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

Jing Wang, Chunyan Cai, Nikhil Padhye, Philip Orlander, Mohammad Zare

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

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 (HbA1c) 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 HbA1c 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 HbA1c at 6 months among the 3 groups (P=.01). We did not find statistical group significance on percentage weight loss (P=.20) and HbA1c 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.

Original languageEnglish (US)
Article numbere92
JournalJMIR mHealth and uHealth
Volume6
Issue number4
DOIs
StatePublished - Apr 2018

Keywords

  • Behavior change
  • Comparative effectiveness trial
  • Connected health
  • Diabetes
  • Lifestyle
  • Mobile health
  • Obesity
  • Patient engagement
  • Patient-generated health data
  • Self-monitoring

ASJC Scopus subject areas

  • Health Informatics

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