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Citing this Article

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Published on 14.03.17 in Vol 5, No 3 (2017): March

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

Works citing "Mobile App-Based Interventions to Support Diabetes Self-Management: A Systematic Review of Randomized Controlled Trials to Identify Functions Associated with Glycemic Efficacy"

Yuan Wu, Xun Yao, Giacomo Vespasiani, Antonio Nicolucci, Yajie Dong, Joey Kwong, Ling Li, Xin Sun, Haoming Tian, Sheyu Li

JMIR Mhealth Uhealth 2017 (Mar 14); 5(3):e35 

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.6522):

(note that this is only a small subset of citations)

  1. Yang Y, Lee EY, Kim H, Lee S, Yoon K, Cho J. Effect of a Mobile Phone–Based Glucose-Monitoring and Feedback System for Type 2 Diabetes Management in Multiple Primary Care Clinic Settings: Cluster Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(2):e16266
    CrossRef
  2. Young HM, Miyamoto S, Dharmar M, Tang-Feldman Y. Nurse Coaching and Mobile Health Compared With Usual Care to Improve Diabetes Self-Efficacy for Persons With Type 2 Diabetes: Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(3):e16665
    CrossRef
  3. Siavash Dastjerdi M, Tabatabaee A. A roundup of the simplest mobile phone uses in diabetes management. Diabetes Research and Clinical Practice 2019;158:107895
    CrossRef
  4. . Updates and advances in technology for diabetes self-management. Pharmacy Today 2019;25(5):43
    CrossRef
  5. Moral-Munoz JA, Zhang W, Cobo MJ, Herrera-Viedma E, Kaber DB. Smartphone-based systems for physical rehabilitation applications: A systematic review. Assistive Technology 2021;33(4):223
    CrossRef
  6. Rhea CK, Felsberg DT, Maher JP. Toward Evidence-Based Smartphone Apps to Enhance Human Health: Adoption of Behavior Change Techniques. American Journal of Health Education 2018;49(4):210
    CrossRef
  7. Osborn CY, van Ginkel JR, Rodbard D, Heyman M, Marrero DG, Huddleston B, Dachis J. One Drop | Mobile: An Evaluation of Hemoglobin A1c Improvement Linked to App Engagement. JMIR Diabetes 2017;2(2):e21
    CrossRef
  8. Zhang Y, Li X, Luo S, Liu C, Xie Y, Guo J, Liu F, Zhou Z. Use, Perspectives, and Attitudes Regarding Diabetes Management Mobile Apps Among Diabetes Patients and Diabetologists in China: National Web-Based Survey. JMIR mHealth and uHealth 2019;7(2):e12658
    CrossRef
  9. Castensøe-Seidenfaden P, Husted GR, Jensen AK, Hommel E, Olsen B, Pedersen-Bjergaard U, Kensing F, Teilmann G. Testing a Smartphone App (Young with Diabetes) to Improve Self-Management of Diabetes Over 12 Months: Randomized Controlled Trial. JMIR mHealth and uHealth 2018;6(6):e141
    CrossRef
  10. Nouri SS, Adler-Milstein J, Thao C, Acharya P, Barr-Walker J, Sarkar U, Lyles C. Patient characteristics associated with objective measures of digital health tool use in the United States: A literature review. Journal of the American Medical Informatics Association 2020;27(5):834
    CrossRef
  11. Tyler NS, Jacobs PG. Artificial Intelligence in Decision Support Systems for Type 1 Diabetes. Sensors 2020;20(11):3214
    CrossRef
  12. Ernsting C, Stühmann LM, Dombrowski SU, Voigt-Antons J, Kuhlmey A, Gellert P. Associations of Health App Use and Perceived Effectiveness in People With Cardiovascular Diseases and Diabetes: Population-Based Survey. JMIR mHealth and uHealth 2019;7(3):e12179
    CrossRef
  13. Offringa R, Sheng T, Parks L, Clements M, Kerr D, Greenfield MS. Digital Diabetes Management Application Improves Glycemic Outcomes in People With Type 1 and Type 2 Diabetes. Journal of Diabetes Science and Technology 2018;12(3):701
    CrossRef
  14. Chiu C, Yu Y, Du Y, Yang Y, Chen J, Wong L, Tanasugarn C. Comparing a Social and Communication App, Telephone Intervention, and Usual Care for Diabetes Self-Management: 3-Arm Quasiexperimental Evaluation Study. JMIR mHealth and uHealth 2020;8(6):e14024
    CrossRef
  15. van Ommen B, Wopereis S, van Empelen P, van Keulen HM, Otten W, Kasteleyn M, Molema JJW, de Hoogh IM, Chavannes NH, Numans ME, Evers AWM, Pijl H. From Diabetes Care to Diabetes Cure—The Integration of Systems Biology, eHealth, and Behavioral Change. Frontiers in Endocrinology 2018;8
    CrossRef
  16. Loh KP, Ramsdale E, Culakova E, Mendler JH, Liesveld JL, O'Dwyer KM, McHugh C, Gilles M, Lloyd T, Goodman M, Klepin HD, Mustian KM, Schnall R, Mohile SG. Novel mHealth App to Deliver Geriatric Assessment-Driven Interventions for Older Adults With Cancer: Pilot Feasibility and Usability Study. JMIR Cancer 2018;4(2):e10296
    CrossRef
  17. Rocha NP, Rodrigues dos Santos M, Cerqueira M, Queirós A. Mobile Health to Support Ageing in Place. International Journal of E-Health and Medical Communications 2019;10(3):1
    CrossRef
  18. Rossmann C, Riesmeyer C, Brew-Sam N, Karnowski V, Joeckel S, Chib A, Ling R. Appropriation of Mobile Health for Diabetes Self-Management: Lessons From Two Qualitative Studies. JMIR Diabetes 2019;4(1):e10271
    CrossRef
  19. Jeddi FR, Nabovati E, Amirazodi S. Features and Effects of Information Technology-Based Interventions to Improve Self-Management in Chronic Kidney Disease Patients: a Systematic Review of the Literature. Journal of Medical Systems 2017;41(11)
    CrossRef
  20. Cresswell KM, McKinstry B, Wolters M, Shah A, Sheikh A. Five key strategic priorities of integrating patient generated health data into United Kingdom electronic health records. BMJ Health & Care Informatics 2018;25(4):254
    CrossRef
  21. Sherr JL, Tauschmann M, Battelino T, de Bock M, Forlenza G, Roman R, Hood KK, Maahs DM. ISPAD Clinical Practice Consensus Guidelines 2018: Diabetes technologies. Pediatric Diabetes 2018;19:302
    CrossRef
  22. Slugocki M, Bialonczyk D, Özdener AE. A Review of Emerging Technologies in Diabetes Management for Multiple-Dose Insulin-Injecting Patients With Type 2 Diabetes Who Self-monitor Blood Glucose. Journal of Pharmacy Technology 2019;35(2):69
    CrossRef
  23. Ye Q, Khan U, Boren SA, Simoes EJ, Kim MS. An Analysis of Diabetes Mobile Applications Features Compared to AADE7™: Addressing Self-Management Behaviors in People With Diabetes. Journal of Diabetes Science and Technology 2018;12(4):808
    CrossRef
  24. Timpel P, Harst L. Research Implications for Future Telemedicine Studies and Innovations in Diabetes and Hypertension—A Mixed Methods Study. Nutrients 2020;12(5):1340
    CrossRef
  25. Gamble A, Pham Q, Goyal S, Cafazzo JA. The Challenges of COVID-19 for People Living With Diabetes: Considerations for Digital Health. JMIR Diabetes 2020;5(2):e19581
    CrossRef
  26. . Advances in psychological interventions for lifestyle disorders. Current Opinion in Psychiatry 2017;30(5):346
    CrossRef
  27. Mosconi P, Radrezza S, Lettieri E, Santoro E. Use of Health Apps and Wearable Devices: Survey Among Italian Associations for Patient Advocacy. JMIR mHealth and uHealth 2019;7(1):e10242
    CrossRef
  28. Do D, Garfein RS, Cuevas-Mota J, Collins K, Liu L. Change in Patient Comfort Using Mobile Phones Following the Use of an App to Monitor Tuberculosis Treatment Adherence: Longitudinal Study. JMIR mHealth and uHealth 2019;7(2):e11638
    CrossRef
  29. Nouri SS, Avila-Garcia P, Cemballi AG, Sarkar U, Aguilera A, Lyles CR. Assessing Mobile Phone Digital Literacy and Engagement in User-Centered Design in a Diverse, Safety-Net Population: Mixed Methods Study. JMIR mHealth and uHealth 2019;7(8):e14250
    CrossRef
  30. Garnweidner-Holme L, Hoel Andersen T, Sando MW, Noll J, Lukasse M. Health Care Professionals’ Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study. JMIR mHealth and uHealth 2018;6(5):e123
    CrossRef
  31. Valencia WM, Botros D, Vera-Nunez M, Dang S. Diabetes Treatment in the Elderly: Incorporating Geriatrics, Technology, and Functional Medicine. Current Diabetes Reports 2018;18(10)
    CrossRef
  32. Schwarz PEH, Piller S, Kokelmann C, Holland M, Timpel P. Digitalisierung in der Diabetologie — Realität, Herausforderung, Vision. Info Diabetologie 2019;13(1):28
    CrossRef
  33. Iribarren SJ, Rodriguez Y, Lin L, Chirico C, Discacciati V, Schnall R, Demiris G. Converting and expanding a mobile support intervention: Focus group and field-testing findings from individuals in active tuberculosis treatment. International Journal of Medical Informatics 2020;136:104057
    CrossRef
  34. Quevedo Rodríguez A, Wägner AM. Mobile phone applications for diabetes management: A systematic review. Endocrinología, Diabetes y Nutrición 2019;66(5):330
    CrossRef
  35. Veazie S, Winchell K, Gilbert J, Paynter R, Ivlev I, Eden KB, Nussbaum K, Weiskopf N, Guise J, Helfand M. Rapid Evidence Review of Mobile Applications for Self-management of Diabetes. Journal of General Internal Medicine 2018;33(7):1167
    CrossRef
  36. Pramanik BK, Angelin JJ, Mathai VJ, Mathai S, Korula S, Simon A. Smartphone App as Motivational Intervention to Improve Glycemic Control in Adolescents with Type 1 Diabetes. The Indian Journal of Pediatrics 2019;86(12):1118
    CrossRef
  37. Su J, Dugas M, Guo X, Gao G. Influence of Personality on mHealth Use in Patients with Diabetes: Prospective Pilot Study. JMIR mHealth and uHealth 2020;8(8):e17709
    CrossRef
  38. Dugan JA, Ahmed S, Vincent M, Perry R, Young CF. Managing Diabetes in the Digital Age. Physician Assistant Clinics 2020;5(2):177
    CrossRef
  39. Vaughn J, Gollarahalli S, Shaw RJ, Docherty S, Yang Q, Malhotra C, Summers-Goeckerman E, Shah N. Mobile Health Technology for Pediatric Symptom Monitoring. Nursing Research 2020;69(2):142
    CrossRef
  40. Sanders I, Short CE, Bogomolova S, Stanford T, Plotnikoff R, Vandelanotte C, Olds T, Edney S, Ryan J, Curtis RG, Maher C. Characteristics of Adopters of an Online Social Networking Physical Activity Mobile Phone App: Cluster Analysis. JMIR mHealth and uHealth 2019;7(6):e12484
    CrossRef
  41. Miele F, Clementi S, Gennaro R, Nicolao I, Romanelli T, Speese K, Piras EM. Text Messaging and Type 1 Diabetes Management: Qualitative Study Exploring Interactions Among Patients and Health Care Professionals. JMIR Diabetes 2019;4(2):e11343
    CrossRef
  42. Owolabi EO, Goon DT. The use of text messaging for improving adherence to anti-diabetic regimen and glycaemic control in low-resource settings of South Africa: A study protocol for a randomised controlled trial. Contemporary Clinical Trials Communications 2019;15:100418
    CrossRef
  43. Brew-Sam N, Chib A. How Do Smart Device Apps for Diabetes Self-Management Correspond with Theoretical Indicators of Empowerment? An Analysis of App Features. International Journal of Technology Assessment in Health Care 2019;35(2):150
    CrossRef
  44. Quevedo Rodríguez A, Wägner AM. Mobile phone applications for diabetes management: A systematic review. Endocrinología, Diabetes y Nutrición (English ed.) 2019;66(5):330
    CrossRef
  45. Greenwood DA, Gee PM, Fatkin KJ, Peeples M. A Systematic Review of Reviews Evaluating Technology-Enabled Diabetes Self-Management Education and Support. Journal of Diabetes Science and Technology 2017;11(5):1015
    CrossRef
  46. Yamaguchi S, Waki K, Nannya Y, Nangaku M, Kadowaki T, Ohe K. Usage Patterns of GlucoNote, a Self-Management Smartphone App, Based on ResearchKit for Patients With Type 2 Diabetes and Prediabetes. JMIR mHealth and uHealth 2019;7(4):e13204
    CrossRef
  47. Krishnan G, Selvam G. Factors influencing the download of mobile health apps: Content review-led regression analysis. Health Policy and Technology 2019;8(4):356
    CrossRef
  48. . Do Smartphone Applications Hold the Secret to Reducing Hypoglycemia in Type 1 Diabetes?. Journal of Diabetes Science and Technology 2018;12(6):1200
    CrossRef
  49. Salazar A, de Sola H, Failde I, Moral-Munoz JA. Measuring the Quality of Mobile Apps for the Management of Pain: Systematic Search and Evaluation Using the Mobile App Rating Scale. JMIR mHealth and uHealth 2018;6(10):e10718
    CrossRef
  50. de Sousa AFL, Bim LL, Schneider G, Hermann PRDS, de Andrade D, Fronteira I. m-Health in the Surgical Context: Prospecting, Review and Analysis of Mobile Applications. The Open Nursing Journal 2019;13(1):18
    CrossRef
  51. Aria R, Archer N. The role of support and sustainability elements in the adoption of an online self-management support system for chronic illnesses. Journal of Biomedical Informatics 2019;95:103215
    CrossRef
  52. Vashistha R, Dangi AK, Kumar A, Chhabra D, Shukla P. Futuristic biosensors for cardiac health care: an artificial intelligence approach. 3 Biotech 2018;8(8)
    CrossRef
  53. Toniazzo MP, Nodari D, Muniz FWMG, Weidlich P. Effect of mHealth in improving oral hygiene: A systematic review with meta‐analysis. Journal of Clinical Periodontology 2019;46(3):297
    CrossRef
  54. Chhabra HS, Sharma S, Verma S. Smartphone app in self-management of chronic low back pain: a randomized controlled trial. European Spine Journal 2018;27(11):2862
    CrossRef
  55. Issom D, Henriksen A, Woldaregay AZ, Rochat J, Lovis C, Hartvigsen G. Factors Influencing Motivation and Engagement in Mobile Health Among Patients With Sickle Cell Disease in Low-Prevalence, High-Income Countries: Qualitative Exploration of Patient Requirements. JMIR Human Factors 2020;7(1):e14599
    CrossRef
  56. Quinn CC, Swasey KK, Crabbe JCF, Shardell MD, Terrin ML, Barr EA, Gruber-Baldini AL. The Impact of a Mobile Diabetes Health Intervention on Diabetes Distress and Depression Among Adults: Secondary Analysis of a Cluster Randomized Controlled Trial. JMIR mHealth and uHealth 2017;5(12):e183
    CrossRef
  57. Owolabi EO, Goon DT, Ajayi AI, Taheri S. Efficacy, acceptability and feasibility of daily text-messaging in promoting glycaemic control and other clinical outcomes in a low-resource setting of South Africa: A randomised controlled trial. PLOS ONE 2019;14(11):e0224791
    CrossRef
  58. Barmanray R, Briganti E. Glycaemic control apps for diabetes: lifting the lid. Medical Journal of Australia 2018;209(10):426
    CrossRef
  59. Rowland SP, Fitzgerald JE, Holme T, Powell J, McGregor A. What is the clinical value of mHealth for patients?. npj Digital Medicine 2020;3(1)
    CrossRef
  60. Skar JB, Garnweidner-Holme LM, Lukasse M, Terragni L. Women's experiences with using a smartphone app (the Pregnant+ app) to manage gestational diabetes mellitus in a randomised controlled trial. Midwifery 2018;58:102
    CrossRef
  61. Jeon E, Park H. Experiences of Patients With a Diabetes Self-Care App Developed Based on the Information-Motivation-Behavioral Skills Model: Before-and-After Study. JMIR Diabetes 2019;4(2):e11590
    CrossRef
  62. Waa JVD, Schoonderwoerd T, Diggelen JV, Neerincx M. Interpretable confidence measures for decision support systems. International Journal of Human-Computer Studies 2020;144:102493
    CrossRef
  63. Qan'ir Y, Song L. Systematic review of technology‐based interventions to improve anxiety, depression, and health‐related quality of life among patients with prostate cancer. Psycho-Oncology 2019;28(8):1601
    CrossRef
  64. Wu Y, Zhou Y, Wang X, Zhang Q, Yao X, Li X, Li J, Tian H, Li S. A Comparison of Functional Features in Chinese and US Mobile Apps for Diabetes Self-Management: A Systematic Search in App Stores and Content Analysis. JMIR mHealth and uHealth 2019;7(8):e13971
    CrossRef
  65. Tyler NS, Mosquera-Lopez CM, Wilson LM, Dodier RH, Branigan DL, Gabo VB, Guillot FH, Hilts WW, El Youssef J, Castle JR, Jacobs PG. An artificial intelligence decision support system for the management of type 1 diabetes. Nature Metabolism 2020;2(7):612
    CrossRef
  66. Donevant SB, Estrada RD, Culley JM, Habing B, Adams SA. Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature. Journal of the American Medical Informatics Association 2018;25(10):1407
    CrossRef
  67. Scott IA, Scuffham P, Gupta D, Harch TM, Borchi J, Richards B. Going digital: a narrative overview of the effects, quality and utility of mobile apps in chronic disease self-management. Australian Health Review 2020;44(1):62
    CrossRef
  68. Bellei EA, Biduski D, Lisboa HRK, De Marchi ACB. Development and Assessment of a Mobile Health Application for Monitoring the Linkage Among Treatment Factors of Type 1 Diabetes Mellitus. Telemedicine and e-Health 2020;26(2):205
    CrossRef
  69. Levine DM, Co Z, Newmark LP, Groisser AR, Holmgren AJ, Haas JS, Bates DW. Design and testing of a mobile health application rating tool. npj Digital Medicine 2020;3(1)
    CrossRef
  70. Dugas M, Gao G, Agarwal R. Unpacking mHealth interventions: A systematic review of behavior change techniques used in randomized controlled trials assessing mHealth effectiveness. DIGITAL HEALTH 2020;6:205520762090541
    CrossRef
  71. Aji M, Glozier N, Bartlett D, Peters D, Calvo RA, Zheng Y, Grunstein R, Gordon C. A feasibility study of a mobile app to treat insomnia. Translational Behavioral Medicine 2021;11(2):604
    CrossRef
  72. . Emerging Pharmacotherapy and Health Care Needs of Patients in the Age of Artificial Intelligence and Digitalization. Annals of Pharmacotherapy 2020;54(10):1038
    CrossRef
  73. Carter DD, Robinson K, Forbes J, Walsh JC, Hayes S. Exploring the perspectives of stroke survivors and healthcare professionals on the use of mobile health to promote physical activity: A qualitative study protocol. HRB Open Research 2019;2:9
    CrossRef
  74. Rinaldi G, Hijazi A, Haghparast-Bidgoli H. Cost and cost-effectiveness of mHealth interventions for the prevention and control of type 2 diabetes mellitus: A systematic review. Diabetes Research and Clinical Practice 2020;162:108084
    CrossRef
  75. Timpel P, Oswald S, Schwarz PEH, Harst L. Mapping the Evidence on the Effectiveness of Telemedicine Interventions in Diabetes, Dyslipidemia, and Hypertension: An Umbrella Review of Systematic Reviews and Meta-Analyses. Journal of Medical Internet Research 2020;22(3):e16791
    CrossRef
  76. Stein N, Brooks K. A Fully Automated Conversational Artificial Intelligence for Weight Loss: Longitudinal Observational Study Among Overweight and Obese Adults. JMIR Diabetes 2017;2(2):e28
    CrossRef
  77. . Behavioral Theory: The Missing Ingredient for Digital Health Tools to Change Behavior and Increase Adherence. Journal of Diabetes Science and Technology 2019;13(2):276
    CrossRef
  78. Zhang Y, Li X, Luo S, Liu C, Liu F, Zhou Z. Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study. JMIR mHealth and uHealth 2018;6(9):e11400
    CrossRef
  79. Chakranon P, Lai YK, Tang YW, Choudhary P, Khunti K, Lee SWH. Distal technology interventions in people with diabetes: an umbrella review of multiple health outcomes. Diabetic Medicine 2020;37(12):1966
    CrossRef
  80. Neerincx MA, van Vught W, Blanson Henkemans O, Oleari E, Broekens J, Peters R, Kaptein F, Demiris Y, Kiefer B, Fumagalli D, Bierman B. Socio-Cognitive Engineering of a Robotic Partner for Child's Diabetes Self-Management. Frontiers in Robotics and AI 2019;6
    CrossRef
  81. Heller SR, Gianfrancesco C, Taylor C, Elliott J. What are the characteristics of the best type 1 diabetes patient education programmes (from diagnosis to long‐term care), do they improve outcomes and what is required to make them more effective?. Diabetic Medicine 2020;37(4):545
    CrossRef
  82. Burgess J, Watt K, Kimble RM, Cameron CM. Combining Technology and Research to Prevent Scald Injuries (the Cool Runnings Intervention): Randomized Controlled Trial. Journal of Medical Internet Research 2018;20(10):e10361
    CrossRef
  83. Öberg U, Orre CJ, Hörnsten , Jutterström L, Isaksson U. Using the Self-Management Assessment Scale for Screening Support Needs in Type 2 Diabetes: Qualitative Study. JMIR Nursing 2020;3(1):e16318
    CrossRef
  84. Trawley S, Baptista S, Browne JL, Pouwer F, Speight J. The Use of Mobile Applications Among Adults with Type 1 and Type 2 Diabetes: Results from the Second MILES—Australia (MILES-2) Study. Diabetes Technology & Therapeutics 2017;19(12):730
    CrossRef
  85. Berman MA, Guthrie NL, Edwards KL, Appelbaum KJ, Njike VY, Eisenberg DM, Katz DL. Change in Glycemic Control With Use of a Digital Therapeutic in Adults With Type 2 Diabetes: Cohort Study. JMIR Diabetes 2018;3(1):e4
    CrossRef
  86. Villinger K, Wahl DR, Boeing H, Schupp HT, Renner B. The effectiveness of app‐based mobile interventions on nutrition behaviours and nutrition‐related health outcomes: A systematic review and meta‐analysis. Obesity Reviews 2019;20(10):1465
    CrossRef
  87. Vehi J, Regincós Isern J, Parcerisas A, Calm R, Contreras I. Impact of Use Frequency of a Mobile Diabetes Management App on Blood Glucose Control: Evaluation Study. JMIR mHealth and uHealth 2019;7(3):e11933
    CrossRef
  88. Surkan PJ, Mezzanotte KS, Sena LM, Chang LW, Gittelsohn J, Trolle Lagerros Y, Quinn CC, Zachary WW. Community-Driven Priorities in Smartphone Application Development: Leveraging Social Networks to Self-Manage Type 2 Diabetes in a Low-Income African American Neighborhood. International Journal of Environmental Research and Public Health 2019;16(15):2715
    CrossRef
  89. Russell‐Jones D, Pouwer F, Khunti K. Identification of barriers to insulin therapy and approaches to overcoming them. Diabetes, Obesity and Metabolism 2018;20(3):488
    CrossRef
  90. Aminuddin HB, Jiao N, Jiang Y, Hong J, Wang W. Effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life and clinical outcomes in patients with type 2 diabetes: A systematic review and meta-analysis. International Journal of Nursing Studies 2021;116:103286
    CrossRef
  91. Cho J, Kim S. Personal and social predictors of use and non-use of fitness/diet app: Application of Random Forest algorithm. Telematics and Informatics 2020;55:101301
    CrossRef
  92. Xie B, Su Z, Zhang W, Cai R. Chinese Cardiovascular Disease Mobile Apps’ Information Types, Information Quality, and Interactive Functions for Self-Management: Systematic Review. JMIR mHealth and uHealth 2017;5(12):e195
    CrossRef
  93. Gong E, Zhang Z, Jin X, Liu Y, Zhong L, Wu Y, Zhong X, Yan LL, Oldenburg B. Quality, Functionality, and Features of Chinese Mobile Apps for Diabetes Self-Management: Systematic Search and Evaluation of Mobile Apps. JMIR mHealth and uHealth 2020;8(4):e14836
    CrossRef
  94. Liu K, Xie Z, Or CK. Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials. JMIR mHealth and uHealth 2020;8(8):e15779
    CrossRef
  95. Najm A, Nikiphorou E, Kostine M, Richez C, Pauling JD, Finckh A, Ritschl V, Prior Y, Balážová P, Stones S, Szekanecz Z, Iagnocco A, Ramiro S, Sivera F, Dougados M, Carmona L, Burmester G, Wiek D, Gossec L, Berenbaum F. EULAR points to consider for the development, evaluation and implementation of mobile health applications aiding self-management in people living with rheumatic and musculoskeletal diseases. RMD Open 2019;5(2):e001014
    CrossRef
  96. . mHealth Apps as Effective Persuasive Health Technology: Contextualizing the “Necessary” Functionalities. JMIR Nursing 2020;3(1):e19302
    CrossRef
  97. Allman-Farinelli M, Gemming L. Technology Interventions to Manage Food Intake: Where Are We Now?. Current Diabetes Reports 2017;17(11)
    CrossRef
  98. Tauschmann M, Hovorka R. Technology in the management of type 1 diabetes mellitus — current status and future prospects. Nature Reviews Endocrinology 2018;14(8):464
    CrossRef
  99. . A Digital-First Model of Diabetes Care. Diabetes Technology & Therapeutics 2019;21(S2):S2-52
    CrossRef
  100. Wang Y, Min J, Khuri J, Xue H, Xie B, A Kaminsky L, J Cheskin L. Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews. JMIR mHealth and uHealth 2020;8(4):e15400
    CrossRef
  101. Iribarren SJ, Akande TO, Kamp KJ, Barry D, Kader YG, Suelzer E. Effectiveness of Mobile Apps to Promote Health and Manage Disease: Systematic Review and Meta-analysis of Randomized Controlled Trials. JMIR mHealth and uHealth 2021;9(1):e21563
    CrossRef
  102. Yang Y, Cho J. Clinical Effects of Remote Glucose Monitoring and Patient-Centered Education Platform for Patients with Diabetes. The Journal of Korean Diabetes 2020;21(4):204
    CrossRef
  103. Ramallo-Fariña Y, García-Bello MA, García-Pérez L, Boronat M, Wägner AM, Rodríguez-Rodríguez L, de Pablos-Velasco P, Llorente Gómez de Segura I, González- Pacheco H, Carmona Rodríguez M, Serrano-Aguilar P. Effectiveness of Internet-Based Multicomponent Interventions for Patients and Health Care Professionals to Improve Clinical Outcomes in Type 2 Diabetes Evaluated Through the INDICA Study: Multiarm Cluster Randomized Controlled Trial. JMIR mHealth and uHealth 2020;8(11):e18922
    CrossRef
  104. Martinez W, Threatt AL, Rosenbloom ST, Wallston KA, Hickson GB, Elasy TA. A Patient-Facing Diabetes Dashboard Embedded in a Patient Web Portal: Design Sprint and Usability Testing. JMIR Human Factors 2018;5(3):e26
    CrossRef
  105. Böhm A, Jensen ML, Sørensen MR, Stargardt T. Real-World Evidence of User Engagement With Mobile Health for Diabetes Management: Longitudinal Observational Study. JMIR mHealth and uHealth 2020;8(11):e22212
    CrossRef
  106. Dugas M, Wang W, Crowley K, Iyer AK, Peeples M, Shomali M, Gao G. Engagement and Outcomes Associated with Contextual Annotation Features of a Digital Health Solution. Journal of Diabetes Science and Technology 2022;16(4):804
    CrossRef
  107. Flors-Sidro JJ, Househ M, Abd-Alrazaq A, Vidal-Alaball J, Fernandez-Luque L, Sanchez-Bocanegra CL. Analysis of Diabetes Apps to Assess Privacy-Related Permissions: Systematic Search of Apps. JMIR Diabetes 2021;6(1):e16146
    CrossRef
  108. Aji M, Gordon C, Stratton E, Calvo RA, Bartlett D, Grunstein R, Glozier N. Framework for the Design Engineering and Clinical Implementation and Evaluation of mHealth Apps for Sleep Disturbance: Systematic Review. Journal of Medical Internet Research 2021;23(2):e24607
    CrossRef
  109. Agarwal P, Gordon D, Griffith J, Kithulegoda N, Witteman HO, Sacha Bhatia R, Kushniruk AW, Borycki EM, Lamothe L, Springall E, Shaw J. Assessing the quality of mobile applications in chronic disease management: a scoping review. npj Digital Medicine 2021;4(1)
    CrossRef
  110. Li J, Wei D, Liu S, Li M, Chen X, Chen L, Wu Y, Zhou W, Ouyang L, Tan C, Meng H, Tong N. Efficiency of an mHealth App and Chest-Wearable Remote Exercise Monitoring Intervention in Patients With Type 2 Diabetes: A Prospective, Multicenter Randomized Controlled Trial. JMIR mHealth and uHealth 2021;9(2):e23338
    CrossRef
  111. Bermejo-Gil BM, Pérez-Robledo F, Llamas-Ramos R, Silva LA, Sales-Mendes A, Leithardt VRQ, Llamas-Ramos I. RespiraConNosotros: A Viable Home-Based Telerehabilitation System for Respiratory Patients. Sensors 2021;21(10):3318
    CrossRef
  112. Ossai CI, Wickramasinghe N. Text Mining and Grounded Theory for Appraising the Self-Management Indicators of Diabetes Mobile Apps. Endocrine and Metabolic Science 2021;4:100101
    CrossRef
  113. Qan’ir Y, Khalifeh AH, Eid M, Hammad B, Al-Batran M. Mobile health apps use among Jordanian outpatients: A descriptive study. Health Informatics Journal 2021;27(2):146045822110179
    CrossRef
  114. El-Gayar O, Ofori M, Nawar N. On the efficacy of behavior change techniques in mHealth for self-management of diabetes: A meta-analysis. Journal of Biomedical Informatics 2021;119:103839
    CrossRef
  115. Fan K, Zhao Y. Mobile health technology: a novel tool in chronic disease management. Intelligent Medicine 2022;2(1):41
    CrossRef
  116. Liu C, Tang S, An K, Zhang S, Zhou Y, Su N, Yang R, Liao X, An Z, Li S. Knowledge, Attitude, and Practice of Metformin Extended-Release Tablets Among Clinicians in China: A Cross-Sectional Survey. Frontiers in Pharmacology 2021;12
    CrossRef
  117. Tu Y, Chang Y, Chiou H, Lai K. The Effects of Continuous Usage of a Diabetes Management App on Glycemic Control in Real-world Clinical Practice: Retrospective Analysis. Journal of Medical Internet Research 2021;23(7):e23227
    CrossRef
  118. Greenwood DA, Litchman ML, Isaacs D, Blanchette JE, Dickinson JK, Hughes A, Colicchio VD, Ye J, Yehl K, Todd A, Peeples MM. A New Taxonomy for Technology-Enabled Diabetes Self-Management Interventions: Results of an Umbrella Review. Journal of Diabetes Science and Technology 2022;16(4):812
    CrossRef
  119. Lee EY, Cha S, Yun J, Lim S, Lee J, Ahn Y, Yoon K, Hyun MK, Ko S. Efficacy of Personalized Diabetes Self-care Using an Electronic Medical Record–Integrated Mobile App in Patients With Type 2 Diabetes: 6-Month Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(7):e37430
    CrossRef
  120. Zahmatkeshan M, Zakerabasali S, Farjam M, Gholampour Y, Seraji M, Yazdani A. The use of mobile health interventions for gestational diabetes mellitus: a descriptive literature review. Journal of Medicine and Life 2021;14(2):131
    CrossRef
  121. Saffari SE, Ning Y, Xie F, Chakraborty B, Volovici V, Vaughan R, Ong MEH, Liu N. AutoScore-Ordinal: an interpretable machine learning framework for generating scoring models for ordinal outcomes. BMC Medical Research Methodology 2022;22(1)
    CrossRef
  122. Zhu T, Uduku C, Li K, Herrero P, Oliver N, Georgiou P. Enhancing self-management in type 1 diabetes with wearables and deep learning. npj Digital Medicine 2022;5(1)
    CrossRef
  123. Stawarz K, Katz D, Ayobi A, Marshall P, Yamagata T, Santos-Rodriguez R, Flach P, O’Kane AA. Co-designing opportunities for Human-Centred Machine Learning in supporting Type 1 diabetes decision-making. International Journal of Human-Computer Studies 2023;173:103003
    CrossRef
  124. Leong CM, Lee T, Chien Y, Kuo L, Kuo Y, Chen H. Social Media–Delivered Patient Education to Enhance Self-management and Attitudes of Patients with Type 2 Diabetes During the COVID-19 Pandemic: Randomized Controlled Trial. Journal of Medical Internet Research 2022;24(3):e31449
    CrossRef
  125. Hietbrink EAG, Middelweerd A, van Empelen P, Preuhs K, Konijnendijk AAJ, Oude Nijeweme-d’Hollosy W, Schrijver LK, Laverman GD, Vollenbroek-Hutten MMR. A Digital Lifestyle Coach (E-Supporter 1.0) to Support People With Type 2 Diabetes: Participatory Development Study. JMIR Human Factors 2023;10:e40017
    CrossRef
  126. Giebel GD, Speckemeier C, Abels C, Börchers K, Wasem J, Blase N, Neusser S. Problems and Barriers Related to the Use of Digital Health Applications: Protocol for a Scoping Review. JMIR Research Protocols 2022;11(4):e32702
    CrossRef
  127. María Gómez A, Cristina Henao D, León Vargas F, Mauricio Muñoz O, David Lucero O, García Jaramillo M, Aldea A, Martin C, Miguel Rodríguez Hortúa L, Patricia Rubio Reyes C, Alejandra Páez Hortúa M, Rondón M. Efficacy of the mHealth application in patients with type 2 diabetes transitioning from inpatient to outpatient care: A randomized controlled clinical trial. Diabetes Research and Clinical Practice 2022;189:109948
    CrossRef
  128. Hou I, Chung T. The Acceptability Study of Heart Transplantation Self-Management Support mHealth Application (iHeart App) in Taiwan: Mix Method Approaches. (Preprint). JMIR Formative Research 2020;
    CrossRef
  129. Stevens S, Gallagher S, Andrews T, Ashall-Payne L, Humphreys L, Leigh S. The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review. Frontiers in Clinical Diabetes and Healthcare 2022;3
    CrossRef
  130. 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
    CrossRef
  131. Sabharwal M, Misra A, Ghosh A, Chopra G. Efficacy of Digitally Supported and Real-Time Self-Monitoring of Blood Glucose-Driven Counseling in Patients with Type 2 Diabetes Mellitus: A Real-World, Retrospective Study in North India. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2022;Volume 15:23
    CrossRef
  132. Yoon S, Kwan YH, Phang JK, Tan WB, Low LL. Personal Goals, Barriers to Self-Management and Desired mHealth Application Features to Improve Self-Care in Multi-Ethnic Asian Patients with Type 2 Diabetes: A Qualitative Study. International Journal of Environmental Research and Public Health 2022;19(22):15415
    CrossRef
  133. Stephen DA, Nordin A, Nilsson J, Persenius M. Using mHealth applications for self-care – An integrative review on perceptions among adults with type 1 diabetes. BMC Endocrine Disorders 2022;22(1)
    CrossRef
  134. Rivière C, Brureau L, Parnot C, Becherirat S, Duverger C, Picchi H, Le Roy A, Vuagnat P, Schernberg A, Vanquaethem H, Helissey C. Effectiveness of a digital telemonitoring platform for cancer care of older patients: The ConnectElderlyPatientToDoctor study. International Journal of Cancer 2023;152(3):504
    CrossRef
  135. Kaveh MH, Faradonbeh MR, Kaveh S. Telehealth impact on biomedical, psychosocial, and behavioural outcomes in patients with diabetes older than 50 years: A systematic synthesis without meta-analysis. Journal of Telemedicine and Telecare 2024;30(2):285
    CrossRef
  136. Smyth S, Curtin E, Tully E, Molphy Z, Breathnach F. Smartphone Apps for Surveillance of Gestational Diabetes: Scoping Review. JMIR Diabetes 2022;7(4):e38910
    CrossRef
  137. Bae S, Borac S, Emre Y, Wang J, Wu J, Kashyap M, Kang S, Chen L, Moran M, Cannon J, Teasley ES, Chai A, Liu Y, Wadhwa N, Krainin M, Rubinstein M, Maciel A, McConnell MV, Patel S, Corrado GS, Taylor JA, Zhan J, Po MJ. Prospective validation of smartphone-based heart rate and respiratory rate measurement algorithms. Communications Medicine 2022;2(1)
    CrossRef
  138. Su N, Xu T, Li X, Zheng H, Wu B, Zhang S, Zhou Y, Du L, Zhao Y. Heparin and Related Substances for Treating Diabetic Foot Ulcers: A Systematic Review and Meta-Analysis. Frontiers in Endocrinology 2022;13
    CrossRef
  139. Laptev DN, Eremina IA, Karpushkina AV, Petryaykina EE, Bezlepkina OB, Peterkova VA. Remote monitoring of adolescents with type 1 diabetes mellitus using a mobile application. Diabetes mellitus 2022;24(5):404
    CrossRef
  140. Kundury KK, Bovilla VR, Kumar KSP, Chandrashekarappa SM, Madhunapantula SV, Hathur B. Providing Diabetes Education through Phone Calls Assisted in the Better Control of Hyperglycemia and Improved the Knowledge of Patients on Diabetes Management. Healthcare 2023;11(4):528
    CrossRef
  141. Santos DS, Batistelli CRS, Lara MMDS, Ferreira EDS, Moreira TR, Cotta RMM. The effectiveness of the use of telehealth programs in the care of individuals with hypertension and, or diabetes mellitus: systematic review and meta-analysis. Diabetology & Metabolic Syndrome 2022;14(1)
    CrossRef
  142. 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)
    CrossRef
  143. Blanchard J, Ahmed S, Clark B, Sanchez Cotto L, Rangasamy S, Thompson B. Design and Testing of a Smartphone Application for Real-Time Tracking of CSII and CGM Site Rotation Compliance in Patients With Type 1 Diabetes. Journal of Diabetes Science and Technology 2022;:193229682211451
    CrossRef
  144. İNKAYA B, YILMAZER T, TÜZER H, ERBİL EY. Given According to Knowledge, Motivation and Behavioral Skills (IMB Model) The Effect of Diabetes Education on Self-Care. Turkish Journal of Diabetes and Obesity 2022;6(3):241
    CrossRef
  145. Pullyblank K, Scribani M, Wyckoff L, Krupa N, Flynn J, Henderson C, Strogatz D. Evaluating the Implementation of the Diabetes Self-Management Program in a Rural Population. Diabetes Spectrum 2022;35(1):95
    CrossRef
  146. Wang H, Jiang Y, Wiley J, Ge L. Effectiveness of Smartphone-Based Lifestyle Interventions on Women with Gestational Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Psychology Research and Behavior Management 2022;Volume 15:3541
    CrossRef
  147. Benton JS, Cotterill S, Hawkes RE, Miles LM, French DP. Changes in a Digital Type 2 Diabetes Self-management Intervention During National Rollout: Mixed Methods Study of Fidelity. Journal of Medical Internet Research 2022;24(12):e39483
    CrossRef
  148. Tews D, Gouveri E, Simon J, Marck C. A Smartphone-Based Application to Assist Insulin Titration in Patients Undergoing Basal Insulin-Supported Oral Antidiabetic Treatment. Journal of Diabetes Science and Technology 2023;17(4):988
    CrossRef
  149. Wangler J, Jansky M. Attitudes and experiences of registered diabetes specialists in using health apps for managing type 2 diabetes: results from a mixed-methods study in Germany 2021/2022. Archives of Public Health 2023;81(1)
    CrossRef
  150. Aydin A, Gürsoy A, Karal H. Mobile care app development process: using the ADDIE model to manage symptoms after breast cancer surgery (step 1). Discover Oncology 2023;14(1)
    CrossRef
  151. Sze WT, Waki K, Enomoto S, Nagata Y, Nangaku M, Yamauchi T, Ohe K. StepAdd: A personalized mHealth intervention based on social cognitive theory to increase physical activity among type 2 diabetes patients. Journal of Biomedical Informatics 2023;145:104481
    CrossRef
  152. . The use of mobile health applications in empowering self-management of type 2 diabetes: a literature review. The European Research Journal 2024;10(1):127
    CrossRef
  153. SHIBAYAMA K, SAKAMOTO T, FURUSHIMA C. Mobile App-based Interventions for Patients with Noncommunicable Diseases in Japan: A Scoping Review. Asian Journal of Human Services 2023;25:177
    CrossRef
  154. Iversen L, Weritz J, Nock A, Waidhas L, Petersen-Ewert C. eHealth im Community Health Nursing – Mobile Anwendungen zur Therapie von Menschen mit Diabetes mellitus Typ 2. Diabetologie und Stoffwechsel 2023;
    CrossRef
  155. Zein S, Salleh N, Grundy J. Systematic reviews in mobile app software engineering: A tertiary study. Information and Software Technology 2023;164:107323
    CrossRef
  156. Jonusas J, Aleknavicius K, Valinskas S. Klinio mobile app for diabetes self-care: A pilot study of HbA1c improvement in type 2 diabetes patients. Smart Health 2023;29:100404
    CrossRef
  157. Alsayed AO, Ismail NA, Hasan L, Syed AH, Embarak F, Da'u A. A systematic literature review for understanding the effectiveness of advanced techniques in diabetes self-care management. Alexandria Engineering Journal 2023;79:274
    CrossRef
  158. Giovanazzi A, Gios L, Mastellaro M, Gentilini MA, Valent F, Condini S, Bincoletto G, Bacchiega A, Zorzi A, Malfatti G, Perini F, Eccher C, Marchesoni M, Dall’Alda M, Orrasch M, Conforti D, Inchiostro S. Organisational models supported by technology for the management of diabetic disease and its complications in a diabetic clinic setting: study protocol for a randomised controlled trial targeting type 2 diabetes individuals with non-ideal glycaemic values (Telemechron study). Trials 2023;24(1)
    CrossRef
  159. Hietbrink EAG, Oude Nijeweme-d’Hollosy W, Middelweerd A, Konijnendijk AAJ, Schrijver LK, ten Voorde AS, Fokkema EMS, Laverman GD, Vollenbroek-Hutten MMR. A Digital Coach (E-Supporter 1.0) to Support Physical Activity and a Healthy Diet in People With Type 2 Diabetes: Acceptability and Limited Efficacy Testing. JMIR Formative Research 2023;7:e45294
    CrossRef
  160. Painter A, van Dael J, Neves AL, Bachtiger P, O’Brien N, Gardner C, Quint J, Adamson A, Peters N, Darzi A, Ghafur S. Identifying benefits and concerns with using digital health services during COVID-19: Evidence from a hospital-based patient survey. Health Informatics Journal 2023;29(4)
    CrossRef
  161. Chong SOK, Pedron S, Abdelmalak N, Laxy M, Stephan A. An umbrella review of effectiveness and efficacy trials for app-based health interventions. npj Digital Medicine 2023;6(1)
    CrossRef
  162. Waki K, Tsurutani Y, Waki H, Enomoto S, Kashiwabara K, Fujiwara A, Orime K, Kinguchi S, Yamauchi T, Hirawa N, Tamura K, Terauchi Y, Nangaku M, Ohe K. Efficacy of StepAdd, a Personalized mHealth Intervention Based on Social Cognitive Theory to Increase Physical Activity Among Patients With Type 2 Diabetes Mellitus: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2024;13:e53514
    CrossRef
  163. Hakami AM, Almutairi B, Alanazi AS, Alzahrani MA. Effect of Mobile Apps on Medication Adherence of Type 2 Diabetes Mellitus: A Systematic Review of Recent Studies. Cureus 2024;
    CrossRef
  164. Biskupiak Z, Ha VV, Rohaj A, Bulaj G. Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases. Journal of Clinical Medicine 2024;13(2):403
    CrossRef
  165. Lee JL, Kim Y. Evaluation of Mobile Applications for Patients with Diabetes Mellitus: A Scoping Review. Healthcare 2024;12(3):368
    CrossRef
  166. Di Martino G, della Valle C, Centorbi M, Buonsenso A, Fiorilli G, Calcagno G, Iuliano E, di Cagno A. Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity. International Journal of Environmental Research and Public Health 2024;21(2):233
    CrossRef
  167. Tarricone R, Petracca F, Svae L, Cucciniello M, Ciani O. Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials. eBioMedicine 2024;103:105091
    CrossRef

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