Background: As of 2016, there are approximately 36.7 million people living with HIV around the world. HIV infection is associated with tremendous psychological burden. Improvements in coping methods would be highly beneficial in this scenario. Crucial to this would be a high Coping Self-Efficacy (CSE). Defined as a “belief about one’s ability to perform specific coping behaviours”, CSE has been related to better adherence to ART, higher CD4 counts, lower viral loads, and a decrease in anxiety and depression in HIV patients. Our study attempted to assess and compare CSE in HIV infected individuals attending two healthcare facilities.

Methods: This was a cross sectional study involving 330 HIV patients registered for treatment at two healthcare facilities, with 165 participants from each. The Coping Self-Efficacy Scale, a 26-item interviewer-administered questionnaire was used to assess CSE. This is a visual analogue rating scale where the respondents are asked to rate their confidence in being able to perform certain coping strategies in times of distress, on a scale from 0 to 10. The sum of the scores for the individual items was then used to derive a Coping Self-Efficacy Score (CSES). Bivariate comparisons were done using CSES as the dependent variable. Variables with P<0.25 were included in a stepwise forward linear regression model.

Results: Mean CSES at Facility A was 184.85±22.99 and that at Facility B was 177.72±31.60 (P=0.020). Younger age, female sex, illiteracy and unemployment were significantly associated with a lower CSES (P<0.05). Similar results in literature have attributed the better CSE with age to confidence instilled by life experiences. In societies with a high “power difference”, like India, self-efficacy has been linked to the approval of authority figures. It could therefore be speculated that individuals with better education and employment may have possibly experienced greater instances of regard, resulting in better CSE. Lower CSE in women has been previously documented. The patients at Facility B had a higher rate of unemployment, possibly contributing to the difference in the scores between the facilities. The association with type of healthcare facility and sex of the participants persisted on linear regression, but accounted for only 5% of the variance, implying other unidentified factors at play, which could be explored in further studies.

Conclusions: In any health intervention, it is important to segment and prioritise beneficiaries and stakeholders. This is especially the case in resource poor settings, where ensuring that efforts reach those who most need them is imperative. Our findings indicate that the healthcare facility, age, sex, education and employment could influence CSE in HIV infected individuals in the study setting. These factors need to be targeted to improve coping with the disease in HIV infected individuals.