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

Viewpoints on Diabetes Technology and Innovation (7) Web-based and Mobile Health Interventions (3297) Depression and Mood Disorders; Suicide Prevention (1363) Diabetes Health Services and System Innovations (117)

Published on in Vol 2, No 1 (2017): Jan-Jun

The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology

The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology

The Case for Jointly Targeting Diabetes and Depression Among Vulnerable Patients Using Digital Technology

Authors of this article:

Adrian Aguilera1, 2 Author Orcid Image ;   Courtney Rees Lyles3 Author Orcid Image
Article Authors Cited by (6) Tweetations (6) Metrics

Journals

  1. Lie S, Karlsen B, Oord E, Graue M, Oftedal B. Dropout From an eHealth Intervention for Adults With Type 2 Diabetes: A Qualitative Study. Journal of Medical Internet Research 2017;19(5):e187 View
  2. Franco P, Gallardo A, Urtubey X. Web-Based Interventions for Depression in Individuals with Diabetes: Review and Discussion. JMIR Diabetes 2018;3(3):e13 View
  3. Sarda A, Munuswamy S, Sarda S, Subramanian V. Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study. JMIR mHealth and uHealth 2019;7(1):e11041 View
  4. Sheon A, Bolen S, Callahan B, Shick S, Perzynski A. Addressing Disparities in Diabetes Management Through Novel Approaches to Encourage Technology Adoption and Use. JMIR Diabetes 2017;2(2):e16 View
  5. Nouri S, Avila-Garcia P, Cemballi A, Sarkar U, Aguilera A, Lyles C. 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 View
  6. Pathak L, Aguilera A, Williams J, Lyles C, Hernandez-Ramos R, Miramontes J, Cemballi A, Figueroa C. Developing Messaging Content for a Physical Activity Smartphone App Tailored to Low-Income Patients: User-Centered Design and Crowdsourcing Approach. JMIR mHealth and uHealth 2021;9(5):e21177 View