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

Mobile Health (mhealth) (2939) Adoption and Change Management of eHealth Systems (712) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1399) Apps, Mobile, Wearables for Diabetes (298) Diabetes Self-Management (484)

Published on in Vol 21, No 8 (2019): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/15023, first published .
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

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

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

Authors of this article:

Yiyu Zhang1, 2, 3 Author Orcid Image ;   Chaoyuan Liu4 Author Orcid Image ;   Shuoming Luo1, 2, 3 Author Orcid Image ;   Yuting Xie1, 2, 3 Author Orcid Image ;   Fang Liu1 Author Orcid Image ;   Xia Li1, 2, 3 Author Orcid Image ;   Zhiguang Zhou1, 2, 3 Author Orcid Image
Article Authors Cited by (118) Tweetations (11) Metrics

Journals

  1. 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
  2. Zhang Y, Liu C, Luo S, Huang J, Li X, Zhou Z. Effectiveness of Lilly Connected Care Program (LCCP) App-Based Diabetes Education for Patients With Type 2 Diabetes Treated With Insulin: Retrospective Real-World Study. JMIR mHealth and uHealth 2020;8(3):e17455 View
  3. Hu J, Liu Z, Tong Y, Mei Z, Xu A, Zhou P, Chen X, Tang W, Zhou Z, Xiao Y. Fibroblast Growth Factor 19 Levels Predict Subclinical Atherosclerosis in Men With Type 2 Diabetes. Frontiers in Endocrinology 2020;11 View
  4. 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
  5. Brew-Sam N, Chib A, Rossmann C. Differential influences of social support on app use for diabetes self-management – a mixed methods approach. BMC Medical Informatics and Decision Making 2020;20(1) View
  6. Du Y, Dennis B, Rhodes S, Sia M, Ko J, Jiwani R, Wang J. Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study. JMIR Diabetes 2020;5(3):e21183 View
  7. 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
  8. Schindler-Ruwisch J, Peters A. Mobile applications for emerging adults transitioning to independent diabetes monitoring. Informatics for Health and Social Care 2021;46(1):56 View
  9. Abd-alrazaq A, Suleiman N, Baagar K, Jandali N, Alhuwail D, Abdalhakam I, Shahbal S, Abou-Samra A, Househ M. Patients and healthcare workers experience with a mobile application for self-management of diabetes in Qatar: A qualitative study. Computer Methods and Programs in Biomedicine Update 2021;1:100002 View
  10. Binyamin S, Zafar B. Proposing a mobile apps acceptance model for users in the health area: A systematic literature review and meta-analysis. Health Informatics Journal 2021;27(1) View
  11. Aydin G, Silahtaroglu G, Khan F. Insights into mobile health application market via a content analysis of marketplace data with machine learning. PLOS ONE 2021;16(1):e0244302 View
  12. Al Aufa B, Renindra I, Putri J, Nurmansyah M. An application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for understanding patient perceptions on using hospital mobile application. Enfermería Clínica 2020;30:110 View
  13. Alsahafi Y, Gay V, Khwaji A. Factors affecting the acceptance of integrated electronic personal health records in Saudi Arabia: The impact of e-health literacy. Health Information Management Journal 2022;51(2):98 View
  14. O'Connor S, Flannagan C, Parahoo K, Steele M, Thompson S, Jain S, Kirby M, Brady N, Maguire R, Connaghan J, McCaughan E. Efficacy, Use, and Acceptability of a Web-Based Self-management Intervention Designed to Maximize Sexual Well-being in Men Living With Prostate Cancer: Single-Arm Experimental Study. Journal of Medical Internet Research 2021;23(7):e21502 View
  15. Baek J, Lin S, Bolin J, Ory M, Flores S, Kash B. Factors Affecting Adoption of a Technology-Based Tool for Diabetes Self-Management Education and Support Among Adult Patients with Type 2 Diabetes in South Texas. The Science of Diabetes Self-Management and Care 2021;47(3):189 View
  16. Xu Y, Xu L, Zhao W, Li Q, Li M, Lu W, Zeng H, Yan J, Yang D, Wu W, Weng J, Pan J, Liu F. Effectiveness of a WeChat Combined Continuous Flash Glucose Monitoring System on Glycemic Control in Juvenile Type 1 Diabetes Mellitus Management: Randomized Controlled Trial. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2021;Volume 14:1085 View
  17. Octavius G, Antonio F, Colloc J. Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers. International Journal of Telemedicine and Applications 2021;2021:1 View
  18. van Velsen L, Flierman I, Tabak M. The formation of patient trust and its transference to online health services: the case of a Dutch online patient portal for rehabilitation care. BMC Medical Informatics and Decision Making 2021;21(1) View
  19. Park J, Han J, Kim Y, Rho M. Development, Acceptance, and Concerns Surrounding App-Based Services to Overcome the COVID-19 Outbreak in South Korea: Web-Based Survey Study. JMIR Medical Informatics 2021;9(7):e29315 View
  20. Brew-Sam N, Parkinson A, Chhabra M, Henschke A, Brown E, Pedley L, Pedley E, Hannan K, Brown K, Wright K, Phillips C, Tricoli A, Nolan C, Suominen H, Desborough J. Toward Diabetes Device Development That Is Mindful to the Needs of Young People Living With Type 1 Diabetes: A Data- and Theory-Driven Qualitative Study. JMIR Diabetes 2023;8:e43377 View
  21. Amiss E, Cottrell M. Evaluation of a Novel Step Training Mobile App Intervention in Cardiopulmonary Rehabilitation: A Single-Arm Prospective Cohort Study. Games for Health Journal 2022;11(5):330 View
  22. Xu Q, Hou X, Xiao T, Zhao W. Factors Affecting Medical Students’ Continuance Intention to Use Mobile Health Applications. Journal of Multidisciplinary Healthcare 2022;Volume 15:471 View
  23. Bian D, Xiao Y, Song K, Dong M, Li L, Millar R, Shi C, Li G. Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory. Journal of Medical Internet Research 2023;25:e37671 View
  24. Young A, Amara D, Bhattacharya A, Wei M. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. The Lancet Digital Health 2021;3(9):e599 View
  25. Schretzlmaier P, Hecker A, Ammenwerth E. Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study. JMIR Human Factors 2022;9(1):e34918 View
  26. Amdie F, Luctkar-Flude M, Snelgrove-Clarke E, Sawhney M, Balcha S, Woo K. Feasibility of Virtual Simulation-Based Diabetes Foot Care Education in Patients with Diabetes in Ethiopia: Protocol for a Randomized Controlled Trial. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2022;Volume 15:995 View
  27. Amankwa E, Asiedu E. Emergency e-learning acceptance in second-cycle institutions in Ghana: a conditional mediation analysis. SN Social Sciences 2022;2(4) View
  28. Alaslawi H, Berrou I, Al Hamid A, Alhuwail D, Aslanpour Z. Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda. JMIR Diabetes 2022;7(3):e28153 View
  29. Bäuerle A, Frewer A, Rentrop V, Schüren L, Niedergethmann M, Lortz J, Skoda E, Teufel M. Determinants of Acceptance of Weight Management Applications in Overweight and Obese Individuals: Using an Extended Unified Theory of Acceptance and Use of Technology Model. Nutrients 2022;14(9):1968 View
  30. Gong L, Jiang H, Wu X, Kong Y, Gao Y, Liu H, Guo Y, Hu D. Exploring Users’ Health Behavior Changes in Online Health Communities: Heuristic-Systematic Perspective Study. International Journal of Environmental Research and Public Health 2022;19(18):11783 View
  31. Gao C, Shen Y, Xu W, Zhang Y, Tu Q, Zhu X, Lu Z, Yang Y. A fuzzy-set qualitative comparative analysis exploration of multiple paths to users’ continuous use behavior of diabetes self-management apps. International Journal of Medical Informatics 2023;172:105000 View
  32. Zahed K, Smith A, McDonald A, Sasangohar F. The Effects of Drowsiness Detection Technology and Education on Nurses’ Beliefs and Attitudes toward Drowsy Driving. IISE Transactions on Occupational Ergonomics and Human Factors 2022;10(2):104 View
  33. Aydin G, Kumru S. Paving the way for increased e-health record use: elaborating intentions of Gen-Z. Health Systems 2023;12(3):281 View
  34. Liu H, Gong L, Wang C, Gao Y, Guo Y, Yi M, Jiang H, Wu X, Hu D. How information processing and risk/benefit perception affect COVID-19 vaccination intention of users in online health communities. Frontiers in Public Health 2023;11 View
  35. Howell P, Abdelhamid M. Protection Motivation Perspective Regarding the Use of COVID-19 Mobile Tracing Apps Among Public Users: Empirical Study. JMIR Formative Research 2023;7:e36608 View
  36. Gao Y, Gong L, Liu H, Kong Y, Wu X, Guo Y, Hu D. Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model. Frontiers in Psychology 2022;13 View
  37. Bults M, van Leersum C, Olthuis T, Bekhuis R, den Ouden M. Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study. JMIR Diabetes 2022;7(1):e31451 View
  38. 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
  39. 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
  40. Cao J, Kurata K, Lim Y, Sengoku S, Kodama K. Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model. International Journal of Environmental Research and Public Health 2022;19(22):15156 View
  41. Aigbogun O, Matinari M, Fawehinmi O. Exploring predictors of e-marketing continuance intention in the Zimbabwean pharmaceutical industry during the COVID-19 pandemic. African Journal of Economic and Management Studies 2023;14(3):379 View
  42. Van Baelen F, De Regge M, Larivière B, Verleye K, Schelfout S, Eeckloo K. Role of Social and App-Related Factors in Behavioral Engagement With mHealth for Improved Well-being Among Chronically Ill Patients: Scenario-Based Survey Study. JMIR mHealth and uHealth 2022;10(8):e33772 View
  43. Oloveze A, Ugwu P, Okeke V, Chukwuoyims K, Ahaiwe E. Factors motivating end-users’ behavioural intention to recommend m-health innovation: multi-group analysis. Health Economics and Management Review 2022;3(3):17 View
  44. Shen Y, Xu W, Liang A, Wang X, Lu X, Lu Z, Gao C. Online health management continuance and the moderating effect of service type and age difference: A meta-analysis. Health Informatics Journal 2022;28(3) View
  45. Lee S, Choi M, Yu S, Kim H, Park S, Choi I. Development and evaluation of smartphone usage management system for preventing problematic smartphone use. DIGITAL HEALTH 2022;8:205520762210890 View
  46. Zha H, Liu K, Tang T, Yin Y, Dou B, Jiang L, Yan H, Tian X, Wang R, Xie W. Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model. BMC Medical Informatics and Decision Making 2022;22(1) View
  47. Chang I, Shih Y, Kuo K. Why would you use medical chatbots? interview and survey. International Journal of Medical Informatics 2022;165:104827 View
  48. 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
  49. Tarfa A, Nordin J, Mott M, Maurer M, Shiyanbola O. A qualitative exploration of the experiences of peer leaders in an intervention to improve diabetes medication adherence in African Americans. BMC Public Health 2023;23(1) View
  50. Ong A, Kurata Y, Castro S, De Leon J, Dela Rosa H, Tomines A. Factors influencing the acceptance of telemedicine in the Philippines. Technology in Society 2022;70:102040 View
  51. Ahikiriza E, Wesana J, Van Huylenbroeck G, Kabbiri R, De Steur H, Lauwers L, Gellynck X. Farmer knowledge and the intention to use smartphone-based information management technologies in Uganda. Computers and Electronics in Agriculture 2022;202:107413 View
  52. Chopdar P. Adoption of Covid-19 contact tracing app by extending UTAUT theory: Perceived disease threat as moderator. Health Policy and Technology 2022;11(3):100651 View
  53. 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
  54. Walsh P, Singh R. Determinants of Millennial behaviour towards current and future use of video streaming services. Young Consumers 2022;23(3):397 View
  55. Liu Y, Hao H, Sharma M, Harris Y, Scofi J, Trepp R, Farmer B, Ancker J, Zhang Y. Clinician Acceptance of Order Sets for Pain Management: A Survey in Two Urban Hospitals. Applied Clinical Informatics 2022;13(02):447 View
  56. Senteio C, Murdock P. The Efficacy of Health Information Technology in Supporting Health Equity for Black and Hispanic Patients With Chronic Diseases: Systematic Review. Journal of Medical Internet Research 2022;24(4):e22124 View
  57. Said G. Factors Affecting mHealth Technology Adoption in Developing Countries: The Case of Egypt. Computers 2022;12(1):9 View
  58. Wu C, Xu H, Bai D, Chen X, Gao J, Jiang X. Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis. BMJ Open 2023;13(1):e066322 View
  59. Breil B, Salewski C, Apolinário-Hagen J. Comparing the Acceptance of Mobile Hypertension Apps for Disease Management Among Patients Versus Clinical Use Among Physicians: Cross-sectional Survey. JMIR Cardio 2022;6(1):e31617 View
  60. Al-Bashayreh M, Almajali D, Al-Okaily M, Masa’deh R, Samed Al-Adwan A. Evaluating Electronic Customer Relationship Management System Success: The Mediating Role of Customer Satisfaction. Sustainability 2022;14(19):12310 View
  61. Schretzlmaier P, Hecker A, Ammenwerth E. Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study. BMJ Health & Care Informatics 2022;29(1):e100640 View
  62. 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
  63. Xie Q, Hu X, Wang Y, Peng J, Cheng L. Exploration of the health needs of patients with poorly controlled type 2 diabetes using a user-centred co-production approach in the area of mHealth: an exploratory sequential mixed-method protocol. BMJ Open 2022;12(12):e063814 View
  64. Zhu Z, Liu Y, Cao X, Dong W. Factors Affecting Customer Intention to Adopt a Mobile Chronic Disease Management Service. Journal of Organizational and End User Computing 2021;34(4):1 View
  65. Yao Y, Li Z, He Y, Zhang Y, Guo Z, Lei Y, Zhao Q, Li D, Zhang Z, Zhang Y, Liao X. Factors affecting wearable ECG device adoption by general practitioners for atrial fibrillation screening: cross-sectional study. Frontiers in Public Health 2023;11 View
  66. Zahed K, Mehta R, Erraguntla M, Qaraqe K, Sasangohar F. Understanding Patient Beliefs in Using Technology to Manage Diabetes: Path Analysis Model From a National Web-Based Sample. JMIR Diabetes 2023;8:e41501 View
  67. Qu S, Zhou M, Kong N, Campy K. Factors influencing user acceptance of weight management apps among Chinese obese individuals during the COVID-19 pandemic. Health Policy and Technology 2023;12(2):100758 View
  68. Koo J, Park Y, Kang D. Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study. JMIR Aging 2023;6:e41429 View
  69. Stehr P, Ermel L, Rossmann C, Reifegerste D, Lindemann A, Schulze A. A Mobile Health Information Behavior Model: Theoretical Development and Mixed-Method Testing in the Context of Mobile Apps on Child Poisoning Prevention. Journal of Health Communication 2023;28(10):648 View
  70. Kruger S, Deacon E, van Rensburg E, Segal D. Identification of psychological constructs for a positive psychology intervention to assist with the adjustment to closed loop technology among adolescents living with type 1 diabetes. Frontiers in Psychology 2023;14 View
  71. Bouteraa M, Al-Daihani M, Chekima B, Ansar R, Tamma E, Lada S, Baddou A, Elkheloufi A, Fook L. A Multi-Analytical Approach to Investigate the Motivations of Sustainable Green Technology in the Banking Industry. International Journal of Social Ecology and Sustainable Development 2023;15(1):1 View
  72. Brunet J, Sharma S, Price J, Black M. Acceptability and Usability of a Theory-Driven Intervention via Email to Promote Physical Activity in Women Who Are Overweight or Obese: Substudy Within a Randomized Controlled Trial. JMIR Formative Research 2023;7:e48301 View
  73. Virtanen L, Kaihlanen A, Kainiemi E, Saukkonen P, Heponiemi T. Patterns of acceptance and use of digital health services among the persistent frequent attenders of outpatient care: A qualitatively driven multimethod analysis. DIGITAL HEALTH 2023;9 View
  74. Alexopoulos C, Rizun N, Matheus R, Pinheiro L, Saxena S. Gender differences and technostress vis-a-vis Open Government Data (OGD) adoption and usage. SSRN Electronic Journal 2023 View
  75. Li T, Zhang Y, Luo X, Wan W, Zhang H, Wang X, Wang D. Exploring Patients' Intentions for Usage of Video Telemedicine Follow-Up Services: Cross-Sectional Study. Telemedicine and e-Health 2024;30(3):731 View
  76. 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
  77. Cho O, Cho J. Changed Digital Technology Perceptions and Influencing Factors among Older Adults during the COVID-19 Pandemic. Healthcare 2023;11(15):2146 View
  78. Kuen L, Schürmann F, Westmattelmann D, Hartwig S, Tzafrir S, Schewe G. Trust transfer effects and associated risks in telemedicine adoption. Electronic Markets 2023;33(1) View
  79. 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
  80. Pienkowska A, Ang C, Mammadova M, Mahadzir M, Car J. A Diabetes Education App for People Living With Type 2 Diabetes: Co-Design Study. JMIR Formative Research 2023;7:e45490 View
  81. Pedersen K, Schlichter B. Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review. Interactive Journal of Medical Research 2023;12:e40205 View
  82. Kamani E, Kalisz D, Szyran-Resiak A. Patients’ behavioral intentions toward robotic adoption in healthcare: An approach on apprehension of embedding robotics. Journal of General Management 2023;48(4):370 View
  83. Han K, Zo H. Understanding the mobile healthcare applications continuance: The regulatory focus perspective. International Journal of Medical Informatics 2023;177:105161 View
  84. Wei S, Ge P, Zhang J, Xu S, Wang Y, Li Q, Feng B, Yu W, Suo B, Zhang Y, Wang M, Sun X, Song Z, Wu Y. Exploring factors that influence the behavioural intention of medical students to use 3D gastroscopic model to learn how to operate gastroscope using UTAUT Model. BMC Medical Education 2023;23(1) View
  85. Schröder S, Buntrock C, Neumann L, Müller J, Fromberger P. Acceptance of a Web-Based Intervention in Individuals Who Committed Sexual Offenses Against Children: Cross-Sectional Study. JMIR Formative Research 2024;8:e48880 View
  86. Donkor A, Ayitey J, Adotey P, Ofori E, Kitson-Mills D, Vanderpuye V, Opoku S, Luckett T, Agar M, Engel-Hills P. Mobile-Based Application Interventions to Enhance Cancer Control and Care in Low- and Middle-Income Countries: A Systematic Review. International Journal of Public Health 2023;68 View
  87. Atinafu W, Tilahun K, Yilma T, Mekonnen Z, Walle A, Adem J. Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022. BMC Health Services Research 2023;23(1) View
  88. Alanzi T, Alzahrani W, Almoraikhi ‏, Algannas ‏, Alghamdi M, Alzahrani ‏, Abutaleb R, Ba Dughaish ‏, Alotibi N, Alkhalifah S, Alshehri ‏, Alzahrani H, Almahdi ‏, Alanzi N, Farhah ‏. Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study. Cureus 2023 View
  89. Wang Q, Ma Y, Mao J, Song J, Xiao M, Zhao Q, Yuan F, Hu L. Driving the implementation of hospital examination reservation system through hospital management. BMC Health Services Research 2024;24(1) View
  90. Lu C, Tsai-Lin T. Are Older Adults Special in Adopting Public eHealth Service Initiatives? The Modified Model of UTAUT. Sage Open 2024;14(1) View
  91. Chen H, Li H, Li L, Zhang X, Gu J, Wang Q, Wu C, Wu Y. Factors Associated with Intention to Use Telerehabilitation for Children with Special Needs: A Cross-Sectional Study. Telemedicine and e-Health 2024;30(5):1425 View
  92. He W, Zhang W, Jin Y, Zhou Q, Zhang H, Xia Q. Physician Versus Large Language Model Chatbot Responses to Web-Based Questions From Autistic Patients in Chinese: Cross-Sectional Comparative Analysis. Journal of Medical Internet Research 2024;26:e54706 View
  93. Deng C, Xie Y, Liu F, Tang X, Fan L, Yang X, Chen Y, Zhou Z, Li X. Simplified integration of optimal self-management behaviors is associated with improved HbA1c in patients with type 1 diabetes. Journal of Endocrinological Investigation 2024;47(11):2691 View
  94. Yeung N, Lau S, Mak W, Cheng C, Chan E, Siu J, Cheung P. Applying the Unified Theory of Acceptance and Use of Technology to Identify Factors Associated With Intention to Use Teledelivered Supportive Care Among Recently Diagnosed Breast Cancer Survivors During COVID-19 in Hong Kong: Cross-Sectional Survey. JMIR Cancer 2024;10:e51072 View
  95. Aini Q, Manongga D, Rahardja U, Sembiring I, Li Y. Understanding Behavioral Intention to Use of Air Quality Monitoring Solutions with Emphasis on Technology Readiness. International Journal of Human–Computer Interaction 2024:1 View
  96. Tang X, Hanif M, Haider N, Rizwan A, Khurshid A. From Friends to Feedback: Effect of Social Influence on Mobile Shopping in the Post-COVID Era. Sustainability 2024;16(12):5134 View
  97. 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
  98. Zhu J, Gu M, Li J, Cui Y. Adoption of Mobile Health Applications for Diabetes Management From a Push–Pull–Mooring Perspective. Journal of Global Information Management 2024;32(1):1 View
  99. de Souza Ferreira E, de Oliveira A, Dias M, da Costa G, Januário J, Botelho G, Cotta R. Mobile solution and chronic diseases: development and implementation of a mobile application and digital platform for collecting, analyzing data, monitoring and managing health care. BMC Health Services Research 2024;24(1) View
  100. Wei C, Cai Y, Liu J, Guo Y, Wu X, He X, Hu D. Factors influencing user’s health information discernment abilities in online health communities: based on SEM and fsQCA. Frontiers in Public Health 2024;12 View
  101. Alhur M, Caamaño-Alegre J, Reyes-Santias F. A public value-based model to understand patients’ adoption of eHealth: Theoretical underpinnings and empirical application. DIGITAL HEALTH 2024;10 View
  102. Chong C, Makmor-Bakry M, Hatah E, Mohd Tahir N, Mustafa N, Capule F, Hermansyah A. Factors infuencing type 2 diabetes mellitus patients’ readiness, acceptance and barriers towards mobile apps adoption for medication adherence. International Journal of Diabetes in Developing Countries 2024 View
  103. Kruger S, Deacon E, van Rensburg E, Segal D. Adjustment experiences of adolescents living with well-controlled type 1 diabetes using closed-loop technology. Frontiers in Clinical Diabetes and Healthcare 2024;5 View
  104. Wang L, Zhang Y, Li Z, Pang X, Zhang Y, Zou M. Analysis of willingness to use health management APP for female college students: application of UTAUT model based on Fogg theory. Frontiers in Psychology 2024;15 View
  105. Shi H, Liu C, Luo H. Impact of community public health care on treatment effect, health cognition, and self-management in patients with type 2 diabetes. World Journal of Clinical Cases 2025;13(5) View

Books/Policy Documents

  1. Petersen F, Jacobs M, Pather S. Responsible Design, Implementation and Use of Information and Communication Technology. View
  2. Pushpa A, Nagadeepa C, Mukthar K, Huaranga-Toledo H, Nivin-Vargas L, Guerra-Muñoz M. Digitalisation: Opportunities and Challenges for Business. View
  3. Alpar P, Driebe T. Innovation Through Information Systems. View
  4. Mouloudj K, Bouarar A, Asanza D, Saadaoui L, Mouloudj S, Njoku A, Evans M, Bouarar A. Integrating Digital Health Strategies for Effective Administration. View
  5. Badr N, Aroutine N, Yeretzian J. Biomedical Engineering Systems and Technologies. View
  6. Breil B. Handbuch Digitale Gesundheitswirtschaft. View
  7. Jayathilake C, Keikhosrokiani P, Isomursu M. Digital Health and Wireless Solutions. View
  8. Ndlovu B, Chipangura B, Singh S. Proceedings of Ninth International Congress on Information and Communication Technology. View