Predictors of the Acceptance of an Electronic Coach Targeting Self-management of Patients With Type 2 Diabetes: Web-Based Survey

Background: Type 2 diabetes (T2D) is a lifestyle-related disease whose prevalence increases with age. Diabetes self-management through mobile health (mHealth) apps enables patients with T2D to improve their health. According to the Technology Acceptance Model (TAM), technology acceptance (ie, intended use) is necessary to ensure mHealth can be implemented successfully. Therefore, the specific acceptance requirements of patients with T2D should be considered. Objective: This cross-sectional study aims to examine the extent to which different TAM predictors are associated with the acceptance of a diabetes app including an electronic coach (eCoach; Iris app) among patients with T2D. Methods: Using a web-based survey, data on 92 patients with T2D (mean age 62.76 years, SD 8.29 years) were collected. Acceptance of the Iris app with the TAM predictors (ie, perceived usefulness, perceived ease of use, social influence, perceived self-efficacy, perceived security, prior usage experience, perceived health, and propensity of data/information sharing) was assessed. Further, control variables (ie, gender, age, education, ethnicity, household, BMI, amount of years with diabetes, diabetes-related complaints, and medication use) were assessed. Results: Multiple linear regression analyses showed that acceptance of the Iris app was positively associated with perceived usefulness (beta=.57, P<.001), social influence (subjective norm; beta=.20, P=.004), and willingness to share data (beta=.25, P<.001). In addition, acceptance regarding the Iris app was higher among patients with T2D with overweight (beta=.23, P=.01) or obese BMI (beta=.21, P=.01). The model explained 75.8% of the variance in the acceptance of the Iris app by patients with T2D. In addition, perceived usefulness of the Iris app was positively related to perceived ease of use (beta=.32, P<.001), subjective norm (beta=.26, P=.004), perceived control (beta=.19, P=.03), willingness to share data (beta=.20, P=.01) regarding the Iris app, and perceived security regarding general use of apps/smartphone/internet (beta=.15, P=.04). The model explained 58.2% of the variance in patients' perceived usefulness about the Iris app. Conclusions: Among patients with T2D, the belief that the use of the Iris app is helpful/beneficial, the willingness to share their Iris app data, and others' approval of using this app can stimulate the acceptance of this app. In addition, the belief that the use of (health) apps is reliable and secure, the belief that the use of the Iris app is easy to use, a higher perceived capability and personal control with using this app, the willingness to share their Iris app data, and others' approval of using this app can stimulate the perceived usefulness of such an app. These TAM predictors explained a high variance in acceptance and perceived usefulness of the Iris app. Implications for practice are addressed.