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

mHealth for Wellness, Behavior Change and Prevention (2457)

Published on in Vol 5 , No 12 (2017) :December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/6394, first published .
Using mHealth Technology in a Self-Management Intervention to Promote Physical Activity Among Adults With Chronic Disabling Conditions: Randomized Controlled Trial

Using mHealth Technology in a Self-Management Intervention to Promote Physical Activity Among Adults With Chronic Disabling Conditions: Randomized Controlled Trial

Using mHealth Technology in a Self-Management Intervention to Promote Physical Activity Among Adults With Chronic Disabling Conditions: Randomized Controlled Trial

Authors of this article:

Matthew Plow 1 Author Orcid Image ;   Meghan Golding 1 Author Orcid Image
Article Authors Cited by (22) Tweetations (27) Metrics

Journals

  1. Setiawan I, Zhou L, Alfikri Z, Saptono A, Fairman A, Dicianno B, Parmanto B. An Adaptive Mobile Health System to Support Self-Management for Persons With Chronic Conditions and Disabilities: Usability and Feasibility Studies. JMIR Formative Research 2019;3(2):e12982 View
  2. Ferrara G, Kim J, Lin S, Hua J, Seto E. A Focused Review of Smartphone Diet-Tracking Apps: Usability, Functionality, Coherence With Behavior Change Theory, and Comparative Validity of Nutrient Intake and Energy Estimates. JMIR mHealth and uHealth 2019;7(5):e9232 View
  3. Phongtankuel V, Adelman R, Reid M. Mobile health technology and home hospice care: promise and pitfalls. Progress in Palliative Care 2018;26(3):137 View
  4. Imani S, Goradel J, Mousavi S, Noroozi A. Internal Consistency and Confirmatory Factor Analysis of Smartphone Addiction Inventory (SPAI). Iranian Journal of Psychiatry and Behavioral Sciences 2019;13(2) View
  5. Giunti G. 3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study. JMIR Serious Games 2018;6(3):e11631 View
  6. Yen H, Chiu H. The effectiveness of wearable technologies as physical activity interventions in weight control: A systematic review and meta‐analysis of randomized controlled trials. Obesity Reviews 2019;20(10):1485 View
  7. Olsen S, Saperstein S, Gold R. Content and Feature Preferences for a Physical Activity App for Adults with Physical Disabilities: Focus Group Findings (Preprint). JMIR mHealth and uHealth 2019 View
  8. Kelechi T, Prentice M, Mueller M, Madisetti M, Vertegel A. A Lower Leg Physical Activity Intervention for Individuals With Chronic Venous Leg Ulcers: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(5):e15015 View
  9. Buck H, Shadmi E, Topaz M, Sockolow P. An integrative review and theoretical examination of chronic illness mHealth studies using the Middle‐Range Theory of Self‐care of Chronic Illness. Research in Nursing & Health 2021;44(1):47 View
  10. Heron N, O’Connor S, Kee F, Mant J, Cupples M, Donnelly M. Usability and Acceptability of a Novel Secondary Prevention Initiative Targeting Physical Activity for Individuals after a Transient Ischaemic Attack or “Minor” Stroke: A Qualitative Study. International Journal of Environmental Research and Public Health 2020;17(23):8788 View
  11. Lemola S, Gkiouleka A, Read B, Realo A, Walasek L, Tang N, Elliott M. Can a ‘rewards-for-exercise app’ increase physical activity, subjective well-being and sleep quality? An open-label single-arm trial among university staff with low to moderate physical activity levels. BMC Public Health 2021;21(1) View
  12. De Angelis M, Lavorgna L, Carotenuto A, Petruzzo M, Lanzillo R, Brescia Morra V, Moccia M. Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review. Journal of Clinical Medicine 2021;10(11):2328 View
  13. de Carvalho Lana R, Ribeiro de Paula A, Souza Silva A, Vieira Costa P, Polese J. Validity of mHealth devices for counting steps in individuals with Parkinson’s disease. Journal of Bodywork and Movement Therapies 2021 View
  14. Bevens W, Gray K, Neate S, Nag N, Weiland T, Jelinek G, Simpson-Yap S. Characteristics of mHealth app use in an international sample of people with multiple sclerosis. Multiple Sclerosis and Related Disorders 2021;54:103092 View
  15. Yang A, Singh N, Varshney U. Mobile Health Interventions and RCTs: Structured Taxonomy and Research Framework. Journal of Medical Systems 2022;46(10) View
  16. Austin R, Martin C, Jones C, Lu S, Jantraporn R, Nestrasil I, Martin K, Monsen K. Translation and validation of the Omaha System into English language simplified Omaha System terms. Kontakt 2022;24(1):48 View
  17. Sockolow P, Buck H, Shadmi E. An integrative review of chronic illness mHealth self-care interventions: Mapping technology features to patient outcomes. Health Informatics Journal 2021;27(3):146045822110439 View
  18. O’Connor S, Kee F, Thompson D, Cupples M, Donnelly M, Heron N. A review of the quality and content of mobile apps to support lifestyle modifications following a transient ischaemic attack or ‘minor’ stroke. DIGITAL HEALTH 2021;7:205520762110652 View
  19. 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 2022:1 View
  20. Mahmood A, Nayak P, Deshmukh A, English C, N M, Solomon M J, B U. Measurement, determinants, barriers, and interventions for exercise adherence: A scoping review. Journal of Bodywork and Movement Therapies 2023;33:95 View

Books/Policy Documents

  1. de Moraes Lopes M, Ferreira D, Ferreira A, da Silva G, Caetano A, Braz V. Artificial Intelligence in Precision Health. View
  2. Cerrato P, Halamka J. The Transformative Power of Mobile Medicine. View