Published on in Vol 9, No 4 (2022): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36987, first published .
Behavior Change App for Self-management of Gestational Diabetes: Design and Evaluation of Desirable Features

Behavior Change App for Self-management of Gestational Diabetes: Design and Evaluation of Desirable Features

Behavior Change App for Self-management of Gestational Diabetes: Design and Evaluation of Desirable Features

Journals

  1. Kytö M, Markussen L, Marttinen P, Jacucci G, Niinistö S, Virtanen S, Korhonen T, Sievänen H, Vähä-Ypyä H, Korhonen I, Heinonen S, Koivusalo S. Comprehensive self-tracking of blood glucose and lifestyle with a mobile application in the management of gestational diabetes: a study protocol for a randomised controlled trial (eMOM GDM study). BMJ Open 2022;12(11):e066292 View
  2. Kytö M, Koivusalo S, Tuomonen H, Strömberg L, Ruonala A, Marttinen P, Heinonen S, Jacucci G. Supporting the Management of Gestational Diabetes Mellitus With Comprehensive Self-Tracking: Mixed Methods Study of Wearable Sensors. JMIR Diabetes 2023;8:e43979 View
  3. Xu N, Han X, Chen S, Zhang J, Gu P. Self‐reported barriers in self‐management of women with gestational diabetes: A systematic review of qualitative studies. Nursing Open 2023;10(11):7130 View
  4. Safiee L, Rough D, George P, Mudenha R. Baseline Perceptions of Women With Gestational Diabetes Mellitus and Health Care Professionals About Digital Gestational Diabetes Mellitus Self-Management Health Care Technologies: Interview Study Among Patients and Health Care Professionals. JMIR Human Factors 2023;10:e51691 View
  5. McGovern L, O'Toole L, Houshialsadat Z, O'Reilly S. Women's perspectives on mHealth behavior change interventions for the management of overweight, obesity, or gestational diabetes: A qualitative meta‐synthesis. Obesity Reviews 2024;25(8) View
  6. Yu J, Kim O, Kang B, Lee S, Lee Y, Hwang H, Lee S, Kim S, Choi Y, Ko H. Demand and Requirements for a Digital Healthcare System to Manage Gestational Diabetes in Patients and Healthcare Professionals: A Cross-sectional Survey. INQUIRY: The Journal of Health Care Organization, Provision, and Financing 2024;61 View
  7. Hotta S, Kytö M, Koivusalo S, Heinonen S, Marttinen P, Nunes E. Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data. PLOS ONE 2024;19(8):e0298506 View
  8. Druye A, Owusu G, Yeboa N, Boso C, Berchie G, Nabe B, Abraham S, Nsatimba F, Agyare D, Agyeiwaa J, Opoku-Danso R, Okantey C, Ofori G, Kagbo J, Obeng P, Amoadu M, Azu T. Self-management interventions for gestational diabetes in Africa: a scoping review. BMC Pregnancy and Childbirth 2024;24(1) View