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

mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (461) Innovations and Technology for Physical Activity Education (703) Mobile Health (mhealth) (2777) Digital Biomarkers and Digital Phenotyping (178) Fitness Trackers and Smart Pedometers/Accelerometers (543) Apps, Mobile, Wearables for Diabetes (288) Diabetes Self-Management (464)

Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17730, first published .
Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis

Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis

Digital Phenotyping Self-Monitoring Behaviors for Individuals With Type 2 Diabetes Mellitus: Observational Study Using Latent Class Growth Analysis

Authors of this article:

Qing Yang1 Author Orcid Image ;   Daniel Hatch1 Author Orcid Image ;   Matthew J Crowley2, 3 Author Orcid Image ;   Allison A Lewinski2 Author Orcid Image ;   Jacqueline Vaughn1 Author Orcid Image ;   Dori Steinberg1 Author Orcid Image ;   Allison Vorderstrasse4 Author Orcid Image ;   Meilin Jiang5 Author Orcid Image ;   Ryan J Shaw1, 6 Author Orcid Image
Article Authors Cited by (17) Tweetations (12) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.