Original Article
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 100% of the participants responded to the first questionnaire. User experience was very high [mean SUS score =94.4 (92.07–96.76)]. Perceived usefulness (PU) was significantly correlated to intention to use (IU) (r=0.707, P<0.0001), and perceived ease of use (PEU) was significantly correlated to PU (r=0.466, P<0.0001). Path analysis confirmed the direct relationship between PU and IU (0.936, P<0.0001), and the indirect relationship between PEU and IU (0.5102, P<0.0001). Logistic regression analysis helped target items strongly influencing IU, such as “The use of the LearnTB application is compatible with my work habits” [OR =3.20 (1.04–9.84), P=0.004] and “The use of the LearnTB application could promote good clinical practice” [OR =5.23 (1.35–20.29); P=0.016].
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.
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 100% of the participants responded to the first questionnaire. User experience was very high [mean SUS score =94.4 (92.07–96.76)]. Perceived usefulness (PU) was significantly correlated to intention to use (IU) (r=0.707, P<0.0001), and perceived ease of use (PEU) was significantly correlated to PU (r=0.466, P<0.0001). Path analysis confirmed the direct relationship between PU and IU (0.936, P<0.0001), and the indirect relationship between PEU and IU (0.5102, P<0.0001). Logistic regression analysis helped target items strongly influencing IU, such as “The use of the LearnTB application is compatible with my work habits” [OR =3.20 (1.04–9.84), P=0.004] and “The use of the LearnTB application could promote good clinical practice” [OR =5.23 (1.35–20.29); P=0.016].
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.
