JOURNAL ARTICLE

PrEP-Related Interactive Toxicity Beliefs: Associations With Stigma, Substance Use, and PrEP Uptake.

  • Published In: AIDS Education & Prevention, 2023, v. 35, n. 2. P. 114 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Brousseau, Natalie M.; Driver, Redd; Simon, Kay; Watson, Ryan J.; Earnshaw, Valerie A.; Chandler, Cristian J.; Kalichman, Seth; Eaton, Lisa A. 3 of 3

Abstract

Despite documented efficacy in reducing HIV transmission, pre-exposure prophylaxis (PrEP) uptake among Black sexual minority men (BSMM) is limited. One understudied factor which may impede PrEP uptake is PrEP-related interactive toxicity beliefs (i.e., believing it is hazardous to use alcohol/drugs while taking PrEP). Data from N = 169 HIV negative BSMM over 4 months showed high rates of agreement with at least one alcohol (78%) or drug (84%) interactive toxicity belief. Univariate analyses showed increased alcohol or drug interactive toxicity beliefs predicted lower PrEP uptake. Multivariable regression suggested those with PrEP-related alcohol or drug interactive toxicity beliefs were more likely to report high PrEP stigma, more negative PrEP beliefs (e.g., concern that taking PrEP disrupts life), and were more likely to use alcohol/drugs (respectively) prior to/during sex. Findings warrant intervention work targeting interactive toxicity beliefs with tailored messaging to mitigate PrEP stigma and correct concerns around substance use and PrEP. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:AIDS Education & Prevention. 2023/04, Vol. 35, Issue 2, p114
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2023
  • ISSN:0899-9546
  • DOI:10.1521/aeap.2023.35.2.114
  • Accession Number:163446851
  • Copyright Statement:Copyright of AIDS Education & Prevention is the property of Guilford Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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