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

Use and User Demographics of mHealth (287) Usability of Apps and User Perceptions of mHealth (794)

Published on in Vol 9, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/26845, first published .
Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study

Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study

Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study

Authors of this article:

Nicky Sabine Klaver 1 Author Orcid Image ;   Joris van de Klundert 1, 2 Author Orcid Image ;   Roy Johannes Gerardus Maria van den Broek 1 Author Orcid Image ;   Marjan Askari 1 Author Orcid Image
Article Authors Cited by (24) Tweetations (6) Metrics

Journals

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  9. Pan J, Dong H, Bryan-Kinns N. Perception and Initial Adoption of Mobile Health Services of Older Adults in London: Mixed Methods Investigation. JMIR Aging 2021;4(4):e30420 View
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  13. Ge F, Qian H, Lei J, Ni Y, Li Q, Wang S, Ding K. Experiences and Challenges of Emerging Online Health Services Combating COVID-19 in China: Retrospective, Cross-Sectional Study of Internet Hospitals. JMIR Medical Informatics 2022;10(6):e37042 View
  14. Wang X, Lee C, Jiang J, Zhang G, Wei Z. Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model. Behavioral Sciences 2023;13(3):277 View
  15. Rho M, Park J. An Investigation of Factors Influencing the Postponement of the Use of Distributed Research Networks in South Korea: Web-Based Users’ Survey Study. JMIR Formative Research 2023;7:e40660 View
  16. Schroeder T, Dodds L, Georgiou A, Gewald H, Siette J. Older Adults and New Technology: Mapping Review of the Factors Associated With Older Adults’ Intention to Adopt Digital Technologies. JMIR Aging 2023;6:e44564 View
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  18. Tandon U, Ertz M, Shashi . Continued Intention of mHealth Care Applications among the Elderly: An Enabler and Inhibitor Perspective. International Journal of Human–Computer Interaction 2023:1 View
  19. Zhang M, Zhang H, Zhu R, Yang H, Chen M, Wang X, Li Z, Xiong Z. Factors affecting the willingness of patients with type 2 diabetes to use digital disease management applications: a cross-sectional study. Frontiers in Public Health 2023;11 View
  20. Ramdowar H, Khedo K, Chooramun N. A comprehensive review of mobile user interfaces in mHealth applications for elderly and the related ageing barriers. Universal Access in the Information Society 2023 View
  21. Nazlin Kamaruzaman K, Hussein Z, Fikry A. Factors Affecting Behavioural Intention to Use Mobile Health Applications among Obese People in Malaysia. European Journal of Business Science and Technology 2023;9(1):92 View
  22. Li Z, Ge J, Zhang C, Peng X, Wu Q, You H. Information-Motivation-Behavioral Skills Model Supplemented With the Moderated-Mediation Path: A Framework for Interpreting Patients’ Online Medical Services Utilization. American Journal of Health Promotion 2023;37(7):924 View
  23. Bakker C, Wyatt T, Breth M, Gao G, Janeway L, Lee M, Martin C, Tiase V. Nurses’ Roles in mHealth App Development: Scoping Review. JMIR Nursing 2023;6:e46058 View
  24. van Elburg F, van de Klundert J, Nieboer A, Askari M. The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic. Frontiers in Public Health 2023;11 View