Validation and usability study of the framework for a user needs-centered mHealth app selection.

ABSTRACT

BACKGROUND: Most mHealth app users rely on an app's rankings, star ratings, or reviews, which may not reflect users' individual healthcare needs. To help healthcare providers, researchers, and users select an optimal mHealth app, the Method of App Selection based on User Needs (MASUN) 1.01 was developed and tested in prior research. Initial testing found the need for improvement. OBJECTIVE: This multiple-phase study aimed to simplify and improve MASUN 1.0, resulting in MASUN 2.0, and verify the feasibility and usability of MASUN 2.0. METHODS: This study was conducted in three phases (1) modification of MASUN 1.0 to improve its importance, applicability, relevance, and clarity, in consultation with 21 experts in medical or nursing informatics; (2) validation of the draft MASUN 2.0, with 13 experts; and (3) feasibility testing of MASUN 2.0 and usability evaluation of the best app found through MASUN 2.0. Menstrual apps were used to test the framework. RESULTS: From Phases 1 and 2, MASUN 2.0, the framework for mHealth App selection, was derived with improved simplicity, usability, and applicability through a reduced number of tasks and time required. In Phase 3, after screening and scoring 2377 menstrual apps, five candidate apps were selected and evaluated by five clinical experts, five app experts, and five potential users. Finally, 194 users evaluated the usability of the app selected as the best. The best app helped users understand their health-related syndromes and patterns. Additionally, user-provided scores for impact, usefulness, and ease of use for the app were higher than for others. CONCLUSIONS: This study successfully modified MASUN 1.0 into MASUN 2.0 and verified MASUN 2.0 through content validity, feasibility, and usability testing. The selected apps through MASUN 2.0 helped health consumers more easily address health discomfort. Future research should extend this work to an automated system and different medical conditions with multiple stakeholders for digital health equity.