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

Overview
Journal JMIR Diabetes
Specialty Endocrinology
Date 2018 Oct 7
PMID 30291080
Citations 6
Authors
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Abstract

It is well publicized that mobile and digital technologies hold great promise to improve health outcomes among patients with chronic illnesses such as diabetes. However, there is growing concern that digital health investments (both from federal research dollars and private venture investments) have not yet resulted in tangible health improvements. We see three major reasons for this limited real-world impact on health outcomes: (1) lack of solutions relevant for patients with multiple comorbidities or conditions, (2) lack of diverse patient populations involved in the design and early testing of products, and (3) inability to leverage existing clinical workflows to improve both patient enrollment and engagement in technology use. We discuss each of these in depth, followed by new research directions to increase effectiveness in this field.

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PMID: 34009130 PMC: 8173396. DOI: 10.2196/21177.


Assessing Mobile Phone Digital Literacy and Engagement in User-Centered Design in a Diverse, Safety-Net Population: Mixed Methods Study.

Nouri S, Avila-Garcia P, Cemballi A, Sarkar U, Aguilera A, Lyles C JMIR Mhealth Uhealth. 2019; 7(8):e14250.

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Using Passive Smartphone Sensing for Improved Risk Stratification of Patients With Depression and Diabetes: Cross-Sectional Observational Study.

Sarda A, Munuswamy S, Sarda S, Subramanian V JMIR Mhealth Uhealth. 2019; 7(1):e11041.

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Addressing Disparities in Diabetes Management Through Novel Approaches to Encourage Technology Adoption and Use.

Sheon A, Bolen S, Callahan B, Shick S, Perzynski A JMIR Diabetes. 2018; 2(2):e16.

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Web-Based Interventions for Depression in Individuals with Diabetes: Review and Discussion.

Franco P, Gallardo A, Urtubey X JMIR Diabetes. 2018; 3(3):e13.

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References
1.
Sigal R, Kenny G, Wasserman D, Castaneda-Sceppa C, White R . Physical activity/exercise and type 2 diabetes: a consensus statement from the American Diabetes Association. Diabetes Care. 2006; 29(6):1433-8. DOI: 10.2337/dc06-9910. View

2.
Aguilera A, Schueller S, Leykin Y . Daily mood ratings via text message as a proxy for clinic based depression assessment. J Affect Disord. 2015; 175:471-4. PMC: 4352380. DOI: 10.1016/j.jad.2015.01.033. View

3.
Lyles C, Schillinger D, Sarkar U . Connecting the Dots: Health Information Technology Expansion and Health Disparities. PLoS Med. 2015; 12(7):e1001852. PMC: 4501812. DOI: 10.1371/journal.pmed.1001852. View

4.
Glynn L, Hayes P, Casey M, Glynn F, Alvarez-Iglesias A, Newell J . Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial. Br J Gen Pract. 2014; 64(624):e384-91. PMC: 4073723. DOI: 10.3399/bjgp14X680461. View

5.
Strawbridge W, Deleger S, Roberts R, Kaplan G . Physical activity reduces the risk of subsequent depression for older adults. Am J Epidemiol. 2002; 156(4):328-34. DOI: 10.1093/aje/kwf047. View