Expanding Access to Non-Medicalized Community-Based Rapid Testing to Men Who Have Sex with Men: An Urgent HIV Prevention Intervention (The ANRS-DRAG Study)
Bibliographic record
Abstract
BACKGROUND: Little is known about the public health benefits of community-based, non-medicalized rapid HIV testing offers (CBOffer) specifically targeting men who have sex with men (MSM), compared with the standard medicalized HIV testing offer (SMOffer) in France. This study aimed to verify whether such a CBOffer, implemented in voluntary counselling and testing centres, could improve access to less recently HIV-tested MSM who present a risk behaviour profile similar to or higher than MSM tested with the SMOffer. METHOD: This multisite study enrolled MSM attending voluntary counselling and testing centres' during opening hours in the SMOffer. CBOffer enrolees voluntarily came to the centres outside of opening hours, following a communication campaign in gay venues. A self-administered questionnaire was used to investigate HIV testing history and sexual behaviours including inconsistent condom use and risk reduction behaviours (in particular, a score of "intentional avoidance" for various at-risk situations was calculated). A mixed logistic regression identified factors associated with access to the CBOffer. RESULTS: Among the 330 participants, 64% attended the CBOffer. Percentages of inconsistent condom use in both offers were similar (51% CBOffer, 50% SMOffer). In multivariate analyses, those attending the CBOffer had only one or no test in the previous two years, had a lower intentional avoidance score, and met more casual partners in saunas and backrooms than SMOffer enrolees. CONCLUSION: This specific rapid CBOffer attracted MSM less recently HIV-tested, who presented similar inconsistent condom use rates to SMOffer enrolees but who exposed themselves more to HIV-associated risks. Increasing entry points for HIV testing using community and non-medicalized tests is a priority to reach MSM who are still excluded.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".