Development and validation of the mobile adherence satisfaction scale (MASS) for medication adherence apps

Abstract

Objective

To develop and validate the Mobile Adherence Satisfaction Scale (MASS) for assessing user satisfaction with mobile health applications aimed to improve medication adherence.

Methods

The study involved patients over 18 with asthma, hypertension, heart failure, or diabetes, who used the CareAide® app for six months. Scale development included a literature review, expert consultations, and patient interviews, initially identifying 129 items. These were refined to 27 using a two-round Delphi technique and grouped into six dimensions: user interface, perceived usability, system quality, service quality, feature satisfaction, and general satisfaction. A pilot study with 30 participants further refined the model, which was then validated with 135 participants using exploratory and confirmatory factor analyses in SPSS 29 and SmartPLS 4. Data were collected via self-administered questionnaires.

Results

A total of 135 complete questionnaires were analysed. Respondents had an average age of 66.7 years (SD = 11.6) with 42.2 % male (n = 57) and 57.8 % female (n = 78). After removal of an item due to cross loading, exploratory factor analysis resulted six dimensions and 26 items with Kaiser-Meyer-Olkin measure of 0.837 and Bartlett's Test of Sphericity (χ²(n = 325) = 2085.673, P < 0.001). The confirmatory factor analysis confirmed high reliability and validity: Cronbach's alpha values > 0.70 for each dimension and an overall alpha of 0.89, with Composite Reliability and Average Variance Extracted both >0.70 and >0.50, respectively, for each dimension. Structural model indicated a significant positive impact of user interface (β = 0.226, P = 0.006) and feature satisfaction (β = 0.230, P = 0.002) on general satisfaction, explaining 23.1 % of the variance (R² = 0.231).

Conclusion

The study developed and validated the MASS, a reliable tool for assessing user satisfaction with mHealth apps. User interface design and feature satisfaction are key for long-term engagement and consistent medication adherence.