Addressing HIV Misconceptions among Heterosexual Black Men and Communities in Ontario
Bibliographic record
Abstract
Background. Black males accounted for 19.7% of all the new HIV diagnoses in Canada in 2020, yet Black people make up only 4.26% of the population. Persistent misconceptions about modes of HIV transmission need to be addressed to reduce the relatively high HIV prevalence among Black men. We described the HIV misconceptions held by some HBM in Ontario. We also identified the social determinants that are protective versus risk factors for HIV misconceptions among heterosexual Black men (HBM) in Ontario with a view to building evidence-based strategies for strengthening HIV prevention and stigma reduction among HBM and their communities in Ontario. Methods. We report quantitative findings of the weSpeak study carried out among HBM in four cities (Ottawa, Toronto, London, and Windsor) in Ontario. Sample size was 866 and sub-samples were: Ottawa (n = 210), Toronto (n = 343), London (n = 157), and Windsor (n = 156). Data were collected with survey questionnaire. The outcome variable, HIV misconception score ranging from 1 to 18, was measured by the number of statements on the HIV Knowledge Questionnaire with incorrect answers. We included three categories of independent variables in the analysis based on a stepwise and forward model selection approach. The variable categories include (i) sociodemographic background; (ii) personalised psychosocial attributes (levels of HIV misconceptions, negative condom attitude, age at sexual debut, and resilience); and (iii) socially ascribed psychosocial experiences (everyday discrimination and pro-community attitudes). After preliminary univariate and bivariate analyses, we used a hierarchical linear regression model (HLM) to predict levels of HIV misconceptions while controlling for the effect of the city of residence. Results. More than 50% of participants in all study sites were aged 20–49 years, married, and have undergone a college or university undergraduate education. Yet, a significant proportion (27.2%) held varying levels of misconceptions about HIV. In those with misconceptions, the two most common misconceptions were: (i) people are likely to get HIV by deep kissing, putting their tongue in their partner’s mouth, if their partner has HIV (40.1%); and (ii) taking a test for HIV one week after having sex will tell a person if she or he has HIV (31.6%). Discrimination (β = 0.23, p < 0.05, 95% CI = 0.01, 0.46), negative condom attitudes (β = 0.07, p < 0.05, 95% CI = 0.01, 0.12), and sexual debut at an older age (β = 0.06, p < 0.05, 95% CI = 0.01, 1) were associated with more HIV misconceptions. Being born in Canada (β = −0.96, p < 0.05, 95% CI = −1.8, −0.12), higher education (β = −0.37, p < 0.05, 95% CI = −0.52, −0.21), and being more resilient (β = −0.04, p < 0.05, 95% CI = −0.08, −0.01) were associated with fewer HIV misconceptions. Conclusion and recommendations. HIV misconceptions are still common, especially among HBM. These misconceptions are associated with structural and behavioural factors. We recommend structural and policy-driven interventions that promote more accessible and equity-driven healthcare, education, and social integration of HBM in Ontario. We also recommend building capacity for collective resilience and critical health and racial literacy as well as creating culturally safe spaces for intergenerational dialogues among HBM in their communities.
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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 | 0.000 |
| 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 | 0.001 |
| 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 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".