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

Mobile Health (mhealth) (2765) Use and User Demographics of mHealth (311) Internet Access and Digital Technology Use in an Elderly Population (179)

Published on in Vol 22, No 9 (2020): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18080, first published .
Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study

Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study

Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study

Authors of this article:

Marjan Askari1 Author Orcid Image ;   Nicky Sabine Klaver1 Author Orcid Image ;   Thimon Johannes van Gestel1 Author Orcid Image ;   Joris van de Klundert1, 2 Author Orcid Image
Article Authors Cited by (40) Tweetations (6) Metrics

Journals

  1. Sülz S, van Elten H, Askari M, Weggelaar-Jansen A, Huijsman R. eHealth Applications to Support Independent Living of Older Persons: Scoping Review of Costs and Benefits Identified in Economic Evaluations. Journal of Medical Internet Research 2021;23(3):e24363 View
  2. . Leefstijlcoaching voor ouderen via internet. Huisarts en wetenschap 2020;63(12):59 View
  3. Kong Q, Riedewald D, Askari M. Factors Affecting Portal Usage Among Chronically Ill Patients During the COVID-19 Pandemic in the Netherlands: Cross-sectional Study. JMIR Human Factors 2021;8(3):e26003 View
  4. Harakeh Z, Van Keulen H, Hogenelst K, Otten W, De Hoogh I, Van Empelen P. Predictors of the Acceptance of an Electronic Coach Targeting Self-management of Patients With Type 2 Diabetes: Web-Based Survey. JMIR Formative Research 2022;6(8):e34737 View
  5. Saha S, Lozano C, Broyles S, Martin C, Apolzan J. Assessing the Initial Validity of the PortionSize App to Estimate Dietary Intake Among Adults: Pilot and Feasibility App Validation Study. JMIR Formative Research 2022;6(6):e38283 View
  6. Yu J, de Antonio A, Villalba-Mora E. Design of an Integrated Acceptance Framework for Older Users and eHealth: Influential Factor Analysis. Journal of Medical Internet Research 2022;24(1):e31920 View
  7. Klaver N, van de Klundert J, van den Broek R, Askari M. Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study. JMIR mHealth and uHealth 2021;9(8):e26845 View
  8. Gelbman B, Reed C. An Integrated, Multimodal, Digital Health Solution for Chronic Obstructive Pulmonary Disease: Prospective Observational Pilot Study. JMIR Formative Research 2022;6(3):e34758 View
  9. Malathi A, Jasim K. Validating the relationship between service quality, patient sensitivity and experience towards medical applications using SERVQUAL. International Journal of Medical Informatics 2022;168:104883 View
  10. Cenamor J. Use of health self-management platform features: The case of a specialist ehealth app. Technological Forecasting and Social Change 2022;185:122066 View
  11. Mendez K, Budhathoki C, Labrique A, Sadak T, Tanner E, Han H. Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study. JMIR mHealth and uHealth 2021;9(8):e27926 View
  12. Yang C, Yang S, Chang Y. Predicting Older Adults’ Mobile Payment Adoption: An Extended TAM Model. International Journal of Environmental Research and Public Health 2023;20(2):1391 View
  13. 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
  14. Imeraj A, Olesen T, Laursen D, Søndergaard J, Brandt C. Agreement Between Clinically Measured Weight and Self-reported Weight Among Patients With Type 2 Diabetes Through an mHealth Lifestyle Coaching Program in Denmark: Secondary Analysis of a Randomized Controlled Trial. JMIR Formative Research 2022;6(9):e40739 View
  15. Lee J, Lim J. Factors Associated With the Experience of Cognitive Training Apps for the Prevention of Dementia: Cross-sectional Study Using an Extended Health Belief Model. Journal of Medical Internet Research 2022;24(1):e31664 View
  16. Ma Y, Luo M. Older people's intention to use medical apps during the COVID-19 pandemic in China: an application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and the Technology of Acceptance Model (TAM). Ageing and Society 2022:1 View
  17. Alzahrani A, Al-Samarraie H, Eldenfria A, Dodoo J, Alalwan N. Users’ intention to continue using mHealth services: A DEMATEL approach during the COVID-19 pandemic. Technology in Society 2022;68:101862 View
  18. Mustafa A, Ali N, Dhillon J, Alkawsi G, Baashar Y. User Engagement and Abandonment of mHealth: A Cross-Sectional Survey. Healthcare 2022;10(2):221 View
  19. Höchsmann C, Fearnbach N, Dorling J, Fazzino T, Myers C, Apolzan J, Martin C. Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake. Nutrients 2021;13(10):3340 View
  20. Ahmad N, Mat Ludin A, Shahar S, Mohd Noah S, Mohd Tohit N. Willingness, perceived barriers and motivators in adopting mobile applications for health-related interventions among older adults: a scoping review. BMJ Open 2022;12(3):e054561 View
  21. Buestan M, Perez C. Identification of Predictive Nursing Workload Factors: A Six Sigma Approach. Sustainability 2022;14(20):13169 View
  22. Kang H, Han J, Kwon G. The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF. International Journal of Environmental Research and Public Health 2022;19(20):13279 View
  23. Chen J, Wijesundara J, Enyim G, Lombardini L, Gerber B, Houston T, Sadasivam R. Understanding Patients’ Intention to Use Digital Health Apps That Support Postdischarge Symptom Monitoring by Providers Among Patients With Acute Coronary Syndrome: Survey Study. JMIR Human Factors 2022;9(1):e34452 View
  24. Romano E, Falegnami A, Cagliano A, Rafele C. Lean ICU Layout Re-Design: A Simulation-Based Approach. Informatics 2022;9(2):35 View
  25. Rahimi R, Khoundabi B, fathian A. Investigating the effective factors of using mHealth apps for monitoring COVID-19 symptoms and contact tracing: A survey among Iranian citizens. International Journal of Medical Informatics 2021;155:104571 View
  26. 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
  27. Chen Z, Qi H, Wang L. Study on the Types of Elderly Intelligent Health Management Technology and the Influencing Factors of Its Adoption. Healthcare 2021;9(11):1494 View
  28. Wilson H, Hayward P, Donkin L. Will they or won't they? Understanding New Zealand adults' attitudes towards using digital interventions. Frontiers in Digital Health 2023;5 View
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  30. 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
  31. Vera Cruz G, Khazaal Y, Etter J. Predicting the Users’ Level of Engagement with a Smartphone Application for Smoking Cessation: Randomized Trial and Machine Learning Analysis. European Addiction Research 2023;29(3):171 View
  32. 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
  33. Hezer B, Massey E, Reinders M, Tielen M, van de Wetering J, Hesselink D, van den Hoogen M. Telemedicine for Kidney Transplant Recipients: Current State, Advantages, and Barriers. Transplantation 2024;108(2):409 View
  34. Langerak A, Regterschot G, Evers M, van Beijnum B, Meskers C, Selles R, Ribbers G, Bussmann J. A Sensor-Based Feedback Device Stimulating Daily Life Upper Extremity Activity in Stroke Patients: A Feasibility Study. Sensors 2023;23(13):5868 View
  35. Huang M, Ren Y, Wang X, Li X, Li L. What affects the use of smartphones by the elderly? A hybrid survey from China. National Accounting Review 2023;5(3):245 View
  36. Paganin G, Margheritti S, Farhane-Medina N, Simbula S, Mazzetti G. Health, Stress and Technologies: Integrating Technology Acceptance and Health Belief Models for Smartphone-Based Stress Intervention. Healthcare 2023;11(23):3030 View
  37. Wu Q, Ngien A, Jiang S. Descriptive Norms and eHealth Use Among Older Adults: A Cross-Country Comparative Study. Health Communication 2023:1 View
  38. Gündüz N, Zaim S, Erzurumlu Y. Investigating impact of health belief and trust on technology acceptance in smartwatch usage: Turkish senior adults case. International Journal of Pharmaceutical and Healthcare Marketing 2024 View
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Books/Policy Documents

  1. George R, Swathi S, Thomas R, Sowmya A. C. , Thomas M. Integrating Digital Health Strategies for Effective Administration. View