https://orcid.org/0000-0002-9923-1663
Abstract
Background
Self-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.
Purpose
This 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 Methods
A 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.
Results
Model 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.
Conclusion
The 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.
Acknowledgments
The authors gratefully appreciate the support of the investigators and all the participants.
Author Contributions
All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.
Disclosure
The authors have no conflicts of interest to declare.