Detecting user experience issues from mHealth apps that support stroke caregiver needs: an analysis of user reviews

Existing research has demonstrated the potential of mHealth apps in improving the caregiving outcomes of stroke. Since most of the apps were published in commercially available app stores without explaining their design and evaluation processes, it is necessary to identify the user experience issues to promote long-term adherence and usage.

The purpose of this study was to utilize published user reviews of commercially available apps to determine the user experience issues to guide future app development in stroke caregiving.

User reviews were extracted from the previously identified 46 apps that support stroke caregiving needs using a python-scraper. The reviews were pre-processed and filtered using python scripts to consider English reviews that described issues faced by the user. The final corpus was categorized based on TF-IDF vectorization and k-means clustering technique, and the issues extracted from the various topics were classified based on the seven dimensions of user experience to highlight factors that may affect the usage of the app.

A total of 117,364 were extracted from the two app stores. After filtration, 13,368 reviews were included and classified based on the user experience dimensions. Findings highlight critical issues that affect the usability, usefulness, desirability, findability, accessibility, credibility, and value of the app that contribute to decreased satisfaction and increased frustration.

The study identified several user experience issues due to the inability of the app developers to understand the needs of the user. Further, the study describes the inclusion of a participatory design approach to promote an improved understanding of user needs; therefore, limiting any issues and ensuring continued use.