Explanation of treatment fatigue in MSM living with HIV: a comprehensive approach combining linear regression analyses, decision tree, and network analysis

Treatment fatigue in men who have sex with men (MSM) living with HIV have been documented in developed countries; there are still not many studies addressing this issue in China. Therefore, we aimed to investigate the current status of treatment fatigue among MSM living with HIV and identified associating factors. The data in this study were provided by the Population Health Data Archive. They were subjected to answering the general questionnaire and the HIV treatment regimen fatigue scale, the 20-item Toronto alexithymia scale, and the 6-item UCLA loneliness scale. Linear regression and decision tree model were used to identify associating factors. Network analysis was performed to construct the symptom network structure. A total of 739 MSM living with HIV from Harbin, China were included. The average score of treatment fatigue was -15.60 ± 22.49. The associating factors were age, household monthly income per capita, alexithymia and loneliness. Network analysis revealed that "Difficulty Identifying Feelings" and "Difficulty Describing Feelings" exhibited the strongest positive connection (weight = 0.483). Centrality metrics highlighted "Difficulty Identifying Feelings" as the most influential node (strength = 1.740, betweenness = 1.677). This study provides an in-depth integration of existing research on treatment fatigue among MSM living with HIV in China and suggests potential targets for MSM living with HIV, for the prevention, relief and cure of treatment fatigue.

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Publication Details

Journal
AIDS Care
Published
2026-07-23
DOI
https://doi.org/10.1080/09540121.2026.2697989
Primary Topic
Mental Health Research Topics
Type
article
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article

Explanation of treatment fatigue in MSM living with HIV: a comprehensive approach combining linear regression analyses, decision tree, and network analysis

W Zhang, Y Li, Jiahong Xie, Jingbo He et al.
AIDS Care
Mental Health Research Topics
article

Explanation of treatment fatigue in MSM living with HIV: a comprehensive approach combining linear regression analyses, decision tree, and network analysis

W Zhang, Y Li, Jiahong Xie, Jingbo He, Dajun Yang, Xianxian Deng, Yisong Yao, Baoyi Liao
article en

Abstract

Treatment fatigue in men who have sex with men (MSM) living with HIV have been documented in developed countries; there are still not many studies addressing this issue in China. Therefore, we aimed to investigate the current status of treatment fatigue among MSM living with HIV and identified associating factors. The data in this study were provided by the Population Health Data Archive. They were subjected to answering the general questionnaire and the HIV treatment regimen fatigue scale, the 20-item Toronto alexithymia scale, and the 6-item UCLA loneliness scale. Linear regression and decision tree model were used to identify associating factors. Network analysis was performed to construct the symptom network structure. A total of 739 MSM living with HIV from Harbin, China were included. The average score of treatment fatigue was -15.60 ± 22.49. The associating factors were age, household monthly income per capita, alexithymia and loneliness. Network analysis revealed that "Difficulty Identifying Feelings" and "Difficulty Describing Feelings" exhibited the strongest positive connection (weight = 0.483). Centrality metrics highlighted "Difficulty Identifying Feelings" as the most influential node (strength = 1.740, betweenness = 1.677). This study provides an in-depth integration of existing research on treatment fatigue among MSM living with HIV in China and suggests potential targets for MSM living with HIV, for the prevention, relief and cure of treatment fatigue.

AIDS Care
North Sichuan Medical University (CN), First Affiliated Hospital of Xiamen University (CN), Affiliated Hospital of North Sichuan Medical College (CN), Primary Health Care (QA), Chinese Academy of Governance (CN)
Openalex Percentile: Top 6%
Mental Health Research Topics
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