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

Design and Usability of Consumer Health Tech and Home Monitoring Devices (330) mHealth for Wellness, Behavior Change and Prevention (3332) mHealth for Rehabilitation (356) Emerging Technologies for Rehabilitation (352) Aging in Place (390) Mobile Devices and Apps for Seniors and Healthy Aging (270) mHealth for Screening (298) Machine Learning (2088) Shared Decision Making and Self-Advocacy (59) Geroinformatics and Electronic Clinical Information/Decision Making in Geriatrics (38)

Published on in Vol 11 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52310, first published .
Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment

Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment

Authors of this article:

Giulia Angonese1, 2 Author Orcid Image ;   Mareike Buhl1, 3 Author Orcid Image ;   Inka Kuhlmann1, 2 Author Orcid Image ;   Birger Kollmeier1, 4, 5 Author Orcid Image ;   Andrea Hildebrandt1, 2, 5 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Angonese G, Buhl M, Kuhlmann I, Kollmeier B, Hildebrandt A. Prediction of Hearing Help Seeking to Design a Recommendation Module of an mHealth Hearing App: Intensive Longitudinal Study of Feature Importance Assessment. JMIR Human Factors 2024;11:e52310 View
  2. Angonese G, Buhl M, Gößwein J, Kollmeier B, Hildebrandt A. Toward an Extended Classification of Noise-Distortion Preferences by Modeling Longitudinal Dynamics of Listening Choices. Trends in Hearing 2025;29 View