Published on in Vol 7, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31451, first published .
Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

Barriers and Drivers Regarding the Use of Mobile Health Apps Among Patients With Type 2 Diabetes Mellitus in the Netherlands: Explanatory Sequential Design Study

Journals

  1. 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
  2. Bults M, van Leersum C, Olthuis T, Bekhuis R, den Ouden M. Mobile Health Apps for the Control and Self-management of Type 2 Diabetes Mellitus: Qualitative Study on Users’ Acceptability and Acceptance. JMIR Diabetes 2023;8:e41076 View
  3. Khalid A, Dong Q, Chuluunbaatar E, Haldane V, Durrani H, Wei X. Implementation Science Perspectives on Implementing Telemedicine Interventions for Hypertension or Diabetes Management: Scoping Review. Journal of Medical Internet Research 2023;25:e42134 View
  4. Joshua S, Abbas W, Lee J. M-Healthcare Model: An Architecture for a Type 2 Diabetes Mellitus Mobile Application. Applied Sciences 2022;13(1):8 View
  5. Fu H, Wyman J, Peden-McAlpine C, Draucker C, Schleyer T, Adam T. App Design Features Important for Diabetes Self-management as Determined by the Self-Determination Theory on Motivation: Content Analysis of Survey Responses From Adults Requiring Insulin Therapy. JMIR Diabetes 2023;8:e38592 View
  6. Jarl F, Davelid A, Hedin K, Stomby A, Petersson C. Overcoming the struggle of living with type 2 diabetes – diabetes specialist nurses’ and patients’ perspectives on digital interventions. BMC Health Services Research 2023;23(1) View
  7. Mejia Salazar I, Moreno Mantilla C, Aguilar Zambrano J, Trujillo Suárez M, Loaiza Ramírez J. Validation of a participant selection method within a mixed sequential research design for case studies of sustainable supply chains*. Cuadernos de Administración 2023;36 View
  8. Smeijers J, Bults M, den Ouden M, Bekhuis R. Apps: eerste keus ‘medicijn’ voor patiënten met diabetes mellitus type 2?. TSG - Tijdschrift voor gezondheidswetenschappen 2023;101(4):178 View
  9. Lee H, Hwang Y. Training with, about, for Metaverse: A Mixed Methods Research on Training Pre-Service Teachers as Metaverse-Certified Practitioners. STEM Journal 2023;24(4):73 View
  10. 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
  11. Yang S, Lim S, Choi Y, Lee J, Yoon K. Effects of an Electronic Medical Records-Linked Diabetes Self-Management System on Treatment Targets in Real Clinical Practice: Retrospective, Observational Cohort Study. Endocrinology and Metabolism 2024;39(2):364 View
  12. Johnson B, George J, Basanth A, Chandran V, Kesavadev J. The Plethora of Possibilities with a Smartphone in Diabetes Prevention and Care. International Journal of Diabetes and Technology 2023;2(4):123 View