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

Health Risk and Perception in Cognitive Reasoning (17) Usability of Apps and User Perceptions of mHealth (974) Mobile Health (mhealth) (2939) User-centred Design Case Studies (596)

Published on in Vol 8, No 1 (2021): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25604, first published .
Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study

Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study

Usability of a Fall Risk mHealth App for People With Multiple Sclerosis: Mixed Methods Study

Authors of this article:

Katherine Hsieh1, 2 Author Orcid Image ;   Jason Fanning3 Author Orcid Image ;   Mikaela Frechette1 Author Orcid Image ;   Jacob Sosnoff1, 4 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Abou L, Wong E, Peters J, Dossou M, Sosnoff J, Rice L. Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review. Multiple Sclerosis and Related Disorders 2021;51:102943 View
  2. Blair R, Horn C, Dias J, McDonnell M, Seely E. Development and Usability of a Text Messaging Program for Women With Gestational Diabetes: Mixed Methods Study. JMIR Human Factors 2022;9(1):e32815 View
  3. Hsieh K, Frechette M, Fanning J, Chen L, Griffin A, Sosnoff J. The Developments and Iterations of a Mobile Technology-Based Fall Risk Health Application. Frontiers in Digital Health 2022;4 View
  4. Frechette M, Fanning J, Hsieh K, Rice L, Sosnoff J. The Usability of a Smartphone-Based Fall Risk Assessment App for Adult Wheelchair Users: Observational Study. JMIR Formative Research 2022;6(9):e32453 View
  5. van Beek J, Lehnick D, Pastore-Wapp M, Wapp S, Kamm C, Nef T, Vanbellingen T. Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial. Disability and Rehabilitation: Assistive Technology 2024;19(3):889 View
  6. Howard Z, Win K, Guan V. Mobile apps used for people living with multiple sclerosis: A scoping review. Multiple Sclerosis and Related Disorders 2023;73:104628 View
  7. Woelfle T, Bourguignon L, Lorscheider J, Kappos L, Naegelin Y, Jutzeler C. Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective. Journal of Medical Internet Research 2023;25:e44428 View
  8. Shankar K, Li A. Older Adult Falls in Emergency Medicine, 2023 Update. Clinics in Geriatric Medicine 2023;39(4):503 View
  9. Block V, Koshal K, Wijangco J, Miller N, Sara N, Henderson K, Reihm J, Gopal A, Mohan S, Gelfand J, Guo C, Oommen L, Nylander A, Rowson J, Brown E, Sanders S, Rankin K, Lyles C, Sim I, Bove R. A Closed-Loop Falls Monitoring and Prevention App for Multiple Sclerosis Clinical Practice: Human-Centered Design of the Multiple Sclerosis Falls InsightTrack. JMIR Human Factors 2024;11:e49331 View
  10. Tea F, Groh A, Lacey C, Fakolade A. A scoping review assessing the usability of digital health technologies targeting people with multiple sclerosis. npj Digital Medicine 2024;7(1) View
  11. Moein S, Peterson E, Li Z, Morris J, Van Denend T, Sosnoff J, Backus D, Pramod J, Hawari L, Nguyen M, Rice L. Engaging wheelchair and scooter users in the co-design of an mHealth application for fall prevention and management: thematic analysis of focus group research. Disability and Rehabilitation: Assistive Technology 2024:1 View
  12. Wäneskog A, Forsberg A, Nilsagård Y. Exploring the Complexity of Falls in People With Multiple Sclerosis: A Qualitative Study. International Journal of MS Care 2024;26(Q4):308 View