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Objective: To Analysis of the mediation effects of adverse mental health outcomes in HIV-infected women of childbearing age from multiple perspectives including discrimination perception, social capital, and other factors. Methods: A cross-sectional survey was conducted among 553 people in Xinjiang region of China using Survey scale. AMOS was used to identify factors that influenced the "discrimination perception/mental resilience/social capital-depression-poor mental health outcomes" pathway. Results: A total of 44.85% and 42.13% of the study participants had anxiety and depression symptoms, as perceived discrimination increased, the higher the level of depression in HIV-infected women of childbearing age. Correlation coefficient among depression with poor mental health outcomes was also significant. Psychological resilience, social capital and depression have mediating effects on perceived discrimination and poor mental health outcomes, discrimination perception had an indirect effect on depression through social capital and an indirect effect on adverse mental health outcomes through depression and psychological resilience. The modified model has a good fitting effect. Conclusion: Discrimination perception was shown to affect adverse mental health outcomes by impacting mental resilience, depression, and social capital. The findings suggest the need for measures to reduce adverse mental health outcomes by decreasing discrimination perception, increasing social capital, and enhancing psychological resilience.
RESUMEN
PURPOSE: The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. PATIENTS AND METHODS: A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ2-test and a binary logistic regression model. RESULTS: This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. CONCLUSION: Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.