified. CONCLUSION: The findings from PROUD demonstrate high uptake of community-based HIV POCT. Peers were able to successfully provide HIV POCT and reach participants who had not previously been tested for HIV. Community-based and peer testing models provide important insights on ways to scale-up HIV prevention and testing among people who use drugs.
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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 | 0.005 | 0.016 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".