• Patient Prefer Adher · Jan 2021

    Identification of Self-Management Behavior Clusters Among People Living with HIV in China: A Latent Class Profile Analysis.

    • Hong Zhang, Yao Yin, Huan Wang, Ying Han, Xia Wang, Yi Liu, and Hong Chen.
    • West China School of Nursing, Sichuan University/West China Hospital, Sichuan University, Chengdu, Sichuan Province, People's Republic of China.
    • Patient Prefer Adher. 2021 Jan 1; 15: 1427-1437.

    BackgroundSelf-management directly affects the health outcomes and quality of life among people living with HIV (PLWH). A better understanding of self-management level will provide evidence for researchers to develop effective interventions.PurposeThis study aims to identify the latent classes among PLWH in their levels of self-management behavior, and to explore the sociodemographic and disease-related predictors within these classes.Materials And MethodsA total of 868 PLWH were recruited from August 2017 to January 2019 in Sichuan Province, China. A latent class profile analysis was used to identify participants' self-management behavior, and multinomial logistic regression was used to explore the sociodemographic and disease-related predictors of the different latent classes.ResultsModel fit indices supported a three-class model. The mean self-management scores in the three classes were 23.56 (SD=6.02), 37.91 (SD=3.80), and 47.95 (SD=4.18), respectively. The latent classes were Class 1 (a poor level of self-management behavior, 12.1%, n=104), Class 2 (a moderate level of self-management behavior, 56.1%, n=491) and Class 3 (a good level of self-management behavior, 31.7%, n=273). Antiretroviral trerapy (ART) status, infection route, and educational level were the main predictors of self-management behavior.ConclusionThe findings indicated that the level of self-management behaviors among PLWH in China is inadequate. Those with a lower educational level, who were infected through blood/injecting drugs, and who were not receiving ART, showed a significantly lower level of self-management behavior. These results could help healthcare professionals to quickly recognize PLWH who are at a high risk of low-level self-management, using individual characteristics and could provide a scientific basis for the development of effective and targeted programs to improve self-management level in PLWH.© 2021 Zhang et al.

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