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

Evaluation and Research Methodology for mHealth (210) Artificial Intelligence (1421) Chatbots and Conversational Agents (543) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (505) Research Instruments, Questionnaires, and Tools (589)

Published on in Vol 8, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13244, first published .
Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study

Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study

Applicability of the User Engagement Scale to Mobile Health: A Survey-Based Quantitative Study

Authors of this article:

Marianne Holdener1 Author Orcid Image ;   Alain Gut2 Author Orcid Image ;   Alfred Angerer1 Author Orcid Image
Article Authors Cited by (27) Tweetations (3) Metrics

Journals

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  2. Miller S, Gilbert S, Virani V, Wicks P. Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study. JMIR Human Factors 2020;7(3):e19713 View
  3. Prochaska J, Vogel E, Chieng A, Kendra M, Baiocchi M, Pajarito S, Robinson A. A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study. Journal of Medical Internet Research 2021;23(3):e24850 View
  4. Lee J, Woo H. Quality Evaluation of Fine Dust Management Mobile Applications. Journal of Health Informatics and Statistics 2021;46(1):110 View
  5. Bonnot O, Adrien V, Venelle V, Bonneau D, Gollier-Briant F, Mouchabac S. Mobile App for Parental Empowerment for Caregivers of Children With Autism Spectrum Disorders: Prospective Open Trial. JMIR Mental Health 2021;8(9):e27803 View
  6. Benoit J, Hartling L, Chan M, Scott S. Characteristics of Acute Childhood Illness Apps for Parents: Environmental Scan. Journal of Medical Internet Research 2021;23(10):e29441 View
  7. Khazaal Y, Potvin S, Pennou A, Djomo W, Borgeat F, Lecomte T. Des repères pour la conception des apps ?. Santé mentale au Québec 2021;46(1):119 View
  8. Basu D, Lohani V. Learning and engagement with an online laboratory for environmental monitoring education. European Journal of Engineering Education 2023;48(5):861 View
  9. Nwolise C, Carey N, Shawe J. Preconception and Diabetes Information (PADI) App for Women with Pregestational Diabetes: a Feasibility and Acceptability Study. Journal of Healthcare Informatics Research 2021;5(4):446 View
  10. White K, Matcham F, Leightley D, Carr E, Conde P, Dawe-Lane E, Ranjan Y, Simblett S, Henderson C, Hotopf M. Exploring the Effects of In-App Components on Engagement With a Symptom-Tracking Platform Among Participants With Major Depressive Disorder (RADAR-Engage): Protocol for a 2-Armed Randomized Controlled Trial. JMIR Research Protocols 2021;10(12):e32653 View
  11. An Z, Zheng D, Wei D, Jiang D, Xing X, Liu C, Sugawara A. Correlation between Acylcarnitine and Peripheral Neuropathy in Type 2 Diabetes Mellitus. Journal of Diabetes Research 2022;2022:1 View
  12. Van Baelen F, De Regge M, Larivière B, Verleye K, Schelfout S, Eeckloo K. Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study. JMIR mHealth and uHealth 2022;10(8):e33772 View
  13. McGowan A, Sittig S, Bourrie D, Benton R, Iyengar S. The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation. JMIR mHealth and uHealth 2022;10(9):e40576 View
  14. Stern E, MICOULAUD FRANCHI J, Dumas G, Moreira J, Mouchabac S, Maruani J, Philip P, Lejoyeux M, GEOFFROY P. How Can Digital Mental Health Enhance Psychiatry?. The Neuroscientist 2023;29(6):681 View
  15. Maatoug R, Oudin A, Adrien V, Saudreau B, Bonnot O, Millet B, Ferreri F, Mouchabac S, Bourla A. Digital phenotype of mood disorders: A conceptual and critical review. Frontiers in Psychiatry 2022;13 View
  16. Mouchabac S, Maatoug R, Conejero I, Adrien V, Bonnot O, Millet B, Ferreri F, Bourla A. In Search of Digital Dopamine: How Apps Can Motivate Depressed Patients, a Review and Conceptual Analysis. Brain Sciences 2021;11(11):1454 View
  17. Voronina A, Shabalina O, Sadovnikova N. SOFTWARE USER ENGAGEMENT: METHODS OF EVALUATION AND APPLICATIONS. Vestnik komp'iuternykh i informatsionnykh tekhnologii 2022;(215):18 View
  18. Lu F, Wang X, Li S, Zhao Q. How Mobile Health Livingstreaming Engages the Consumer-Insights from a Dual-Process Model. Sustainability 2023;15(10):8097 View
  19. White K, Carr E, Leightley D, Matcham F, Conde P, Ranjan Y, Simblett S, Dawe-Lane E, Williams L, Henderson C, Hotopf M. Engagement With a Remote Symptom-Tracking Platform Among Participants With Major Depressive Disorder: Randomized Controlled Trial. JMIR mHealth and uHealth 2024;12:e44214 View
  20. Cabrera-Moya D, Vasudevan H, Prieto-Rodriguez G. KASH TRAINING MODELS: INCREASING LEVELS OF COMMITMENT AND ORGANIZATIONAL EFFECTIVENESS. Business: Theory and Practice 2023;24(1):239 View
  21. Chang I, Hsu P, Chen R. The effects of trust on user satisfaction with parenting apps for Taiwanese parents: The mediating roles of social ties and perceived value. Education and Information Technologies 2024 View
  22. Keedle H, Young K, Arundell F, Burns E. Midwifery student engagement with digital interactive books: A cross sectional survey. Women and Birth 2024;37(6):101826 View

Books/Policy Documents

  1. Belter M, Lukosch H, Lindeman R, Wu Y, Steinicke F. HCI in Games. View
  2. Preuss A, Jansen M, Justenhoven R. Personalauswahl 4.0. View