JOURNAL ARTICLE
Moderated Effects of Latinx Ethnicity for a Stepped-Care, Technology and Counseling-Based Intervention (Positive STEPS) on Antiretroviral Adherence and Viral Load Suppression Among Youths With HIV, United States, 2018‒2023.
Published In: American Journal of Public Health, 2026, v. 116. P. S36 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Yonko, Elizabeth A.; Garofalo, Robert; Mimiaga, Matthew J. 3 of 3
Abstract
This article focuses on a secondary analysis of the Positive Strategies to Enhance Problem-Solving Skills (Positive STEPS) intervention, a stepped-care, technology and counseling–based program designed to improve antiretroviral therapy (ART) adherence and viral load suppression among adolescents and young adults (AYA) with HIV in the United States. The analysis examined whether Latinx ethnicity moderated the intervention's effects, finding that Latinx participants randomized to Positive STEPS experienced equal or greater improvements in ART adherence and viral suppression compared with non-Latinx peers, despite facing unique behavioral and psychosocial barriers. The intervention, implemented from 2018 to 2023 in Providence, Boston, and Chicago, used personalized text reminders and cognitive behavioral therapy sessions tailored to adherence needs. These findings suggest that Positive STEPS may effectively address disparities in HIV treatment outcomes among Latinx AYA, though further research is needed to assess its applicability in broader geographic and cultural contexts.
Additional Information
- Source:American Journal of Public Health. 2026/03, Vol. 116, pS36
- Document Type:Article
- Subject Area:Consumer Health
- Publication Date:2026
- ISSN:0090-0036
- DOI:10.2105/AJPH.2025.308341
- Accession Number:191890526
- Copyright Statement:Copyright of American Journal of Public Health is the property of American Public Health Association 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.