Published on in Vol 6, No 3 (2018): Jul-Sep

Preprints (earlier versions) of this paper are available at, first published .
3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study

3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study

3MD for Chronic Conditions, a Model for Motivational mHealth Design: Embedded Case Study

Authors of this article:

Guido Giunti1, 2 Author Orcid Image


  1. Guisado-Fernández E, Giunti G, Mackey L, Blake C, Caulfield B. Factors Influencing the Adoption of Smart Health Technologies for People With Dementia and Their Informal Caregivers: Scoping Review and Design Framework. JMIR Aging 2019;2(1):e12192 View
  2. Koledova E, Tornincasa V, van Dommelen P. Analysis of real-world data on growth hormone therapy adherence using a connected injection device. BMC Medical Informatics and Decision Making 2020;20(1) View
  3. Sittig S, Wang J, Iyengar S, Myneni S, Franklin A. Incorporating Behavioral Trigger Messages Into a Mobile Health App for Chronic Disease Management: Randomized Clinical Feasibility Trial in Diabetes. JMIR mHealth and uHealth 2020;8(3):e15927 View
  4. Giunti G, Rivera-Romero O, Kool J, Bansi J, Sevillano J, Granja-Dominguez A, Izquierdo-Ayuso G, Giunta D. Evaluation of More Stamina, a Mobile App for Fatigue Management in Persons with Multiple Sclerosis: Protocol for a Feasibility, Acceptability, and Usability Study. JMIR Research Protocols 2020;9(8):e18196 View
  5. Bt Wan Mohamed Radzi C, Salarzadeh Jenatabadi H, Samsudin N. mHealth Apps Assessment among Postpartum Women with Obesity and Depression. Healthcare 2020;8(2):72 View
  6. Martinez-Millana A, Jarones E, Fernandez-Llatas C, Hartvigsen G, Traver V. App Features for Type 1 Diabetes Support and Patient Empowerment: Systematic Literature Review and Benchmark Comparison. JMIR mHealth and uHealth 2018;6(11):e12237 View
  7. Korhonen O, Väyrynen K, Krautwald T, Bilby G, Broers H, Giunti G, Isomursu M. Data-Driven Personalization of a Physiotherapy Care Pathway: Case Study of Posture Scanning. JMIR Rehabilitation and Assistive Technologies 2020;7(2):e18508 View
  8. Rewolinski J, Kelemen A, Liang Y. Type I Diabetes Self-management With Game-Based Interventions for Pediatric and Adolescent Patients. CIN: Computers, Informatics, Nursing 2021;39(2):78 View
  9. Warsinsky S, Schmidt-Kraepelin M, Rank S, Thiebes S, Sunyaev A. Conceptual Ambiguity Surrounding Gamification and Serious Games in Health Care: Literature Review and Development of Game-Based Intervention Reporting Guidelines (GAMING). Journal of Medical Internet Research 2021;23(9):e30390 View
  10. Cucciniello M, Petracca F, Ciani O, Tarricone R. Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials. npj Digital Medicine 2021;4(1) View
  11. Bagge-Petersen C, Langstrup H, Larsen J, Frølich A. Critical user-configurations in mHealth design: How mHealth-app design practices come to bias design against chronically ill children and young people as mHealth users. DIGITAL HEALTH 2022;8:205520762211095 View

Books/Policy Documents

  1. Berg V, Haugland V, Wiik M, Michalsen H, Anke A, Muzny M, Gomez J, Martinez S, Martinez-Millana A, Henriksen A, Sato K, Hartvigsen G. Digital Transformation for a Sustainable Society in the 21st Century. View
  2. Wu A, Tse S, Balli F. Precision in Pulmonary, Critical Care, and Sleep Medicine. View