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

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

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

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

Journals

  1. 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 View
  2. Ye T, Xue J, He M, Gu J, Lin H, Xu B, Cheng Y. Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study. Journal of Medical Internet Research 2019;21(10):e14316 View
  3. 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 View
  4. Tang J, James L, Howell M, Tong A, Wong G. eHealth Interventions for Solid Organ Transplant Recipients: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Transplantation 2020;104(8):e224 View
  5. 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 View
  6. Richardson B, Benoit B, Rutledge K, Dol J, Misener R, Latimer M, Smit M, McGrath P, Campbell-Yeo M. The impact of parent-targeted eHealth educational interventions on infant procedural pain management. JBI Database of Systematic Reviews and Implementation Reports 2019;17(8):1589 View
  7. Fox G, Connolly R. Mobile health technology adoption across generations: Narrowing the digital divide. Information Systems Journal 2018;28(6):995 View
  8. 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 View
  9. Anderberg P, Eivazzadeh S, Berglund J. A Novel Instrument for Measuring Older People’s Attitudes Toward Technology (TechPH): Development and Validation. Journal of Medical Internet Research 2019;21(5):e13951 View
  10. Lee H, Kim J, Kim K. 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 View
  11. Ali R, Zhang Z, Bux Soomro M. Smoking-cessation acceptance via mobile health. Human Systems Management 2019;38(3):313 View
  12. Abuhammad S, Khabour O, Alzoubi K. <p>COVID-19 Contact-Tracing Technology: Acceptability and Ethical Issues of Use</p>. Patient Preference and Adherence 2020;Volume 14:1639 View
  13. Salisbury C, O’Cathain A, Thomas C, Edwards L, Montgomery A, 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 View
  14. Tavares J, Oliveira T. New Integrated Model Approach to Understand the Factors That Drive Electronic Health Record Portal Adoption: Cross-Sectional National Survey. Journal of Medical Internet Research 2018;20(11):e11032 View
  15. Apolinário-Hagen J, Hennemann S, Fritsche L, Drüge M, Breil B. Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study. JMIR Mental Health 2019;6(11):e15373 View
  16. Kao Y, Nawata K, Huang C. An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers. International Journal of Environmental Research and Public Health 2019;16(18):3227 View
  17. 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 View
  18. Rajković P, Janković D, Milenković A, Kocić I. ANALYSIS OF THE LEVEL OF USE AND ACCEPTA NCE OF THE MEDICAL INFORMATION SYSTEM IN PRIMARY HEALTH CAR E. Acta Medica Medianae 2018;57(4):122 View
  19. 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;47(6):728 View
  20. 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
  21. Gabarron E, Serrano J, 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) View
  22. Middlemass J, Vos J, Siriwardena A. 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) View
  23. Mooney K, McElnay J, Donnelly R. 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 View
  24. Wu D, Huang W, Zhao P, Li C, Cao B, Wang Y, Stoneking S, Tang W, Luo Z, Wei C, Tucker J. A Crowdsourced Physician Finder Prototype Platform for Men Who Have Sex with Men in China: Qualitative Study of Acceptability and Feasibility. JMIR Public Health and Surveillance 2019;5(4):e13027 View
  25. Frontini R, Sousa P, Dixe M, Ferreira R, Figueiredo M. Designing a mobile app to promote healthy behaviors and prevent obesity: analysis of adolescents’ preferences. Informatics for Health and Social Care 2020;45(3):327 View
  26. Jeffrey B, Bagala M, Creighton A, Leavey T, Nicholls S, Wood C, Longman J, Barker J, Pit S. Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users. Diabetology & Metabolic Syndrome 2019;11(1) View
  27. Cook N, Winkler S. Acceptance, Usability and Health Applications of Virtual Worlds by Older Adults: A Feasibility Study. JMIR Research Protocols 2016;5(2):e81 View
  28. 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 View
  29. Wakefield B, Turvey C, Nazi K, Holman J, Hogan T, Shimada S, Kennedy D. Psychometric Properties of Patient-Facing eHealth Evaluation Measures: Systematic Review and Analysis. Journal of Medical Internet Research 2017;19(10):e346 View
  30. Gow C, Wong S, Lim C. Effect of Output Quality and Result Demonstrability on Generation Y’s Behavioural Intention in Adopting Mobile Health Applications. Asia-Pacific Journal of Management Research and Innovation 2019;15(3):111 View
  31. Pai R, Alathur S. Determinants of individuals’ intention to use mobile health: insights from India. Transforming Government: People, Process and Policy 2019;13(3/4):306 View
  32. de Graaf M, Totté J, van Os-Medendorp H, van Renselaar W, Breugem C, Pasmans S. 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 View
  33. 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 View
  34. 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 View
  35. Hsiao S, Tseng H. The Impact of the Moderating Effect of Psychological Health Status on Nurse Healthcare Management Information System Usage Intention. Healthcare 2020;8(1):28 View
  36. Tao D, Yuan J, Shao F, Li D, Zhou Q, Qu X. Factors Affecting Consumer Acceptance of an Online Health Information Portal Among Young Internet Users. CIN: Computers, Informatics, Nursing 2018;36(11):530 View
  37. 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 View
  38. Zhang L, Jung E, Chen Z. Modeling the Pathway Linking Health Information Seeking to Psychological Well-Being on WeChat. Health Communication 2020;35(9):1101 View
  39. Dias S, Frontinia R, Sousa P. Implementation of a mobile app (TeenPower) to prevent overweight and obesity: Preliminary results regarding lifestyle and usability. Procedia Computer Science 2019;164:581 View
  40. Nadal C, Sas C, Doherty G. Technology Acceptance in Mobile Health: Scoping Review of Definitions, Models, and Measurement. Journal of Medical Internet Research 2020;22(7):e17256 View
  41. Trang S, Trenz M, Weiger W, Tarafdar M, Cheung C. One app to trace them all? Examining app specifications for mass acceptance of contact-tracing apps. European Journal of Information Systems 2020;29(4):415 View
  42. Edwards L, Thomas C, Gregory A, Yardley L, O'Cathain A, Montgomery A, 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 View
  43. Ghaddar S, Vatcheva K, Alvarado S, Mykyta L. Understanding the Intention to Use Telehealth Services in Underserved Hispanic Border Communities: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(9):e21012 View
  44. 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 View
  45. 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 View
  46. Agudelo-Londoño S. Reflexión sobre la evaluación de impacto en eSalud. «No todo lo que brilla es oro». Trilogía Ciencia Tecnología Sociedad 2020;12(22):103 View
  47. 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) View
  48. Sterling R, LeRouge C. On-Demand Telemedicine as a Disruptive Health Technology: Qualitative Study Exploring Emerging Business Models and Strategies Among Early Adopter Organizations in the United States. Journal of Medical Internet Research 2019;21(11):e14304 View
  49. Shin D, Biocca F. Health experience model of personal informatics: The case of a quantified self. Computers in Human Behavior 2017;69:62 View
  50. 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 View
  51. Ramírez-Correa P, Ramírez-Rivas C, Alfaro-Pérez J, Melo-Mariano A. Telemedicine Acceptance during the COVID-19 Pandemic: An Empirical Example of Robust Consistent Partial Least Squares Path Modeling. Symmetry 2020;12(10):1593 View
  52. Ammerlaan J, Scholtus L, Drossaert C, van Os-Medendorp H, Prakken B, Kruize A, Bijlsma J. 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 View
  53. Huang G, Ren Y. Linking technological functions of fitness mobile apps with continuance usage among Chinese users: Moderating role of exercise self-efficacy. Computers in Human Behavior 2020;103:151 View
  54. Zimmerman M, Shaw G. Health information seeking behaviour: a concept analysis. Health Information & Libraries Journal 2020;37(3):173 View
  55. Chang S, Im E. A path analysis of Internet health information seeking behaviors among older adults. Geriatric Nursing 2014;35(2):137 View
  56. Buitenweg D, van de Mheen D, Grund J, van Oers H, van Nieuwenhuizen C. Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems: Qualitative Evaluation. JMIR Mental Health 2020;7(12):e19593 View
  57. Langford A, Loeb S. Perceived Patient-Provider Communication Quality and Sociodemographic Factors Associated With Watching Health-Related Videos on YouTube: A Cross-Sectional Analysis. Journal of Medical Internet Research 2019;21(5):e13512 View
  58. 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 View
  59. Hussein Z, Oon S, Fikry A. Consumer Attitude: Does It Influencing the Intention to Use mHealth?. Procedia Computer Science 2017;105:340 View
  60. Ahadzadeh A, 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 View
  61. Duan H, Wang Z, Ji Y, Ma L, Liu F, Chi M, Deng N, An J. Using Goal-Directed Design to Create a Mobile Health App to Improve Patient Compliance With Hypertension Self-Management: Development and Deployment. JMIR mHealth and uHealth 2020;8(2):e14466 View
  62. Ali M, Raza S, Qazi W, Puah C. Assessing e-learning system in higher education institutes. Interactive Technology and Smart Education 2018;15(1):59 View
  63. Wei J, Vinnikova A, Lu L, Xu J. Understanding and Predicting the Adoption of Fitness Mobile Apps: Evidence from China. Health Communication 2021;36(8):950 View
  64. 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 View
  65. Jeon E, Park H. Factors Affecting Acceptance of Smartphone Application for Management of Obesity. Healthcare Informatics Research 2015;21(2):74 View
  66. Cho J. The impact of post-adoption beliefs on the continued use of health apps. International Journal of Medical Informatics 2016;87:75 View
  67. C.C. S, Prathap S. Continuance adoption of mobile-based payments in Covid-19 context: an integrated framework of health belief model and expectation confirmation model. International Journal of Pervasive Computing and Communications 2020;16(4):351 View
  68. Ali R, Zhang Z, Soomro M. Smoking-Cessation Acceptance Via Mobile Health and Quick Response Code Technologies: Empirical Evidence of a Pilot Study from China and Pakistan. Current Psychology 2019 View
  69. Medlock S, Eslami S, Askari M, Arts D, Sent D, de Rooij S, Abu-Hanna A. Health Information–Seeking Behavior of Seniors Who Use the Internet: A Survey. Journal of Medical Internet Research 2015;17(1):e10 View
  70. Marco-Ruiz L, Bønes E, de la Asunción E, Gabarron E, Aviles-Solis J, Lee E, Traver V, Sato K, Bellika J. Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. Journal of Biomedical Informatics 2017;74:104 View
  71. Asingizwe D, Poortvliet P, Koenraadt C, Van Vliet A, Murindahabi M, Ingabire C, Mutesa L, Feindt P. Applying citizen science for malaria prevention in Rwanda: An integrated conceptual framework. NJAS - Wageningen Journal of Life Sciences 2018;86-87:111 View
  72. Ahlan A, Ahmad B. User Acceptance of Health Information Technology (HIT) in Developing Countries: A Conceptual Model. Procedia Technology 2014;16:1287 View
  73. Povey J, Mills P, Dingwall K, Lowell A, Singer J, Rotumah D, Bennett-Levy J, Nagel T. Acceptability of Mental Health Apps for Aboriginal and Torres Strait Islander Australians: A Qualitative Study. Journal of Medical Internet Research 2016;18(3):e65 View
  74. Abdelhamid M. Greater patient health information control to improve the sustainability of health information exchanges. Journal of Biomedical Informatics 2018;83:150 View
  75. 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 View
  76. Sima V, Gheorghe I, Subić J, Nancu D. Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability 2020;12(10):4035 View
  77. Silver R, Subramaniam C, Stylianou A. The Impact of Portal Satisfaction on Portal Use and Health-Seeking Behavior: Structural Equation Analysis. Journal of Medical Internet Research 2020;22(3):e16260 View
  78. Billmann M, Böhm M, Krcmar H. Use of workplace health promotion apps: Analysis of employee log data. Health Policy and Technology 2020;9(3):285 View
  79. Thilo F, Hürlimann B, Hahn S, Bilger S, Schols J, Halfens R. Involvement of older people in the development of fall detection systems: a scoping review. BMC Geriatrics 2016;16(1) View
  80. Anderson K, Burford O, Emmerton L, van Ooijen P. Mobile Health Apps to Facilitate Self-Care: A Qualitative Study of User Experiences. PLOS ONE 2016;11(5):e0156164 View
  81. 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
  82. Tavares J, Oliveira T. Electronic Health Record Portal Adoption: a cross country analysis. BMC Medical Informatics and Decision Making 2017;17(1) View
  83. Anil Kumar K, Natarajan S. An extension of the Expectation Confirmation Model (ECM) to study continuance behavior in using e-Health services. Innovative Marketing 2020;16(2):15 View
  84. Zhao Y, Li K, Zhang L. A meta-analysis of online health adoption and the moderating effect of economic development level. International Journal of Medical Informatics 2019;127:68 View
  85. 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 View
  86. Abolhassani N, Santos-Eggimann B, Chiolero A, Santschi V, Henchoz Y. Readiness to accept health information and communication technologies: A population-based survey of community-dwelling older adults. International Journal of Medical Informatics 2019;130:103950 View
  87. Singh G, MacGillivray M, Mills P, Adams J, Sawatzky B, Mortenson W. Patients’ Perspectives on the Usability of a Mobile App for Self-Management following Spinal Cord Injury. Journal of Medical Systems 2020;44(1) View
  88. Mooney K, McElnay J, Donnelly R. 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 View
  89. 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
  90. 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 View
  91. Vugts M, Joosen M, van Bergen A, Vrijhoef H. 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 View
  92. 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 View
  93. Kim J. Analysis of Health Consumers' Behavior Using Self-Tracker for Activity, Sleep, and Diet. Telemedicine and e-Health 2014;20(6):552 View
  94. Salgado T, Tavares J, Oliveira T. Drivers of Mobile Health Acceptance and Use From the Patient Perspective: Survey Study and Quantitative Model Development. JMIR mHealth and uHealth 2020;8(7):e17588 View
  95. Ahadzadeh A, Pahlevan Sharif S, Ong F, Khong K. Integrating Health Belief Model and Technology Acceptance Model: An Investigation of Health-Related Internet Use. Journal of Medical Internet Research 2015;17(2):e45 View
  96. Puspitasari I, Firdauzy A. Characterizing Consumer Behavior in Leveraging Social Media for E-Patient and Health-Related Activities. International Journal of Environmental Research and Public Health 2019;16(18):3348 View
  97. 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 View
  98. Chauhan S, Jaiswal M. A meta-analysis of e-health applications acceptance. Journal of Enterprise Information Management 2017;30(2):295 View
  99. Zhang Y, Wen N, Chao N. Effects of mobile information-seeking on the intention to obtain reproductive cancer screening among chinese women: testing an integrative model. Chinese Journal of Communication 2019;12(1):102 View
  100. Ghezzi P, Bannister P, Casino G, Catalani A, Goldman M, Morley J, Neunez M, Prados-Bo A, Smeesters P, Taddeo M, Vanzolini T, Floridi L. Online Information of Vaccines: Information Quality, Not Only Privacy, Is an Ethical Responsibility of Search Engines. Frontiers in Medicine 2020;7 View
  101. 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 View
  102. Melo C, Filho A, de Oliveira E, de Araújo A, Cavalcanti H, Melo C, Bushatsky M, Sanches L, Barros M. Development and Assessment of an Application for Primary Care for Users with Diabetes Mellitus. Aquichan 2020;20(2):1 View
  103. Messer L. Why Expectations Will Determine the Future of Artificial Pancreas. Diabetes Technology & Therapeutics 2018;20(S2):S2-65 View
  104. Tofighi B, Nicholson J, McNeely J, Muench F, Lee J. Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature. Drug and Alcohol Review 2017;36(4):477 View
  105. 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 View
  106. Sousa P, Duarte E, Ferreira R, Esperança A, Frontini R, Santos-Rocha R, Luís L, Dias S, Marques N. An mHealth intervention programme to promote healthy behaviours and prevent adolescent obesity (TeenPower): A study protocol. Journal of Advanced Nursing 2019;75(3):683 View
  107. Januraga P, Izwardi D, Crosita Y, Indrayathi P, Kurniasari E, Sutrisna A, Tumilowicz A. Qualitative evaluation of a social media campaign to improve healthy food habits among urban adolescent females in Indonesia. Public Health Nutrition 2021;24(S2):s98 View
  108. Martínez-Pernía D, Núñez-Huasaf J, del Blanco Á, 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 View
  109. 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 View
  110. Sousa P, Martinho R, Reis C, Dias S, Gaspar P, Dixe M, Luis L, Ferreira R. Controlled trial of an mHealth intervention to promote healthy behaviours in adolescence (TeenPower): Effectiveness analysis. Journal of Advanced Nursing 2020;76(4):1057 View
  111. 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 View
  112. 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 View
  113. Sin D, Guo X, Yong D, Qiu T, Moey P, Falk M, Tan N. Assessment of willingness to Tele-monitoring interventions in patients with type 2 diabetes and/or hypertension in the public primary healthcare setting. BMC Medical Informatics and Decision Making 2020;20(1) View
  114. Phillips K. No, Bananas Don’t Cure HIV, Nor Will Garlic Cure COVID-19: Searching for, Assessing, and Consuming Health Information Online. Journal of Consumer Health on the Internet 2020;24(2):175 View
  115. Lee J, Kim J, 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 View
  116. Yu N, Huang Y. Important Factors Affecting User Experience Design and Satisfaction of a Mobile Health App—A Case Study of Daily Yoga App. International Journal of Environmental Research and Public Health 2020;17(19):6967 View
  117. Kouton J, Bétila R, Lawin M. The Impact of ICT Development on Health Outcomes in Africa: Does Economic Freedom Matter?. Journal of the Knowledge Economy 2020 View
  118. Saprikis V, Avlogiaris G, Katarachia A. Determinants of the Intention to Adopt Mobile Augmented Reality Apps in Shopping Malls among University Students. Journal of Theoretical and Applied Electronic Commerce Research 2020;16(3):491 View
  119. Wang H, Liang L, Du C, Wu Y. Implementation of Online Hospitals and Factors Influencing the Adoption of Mobile Medical Services in China: Cross-Sectional Survey Study. JMIR mHealth and uHealth 2021;9(2):e25960 View
  120. Jackman K, Kane J, Kharrazi H, Johnson R, Latkin C. Using the Patient Portal Sexual Health Instrument in Surveys and Patient Questionnaires Among Sexual Minority Men in the United States: Cross-sectional Psychometric Validation Study. Journal of Medical Internet Research 2021;23(2):e18750 View
  121. You (Ryu) K, Cho J. Investigation of the Influential Factors in Leading People to Seek Mobile Information for the Promotion of Health-Related Behaviors. Sustainability 2020;12(24):10512 View
  122. Jacobs J, Walsh E, Rapoport C, Antoni M, Park E, Post K, Comander A, Peppercorn J, Safren S, Temel J, Greer J. Development and Refinement of a Telehealth Intervention for Symptom Management, Distress, and Adherence to Adjuvant Endocrine Therapy after Breast Cancer. Journal of Clinical Psychology in Medical Settings 2020 View
  123. Andrade A, LeBlanc V, Kalisch-Ellett L, Pratt N, Moffat A, Blacker N, Westaway K, Barratt J, Roughead E. Determinants of usefulness in professional behaviour change interventions: observational study of a 15-year national program. BMJ Open 2020;10(10):e038016 View
  124. Lee M, Kang D, Yoon J, Shim S, Kim I, Oh D, Shin S, Hesse B, Cho J, Weston K. The difference in knowledge and attitudes of using mobile health applications between actual user and non-user among adults aged 50 and older. PLOS ONE 2020;15(10):e0241350 View
  125. Alhusseini N, Banta J, Oh J, Montgomery S. Understanding the Use of Electronic Means to Seek Personal Health Information Among Adults in the United States. Cureus 2020 View
  126. Han Y, Jiang B, Guo R. Factors Affecting Public Adoption of Prevention and Treatment Information Under the Infodemic: An Integrated Conceptual Adoption Framework (Preprint). Journal of Medical Internet Research 2020 View
  127. O’Neill M, Houghton C, Crilly G, Dowling M. A qualitative evidence synthesis of users’ experience of mobile health applications in the self-management of type 2 diabetes. Chronic Illness 2021:174239532098387 View
  128. Nadal C, Earley C, Enrique A, Vigano N, Sas C, Richards D, Doherty G. Integration of a smartwatch within an internet-delivered intervention for depression: Protocol for a feasibility randomized controlled trial on acceptance. Contemporary Clinical Trials 2021;103:106323 View
  129. Kim T, Ho C. Validating the moderating role of age in multi-perspective acceptance model of wearable healthcare technology. Telematics and Informatics 2021;61:101603 View
  130. Akintunde T, Chen S, Ibrahim E, Tassang A. Maternal Self-rated Capability Status and Its Association with Under-Five Children Morbidity. Journal of Primary Care & Community Health 2021;12:215013272110021 View
  131. Gimpel H, Manner-Romberg T, Schmied F, Winkler T. Understanding the evaluation of mHealth app features based on a cross-country Kano analysis. Electronic Markets 2021 View
  132. Kim B, Hong S, Kim S. The Integrated Model of Wearable Activity Tracker Use: Exploring Health Beliefs and Obesity Information Seeking Behaviors from a National Quota Sample (Preprint). JMIR Formative Research 2020 View
  133. Cho Y, Zhang H, Harris M, Gong Y, Smith E, Jiang Y. Acceptance and Use of Home-Based Electronic Symptom Self-Reporting Systems in Patients With Cancer: Systematic Review. Journal of Medical Internet Research 2021;23(3):e24638 View
  134. 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
  135. Tsai W, Wu Y, Cheng C, Kuo M, Chang Y, Hu F, Sun C, Chang C, Chan T, Chen C, Lee C, Chu C. A Technology Acceptance Model for Deploying Masks to Combat the COVID-19 Pandemic in Taiwan (My Health Bank): Web-Based Cross-sectional Survey Study. Journal of Medical Internet Research 2021;23(4):e27069 View
  136. Jeong G, Choi H. Health Information-seeking Behaviors: A Review of National Survey Instruments (Preprint). Journal of Medical Internet Research 2021 View
  137. Liu L, Shi L. Does the ownership of health website matter? A cross-sectional study on Chinese consumer behavior. International Journal of Medical Informatics 2021;152:104485 View
  138. Khorram-Manesh A, Dulebenets M, Goniewicz K. Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review. International Journal of Environmental Research and Public Health 2021;18(11):5888 View
  139. Palos-Sanchez P, Saura J, Rios Martin M, Aguayo Camacho M. M-Health Apps: Towards a Better Understanding Intention to Use (Preprint). JMIR mHealth and uHealth 2021 View
  140. Moqbel M, Hewitt B, Nah F, McLean R. Sustaining Patient Portal Continuous Use Intention and Enhancing Deep Structure Usage: Cognitive Dissonance Effects of Health Professional Encouragement and Security Concerns. Information Systems Frontiers 2021 View
  141. Park H, Kim K, Chung H, Jeong S, Soh J, Hyun Y, Kim H. A worker-centered personal health record app for workplace health promotion using national healthcare datasets: A design and development study (Preprint). JMIR Medical Informatics 2021 View
  142. Alsaad A, Al-Okaily M. Acceptance of protection technology in a time of fear: the case of Covid-19 exposure detection apps. Information Technology & People 2021;ahead-of-print(ahead-of-print) View
  143. Ahadzadeh A, Wu S, Ong F, Deng R. Internal Health Locus of Control and mHealth Adoption: The Mediating Influence of Unified Theory of Acceptance and Use of Technology (UTAUT) (Preprint). Journal of Medical Internet Research 2021 View
  144. Walling B, Totzkay D, Silk K, Boumis J, Thomas B, Smith S. Evaluating the Feasibility of Continuing Medical Education for Disseminating Emerging Science on the Breast Cancer and Environment Connection. Journal of Health Communication 2021:1 View
  145. Kirkscey R. Development and Patient User Experience Evaluation of an mHealth Informational App for Osteoporosis. International Journal of Human–Computer Interaction 2021:1 View
  146. Cheung Y, Lam P, Lam T, Lam H, Li C. Technology Acceptance of Patients with Hemophilia in Hong Kong and Their Expectations of an mHealth Application to Promote Self-Management: A Survey Study (Preprint). JMIR Formative Research 2021 View
  147. Kallmerten P, Chia L, Jakub K, Turk M. Patient Portal Use by Adults With Heart Failure. CIN: Computers, Informatics, Nursing 2021;39(8):418 View

Books/Policy Documents

  1. Chen H, Levkoff S. Human Aspects of IT for the Aged Population. Design for Everyday Life. View
  2. Šmahel D, Macháčková H, Šmahelová M, Čevelíček M, Almenara C, Holubčíková J. Digital Technology, Eating Behaviors, and Eating Disorders. View
  3. Boontarig W, Papasratorn B, Chutimaskul W. Technology Adoption and Social Issues. View
  4. Kuika Watat J, Moukoko Mbonjo M. Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. View
  5. Zhu Y, Sun S. Digital Health and Medical Analytics. View