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

Patient Experiences with Diabetes Technology (29) mHealth for Wellness, Behavior Change and Prevention (2754) Exercise and Diet Tracking for Diabetes Patients (78)

Published on in Vol 5, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21183, first published .
Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study

Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study

Technology-Assisted Self-Monitoring of Lifestyle Behaviors and Health Indicators in Diabetes: Qualitative Study

Authors of this article:

Yan Du1 Author Orcid Image ;   Brittany Dennis1 Author Orcid Image ;   Shanae Lakel Rhodes2 Author Orcid Image ;   Michelle Sia1 Author Orcid Image ;   Jisook Ko2 Author Orcid Image ;   Rozmin Jiwani2 Author Orcid Image ;   Jing Wang1 Author Orcid Image
Article Authors Cited by (14) Tweetations (1) Metrics

Journals

  1. Hyun M, Lee J, Ko S, Hwang J. Improving Glycemic Control in Type 2 Diabetes Using Mobile Applications and e-Coaching: A Mixed Treatment Comparison Network Meta-Analysis. Journal of Diabetes Science and Technology 2022;16(5):1239 View
  2. Kimura M, Toyoda M, Saito N, Takahashi M, Isozumi K, Kato E, Kawanami D, Fukagawa M. The Importance of Patient and Family Engagement, the Needs for Self-Monitoring of Blood Glucose (SMBG) – Our Perspectives Learned Through a Story of SMBG Assistive Devices Made by a Husband of the Patient with Diabetes. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy 2022;Volume 15:1627 View
  3. Wong V, Ho F, Shi N, Sarris J, Ng C, Tam O. Lifestyle medicine for anxiety symptoms: A meta-analysis of randomized controlled trials. Journal of Affective Disorders 2022;310:354 View
  4. Bergevi J, Andermo S, Woldamanuel Y, Johansson U, Hagströmer M, Rossen J. User Perceptions of eHealth and mHealth Services Promoting Physical Activity and Healthy Diets: Systematic Review. JMIR Human Factors 2022;9(2):e34278 View
  5. Klonoff D, Nguyen K, Xu N, Gutierrez A, Espinoza J, Vidmar A. Use of Continuous Glucose Monitors by People Without Diabetes: An Idea Whose Time Has Come?. Journal of Diabetes Science and Technology 2023;17(6):1686 View
  6. Bassi-Dibai D, Santos-de-Araújo A, Dibai-Filho A, de Azevedo L, Goulart C, Luz G, Burke P, Garcia-Araújo A, Borghi-Silva A. Rehabilitation of Individuals With Diabetes Mellitus: Focus on Diabetic Myopathy. Frontiers in Endocrinology 2022;13 View
  7. 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
  8. Kwan Y, Ong Z, Choo D, Phang J, Yoon S, Low L. A Mobile Application to Improve Diabetes Self-Management Using Rapid Prototyping: Iterative Co-Design Approach in Asian Settings. Patient Preference and Adherence 2023;Volume 17:1 View
  9. Østervang C, Lassen A, Schmidt T, Coyne E, Dieperink K, Jensen C. Development of a health information system to promote emergency care pathways: A participatory design study. DIGITAL HEALTH 2022;8:205520762211458 View
  10. Madanian S, Nakarada-Kordic I, Reay S, Chetty T. Patients' perspectives on digital health tools. PEC Innovation 2023;2:100171 View
  11. Mora N, Arvanitakis Z, Thomas M, Kramer H, Morrato E, Markossian T. Applying Customer Discovery Method to a Chronic Disease Self-Management Mobile App: Qualitative Study. JMIR Formative Research 2023;7:e50334 View
  12. Østervang C, Jensen C, Coyne E, Dieperink K, Lassen A. Usability and Evaluation of a Health Information System in the Emergency Department: Mixed Methods Study. JMIR Human Factors 2024;11:e48445 View
  13. Alvarez-Romero C, Polo-Molina A, Sánchez-Úbeda E, Jimenez-De-Juan C, Cuadri-Benitez M, Rivas-Gonzalez J, Portela J, Palacios R, Rodriguez-Morcillo C, Muñoz A, Parra-Calderon C, Nieto-Martin M, Ollero-Baturone M, Hernández-Quiles C. Machine Learning–Based Prediction of Changes in the Clinical Condition of Patients With Complex Chronic Diseases: 2-Phase Pilot Prospective Single-Center Observational Study. JMIR Formative Research 2024;8:e52344 View
  14. Sheng C, Wang L, Long C, Yue R. Group-informed attentive framework for enhanced diabetes mellitus progression prediction. Frontiers in Endocrinology 2024;15 View