Evaluating clinicians’ user experience and acceptability of LearnTB, a smartphone application for tuberculosis in India

Abstract

Background: Tuberculosis (TB) is the leading infectious killer, and India accounts for 2.8 of the 10.4 million TB cases that occur each year, making it the highest TB burden country worldwide. Poor quality of TB care is a major driver of the epidemic in India. India's large private, unregulated sector manages over 50% of the TB patients, with studies showing suboptimal diagnosis and treatment in the private sector. Better education of doctors using mobile applications (apps) is a possible solution. While India has seen an explosion of mobile phone services, and while the use of mobile health interventions has been gaining interest, little is known about mHealth around tuberculosis in India.Methods: Our study aimed to understand the user experience and acceptability of a smartphone application, LearnTB, amongst private sector academic clinicians in India. This study was conducted amongst 101 clinicians at Kasturba Hospital, Manipal, India. The user experience of participants (part 1) and acceptability (part 2) were evaluated with the use of two valid, English, paper-based questionnaires. The first questionnaire was based on the System Usability Scale (SUS); the second questionnaire was based on the Technology Acceptance Model (TAM). Data were collected during February and March 2017 and were analyzed using descriptive statistics, multiple linear regression as well as logistic regression analysis.Results: A response rate of 99% was achieved; 100 participants responded to the second questionnaire and Conclusion:The first part of the study indicated high user experience of the LearnTB application. The TAM questionnaire (second part) explained a significant portion of the variance in clinicians' IU the LearnTB application. The PU of the application has the highest impact on the clinicians' IU the Learn TB application.This study provides a preliminary analysis of mobile health interventions for tuberculosis in India, and emphasizes the need for future research in this domain. mHealth, 2017

A review of mobile health interventions for public private mix in tuberculosis care

“…All the papers that were included in this review were of moderate or high quality ranging from 62.5% ( Ali et al, 2016 ) to 83.3% ( Pande et al, 2017 ).…”

“…Four studies ( Lestari et al, 2017 ; Khan et al, 2012 ; Chadha et al, 2017 ; Pande et al, 2017 ) described data security protocols. Five studies ( Velayutham et al, 2015 ; Choun et al, 2017 ; Khan et al, 2012 ; Chadha et al, 2017 ; Ali et al, 2016 ) described support for replicability.…”

“…Five studies reported feedback from users ( Velayutham et al, 2015 ; Choun et al, 2017 ; Thu et al, 2020 ; Lestari et al, 2017 ; Ali et al, 2016 ). Six studies ( Velayutham et al, 2015 ; Lestari et al, 2017 ; Khan et al, 2012 ; Chadha et al, 2017 ; Pande et al, 2017 ; Ali et al, 2016 ) reported details about the content of the intervention (Intervention Content). Four studies ( Velayutham et al, 2015 ; Thu et al, 2020 ; Lestari et al, 2017 ; Khan et al, 2012 ) documented the usability/content testing with the participants.…”

“… The Rural Health Care Practitioners using mobile technology referred nearly nine times more presumptive TB cases than those without the technology Reduced the amount of time taken for diagnosis and treatment initiation. Pande et al, 2017 A pilot study among clinicians at a private hospital in Manipal India Study duration : 1 month Participants : 101 clinicians Learn TB Mobile app among private sector academic clinicians in Kasturba hospital, India To understand the user experience and acceptability of a smart phone application LearnTB among private sector academic clinicians. Experiences and acceptability 101 clinicians received the mobile app on iPads for use.…”

“… Based on the VoiceNet architecture that allows the usability on low-end mobile phones System complexity resulted into non usability Long period of time for case notification Poor system configuration that resulted into delays in notifying cases due to busy phone lines Mobile applications Thu et al, 2020 A mobile application for enhancing patient follow up by community health workers Notification of every diagnosed case by alerting the healthcare system and community health workers to proactively track and follow up patients The operation of the app are not discussed (how case notification was done, how the alerts for follow up were done) Doesn't describe the software framework on which the app was developed Lestari et al, 2017 A referral and reporting back system mobile phone app for case notification Utilized simplified version of NTP forms for case notification Secure centralized server for inputted information User registration and account creation Doesn't describe the software framework on which the app was developed Not standalone (requires internet to access) No reminder system to alert the private provider if the patient doesn't complete their treatment follow-up Chadha et al, 2017 ComCare mobile application for assisting rural health care providers (RHCPs) to identify and refer presumptive TB patients to the nearest microscopy Centre Generates SMS reminders for patients to adhere to referral Assists healthcare providers in providing guidance and counselling to patients Uses multimedia educational messages for RHCPs Not standalone (requires internet to access) Doesn't describe the software framework on which the app was developed Khan et al, 2012 A mobile phone based interactive application for community lay people to screen patients for TB in private clinics. The app allowed scheduling for sputum collection, initiation of treatment, clinic visits and drug dispersal Allows data entry and retrieval Secure centralized server for inputted information Doesn't describe the software framework on which the app was developed Pande et al, 2017 The ...…”