Addressing HIV Misconceptions among Heterosexual Black Men and Communities in Ontario
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».