Can an HIVSmart! App-optimized Self-Testing Strategy be Operationalized in Canada?
Bibliographic record
Abstract
Abstract Background Although HIV self-tests are recommended by the WHO, they are not yet approved in Canada. Service delivery gaps such as linkages to counseling and care remain unachieved by offering self-tests without adequate support. In this first Canadian study, we evaluated the feasibility of operationalizing an innovative HIVSmart! app-optimized oral HIV self-testing strategy in men who have sex with men (MSM), presenting at a large sexual health clinic in Montreal. Methods Between July 2016 to February 2017, participants were offered the OraQuick In-Home HIV Test, and a tablet installed with the HIVSmart! app, at a private office in the clinic to simulate an unsupervised home environment. With the HIVSmart! app, participants independently performed and interpreted self-tests, and were linked to in-person post-test counseling and care. Self-test results were confirmed by laboratory tests (p24, Western Blot, RNA as needed). Results The mean age of the 451 participants was 34 years (18–73); 85% were well educated (beyond high school, n = 371/438); 53% (230/438) were frequent testers (past 6 months), and 13% were on PrEP (52/451). 99% (417/422) of participants found the HIVSmart! app helpful in guiding them through the self-testing procedure; 93% (418/451) of participants interpreted their tests accurately; and 94% (395/419) stated they would recommend the app-optimized self-testing strategy to their partners. Feasibility (completion rate of self-testing) was 93% (419/451), and acceptability of the strategy was high at 99% (451/458). All HIV self-test negative participants (448/451, 100%) were counseled following the self-test. Three participants self-tested positive, were confirmed HIV positive (0.7% prevalence), and were rapidly linked to care with a physician. Conclusion The HIVSmart! app-optimized strategy was feasible, and highly accepted by an educated, frequently testing, urban MSM population of Montréal. With the app, participants were able to interpret their test results accurately and were rapidly linked to care. Innovations like HIVSmart! which engage, aid, and facilitate linkages to care, can be adapted to suit the needs of many populations in Canada and internationally, maximizing global impact through reverse innovation. Disclosures All authors: No reported disclosures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".