Factors Associated with the Uptake of HIV Testing in Canada: Evidence from a Nationally Representative Study
Bibliographic record
Abstract
In this study, we explore the factors associated with the uptake of HIV testing at the national level in Canada. Using the 2015–16 Canadian Community Health Survey and applying logistic regression analysis, we examine the associations between HIV testing and factors identified by the Andersen’s behavioral model of healthcare utilization. We find that a range of predisposing, enabling, and need factors are significantly associated with HIV testing. For example, compared to the oldest respondents (i.e. 55–64), their younger counterparts (i.e. 45–54, 35–44, and 25–34) are more likely to have been tested for HIV. Compared to those in Atlantic Canada, respondents in Quebec (OR = 1.96, p < .001), Ontario (OR = 1.44, p < .001), Prairies (OR = 1.37, p < .001), British Columbia (OR = 1.99, p < .001), and the Territories (OR = 2.22, p < .001) are all more likely to have been tested for HIV. Based on these findings, we provide several important suggestions for policymakers and future 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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".