Jun 2025 DOI 10.14302/issn.2324-7339.jcrhap-25-5559
Gamba PerryCorresponding author
Background HIV status disclosure is a complex process influenced by multiple factors beyond health system support. Understanding these factors is essential for developing comprehensive interventions to promote disclosure and improve HIV prevention and care outcomes. Methods A descriptive cross-sectional study was conducted in 10 health facilities offering comprehensive HIV/AIDS care in Mukono district, Uganda. Data was collected from 317 clients through interview-guided questionnaires. Data was entered using EPI data and analyzed using SPSS version 16, including logistic regression to identify factors associated with disclosure. Results Multiple factors influenced HIV status disclosure. Individual factors included knowledge about HIV (OR=2.34, 95% CI: 1.45-3.78), self-efficacy (OR=3.12, 95% CI: 1.87-5.21), and psychological readiness (OR=2.89, 95% CI: 1.76-4.75). Relationship factors included relationship quality (OR=3.56, 95% CI: 2.13-5.94), communication patterns (OR=2.78, 95% CI: 1.65-4.69), and anticipated partner reaction (OR=4.23, 95% CI: 2.54-7.05). Community factors included perceived stigma (OR=0.34, 95% CI: 0.21-0.56), cultural norms (OR=0.45, 95% CI: 0.27-0.75), and religious beliefs (OR=1.87, 95% CI: 1.12-3.14). Structural factors included economic dependence (OR=0.38, 95% CI: 0.23-0.63) and access to support services (OR=2.45, 95% CI: 1.47-4.08). Conclusions HIV status disclosure is influenced by a complex interplay of individual, relationship, community, and structural factors. Effective interventions to promote disclosure must address these multiple levels of influence, going beyond health system support to create enabling environments for disclosure at the individual, relationship, community, and structural levels.
Jan 2019 DOI 10.14302/issn.2643-6655.jcap-18-2541
S.O OyamakinCorresponding author
Department of Statistics, University of Ibadan, Nigeria
Many researchers have devoted considerable attention to the impact of individual-level factors on child mortality, but little is known about how family and community characteristics affect health of children. Trend in child mortality as well as its determinants, has long been the subject of academic and policy debates. In spite of this, the problem of child mortality remains as daunting as ever. In fact, advancement in medical sciences and the upsurge in information and telecommunication technology equipment have not significantly reduced child mortality in the country, unlike in the West. The Multilevel proportional hazards model for data that are hierarchically clustered at three levels was applied to the study of covariates of child mortality in Nigeria. This study merges two parallel developments of statistical tools for data analysis: statistical methods known as hazard models that are used for analyzing event-duration data and statistical methods for analyzing hierarchically clustered data known as multilevel models. These developments have rarely been integrated in research practice and the formalization and estimation of models for hierarchically clustered survival data remain largely uncharted. The model was estimated using the Newton-Raphsons numerical search approach. The model accounts for hierarchical clustering with three random effects or frailty effects. We assume that the random effects are independent and follow the Exponential and Weibull distribution. The results indicate that bio-demographic factors are more important in infancy while socioeconomic factors and household and environmental conditions have a greater effect in childhood. Furthermore, there is significant variation in child mortality risks even after controlling for measured determinants of mortality. Also, factors that fall under family and community level are more significant indicating that child survival is most controlled or determined by family and community factors and variables at the child level is not weighty. This suggests that there may exits unobserved or unobservable factors related to mortality.