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

Journals

  1. ALsharif A. Attitudes of Patients with Chronic Diseases toward Management eHealth Applications Systems in Post-COVID-19 Times. International Journal of Environmental Research and Public Health 2022;19(7):4289 View
  2. Pan J, Dong H. mHealth Adoption Among Older Chinese Adults: A Conceptual Model With Design Suggestions. International Journal of Human–Computer Interaction 2023;39(5):1072 View
  3. Liu J, Sorwar G, Rahman M, Hoque M. The role of trust and habit in the adoption of mHealth by older adults in Hong Kong: a healthcare technology service acceptance (HTSA) model. BMC Geriatrics 2023;23(1) View
  4. van Elburg F, Klaver N, Nieboer A, Askari M. Gender differences regarding intention to use mHealth applications in the Dutch elderly population: a cross-sectional study. BMC Geriatrics 2022;22(1) View
  5. Wu Y, Wen J, Wang X, Wang Q, Wang W, Wang X, Xie J, Cong L. Associations between e-health literacy and chronic disease self-management in older Chinese patients with chronic non-communicable diseases: a mediation analysis. BMC Public Health 2022;22(1) View
  6. Uncovska M, Freitag B, Meister S, Fehring L. Patient Acceptance of Prescribed and Fully Reimbursed mHealth Apps in Germany: An UTAUT2-based Online Survey Study. Journal of Medical Systems 2023;47(1) View
  7. Vincent W. Developing and Evaluating a Measure of the Willingness to Use Pandemic-Related mHealth Tools Using National Probability Samples in the United States: Quantitative Psychometric Analyses and Tests of Sociodemographic Group Differences. JMIR Formative Research 2023;7:e38298 View
  8. Wang X, Lee C, Jiang J, Zhu X. Factors Influencing the Aged in the Use of Mobile Healthcare Applications: An Empirical Study in China. Healthcare 2023;11(3):396 View
  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
  10. Marshall-McKenna R, Kotronoulas G, Kokoroskos E, Granados A, Papachristou P, Papachristou N, Collantes G, Petridis G, Billis A, Bamidis P. A multinational investigation of healthcare needs, preferences, and expectations in supportive cancer care: co-creating the LifeChamps digital platform. Journal of Cancer Survivorship 2023;17(4):1094 View
  11. Tu R, Park S, Ding Y. Travel intentions of travelers in the COVID-19 context: The moderation of fear of COVID-19. Frontiers in Psychology 2023;14 View
  12. Wong A, Wong F, Bayuo J, Chow K, Wong S, Lee A. A randomized controlled trial of an mHealth application with nursing interaction to promote quality of life among community-dwelling older adults. Frontiers in Psychiatry 2022;13 View
  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
  17. Wang X, Luo R, Liu Y, Chen P, Tao Y, He Y. Revealing the complexity of users’ intention to adopt healthcare chatbots: A mixed-method analysis of antecedent condition configurations. Information Processing & Management 2023;60(5):103444 View
  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 2024;40(18):5026 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 2024;23(4):1613 View
  21. 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
  25. Sujarwoto S, Maharani A. Facilitators and barriers to the adoption of mHealth apps for COVID-19 contact tracing: a systematic review of the literature. Frontiers in Public Health 2023;11 View
  26. Ullman A, Larsen E, Gibson V, Binnewies S, Ohira R, Marsh N, Mcbride C, Winterbourn K, Boyte F, Cunninghame J, Dufficy M, Plummer K, Roberts N, Takashima M, Cooke M, Byrnes J, Rickard C, Kleidon T. An mHealth application for chronic vascular access: A multi‐method evaluation. Journal of Clinical Nursing 2024;33(5):1762 View
  27. Zou X, Na Y, Lai K, Liu G. Unpacking public resistance to health Chatbots: a parallel mediation analysis. Frontiers in Psychology 2024;15 View
  28. Chun M, Yu H, Jung H. A Deep Learning–Based Rotten Food Recognition App for Older Adults: Development and Usability Study. JMIR Formative Research 2024;8:e55342 View
  29. Harun Z, Muhammad N, Hussein Z, Fikri A, Abdul A. Factors influencing patients’ intention to use the Health Clinic Online Appointment System app. Information Management and Business Review 2024;16(2(I)):53 View
  30. Goel A, Singh A, Taneja U, Jain S. Consumer adoption of digital health services: A systematic literature review and research agenda. International Journal of Consumer Studies 2024;48(4) View
  31. Mathew G, Bava N, Varghese A, Sushan A, Benjamin A. Project Vayoraksha: Implementation of novel mHealth technology for healthcare delivery during COVID-19 in geriatric population of Kerala. Indian Journal of Medical Research 2024;159:289 View
  32. Xin H, Liu F, Wei Z. What decision-making process do mHealth users go through when faced with privacy disclosure behaviors? A dual trade-off perspective. Aslib Journal of Information Management 2024 View
  33. Leung W, Law S, Cheung M, Chang M, Lai C, Liu N. From resistance to acceptance: developing health task measures to boost mHealth adoption among older adults: mixed-methods approach and innovation resistance. Internet Research 2025;35(4):1678 View
  34. He H, Abdul-Rashid S, Raja Ghazilla R. Research Trends and Hot Spots in Telemedicine for the Elderly: A Scientometric Analysis. Healthcare 2024;12(18):1853 View
  35. Abolafio P, Lopes P, Pereira L, Silveira F. Identificação e categorização de riscos em serviços de telessaúde: uma revisão sistemática da literatura. Journal of Health Informatics 2024;16(Especial) View
  36. Wu C, Yang Z, Yuan Q, Zhang H. Helping others is helping oneself: A mixed-methods investigation of antecedents driving consumer engagement in the value co-creation of mHealth platforms. International Journal of Information Management 2025;81:102867 View
  37. Nautiyal S, Shrivastava A, Deka C. Smartphone Adoption and Healthcare Usage Among Older Adults in India. Activities, Adaptation & Aging 2024:1 View
  38. Jin H, Qu Y. Association Between Intergenerational Support, Technology Perception and Trust, and Intention to Seek Medical Care on the Internet Among Chinese Older Adults: Cross-Sectional Questionnaire Study. Journal of Medical Internet Research 2025;27:e65065 View
  39. Sun T, Ding Z, Xie H, Chen X, Wang Y, Li Y, Zhang G, Xu X, Xia Y, Ma Z. Pathways to usage intention of mobile health apps among hypertensive patients: A fuzzy-set qualitative comparative analysis. Health Informatics Journal 2025;31(1) View
  40. Al-Jabali R, Ahmad N, Khatib S. Holistic framework for the adoption determinants of mobile health applications: a systematic literature review. International Journal of Pharmaceutical and Healthcare Marketing 2025;19(3):794 View
  41. Alzghaibi H. Barriers to the Utilization of mHealth Applications in Saudi Arabia: Insights from Patients with Chronic Diseases. Healthcare 2025;13(6):665 View
  42. Tsirozidis G, Kirk U, Zaggl M. Benefits for thee, not for me? mHealth engagement through the lens of privacy calculus theory and trust. Behaviour & Information Technology 2025;44(19):4663 View
  43. Chen Z, Lee J. The Influence of UI Design Attributes and Users’ Uncertainty Avoidance on Stickiness of the Young Elderly Toward mHealth Applications. Behavioral Sciences 2025;15(5):581 View
  44. Yang T, Zheng H, Cao S, Jing M, Hu J, Zuo Y, Chen Q, Zhang J. Harnessing an Artificial Intelligence–Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study. Journal of Medical Internet Research 2025;27:e68762 View
  45. Dantas P, Bezerra A, Costa M. Pessoas Idosas em Tempo de Pandemia: Análise da Satisfação dos(as) Usuários(as) com um Programa de Prevenção para a Saúde Frente à COVID-19. Saúde Coletiva (Barueri) 2025;15(95):15458 View
  46. Wang Z, Wang Y, Zeng Y, Su J, Li Z. An investigation into the acceptance of intelligent care systems: an extended technology acceptance model (TAM). Scientific Reports 2025;15(1) View
  47. Lu G, Qu S, Chen Y. Understanding user experience for mobile applications: a systematic literature review. Discover Applied Sciences 2025;7(6) View
  48. Brady J, McCloud R, Higgins E, Mahesh A, LeJeune K, Black J, Singh A. The evolution of barriers and facilitators to using a COPD app among older adults: results from a pilot study. Frontiers in Digital Health 2025;7 View
  49. Pratama Z, Suhartanto D. ENCOURAGING THE INTENTION TO USE MOBILE JKN APPLICATION FOR PATIENT REGISTRATION AND APPOINTMENT IN INDONESIA: A CROSS-SECTIONAL STUDY. Journal of Public Health Research and Community Health Development 2025;8(2):97 View
  50. Yang S, Cha M, van Kessel R, Warrier G, Thrul J, Lee M, Yoon J, Kang D, Cho J. Understanding Inequalities in Mobile Health Utilization Across Phases: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2025;27:e71349 View
  51. Wang Y, Yan P, You S, Wan X, Jiang D, Guo Y, Feng H. mHealth-based educational needs in older adults with declines in intrinsic capacity: A qualitative research study. Geriatric Nursing 2025;66:103577 View
  52. Zhi H, Zolotova M. Wearable Devices & Elderly: A Bibliometric Analysis of 2014–2024. Healthcare 2025;13(16):2066 View
  53. Jin X, Feng Y, Zhou Z. Exploring the motivation-usage nexus: a configurational analysis of users'behavior patterns in mobile health. Information Technology and Management 2025 View
  54. Goel A, Soti N, Taneja U, Kumar A. Decoding consumer perspective for tech-based health insurance products. Innovation & Management Review 2025;22(4):251 View
  55. Xu Z, Meng Z, Yu X. Exploring the senior-friendly transformation requirements of older mHealth app users: a mixed approach. Information Technology & People 2025:1 View
  56. Yang Y, Xu S. Determining the Factors Influencing College Students’ Intention to Use Mobile Health Applications: An Integrated SEM-ANN Approach. SAGE Open 2025;15(3) View
  57. Han Y, Zhang J, Qing W, Zheng S, Xia L, Li Y, He L. Influencing factors of digital health technology anxiety in the elderly: a systematic review and meta-analysis. Frontiers in Psychology 2025;16 View
  58. Mahajan Y, Agarwal P, Chintamani A, Pahurkar R, Bhinde H, Sharma V. Perceived ease of use and health literacy as determinants of mHealth app usage among older adults in India: a SEM approach. Discover Social Science and Health 2025;5(1) View
  59. Ma X, Jiang L, Han B, Ding W, Liu S, Li B, Zhang M, Yao S. Trends in liver cancer burden in China and G20: a comparative analysis using GBD 2021. Frontiers in Oncology 2025;15 View
  60. Kassie S, Shibabaw A, Chereka A, Dubale A, Demsash A, Damtie Y, Ngusie H, Walle A. The impact of confidentiality and privacy concerns on behavioral intention to adopt electronic personal health records among chronic patients in southwest Ethiopia in 2023: an application of the UTAUT2 model. Frontiers in Digital Health 2025;7 View
  61. Kim J, Kim J, Youn B. Using a Technology Acceptance Model to Explore the Intention to Use Digital Health Technologies Among People With Disabilities: Cross-Sectional Survey Study. Journal of Medical Internet Research 2025;27:e79595 View
  62. Monasterio G, Fernández-López M, Valero E, Martin U, Ayala-García A. Digital inequalities in the use of eHealth services in European public healthcare systems: a systematic review of observational studies (Preprint). Journal of Medical Internet Research 2025 View
  63. Bassler C, Reichel P, Spörrle M. Too old for risk? Enhancing effects between risk assessment and age on the perceived usefulness of cyborg technologies. Acta Psychologica 2026;262:106007 View
  64. Zhao Y, Lu G, Fang S, Cai L, He X, Liang Y. Digital healthcare services in the context of age-friendly community initiatives in China: a realist evaluation. BMC Health Services Research 2025 View
  65. Ruotsalainen I, Valtanen M, Kärsämä R, Umer A, Liedes H, Parikka S, Lundqvist A, Aittola K, Koivunen S, Pihlajamäki J, Vuorinen A, Lindström J. Unraveling the Factors Associated With Digital Health Intervention Uptake: Cross-Sectional Study. JMIR mHealth and uHealth 2025;13:e63896 View

Conference Proceedings

  1. Putra Antonio E, Halim E, Hartono H. 2023 29th International Conference on Telecommunications (ICT). Physician Behaviors and Blockchain Possibilities Implementation on the Intention to Use Telemedicine Applications View
  2. Pang W, Liew T, Tan S, Teo S, Lee Y, Lim T. Proceedings of the 2024 The 6th World Symposium on Software Engineering (WSSE). Analyzing Use Intentions for Health-Diagnostic Chatbots: An Extended Technology Acceptance Model Approach View
  3. Tejera J, Gokhale S, Gromisch E. 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC). Trustworthiness Features of Commercially Available Mobile Health (mHealth) Applications View