Post-test comparison of HIV test knowledge and changes in sexual risk behaviour between clients accessing HIV testing online versus in-clinic
Bibliographic record
Abstract
Objective Internet-based HIV testing offers the potential to address privacy-related barriers to testing and increase frequency of testing but may result in missed opportunities related to sexual health education and prevention that typically occur in face-to-face encounters. In this study, we assessed the HIV test knowledge and sexual risk behaviour of clients testing for HIV throughGetCheckedOnline, an internet-based sexually transmitted and bloodborne infection testing platform inclusive of HIV testing, in comparison to clients testing through a large sexual health clinic. Methods We concurrently recruitedGetCheckedOnlineclients and clinic clients from Vancouver, Canada, over the course of a 10-month period during 2015–2016. Participants completed baseline and 3-month questionnaires, anonymous and online. A six-item score was used to estimate knowledge of HIV test concepts typically conveyed during an HIV pretest encounter in a clinic. We used multiple regression to estimate associations between testing modality (online vs clinic based) and two outcomes—HIV test knowledge and change in condom use pre/post-test—with adjustment for relevant background factors. Results Among 352 participants, online testers demonstrated higher HIV post-test knowledge than clinic-based testers (mean score 4.65/6 vs 4.09/6; p<0.05); this difference was reduced in adjusted analysis (p>0.05). Men who have sex with men, clients with a university degree, those who have lived in Canada >10 years and English speakers had higher HIV post-test knowledge (p<0.05). Eighteen per cent of online testers and 10% of clinic-based testers increased condom use during the 3 months post-test (p>0.05). Conclusions In this comparative study between online and clinic-based testers, we found no evidence of decreased HIV test knowledge or decreased condom use following HIV testing throughGetCheckedOnline. Our findings suggest that with careful design and attention to educational content, online testing services may not lead to missed opportunities for HIV education and counselling.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".