4.6 Article

A Behavioral Lifestyle Intervention Enhanced With Multiple-Behavior Self-Monitoring Using Mobile and Connected Tools for Underserved Individuals With Type 2 Diabetes and Comorbid Overweight or Obesity: Pilot Comparative Effectiveness Trial

Journal

JMIR MHEALTH AND UHEALTH
Volume 6, Issue 4, Pages -

Publisher

JMIR PUBLICATIONS, INC
DOI: 10.2196/mhealth.4478

Keywords

self-monitoring; diabetes; obesity; mobile health; behavior change; connected health; patient-generated health data; lifestyle; patient engagement; comparative effectiveness trial

Funding

  1. PARTNERS Awards at the Cizik School of Nursing at UTHealth
  2. Robert Wood Johnson Foundation Nurse Faculty Scholars Program
  3. National Institutes of Health's Clinical and Translational Science Award [UL1 TR000371]

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Background: Self-monitoring is a cornerstone of behavioral lifestyle interventions for obesity and type 2 diabetes mellitus. Mobile technology has the potential to improve adherence to self-monitoring and patient outcomes. However, no study has tested the use of a smartphone to facilitate self-monitoring in overweight or obese adults with type 2 diabetes mellitus living in the underserved community. Objective: The aim of this study was to examine the feasibility of and compare preliminary efficacy of a behavioral lifestyle intervention using smartphone- or paper-based self-monitoring of multiple behaviors on weight loss and glycemic control in a sample of overweight or obese adults with type 2 diabetes mellitus living in underserved communities. Methods: We conducted a randomized controlled trial to examine the feasibility and preliminary efficacy of a behavioral lifestyle intervention. Overweight or obese patients with type 2 diabetes mellitus were recruited from an underserved minority community health center in Houston, Texas. They were randomly assigned to one of the three groups: (1) behavior intervention with smartphone-based self-monitoring, (2) behavior intervention with paper diary-based self-monitoring, and (3) usual care group. Both the mobile and paper groups received a total of 11 face-to-face group sessions in a 6-month intervention. The mobile group received an Android-based smartphone with 2 apps loaded to help them record their diet, physical activity, weight, and blood glucose, along with a connected glucometer, whereas the paper group used paper diaries for these recordings. Primary outcomes of the study included percentage weight loss and glycated hemoglobin (HbA(1c)) changes over 6 months. Results: A total of 26 patients were enrolled: 11 in the mobile group, 9 in the paper group, and 6 in the control group. We had 92% (24/26) retention rate at 6 months. The sample is predominantly African Americans with an average age of 56.4 years and body mass index of 38.1. Participants lost an average of 2.73% (mobile group) and 0.13% (paper group) weight at 6 months, whereas the control group had an average 0.49% weight gain. Their HbA(1c) changed from 8% to 7 % in mobile group, 10% to 9% in paper group, and maintained at 9% for the control group. We found a significant difference on HbA(1c) at 6 months among the 3 groups (P=.01). We did not find statistical group significance on percentage weight loss (P=.20) and HbA(1c) changes (P=.44) overtime; however, we found a large effect size of 0.40 for weight loss and a medium effect size of 0.28 for glycemic control. Conclusions: Delivering a simplified behavioral lifestyle intervention using mobile health-based self-monitoring in an underserved community is feasible and acceptable and shows higher preliminary efficacy, as compared with paper-based self-monitoring. A full-scale randomized controlled trial is needed to confirm the findings in this pilot study.

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