Published on in Vol 10, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33247, first published .
mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review

mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review

mHealth Apps Using Behavior Change Techniques to Self-report Data: Systematic Review

Journals

  1. Sivakumar B, Lemonde M, Stein M, Mak S, Al-Hesayen A, Arcand J, White S. Patient perspectives on the use of mobile apps to support heart failure management: A qualitative descriptive study. PLOS ONE 2023;18(5):e0285659 View
  2. Uspenskiy V, Saprankov V, Mazin V, Filippov A, Boyarskaya N, Malashicheva A, Moiseeva O. Machine learning and artificial intelligence in the prediction, diagnosis and treatment of thoracic aortic diseases (literature review). Part 2. Russian Journal for Personalized Medicine 2023;3(3):132 View
  3. Metzendorf M, Wieland L, Richter B. Mobile health (m-health) smartphone interventions for adolescents and adults with overweight or obesity. Cochrane Database of Systematic Reviews 2024;2024(2) View
  4. Eaton C, McWilliams E, Yablon D, Kesim I, Ge R, Mirus K, Sconiers T, Donkoh A, Lawrence M, George C, Morrison M, Muther E, Oates G, Sathe M, Sawicki G, Snell C, Riekert K. Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review. JMIR mHealth and uHealth 2024;12:e49024 View
  5. Benthem de Grave R, Bull C, Monjardino de Souza Monteiro D, Margariti E, McMurchy G, Hutchinson J, Smeddinck J. Smartphone Apps for Food Purchase Choices: Scoping Review of Designs, Opportunities, and Challenges. Journal of Medical Internet Research 2024;26:e45904 View
  6. Bucher A, Blazek E, Symons C. How are Machine Learning and Artificial Intelligence Used in Digital Behavior Change Interventions? A Scoping Review. Mayo Clinic Proceedings: Digital Health 2024;2(3):375 View
  7. Reen J, Chan G, Orji R. iCare: Insights from the Evaluation of an App for Managing Stress Among Working-Class Indian Women. International Journal of Human–Computer Interaction 2025;41(9):5797 View
  8. Saliasi I, Lan R, Rhanoui M, Fraticelli L, Viennot S, Tardivo D, Clément C, du Sartz de Vigneulles B, Bernard S, Darlington-Bernard A, Dussart C, Bourgeois D, Carrouel F. French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study. JMIR mHealth and uHealth 2024;12:e63776 View
  9. Cheng M, Dai Q, Liu Z, Wang Y, Zhou C. New progress in pediatric allergic rhinitis. Frontiers in Immunology 2024;15 View
  10. Oliveira A, Alfouzan N, Yu J, Yahya A, Lammy K, Wright M, Reinhold D, Peterson L, Brewer A, Liechty J, Nakamura M. Feasibility and acceptability pilot study of an online weight loss program in rural, underserved communities. PeerJ 2024;12:e18268 View
  11. Oliveira A, Wolff J, Alfouzan N, Yu J, Yahya A, Lammy K, Nakamura M. A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study. JMIR Formative Research 2024;8:e58363 View
  12. Martin-Payo R, González-Nuevo-Vázquez C, Álvarez-Gómez E, Surendran S, Cachero-Rodríguez J, Fernandez-Alvarez M, Cudejko T. Spanish versión of The App Behavior Change Scale (ABACUS-Es): Adaptation and validation study. PLOS ONE 2024;19(12):e0314753 View
  13. Aguiar M, Cejudo A, Epelde G, Chaves D, Trujillo M, Artola G, Ayala U, Bilbao R, Tueros I. An approach to boost adherence to self-data reporting in mHealth applications for users without specific health conditions. BMC Medical Informatics and Decision Making 2025;25(1) View
  14. Lee J, Yoo S, Kim Y, Kim E, Park H, Sohn Y, Kim Y, Chung S, Baik K, Kim K, Yoo J. Effect of the Yon PD App on the Management of Self-Care in People With Parkinson Disease: Randomized Controlled Trial. Journal of Medical Internet Research 2025;27:e62822 View
  15. Wei X, Li C, Yu H, Xu L, Meng S, Xing C, Gao Q, Chang G, Wang Y. Study on the status and countermeasures of disease self-management ability in chronic kidney disease patients in cold regions. Frigid Zone Medicine 2025;5(1):10 View
  16. Sivakumar B, Ricupero M, Mahajan A, Jefferson K, Wenger J, Code J, Theodorou A, Arcand J. A mobile app intervention to support nutrition education for heart failure management: co-design, development and user-testing. BMC Nutrition 2025;11(1) View
  17. Mainez J, Galán J, López J, Isern-Amengual B, Sanchís-Cortés P. User profile and engagement with a digital health application for urolithiasis management: A descriptive study of the first 699 users. Actas Urológicas Españolas (English Edition) 2025;49(8):501819 View
  18. Mainez J, Galán J, López J, Isern-Amengual B, Sanchís-Cortés P. Perfil e interacción de los usuarios con una app de salud digital para urolitiasis: estudio descriptivo de los primeros 699 usuarios. Actas Urológicas Españolas 2025;49(8):501819 View
  19. Yao T, Dorneich M, Thomas R, Brito Diaz A, Maduwuba C, Schwab N, Losch M, Krejci C, Caron J, Passe U. Evaluating User Perceptions and Usability of CommHEAT: A Community-Based Heat Alert Application. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2025;69(1):988 View
  20. Abe M, Hirata T, Morito N, Kawashima M, Yoshida S, Takami Y, Fujimoto T, Kawasoe S, Shibukawa T, Segawa H, Yamanokuchi T, Ishida S, Takahashi K, Tada K, Kato Y, Sakima A, Arima H. Smartphone application-based interventions for cardiometabolic risk factor management: A systematic review and meta-analysis. Hypertension Research 2025 View
  21. Niazi Y, Riaz H, Naeem M, Saeed A. Development of the Pelvi-Fit app for women with urinary incontinence. European Journal of Obstetrics & Gynecology and Reproductive Biology 2025;315:114726 View
  22. Leysen D, Reich B, Carrozzo A, Crutzen R, Grote V, Kumar D, Mayr B, Niebauer J, Pfannerstill F, Propst E, Wurhofer D, Sareban M, Smeddinck J, Treff G, Kulnik S. Feasibility of the aktivplan Digital Health Intervention for Regular Physical Activity Following Phase II Rehabilitation: Protocol for a Mixed Method Randomized Controlled Pilot Study (ACTIVE-CaRe Pilot). JMIR Research Protocols 2025;14:e73704 View
  23. Minian N, Mehra K, Rose J, Veldhuizen S, Zawertailo L, Ratto M, Ting-A-Kee R, Melamed O, Tang V, Selby P. Using the behaviour change wheel framework to develop a rule-based chatbot to support varenicline adherence for smoking cessation. DIGITAL HEALTH 2025;11 View
  24. Motta-Yanac E, Victoria R, Ellis N, Gidlow C. Unlocking the Potential of mHealth: Integrating Behaviour Change Techniques in Hypertension App Design. International Journal of Environmental Research and Public Health 2025;22(10):1487 View
  25. Sheen F, Porter L, Papakonstantinou T, Ceka M, Bondaronek P. Living well? The unintended consequences of highly popular commercial fitness apps through social listening using Machine‐Assisted Topic Analysis: Evidence from X. British Journal of Health Psychology 2025;30(4) View
  26. Sobrinho A, Rodrigues G, Oliveira G, Oliveira Gomes G, Júnior C. Everyday Digital Support to Promote Health and Literacy Among Older Adults: A 14-Week Randomized Digital Pilot Trial by Engagement Level (Preprint). JMIR Formative Research 2025 View
  27. Amaritei C, Iftene A. VITAL: A Design Framework for Prototyping Health Behavior Change Applications. Procedia Computer Science 2025;270:2640 View