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Citing this Article

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Published on 19.12.16 in Vol 4, No 4 (2016): Oct-Dec

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

Works citing "Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review"

According to Crossref, the following articles are citing this article (DOI 10.2196/mhealth.6445):

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

  1. Tarricone R, Cucciniello M, Armeni P, Petracca F, Desouza KC, Hall LK, Keefe D. Mobile Health Divide Between Clinicians and Patients in Cancer Care: Results From a Cross-Sectional International Survey. JMIR mHealth and uHealth 2019;7(9):e13584
    CrossRef
  2. Park YR, Lee E, Na W, Park S, Lee Y, Lee J. Is Blockchain Technology Suitable for Managing Personal Health Records? Mixed-Methods Study to Test Feasibility. Journal of Medical Internet Research 2019;21(2):e12533
    CrossRef
  3. Bhattacharyya O, Mossman K, Gustafsson L, Schneider EC. Using Human-Centered Design to Build a Digital Health Advisor for Patients With Complex Needs: Persona and Prototype Development. Journal of Medical Internet Research 2019;21(5):e10318
    CrossRef
  4. Singh K, Diamantidis CJ, Ramani S, Bhavsar NA, Mara P, Warner J, Rodriguez J, Wang T, Wright-Nunes J. Patients’ and Nephrologists’ Evaluation of Patient-Facing Smartphone Apps for CKD. Clinical Journal of the American Society of Nephrology 2019;14(4):523
    CrossRef
  5. Park YR, Lee Y, Kim JY, Kim J, Kim HR, Kim Y, Kim WS, Lee J. Managing Patient-Generated Health Data Through Mobile Personal Health Records: Analysis of Usage Data. JMIR mHealth and uHealth 2018;6(4):e89
    CrossRef
  6. Kim H, Park E, Lee S, Kim M, Park EJ, Hong S. Self-management of Older Korean Adults Living with Chronic Diseases: The mHealth Training Protocol and Feasibility Study (Preprint). JMIR Research Protocols 2018;
    CrossRef
  7. Breton MD, Patek SD, Lv D, Schertz E, Robic J, Pinnata J, Kollar L, Barnett C, Wakeman C, Oliveri M, Fabris C, Chernavvsky D, Kovatchev BP, Anderson SM. Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus. Diabetes Technology & Therapeutics 2018;20(8):531
    CrossRef
  8. Kim H, Park E, Lee S, Kim M, Park EJ, Hong S. Self-Management of Chronic Diseases Among Older Korean Adults: An mHealth Training, Protocol, and Feasibility Study. JMIR mHealth and uHealth 2018;6(6):e147
    CrossRef
  9. Rodriguez JA, Singh K. The Spanish Availability and Readability of Diabetes Apps. Journal of Diabetes Science and Technology 2018;12(3):719
    CrossRef
  10. DiFilippo KN, Huang WD, Chapman-Novakofski KM. Mobile Apps for the Dietary Approaches to Stop Hypertension (DASH): App Quality Evaluation. Journal of Nutrition Education and Behavior 2018;50(6):620
    CrossRef
  11. Wang P, Luo D, Lu F, Elias JS, Landman AB, Michaud KD, Lee YC. A Novel Mobile App and Population Management System to Manage Rheumatoid Arthritis Flares: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2018;7(4):e84
    CrossRef
  12. Klimova B. Mobile Phone Apps in the Management and Assessment of Mild Cognitive Impairment and/or Mild-to-Moderate Dementia: An Opinion Article on Recent Findings. Frontiers in Human Neuroscience 2017;11
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/mhealth.6445)

:
  1. Singh K, Landman AB. Key Advances in Clinical Informatics. 2017. :183
    CrossRef