Abstract
This study investigated health-related quality of life and identified factors affecting it among people with the HIV in South Korea. A total of 243 people living with HIV participated in this cross-sectional survey. Data were collected from five hospitals between November 2021 and August 2022 using structured online questionnaires. Data were analyzed using descriptive statistics, Mann-Whitney U test, Kruskal-Wallis test, Spearman’s rho analysis, and Tobit regression analysis because a significant ceiling effect was observed for the dependent variable. The mean score for the health-related quality of life was 75.74 ± 16.48. The significant factors that positively influence the health-related quality of life were “employment” (B = 4.57, p = .035), “not participating in the self-help group” (B = 6.10, p = .004), “higher self-efficacy for managing symptoms” (B = 1.32, p = .036), “higher self-efficacy for getting support/help” (B = 0.95, p = .035), and “higher self-efficacy for managing fatigue” (B = 2.80, p < .001) in the Tobit regression analysis. The results suggest that interventions to increase self-efficacy should involve developing programs and policies for people living with HIV. There is a need for efforts to provide healthcare services linked to employment support, as well as to establish a social environment in which they can work without stigma. Further, self-help groups could be utilized as intervention channels.
Funder
National Research Foundation of Korea grant funded by the Korea government
Brain Korea 21 FOUR Project funded by National Research Foundation
Publisher
Public Library of Science (PLoS)
Reference46 articles.
1. Joint United Nations Program on HIV/AIDS (UNAIDS). 2021. UNAIDS Data. [Cited 2023 March 21]. https://www.unaids.org/en/resources/documents/2021/2021_unaids_data.
2. Korea Disease Control and Prevention Agency. HIV/AIDS notifications in the Republic of Korea; 2021. Database: Figshare. [Cited 2023 March 21]. https://www.kdca.go.kr/contents.es?mid=a20301070504.
3. Narrowing the gap in life expectancy between HIV-infected and HIV-uninfected individuals with access to care;JL Marcus;J Acquir Immune Defic Syndr,2016
4. Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status;GS Kim;AIDS Care,2022
5. The role of stigma in the acceptance and disclosure of HIV among recently diagnosed men who have sex with men in Australia: A qualitative study;JE Bilardi;PLoS ONE,2019