Characteristics and influencing factors of anticipated HIV stigma among HIV‐negative/unknown MSM in China: A regression mixture model

• Published in: Brain and behavior 2024-04, Vol.14 (4), p.e3472-n/a
• Main Authors: Dai, Zhenwei, Wu, Yijin, Liu, Xin, Fu, Jiaqi, Si, Mingyu, Chen, Xu, Wang, Hao, Xiao, Weijun, Huang, Yiman, Yu, Fei, Mi, Guodong, Su, Xiaoyou
• Format: Article
• Language: English
• Subjects: Acquired immune deficiency syndrome; AIDS; anticipated stigma; China; Cross-Sectional Studies; Discrimination; Disease prevention; HIV; HIV Infections - psychology; HIV‐negative/unknown MSM; Homosexuality, Male - psychology; Human immunodeficiency virus; Humans; Male; Males; Mental health; Questionnaires; regression mixture model; Sexual and Gender Minorities; Social support; Statistical analysis; Stigma
• ISSN: 2162-3279; 2162-3279
• DOI: 10.1002/brb3.3472

Background Anticipated HIV stigma among men who have sex with men's (MSM) has a severe negative effect on their physical and mental health wellbeing and hence requires specific attention. The current study aims to identify the characteristics and the psychosocial influencing factors of anticipated HIV stigma in MSM using regression mixture model (RMM) and to determine the cut‐off point of the seven‐item Anticipated HIV Stigma Questionnaire (AHSQ) using the receiver operating characteristic (ROC) analysis. Methods A cross‐sectional study was conducted among HIV‐negative/unknown MSM from Blued online platform in China from December 16th, 2020 to March 1st, 2021, enrolling 1394 participants. Data were collected on demographic characteristics, perceived social support, anticipated HIV stigma, depressive symptoms, and HIV knowledge. Latent profile analysis was performed to identify different profiles of anticipated HIV stigma level. Chi‐square test, analysis of variance, and RMM analysis were conducted to explore the influencing factors in different profiles. ROC analyses were carried out to identify the cut‐off value of anticipated stigma. Results Among the participants, three profiles of anticipated stigma were identified: “low anticipated HIV stigma” (12.0%), “moderate anticipated HIV stigma” (52.1%), and “severe anticipated HIV stigma” (35.9%). RMM analysis showed that higher income and higher levels of knowledge were positively associated with moderate anticipated HIV stigma, whereas full‐time job and social support were negatively associated with moderate anticipated HIV stigma; higher income, depressive symptoms, and knowledge were positively associated with severe anticipated HIV stigma, whereas minor ethnicity and social support were negatively associated with severe anticipated HIV stigma. ROC curve of the AHSQ showed that the optimal cut‐off value of ≥16 could indicate positive anticipated HIV stigma. Conclusion The study focuses on the level of anticipated HIV stigma and its psycho‐socio influencing factors among HIV‐negative/unknown MSM. It provides evidence for implementing relevant psychological interventions to HIV‐negative/unknown MSM. Profiles of anticipated HIV stigma in MSM.