Engaging young adult clients of community pharmacies for HIV screening in Coastal Kenya: a cross-sectional study: Table 1
Bibliographic record
Abstract
Background Adults in developing countries frequently use community pharmacies as the first and often only source of care. The objective of this study was to assess the success of pharmacy referrals and uptake of HIV testing by young adult clients of community pharmacies in the context of a screening programme for acute HIV-1 infection (AHI). Methods We requested five pharmacies to refer clients meeting predefined criteria (ie, 18–29 years of age and requesting treatment for fever, diarrhoea, sexually transmitted infection (STI) symptoms or body pains) for HIV-1 testing and AHI screening at selected clinics. Using multivariable logistical regression, we determined client characteristics associated with HIV-1 test uptake. Results From February through July 2013, 1490 pharmacy clients met targeting criteria (range of weekly averages across pharmacies: 4–35). Of these, 1074 (72%) accepted a referral coupon, 377 (25%) reported at a study clinic, 353 (24%) were HIV-1 tested and 127 (9%) met criteria for the AHI study. Of those tested, 14 (4.0%) were HIV-1 infected. Test uptake varied significantly by referring pharmacy and was higher for clients who presented at the pharmacy without a prescription versus those with a prescription, and for clients who sought care for STI symptoms. Conclusions About a quarter of targeted pharmacy clients took up HIV-1 testing. Clients seeking care directly at the pharmacy (ie, without a prescription) and those with STI symptoms were more likely to take up HIV-1 testing. Engagement of adult pharmacy clients for HIV-1 screening may identify undiagnosed individuals and offers opportunities for HIV-1 prevention research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".