Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Dec 4, 2023
Open Peer Review Period: Dec 4, 2023 - Jan 30, 2024
Date Accepted: Oct 28, 2024
(closed for review but you can still tweet)
User Experience and Extended Technology Acceptance Model in Commercial Healthcare App Usage among Cancer Patients: A Mixed-Methods Study
ABSTRACT
Background:
The shift in medical care towards prediction and prevention has led to the emergence of digital healthcare as a valuable tool for managing health issues. Aiding long-term follow-up care for cancer survivors and contributing to improved survival rates. However, potential barriers to mobile health utilization, including age-related disparities and challenges in user retention for commercial health apps, highlight the need to assess the impact of patients' abilities and health status on the adoption of these interventions.
Objective:
This study aims to investigate the app adherence and user experience of commercial healthcare apps among cancer survivors using an extended Technology Acceptance Model (TAM).
Methods:
The study enrolled 264 cancer survivors. We collected survey results from May to August 2022 and app usage records from the app companies. The following survey questions were created based on TAM.
Results:
The study revealed significant differences in app usage behavior among three clusters (short-use, medium-use, and long-use), categorized based on actual app usage data using K-means clustering. The extended TAM, examined through structural equation modeling, demonstrated positive paths linking motivation to perceived usefulness, perceived ease-of-use to usefulness, and attitude to behavioral intention, ultimately impacting actual app usage.
Conclusions:
This study showed the importance of a positive user experience and clinician recommendations in facilitating the effective utilization of digital healthcare tools among cancer survivors and contributing to the evolving landscape of medical care.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.