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Citing this Article

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Published on 01.10.12 in Vol 14, No 5 (2012): Sep-Oct

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

Works citing "Development of a Health Information Technology Acceptance Model Using Consumers’ Health Behavior Intention"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.2143):

(note that this is only a small subset of citations)

  1. Rajković P, Aleksić D, Janković D, Milenković A, Petković I. Checking the potential shift to perceived usefulness—The analysis of users’ response to the updated electronic health record core features. International Journal of Medical Informatics 2018;115:80
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  2. Wang L, Wu T, Guo X, Zhang X, Li Y, Wang W. Exploring mHealth monitoring service acceptance from a service characteristics perspective. Electronic Commerce Research and Applications 2018;30:159
    CrossRef
  3. Abdelhamid M. Greater patient health information control to improve the sustainability of health information exchanges. Journal of Biomedical Informatics 2018;83:150
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  4. Connor K, Wambach K, Baird M. Descriptive, Qualitative Study of Women Who Use Mobile Health Applications to Obtain Perinatal Health Information. Journal of Obstetric, Gynecologic & Neonatal Nursing 2018;
    CrossRef
  5. Messer LH. Why Expectations Will Determine the Future of Artificial Pancreas. Diabetes Technology & Therapeutics 2018;20(S2):S2-65
    CrossRef
  6. Tavares J, Goulão A, Oliveira T. Electronic Health Record Portals adoption: Empirical model based on UTAUT2. Informatics for Health and Social Care 2018;43(2):109
    CrossRef
  7. Pal D, Funilkul S, Charoenkitkarn N, Kanthamanon P. Internet-of-Things and Smart Homes for Elderly Healthcare: An End User Perspective. IEEE Access 2018;6:10483
    CrossRef
  8. Asingizwe D, Poortvliet PM, Koenraadt CJ, Van Vliet AJ, Murindahabi MM, Ingabire C, Mutesa L, Feindt PH. Applying citizen science for malaria prevention in Rwanda: An integrated conceptual framework. NJAS - Wageningen Journal of Life Sciences 2018;
    CrossRef
  9. Hauk N, Hüffmeier J, Krumm S. Ready to be a Silver Surfer? A Meta-analysis on the Relationship Between Chronological Age and Technology Acceptance. Computers in Human Behavior 2018;84:304
    CrossRef
  10. Ali M, Raza SA, Qazi W, Puah C. Assessing e-learning system in higher education institutes. Interactive Technology and Smart Education 2018;15(1):59
    CrossRef
  11. Ahadzadeh AS, Pahlevan Sharif S, Sim Ong F. Online health information seeking among women: the moderating role of health consciousness. Online Information Review 2018;42(1):58
    CrossRef
  12. Fox G, Connolly R. Mobile health technology adoption across generations: Narrowing the digital divide. Information Systems Journal 2018;
    CrossRef
  13. Middlemass JB, Vos J, Siriwardena AN. Perceptions on use of home telemonitoring in patients with long term conditions – concordance with the Health Information Technology Acceptance Model: a qualitative collective case study. BMC Medical Informatics and Decision Making 2017;17(1)
    CrossRef
  14. Heidarizadeh K, Rassouli M, Manoochehri H, Zagheri Tafreshi M, Kashef Ghorbanpour R. Nurses’ Perception of Challenges in the Use of an Electronic Nursing Documentation System. CIN: Computers, Informatics, Nursing 2017;35(11):599
    CrossRef
  15. Tofighi B, Nicholson JM, McNeely J, Muench F, Lee JD. Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature. Drug and Alcohol Review 2017;36(4):477
    CrossRef
  16. Lee J, Kim JGB, Jin M, Ahn K, Kim B, Kim S, Kim J. Beneficial Effects of Two Types of Personal Health Record Services Connected With Electronic Medical Records Within the Hospital Setting. CIN: Computers, Informatics, Nursing 2017;35(11):574
    CrossRef
  17. Shin D, Lee S, Hwang Y. How do credibility and utility play in the user experience of health informatics services?. Computers in Human Behavior 2017;67:292
    CrossRef
  18. Dou K, Yu P, Deng N, Liu F, Guan Y, Li Z, Ji Y, Du N, Lu X, Duan H. Patients’ Acceptance of Smartphone Health Technology for Chronic Disease Management: A Theoretical Model and Empirical Test. JMIR mHealth and uHealth 2017;5(12):e177
    CrossRef
  19. Chauhan S, Jaiswal M. A meta-analysis of e-health applications acceptance. Journal of Enterprise Information Management 2017;30(2):295
    CrossRef
  20. Hussein Z, Oon SW, Fikry A. Consumer Attitude: Does It Influencing the Intention to Use mHealth?. Procedia Computer Science 2017;105:340
    CrossRef
  21. Wakefield BJ, Turvey CL, Nazi KM, Holman JE, Hogan TP, Shimada SL, Kennedy DR. Psychometric Properties of Patient-Facing eHealth Evaluation Measures: Systematic Review and Analysis. Journal of Medical Internet Research 2017;19(10):e346
    CrossRef
  22. Crane D, Garnett C, Brown J, West R, Michie S. Factors Influencing Usability of a Smartphone App to Reduce Excessive Alcohol Consumption: Think Aloud and Interview Studies. Frontiers in Public Health 2017;5
    CrossRef
  23. Tavares J, Oliveira T. Electronic Health Record Portal Adoption: a cross country analysis. BMC Medical Informatics and Decision Making 2017;17(1)
    CrossRef
  24. Koivumäki T, Pekkarinen S, Lappi M, Väisänen J, Juntunen J, Pikkarainen M. Consumer Adoption of Future MyData-Based Preventive eHealth Services: An Acceptance Model and Survey Study. Journal of Medical Internet Research 2017;19(12):e429
    CrossRef
  25. Martínez-Pernía D, Núñez-Huasaf J, del Blanco , Ruiz-Tagle A, Velásquez J, Gomez M, Robert Blesius C, Ibañez A, Fernández-Manjón B, Slachevsky A. Using game authoring platforms to develop screen-based simulated functional assessments in persons with executive dysfunction following traumatic brain injury. Journal of Biomedical Informatics 2017;74:71
    CrossRef
  26. Salisbury C, O’Cathain A, Thomas C, Edwards L, Montgomery AA, Hollinghurst S, Large S, Nicholl J, Pope C, Rogers A, Lewis G, Fahey T, Yardley L, Brownsell S, Dixon P, Drabble S, Esmonde L, Foster A, Garner K, Gaunt D, Horspool K, Man M, Rowsell A, Segar J. An evidence-based approach to the use of telehealth in long-term health conditions: development of an intervention and evaluation through pragmatic randomised controlled trials in patients with depression or raised cardiovascular risk. Programme Grants for Applied Research 2017;5(1):1
    CrossRef
  27. Shin D, Biocca F. Health experience model of personal informatics: The case of a quantified self. Computers in Human Behavior 2017;69:62
    CrossRef
  28. Marco-Ruiz L, Bønes E, de la Asunción E, Gabarron E, Aviles-Solis JC, Lee E, Traver V, Sato K, Bellika JG. Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. Journal of Biomedical Informatics 2017;74:104
    CrossRef
  29. Khan S, Peña J. Playing to beat the blues: Linguistic agency and message causality effects on use of mental health games application. Computers in Human Behavior 2017;71:436
    CrossRef
  30. Cimperman M, Makovec Brenčič M, Trkman P. Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model. International Journal of Medical Informatics 2016;90:22
    CrossRef
  31. Cho J. The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics 2016;87:75
    CrossRef
  32. Anderson K, Burford O, Emmerton L. App Chronic Disease Checklist: Protocol to Evaluate Mobile Apps for Chronic Disease Self-Management. JMIR Research Protocols 2016;5(4):e204
    CrossRef
  33. Tavares J, Oliveira T. Electronic Health Record Patient Portal Adoption by Health Care Consumers: An Acceptance Model and Survey. Journal of Medical Internet Research 2016;18(3):e49
    CrossRef
  34. Cook N, Winkler SL. Acceptance, Usability and Health Applications of Virtual Worlds by Older Adults: A Feasibility Study. JMIR Research Protocols 2016;5(2):e81
    CrossRef
  35. Thilo FJ, Hürlimann B, Hahn S, Bilger S, Schols JM, Halfens RJ. Involvement of older people in the development of fall detection systems: a scoping review. BMC Geriatrics 2016;16(1)
    CrossRef
  36. Anderson K, Burford O, Emmerton L, van Ooijen PM. Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences. PLOS ONE 2016;11(5):e0156164
    CrossRef
  37. Roettl J, Bidmon S, Terlutter R. What Predicts Patients’ Willingness to Undergo Online Treatment and Pay for Online Treatment? Results from a Web-Based Survey to Investigate the Changing Patient-Physician Relationship. Journal of Medical Internet Research 2016;18(2):e32
    CrossRef
  38. Vugts MAP, Joosen MCW, van Bergen AHMM, Vrijhoef HJM. Feasibility of Applied Gaming During Interdisciplinary Rehabilitation for Patients With Complex Chronic Pain and Fatigue Complaints: A Mixed-Methods Study. JMIR Serious Games 2016;4(1):e2
    CrossRef
  39. Ammerlaan JJ, Scholtus LW, Drossaert CH, van Os-Medendorp H, Prakken B, Kruize AA, Bijlsma JJ. Feasibility of a Website and a Hospital-Based Online Portal for Young Adults With Juvenile Idiopathic Arthritis: Views and Experiences of Patients. JMIR Research Protocols 2015;4(3):e102
    CrossRef
  40. Liu C, Cheng T. Exploring critical factors influencing physicians’ acceptance of mobile electronic medical records based on the dual-factor model: a validation in Taiwan. BMC Medical Informatics and Decision Making 2015;15(1)
    CrossRef
  41. Baumeister H, Seifferth H, Lin J, Nowoczin L, Lüking M, Ebert D. Impact of an Acceptance Facilitating Intervention on Patients’ Acceptance of Internet-based Pain Interventions. The Clinical Journal of Pain 2015;31(6):528
    CrossRef
  42. Mooney K, McElnay JC, Donnelly RF. Parents' perceptions of microneedle-mediated monitoring as an alternative to blood sampling in the monitoring of their infants. International Journal of Pharmacy Practice 2015;23(6):429
    CrossRef
  43. Medlock S, Eslami S, Askari M, Arts DL, Sent D, de Rooij SE, Abu-Hanna A. Health Information–Seeking Behavior of Seniors Who Use the Internet: A Survey. Journal of Medical Internet Research 2015;17(1):e10
    CrossRef
  44. Jeon E, Park H. Factors Affecting Acceptance of Smartphone Application for Management of Obesity. Healthcare Informatics Research 2015;21(2):74
    CrossRef
  45. Lee H, Kim J, Kim KS. The Effects of Nursing Interventions Utilizing Serious Games That Promote Health Activities on the Health Behaviors of Seniors. Games for Health Journal 2015;4(3):175
    CrossRef
  46. Mooney K, McElnay JC, Donnelly RF. Paediatricians’ opinions of microneedle-mediated monitoring: a key stage in the translation of microneedle technology from laboratory into clinical practice. Drug Delivery and Translational Research 2015;5(4):346
    CrossRef
  47. Gabarron E, Serrano JA, Fernandez-Luque L, Wynn R, Schopf T. Randomized trial of a novel game-based appointment system for a university hospital venereology unit: study protocol. BMC Medical Informatics and Decision Making 2015;15(1)
    CrossRef
  48. Ahadzadeh AS, Pahlevan Sharif S, Ong FS, Khong KW. Integrating Health Belief Model and Technology Acceptance Model: An Investigation of Health-Related Internet Use. Journal of Medical Internet Research 2015;17(2):e45
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  49. Ebert D, Berking M, Cuijpers P, Lehr D, Pörtner M, Baumeister H. Increasing the acceptance of internet-based mental health interventions in primary care patients with depressive symptoms. A randomized controlled trial. Journal of Affective Disorders 2015;176:9
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  50. Edwards L, Thomas C, Gregory A, Yardley L, O'Cathain A, Montgomery AA, Salisbury C. Are People With Chronic Diseases Interested in Using Telehealth? A Cross-Sectional Postal Survey. Journal of Medical Internet Research 2014;16(5):e123
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  51. Chang SJ, Im E. A path analysis of Internet health information seeking behaviors among older adults. Geriatric Nursing 2014;35(2):137
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  52. Nikayin F, Heikkilä M, de Reuver M, Solaimani S. Workplace primary prevention programmes enabled by information and communication technology. Technological Forecasting and Social Change 2014;89:326
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  53. Ahlan AR, Ahmad BI. User Acceptance of Health Information Technology (HIT) in Developing Countries: A Conceptual Model. Procedia Technology 2014;16:1287
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  54. Bidmon S, Terlutter R, Röttl J. What Explains Usage of Mobile Physician-Rating Apps? Results From a Web-Based Questionnaire. Journal of Medical Internet Research 2014;16(6):e148
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  55. de Graaf M, Totté JE, van Os-Medendorp H, van Renselaar W, Breugem CC, Pasmans SG. Treatment of Infantile Hemangioma in Regional Hospitals With eHealth Support: Evaluation of Feasibility and Acceptance by Parents and Doctors. JMIR Research Protocols 2014;3(4):e52
    CrossRef
  56. Kim J. Analysis of Health Consumers' Behavior Using Self-Tracker for Activity, Sleep, and Diet. Telemedicine and e-Health 2014;20(6):552
    CrossRef
  57. Baumeister H, Nowoczin L, Lin J, Seifferth H, Seufert J, Laubner K, Ebert D. Impact of an acceptance facilitating intervention on diabetes patients’ acceptance of Internet-based interventions for depression: A randomized controlled trial. Diabetes Research and Clinical Practice 2014;105(1):30
    CrossRef
  58. Kim J. A Qualitative Analysis of User Experiences With a Self-Tracker for Activity, Sleep, and Diet. interactive Journal of Medical Research 2014;3(1):e8
    CrossRef
  59. LeRouge C, Van Slyke C, Seale D, Wright K. Baby Boomers’ Adoption of Consumer Health Technologies: Survey on Readiness and Barriers. Journal of Medical Internet Research 2014;16(9):e200
    CrossRef
  60. Chung Y, Han H. A Study of Factors Influencing the Intention of University Students to Accept Healthcare Information Technology Services. Journal of the Korea Academia-Industrial cooperation Society 2013;14(11):5698
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  61. de Graaf M, Totte J, Breugem C, van Os-Medendorp H, Pasmans S. Evaluation of the Compliance, Acceptance, and Usability of a Web-Based eHealth Intervention for Parents of Children With Infantile Hemangiomas: Usability Study. JMIR Research Protocols 2013;2(2):e54
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