South Africa has one of the highest HIV prevalence rates globally, with nearly 2.5 million people accessing antiretroviral treatment (ART) at the end of 2013. Retaining patients on ART has become a major problem in this country. When patients no longer show up for ART for unknown reasons, they are considered lost to follow-up (LTF). LTF is the highest contributor to ART attrition. This study, guided by the health belief model, evaluated the effectiveness of a technology-based, mobile health (mHealth) appointment reminder intervention on LTF among patients accessing ART services. The study ascertained differences in 6- and 12-month LTF rates between patients enrolled in the mHealth intervention (n = 832) and those in the standard of care comparison group (n = 918). A quantitative, retrospective cohort approach was used to answer the research questions using binary logistic regression analyses. The mHealth intervention was found to be significantly linked to lower likelihood of 6- and/or 12-month LTF among patients. There were 2 other key findings: a positive correlation between pregnancy and LTF, and a positive correlation between viral load increases and LTF. This study added evidence to the existing literature on the effectiveness of using mHealth-based interventions to improve HIV/AIDS care. Based on these findings, professionals should pay special attention to pregnant women and those clients with increasing viral loads to ensure they are not LTF. Positive social change that may result from this study is better health outcomes for patients on ART due to reduced risk of HIV related complications and other illnesses. This awareness would improve the lives of the patients, and positively impact their families, communities, and ultimately the global community, by reducing the overall impact of HIV disease.
Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-2346 |
Date | 01 January 2015 |
Creators | Jaffer, Ambereen |
Publisher | ScholarWorks |
Source Sets | Walden University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Walden Dissertations and Doctoral Studies |
Page generated in 0.0019 seconds