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Citation |
O'Donnell S, Scott-Storey K, Malcolm J, Vincent CD, Wuest J. Res. Nurs. Health 2024; ePub(ePub): ePub. |
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Copyright |
(Copyright © 2024, John Wiley and Sons) |
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DOI |
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PMID |
38722053 |
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Abstract |
Despite Canada having the highest disease burden globally for cannabis use disorder (CUD) and violence being ubiquitous in men's lives, little is known about how intersections among social determinants of health (SDOH) and cumulative lifetime violence severity (CLVS) influence CUD in men post-cannabis legalization. Using data collected in a survey with a national community sample of 597 men who self-identified as having experienced violence, we conducted a latent profile analysis using 11 subscales of the CLVS-44 scale and explored differential associations between CLVS profiles and CUD considering SDOH covariates. Four profiles were distinguished by intersections among CLVS-44 subscale severity and roles as target and perpetrator. CLVS profiles were significantly associated with CUD in the unadjusted model and in the adjusted model where age, adverse housing, and education were significant covariate controls. In the adjusted model, CUD was differentially associated with CLVS profiles and significantly higher in Profile 4 (highest severity target and perpetrator) than in Profile 1 (lowest severity target, no perpetration). Chi-square tests showed significant intersection between adverse housing, younger age, Profile 4 CLVS, and moderate to severe CUD among cannabis users. These results reveal the importance of understanding simultaneous intersections among indicators of CLVS in determining profiles of lifetime violence. Also critical are intersections among CLVS profiles and significant covariates as a basis for trauma- and violence-informed care for CUD that prioritizes men most disadvantaged by this convergence and attends to individual and structural health disparities at practice and policy levels. Language: en |
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Keywords |
cannabis use disorder; cumulative lifetime violence; housing; intersectionality; latent profile analysis |