Preferences for testing for sexually transmitted and blood-borne infections in adults in Canada: a discrete choice experiment
Bibliographic record
Abstract
OBJECTIVE: To quantify preferences for sexually transmitted and blood-borne infections (STBBI) testing in the general adult population in Canada. METHOD: We developed an online discrete choice experiment survey and administered it to a sample of the general Canadian population aged 19 and up recruited using an online market research panel. We included six attributes based on the literature and a qualitative study: location of test administration; requisition and personal information requirement; specimen collection method; test accuracy (false-negative rate); time to result and out-of-pocket costs. The final design consisted of six blocks of 10 choice tasks, plus three choice tasks that were used for consistency checks. Data were analysed using conditional logit, mixed logit and latent class models. RESULTS: Analyses were based on 5113 respondents. There were positive preferences for STBBI testing using less invasive methods of testing, missing fewer infections, having a shorter time to result and lower costs. Latent class analysis identified four classes: non-testers, accuracy-driven testers, doctor's office testers and multiattribute testers. Regardless of class, accuracy and costs remained the two most important attributes. These classes had different preferences for the location of testing and requisition and personal information requirements. Compared with non-testers, multiattribute testers were more likely to be African, Caribbean and/or black; under 25 years; indicate sexual activities that would place people at high risk for acquiring HIV; and use injection drugs. CONCLUSION: Adults in the general population in Canada indicated strong preferences for low-cost and accurate tests. A variety of testing locations may be needed to reach diverse populations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".