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

Ecological Momentary Assessment (EMA) (321) User-centred Design Case Studies (602) mHealth for Data Collection and Research (981) mHealth for Wellness, Behavior Change and Prevention (2922)

Published on in Vol 7, No 4 (2019): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10894, first published .
Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report

Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report

Context-Sensitive Ecological Momentary Assessment: Application of User-Centered Design for Improving User Satisfaction and Engagement During Self-Report

Authors of this article:

Preethi Srinivas1, 2 Author Orcid Image ;   Kunal Bodke1, 2 Author Orcid Image ;   Susan Ofner3 Author Orcid Image ;   NiCole R Keith1, 2, 4 Author Orcid Image ;   Wanzhu Tu1, 3 Author Orcid Image ;   Daniel O Clark1, 2, 5 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Bond R, Moorhead A, Mulvenna M, O'Neill S, Potts C, Murphy N. Exploring temporal behaviour of app users completing ecological momentary assessments using mental health scales and mood logs. Behaviour & Information Technology 2019;38(10):1016 View
  2. Dauber S, Beacham A, Hammond C, West A, Thrul J. Adaptive Text Messaging for Postpartum Risky Drinking: Conceptual Model and Protocol for an Ecological Momentary Assessment Study. JMIR Research Protocols 2022;11(4):e36849 View
  3. Göttgens I, Oertelt-Prigione S. The Application of Human-Centered Design Approaches in Health Research and Innovation: A Narrative Review of Current Practices. JMIR mHealth and uHealth 2021;9(12):e28102 View
  4. Elliott A, Lang S, Truby H, Brennan L, Gibson S. Tackling the challenge of treating obesity using design research methods: A scoping review. Obesity Reviews 2022;23(2) View
  5. Daryabeygi-Khotbehsara R, Shariful Islam S, Dunstan D, McVicar J, Abdelrazek M, Maddison R. Smartphone-Based Interventions to Reduce Sedentary Behavior and Promote Physical Activity Using Integrated Dynamic Models: Systematic Review. Journal of Medical Internet Research 2021;23(9):e26315 View
  6. Clark D, Keith N, Ofner S, Hackett J, Li R, Agarwal N, Tu W. Environments and situations as correlates of eating and drinking among women living with obesity and urban poverty. Obesity Science & Practice 2022;8(2):153 View
  7. Dauber S, Beacham A, West A, Devkota J, Barrie K, Thrul J. Ecological momentary assessment of heavy episodic drinking in the early postpartum period: A feasibility study. Drug and Alcohol Dependence Reports 2023;7:100146 View
  8. Kornacka M, Jaskulska A, Skorupska K, Szastok M, Nadziejko M, Kopeć W. A solution for creating dynamic networks of symptoms in cognitive-behavioral functional analysis and therapy – participatory design protocol. Mental Health and Social Inclusion 2023;27(2):167 View
  9. Jung D, Choi J, Park S, Choi K. Improving older adults' autobiographical memory through video‐conferencing intervention during COVID‐19. International Journal of Geriatric Psychiatry 2023;38(8) View
  10. Guo Y, Li K, Zhao Y, Wang C, Mo H, Li Y. Association between long-term sedentary behavior and depressive symptoms in U.S. adults. Scientific Reports 2024;14(1) View
  11. Golsong K, Kaufmann L, Baldofski S, Kohls E, Rummel-Kluge C. Acceptability, User Satisfaction, and Feasibility of an App-Based Support Service During the COVID-19 Pandemic in a Psychiatric Outpatient Setting: Prospective Longitudinal Observational Study. JMIR Formative Research 2024;8:e60461 View

Books/Policy Documents

  1. Quezada P, Cueva R, Paz F. Design, User Experience, and Usability: UX Research and Design. View
  2. Chui K, Lytras M, Visvizi A, Sarirete A. Artificial Intelligence and Big Data Analytics for Smart Healthcare. View