Social support factors influencing adherence to ARV among patients attending Kisii Level Five Hospital

Abstract

Background: Antiretroviral adherence is the second strongest predictor of progression to AIDS and death, after CD4 count. The average rate of adherence to ART is approximately 70%, despite the fact that long-term viral suppression requires near-perfect adherence rate. Achieving such high rates of adherence is very challenging to patients due to a range of factors but more so on social support related factors. This study sought to investigate the influence of social support factors to ART adherence and the underlying factors. Methods: A cross sectional study involving 333 adult HIV clients enrolled on ART for more than three months in Kisii Hospital. The clients were selected through systematic sampling and data was collected using interviewer administered questionnaire. Two homogeneous focus group discussions for men and women were conducted. Data from interviewer administered questionnaire was cleaned, coded and entered into Statistical Package for Social Scientists (SPSS) version 11.5 and analyzed for frequencies, cross-tabulations and Chi-Squared test at statistical significance set at p<0.05. Qualitative data from focus group discussion was translated, transcribed and coded through listing and organization of the data under key thematic areas derived from the objectives. Results: Seventy percent (69.7%) of the respondents were females while 30% were males. Among all respondents, 49.2% were married with more females at 25.8% married as compared to men at 23.4%. The mean age of the patients was 37.7 years with a range of between 21- 63 years. About 40.8% of the respondents had attained secondary or post secondary education. Eighty percent (79.9%) of the respondents took drugs according to the prescribed time. The most cited reasons for missing the timing of the drugs were forgetting 13.2%, being busy 6% and being away from home 3%. Main social support factors that were found to significantly influence adherence based on timing of taking drugs included membership to CBO (p=0.002) and disclosure to close family members who included brother (p=0.02) and sister (p=0.014). The study found high knowledge levels that significantly affected adherence (p=0.001). Conclusion: Adherence rates were found to be relatively high and key social support variables that were found to be significantly associated with adherence were disclosure and membership to CBO. Other key factors affecting adherence include forgetting, being too busy, being away from home and lack of transport. Recommendations: PLWHIV should be facilitated to join existing community groups so as they can discuss and interact together with the rest of community members as this can greatly help and motivate them in their treatment and adherence. Disclosure being an entry point to social related support for PLWHIV, there is need to scale up couple and family counseling sessions as well as support initiatives that are geared towards reducing stigma and discrimination to PLWHIV.