This paper is in the following e-collection/theme issue:

Design and Usability of Consumer Health Tech and Home Monitoring Devices (218) Breast Cancer (206) Mobile Health (mhealth) (2939) Mobile Apps for Cancer Care and Cancer Prevention and Screening (206) Usability Evaluation Case Studies (191) Human Factors and Usability Case Studies (787) Design and Formative Evaluation of Mobile Apps (694) Formative Evaluation of Digital Health Interventions (2409) Usability of Apps and User Perceptions of mHealth (974)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50926, first published .
Usability and User Experience of an mHealth App for Therapy Support of Patients With Breast Cancer: Mixed Methods Study Using Eye Tracking

Usability and User Experience of an mHealth App for Therapy Support of Patients With Breast Cancer: Mixed Methods Study Using Eye Tracking

Usability and User Experience of an mHealth App for Therapy Support of Patients With Breast Cancer: Mixed Methods Study Using Eye Tracking

Authors of this article:

Carolin Anders1 Author Orcid Image ;   Preetha Moorthy2 Author Orcid Image ;   Laura Svensson1 Author Orcid Image ;   Julia Müller1 Author Orcid Image ;   Oliver Heinze1 Author Orcid Image ;   Petra Knaup1 Author Orcid Image ;   Markus Wallwiener3 Author Orcid Image ;   Thomas M Deutsch3 Author Orcid Image ;   Thao-Vy Le3 Author Orcid Image ;   Lina Weinert1, 4 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Li F, Chen C, Liu Y, Chang D, Cui J, Sourina O. Autoencoder-enabled eye-tracking data analytics for objective assessment of user preference in humanoid robot appearance design. Expert Systems with Applications 2024;249:123857 View