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

Special Issue 2019: Computing and Mental Health (Guest Editors: Torous, Calvo, Wadley, Wolters) (14)

Published on in Vol 6, No 5 (2019): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13895, first published .
Exploring User Needs and Preferences for Mobile Apps for Sleep Disturbance: Mixed Methods Study

Exploring User Needs and Preferences for Mobile Apps for Sleep Disturbance: Mixed Methods Study

Exploring User Needs and Preferences for Mobile Apps for Sleep Disturbance: Mixed Methods Study

Authors of this article:

Melissa Aji1, 2 Author Orcid Image ;   Christopher Gordon2, 3, 4 Author Orcid Image ;   Dorian Peters5 Author Orcid Image ;   Delwyn Bartlett3, 6 Author Orcid Image ;   Rafael A Calvo5, 7 Author Orcid Image ;   Khushnood Naqshbandi5 Author Orcid Image ;   Nick Glozier1 Author Orcid Image
Article Authors Cited by (24) Tweetations (11) Metrics

Journals

  1. Wang Y, Liu Y, Shi Y, Yu Y, Yang J. User Perceptions of Virtual Hospital Apps in China: Systematic Search. JMIR mHealth and uHealth 2020;8(8):e19487 View
  2. Ding E, Ensom E, Hafer N, Buchholz B, Picard M, Dunlap D, Rogers E, Lawton C, Koren A, Lilly C, Fitzgibbons T, McManus D. Point-of-care technologies in heart, lung, blood and sleep disorders from the Center for Advancing Point-of-Care Technologies. Current Opinion in Biomedical Engineering 2019;11:58 View
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  4. Wei Y, Zheng P, Deng H, Wang X, Li X, Fu H. Design Features for Improving Mobile Health Intervention User Engagement: Systematic Review and Thematic Analysis. Journal of Medical Internet Research 2020;22(12):e21687 View
  5. Aji M, Gordon C, Stratton E, Calvo R, Bartlett D, Grunstein R, Glozier N. Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review. Journal of Medical Internet Research 2021;23(2):e24607 View
  6. Hensher M, Cooper P, Dona S, Angeles M, Nguyen D, Heynsbergh N, Chatterton M, Peeters A. Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers. Journal of the American Medical Informatics Association 2021;28(6):1318 View
  7. Zidaru T, Morrow E, Stockley R. Ensuring patient and public involvement in the transition to AI‐assisted mental health care: A systematic scoping review and agenda for design justice. Health Expectations 2021;24(4):1072 View
  8. Aji M, Glozier N, Bartlett D, Grunstein R, Calvo R, Marshall N, White D, Gordon C. The Effectiveness of Digital Insomnia Treatment with Adjunctive Wearable Technology: A Pilot Randomized Controlled Trial. Behavioral Sleep Medicine 2022;20(5):570 View
  9. Oh E, Kearns W, Laine M, Demiris G, Thompson H. Perceptions of and Experiences with Consumer Sleep Technologies That Use Artificial Intelligence. Sensors 2022;22(10):3621 View
  10. Liang Z. Context-Aware Sleep Health Recommender Systems (CASHRS): A Narrative Review. Electronics 2022;11(20):3384 View
  11. Wang H, Ho A, Wiener R, Sambamoorthi U. The Association of Mobile Health Applications with Self-Management Behaviors among Adults with Chronic Conditions in the United States. International Journal of Environmental Research and Public Health 2021;18(19):10351 View
  12. Balaskas A, Schueller S, Cox A, Doherty G. Understanding users’ perspectives on mobile apps for anxiety management. Frontiers in Digital Health 2022;4 View
  13. Al Mahmud A, Wu J, Mubin O. A scoping review of mobile apps for sleep management: User needs and design considerations. Frontiers in Psychiatry 2022;13 View
  14. Murray J, Magee M, Giliberto E, Booker L, Tucker A, Galaska B, Sibenaller S, Baer S, Postnova S, Sondag T, Phillips A, Sletten T, Howard M, Rajaratnam S. Mobile app for personalized sleep–wake management for shift workers: A user testing trial. DIGITAL HEALTH 2023;9:205520762311659 View
  15. Cheng P, Santarossa S, Kalmbach D, Sagong C, Hu K, Drake C. Patient perspectives on facilitators and barriers to equitable engagement with digital CBT-I. Sleep Health 2023;9(5):571 View
  16. Tsai C, Rajput G, Gao A, Wu Y, Wu D. Improving the design of patient-generated health data visualizations: design considerations from a Fitbit sleep study. Journal of the American Medical Informatics Association 2024;31(2):465 View
  17. Kreyenschulte T, Bohnet-Joschko S. Transparenz und Effizienz durch digitale Gesundheitsversorgung? Ergebnisse eines Surveys der Generation Y. Das Gesundheitswesen 2024;86(01):49 View
  18. Armitage B, Potts H, Irwin M, Fisher A. Exploring the impact of a sleep app on sleep quality in a general population sample: a randomised controlled pilot trial (Preprint). JMIR Formative Research 2022 View

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