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

Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (542) Adoption and Change Management of eHealth Systems (674) Electronic Health Records (966)

Published on in Vol 19, No 12 (2017): December

Consumer Adoption of Future MyData-Based Preventive eHealth Services: An Acceptance Model and Survey Study

Consumer Adoption of Future MyData-Based Preventive eHealth Services: An Acceptance Model and Survey Study

Consumer Adoption of Future MyData-Based Preventive eHealth Services: An Acceptance Model and Survey Study

Authors of this article:

Timo Koivumäki1, 2 Author Orcid Image ;   Saara Pekkarinen3 Author Orcid Image ;   Minna Lappi3 Author Orcid Image ;   Jere Väisänen3 Author Orcid Image ;   Jouni Juntunen3 Author Orcid Image ;   Minna Pikkarainen1, 2, 4 Author Orcid Image
Article Authors Cited by (48) Tweetations (15) Metrics

Journals

  1. Harst L, Lantzsch H, Scheibe M. Theories Predicting End-User Acceptance of Telemedicine Use: Systematic Review. Journal of Medical Internet Research 2019;21(5):e13117 View
  2. Herrenkind B, Nastjuk I, Brendel A, Trang S, Kolbe L. Young people’s travel behavior – Using the life-oriented approach to understand the acceptance of autonomous driving. Transportation Research Part D: Transport and Environment 2019;74:214 View
  3. Queiroz M, Fosso Wamba S, De Bourmont M, Telles R. Blockchain adoption in operations and supply chain management: empirical evidence from an emerging economy. International Journal of Production Research 2020:1 View
  4. Häikiö J, Yli-Kauhaluoma S, Pikkarainen M, Iivari M, Koivumäki T. Expectations to data: Perspectives of service providers and users of future health and wellness services. Health and Technology 2020;10(3):621 View
  5. Grundstrom C, Korhonen O, Väyrynen K, Isomursu M. Insurance Customers’ Expectations for Sharing Health Data: Qualitative Survey Study. JMIR Medical Informatics 2020;8(3):e16102 View
  6. Herrenkind B, Brendel A, Nastjuk I, Greve M, Kolbe L. Investigating end-user acceptance of autonomous electric buses to accelerate diffusion. Transportation Research Part D: Transport and Environment 2019;74:255 View
  7. Park H, Kim K, Soh J, Hyun Y, Jang S, Lee S, Hwang G, Kim H. Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2020;8(6):e16723 View
  8. Zhang Y, Liu C, Luo S, Xie Y, Liu F, Li X, Zhou Z. Factors Influencing Patients’ Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey. Journal of Medical Internet Research 2019;21(8):e15023 View
  9. van Velsen L, Evers M, Bara C, Op den Akker H, Boerema S, Hermens H. Understanding the Acceptance of an eHealth Technology in the Early Stages of Development: An End-User Walkthrough Approach and Two Case Studies. JMIR Formative Research 2018;2(1):e10474 View
  10. Tao D, Wang T, Wang T, Zhang T, Zhang X, Qu X. A systematic review and meta-analysis of user acceptance of consumer-oriented health information technologies. Computers in Human Behavior 2020;104:106147 View
  11. Choi Y, Kim J, Kwon I, Kim T, Kim S, Cha W, Jeong J, Lee J. Development of a Mobile Personal Health Record Application Designed for Emergency Care in Korea; Integrated Information from Multicenter Electronic Medical Records. Applied Sciences 2020;10(19):6711 View
  12. Yusif S, Hafeez-Baig A, Soar J, Teik D. PLS-SEM path analysis to determine the predictive relevance of e-Health readiness assessment model. Health and Technology 2020;10(6):1497 View
  13. Mathai N, McGill T, Toohey D. Factors Influencing Consumer Adoption of Electronic Health Records. Journal of Computer Information Systems 2022;62(2):267 View
  14. Qi M, Cui J, Li X, Han Y. Perceived Factors Influencing the Public Intention to Use E-Consultation: Analysis of Web-Based Survey Data. Journal of Medical Internet Research 2021;23(1):e21834 View
  15. Li D, Hu Y, Pfaff H, Wang L, Deng L, Lu C, Xia S, Cheng S, Zhu X, Wu X. Determinants of Patients’ Intention to Use the Online Inquiry Services Provided by Internet Hospitals: Empirical Evidence From China. Journal of Medical Internet Research 2020;22(10):e22716 View
  16. Pan M, Gao W. Determinants of the behavioral intention to use a mobile nursing application by nurses in China. BMC Health Services Research 2021;21(1) View
  17. Günthner T, Proff H. On the way to autonomous driving: How age influences the acceptance of driver assistance systems. Transportation Research Part F: Traffic Psychology and Behaviour 2021;81:586 View
  18. Sora B, Nieto R, Montesano del Campo A, Armayones M. Acceptance and Use of Telepsychology From the Clients’ Perspective: Questionnaire Study to Document Perceived Advantages and Barriers. JMIR Mental Health 2021;8(10):e22199 View
  19. Günthner T. The moderating influence of life events on the acceptance of advanced driver assistance systems in aging societies. Computers in Human Behavior Reports 2022;7:100202 View
  20. Xu L, Li P, Hou X, Yu H, Tang T, Liu T, Xiang S, Wu X, Huang C. Middle-aged and elderly users’ continuous usage intention of health maintenance-oriented WeChat official accounts: empirical study based on a hybrid model in China. BMC Medical Informatics and Decision Making 2021;21(1) View
  21. Choi W, Chang S, Yang Y, Jung S, Lee S, Chun J, Kim D, Lee W, Choi I. Study of the factors influencing the use of MyData platform based on personal health record data sharing system. BMC Medical Informatics and Decision Making 2022;22(1) View
  22. Mensah I, Zeng G, Mwakapesa D. The behavioral intention to adopt mobile health services: The moderating impact of mobile self-efficacy. Frontiers in Public Health 2022;10 View
  23. Tang J, Howell M, Roger S, Wong G, Tong A. Perspectives of Kidney Transplant Recipients on eHealth: Semistructured Interviews. Transplantation Direct 2022;8(12):e1404 View
  24. 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
  25. Trkman M, Popovič A, Trkman P. The roles of privacy concerns and trust in voluntary use of governmental proximity tracing applications. Government Information Quarterly 2023;40(1):101787 View
  26. Leväsluoto J, Kohl J, Sigfrids A, Pihlajamäki J, Martikainen J. Digitalization as an Engine for Change? Building a Vision Pathway towards a Sustainable Health Care System by Using the MLP and Health Economic Decision Modelling. Sustainability 2021;13(23):13007 View
  27. Azimi S, Estai M, Patel J, Silva D. The feasibility of a digital health approach to facilitate remote dental screening among preschool children during COVID‐19 and social restrictions. International Journal of Paediatric Dentistry 2023;33(3):234 View
  28. Sumaedi S, Sumardjo , Saleh A, Syukri A. Factors influencing millennials' online healthy food information-sharing behaviour during the Covid-19 pandemic. British Food Journal 2022;124(9):2772 View
  29. Jacob C, Sezgin E, Sanchez-Vazquez A, Ivory C. Sociotechnical Factors Affecting Patients’ Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis. JMIR mHealth and uHealth 2022;10(5):e36284 View
  30. Mukherjee S, Baral M, Lavanya B, Nagariya R, Singh Patel B, Chittipaka V. Intentions to adopt the blockchain: investigation of the retail supply chain. Management Decision 2023;61(5):1320 View
  31. Pagé I, Roos M, Collin O, Lynch S, Lamontagne M, Massé-Alarie H, K. Blanchette A. UTAUT2-based questionnaire: cross-cultural adaptation to Canadian French. Disability and Rehabilitation 2023;45(4):709 View
  32. Devkota B, Montalvo F, McConnell D, Smither J. Combined Model of Technology Use and Medical Adherence in eHealth Technology Implementation. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2021;65(1):776 View
  33. Kalańska-Łukasik B, Gładyś A, Jadczyk T, Gruz-Kwapisz M, Wojakowski W, Kowalska M. Readiness for Telemedical Services in Patients With Cardiovascular Diseases: Cross-sectional Study. JMIR Formative Research 2022;6(10):e33769 View
  34. Phibbs C, Rahman S. A Synopsis of “The Impact of Motivation, Price, and Habit on Intention to Use IoT-Enabled Technology: A Correlational Study”. Journal of Cybersecurity and Privacy 2022;2(3):662 View
  35. Shao H, Liu C, Tang L, Wang B, Xie H, Zhang Y. Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study. JMIR Human Factors 2023;10:e46624 View
  36. Priyank H, Verma A, Zama Khan D, Prakash Rai N, Kalburgi V, Singh S. Comparative Evaluation of Dental Caries Score Between Teledentistry Examination and Clinical Examination: A Systematic Review and Meta-Analysis. Cureus 2023 View
  37. Busch-Casler J, Radic M. Trust and Health Information Exchanges: Qualitative Analysis of the Intent to Share Personal Health Information. Journal of Medical Internet Research 2023;25:e41635 View
  38. Memenga P, Baumann E, Luetke Lanfer H, Reifegerste D, Geulen J, Weber W, Hahne A, Müller A, Weg-Remers S. Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey. Journal of Medical Internet Research 2023;25:e45198 View
  39. Altawaiha I, Atan R, Yaakob R, Abdullah R. A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption. International Journal of Information Technology 2024 View
  40. Rosenberg D. The Use of Online Medical Record Functionalities in Older Adulthood: The Role of Use Encouragement and Access Frequency. Journal of Technology in Human Services 2024;42(1):65 View
  41. Nguyen H, Tapanainen T, Hubona G. Behavioral responses resulting from e-health services and the role of user satisfaction: the case of the online diabetes test. Journal of Systems and Information Technology 2024;26(2):141 View
  42. Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View
  43. 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

Books/Policy Documents

  1. Parra L, Rocher J, Sendra S, Lloret J. Energy Conservation for IoT Devices. View
  2. Günthner T. Making Connected Mobility Work. View
  3. Jayathilake C, Keikhosrokiani P, Isomursu M. Digital Health and Wireless Solutions. View
  4. Hyry J, Karppinen P, Kobayashi T, Anzai D. Digital Health and Wireless Solutions. View