Acceptability of an existing online sexually transmitted and blood-borne infection testing model among gay, bisexual and other men who have sex with men in Ontario, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives: Gay, bisexual and other men who have sex with men (GBM) are disproportionately affected by sexually transmitted and blood-borne infections (STBBI) due to stigma and other factors such as structural barriers, which delay STBBI testing in this population. Understanding acceptability of online testing is useful in expanding access in this population, thus we examined barriers to clinic-based testing, acceptability of a potential online testing model, and factors associated with acceptability among GBM living in Ontario. Methods: Sex Now 2019 was a community-based, online, bilingual survey of GBM aged ≥15. Prevalence ratios (PR) and 95% confidence intervals (95%CI) were calculated using modified Poisson regression with robust variances. Multivariable modelling was conducted using the Hosmer-Lemeshow-Sturdivant approach. Results: Among 1369 participants, many delayed STBBI testing due to being too busy (31%) or inconvenient clinic hours (29%). Acceptability for online testing was high (80%), with saving time (67%) as the most common benefit, and privacy concerns the most common drawback (38%). Statistically significant predictors of acceptability for online testing were younger age (PR = 0.993; 95%CI: 0.991-0.996); a greater number of different sexual behaviours associated with STBBI transmission (PR = 1.031; 95%CI: 1.018-1.044); identifying as an Indigenous immigrant (PR = 1.427; 95%CI: 1.276-1.596) or immigrant of colour (PR = 1.158; 95%CI: 1.086-1.235) compared with white non-immigrants; and currently using HIV pre-exposure prophylaxis (PrEP) compared to not currently using PrEP (PR = 0.894; 95%CI: 0.828-0.965). Conclusions: Acceptability of online testing was high among GBM in Ontario. Implementing online STBBI testing may expand access for certain subpopulations of GBM facing barriers to current in-person testing.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it