Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 17, 2019
Date Accepted: Jun 22, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Explaining differences in the acceptability of 99DOTS, a cellphone-based strategy for monitoring adherence to tuberculosis medications: a qualitative study of patients and healthcare providers
ABSTRACT
Background:
99DOTS is a cellphone-based strategy for monitoring tuberculosis (TB) medication adherence that has been rolled out to more than 150,000 patients in India’s public health sector. A considerable proportion of patients stop using this monitoring approach during TB therapy. We aimed to understand reasons for variability in the acceptance of 99DOTS by TB patients and healthcare providers (HCPs).
Objective:
We aimed to understand reasons for variability in the acceptance of 99DOTS by TB patients and healthcare providers (HCPs).
Methods:
We conducted qualitative interviews with individuals taking TB therapy in the government program in Chennai (HIV co-infected patients) and Mumbai (HIV un-infected patients) across both the intensive and continuation treatment phases. We also conducted interviews with HCPs with various roles in TB care, all of whom were involved in implementing 99DOTS. Interviews were transcribed, coded using a deductive approach, and analyzed with Dedoose 8.0.35 software. Study findings were interpreted using the Unified Theory of Acceptance and Use of Technology (UTAUT), which highlights four constructs associated with technology acceptance: performance expectancy, effort expectancy, social influences, and facilitating conditions.
Results:
We conducted 62 interviews with TB patients, of whom 30 (48%) were HIV co-infected, and 31 interviews with HCPs. Acceptance of 99DOTS by patients was variable. Greater patient acceptance was related to perceptions of improved patient-HCP relationship due to increased phone communication, TB pill-taking habit formation due to SMS reminders, and reduced need to visit health facilities (performance expectancy); improved family involvement in TB care (social influences); and from 99DOTS leading HCPs to engage positively in their care through increased outreach and interactions (facilitating conditions). Lower patient acceptance was related to perceptions of a poorer patient-HCP relationship due to less face-to-face contact (performance expectancy); problems with cellphone access, literacy or signal, or program fatigue (effort expectancy); high TB- and HIV-related stigma within the family or community (social influences); and poor counseling in 99DOTS by HCPs or perceptions HCPs were not acting upon adherence data (facilitating conditions). Acceptance of 99DOTS by HCPs was generally high and related to perceptions that the 99DOTS patient adherence dashboard and patient-related SMS alerts improve quality of care, efficiency of care, and the TB patient-HCP relationship (performance expectancy); that the dashboard is easy to use (effort expectancy); and that 99DOTS leads to better coordination among HCPs (social influences). However, HCPs described suboptimal facilitating conditions during 99DOTS rollout, including inadequate training of HCPs, unequal changes in HCP workload, and shortages of 99DOTS medication envelopes.
Conclusions:
In India’s government TB program, 99DOTS had high acceptance by HCPs but variable acceptance by TB patients. While some factors contributing to suboptimal patient acceptance are modifiable, others—such as TB- and HIV-related stigma and poor cellphone accessibility, cellular signal, and literacy—are more difficult to address. Screening for these barriers may facilitate better targeting of 99DOTS to patients more likely to use this technology.
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