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

Mobile Health and Apps for Maternal and Child Health (222) mHealth for Rehabilitation (365) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1781) mHealth for Telemedicine and Homecare (547) Mobile Health (mhealth) (3570)

Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/53186, first published .
Response Rate Patterns in Adolescents With Concussion Using Mobile Health and Remote Patient Monitoring: Observational Study

Response Rate Patterns in Adolescents With Concussion Using Mobile Health and Remote Patient Monitoring: Observational Study

Response Rate Patterns in Adolescents With Concussion Using Mobile Health and Remote Patient Monitoring: Observational Study

Authors of this article:

Sicong Ren1 Author Orcid Image ;   Catherine C McDonald1, 2, 3 Author Orcid Image ;   Daniel J Corwin1, 2, 4 Author Orcid Image ;   Douglas J Wiebe5, 6 Author Orcid Image ;   Christina L Master1, 2, 7 Author Orcid Image ;   Kristy B Arbogast1, 2, 4 Author Orcid Image
Article Authors Cited by (3) Tweetations (2) Metrics

Journals

  1. Wang B, Shi X, Han X, Xiao G. The digital transformation of nursing practice: an analysis of advanced IoT technologies and smart nursing systems. Frontiers in Medicine 2024;11 View
  2. Ingram E, Carmo M, Rast P, Manderino L, Karr J. An Exploratory Analysis and Comparison of Post-Concussion Symptom Networks in Young Adults with and without a Remote History of Concussion. Archives of Clinical Neuropsychology 2026;41(2) View

Conference Proceedings

  1. Donawa A, Millan J, Millan L, Reeves T, Lopez-Tucux R, Shafagati N, Arays R, Zinner R, Baker C. 2025 IEEE 21st International Conference on Body Sensor Networks (BSN). Motivating Adherence to Symptom Reporting Among Patients with Cancer: Pilot Study View