Immigrant generational status and the uptake of HIV screening services among heterosexual men of African descent in Canada: Evidence from the weSpeak study
Bibliographic record
Abstract
Canada became a preferred destination for many non-European and non-American migrants since the introduction of favorable immigration policies in the late 1960 s. Blackimmigrants from the African and Caribbean regions however are a known vulnerable population to HIV infection in Canada. Even though first-generation immigrants might differ from subsequent generations in terms of culture and beliefs which are important for health outcomes and behaviors, research examining disparities in their use of preventative healthcare is limited. This study aimed to examine generational disparities in the uptake of HIV screening services among a sample of heterosexual Black men in Ontario, Canada. We used data from a cross-sectional survey sample (n = 829) that was collected from heterosexual Black men in four Ontarian cities (Toronto, Ottawa, London and Windsor) between March 2018 and February 2019. We used the negative log-log link function of the binomial family to examine the independent relationship between immigration status and the uptake of HIV testing and the cumulative effect of other predictor variables on HIV testing in nested models. Findings from multivariate analysis show second-generation immigrants were significantly less likely to test for HIV compared with their first-generation immigrant counterparts. After controlling for theoretically relevant variables, the second-generation immigrants were 53% less likely to test for HIV. We further observed that participants with good knowledge of HIV transmission (OR=1.05; p > 0.05) and those who were older were more likely to test for HIV. Those with masculine tendencies (OR=0.98; p > 0.05) and those who reported not having sexual partner were less likely to test (OR=0.57; p > 0.01). Religion emerged as a significant predictor of HIV testing as Christians (OR=1.62; p > 0.05) and other believers (OR=1.59; p > 0.05) were more likely to test for HIV when compared to their Muslim counterparts. HIV prevention policies may need not only prioritize first-generation immigrants, but the wellbeing of their descendants as well. This could be achieved by implementing programs that will enhance second-generation immigrants’ use of HIV screening services. Additionally, HIV educational programs would be of relevance and especially so as respondents with good knowledge of HIV transmission consistently demonstrated higher likelihood of testing for their HIV status.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| 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".