How Do Mobile Phone Diabetes Programs Drive Behavior Change?

Diabetes Educ. 2014 Oct 2. pii: 0145721714551992. [Epub ahead of print]

How Do Mobile Phone Diabetes Programs Drive Behavior Change? Evidence From a Mixed Methods Observational Cohort Study.

Nundy S1, Mishra A1, Hogan P1, Lee SM1, Solomon MC1, Peek ME2.

Author information

• 1Department of Medicine, University of Chicago Medical Center, Chicago, Illinois (Dr Nundy, Ms Mishra, Mr Hogan, Dr Peek)Chicago Center for Diabetes Translation Research, Chicago, Illinois (Dr Nundy, Dr Peek)Department of Health Studies, University of Chicago, Chicago, Illinois (Dr Lee)Department of Pediatrics, University of Illinois at Chicago, Chicago, Illinois (Ms Solomon)Center for Health and Social Sciences, University of Chicago, Chicago, Illinois (Dr Peek)Center for the Study of Race, Politics and Culture, University of Chicago, Chicago, Illinois (Dr Peek).
• 2Department of Medicine, University of Chicago Medical Center, Chicago, Illinois (Dr Nundy, Ms Mishra, Mr Hogan, Dr Peek)Chicago Center for Diabetes Translation Research, Chicago, Illinois (Dr Nundy, Dr Peek)Department of Health Studies, University of Chicago, Chicago, Illinois (Dr Lee)Department of Pediatrics, University of Illinois at Chicago, Chicago, Illinois (Ms Solomon)Center for Health and Social Sciences, University of Chicago, Chicago, Illinois (Dr Peek)Center for the Study of Race, Politics and Culture, University of Chicago, Chicago, Illinois (Dr Peek) mpeek@medicine.bsd.uchicago.edu.

Abstract

PURPOSE:

The purpose of this study was to investigate the behavioral effects of a theory-driven, mobile phone-based intervention that combines automated text messaging and remote nursing, using an automated, interactive text messaging system.

METHODS:

This was a mixed methods observational cohort study. Study participants were members of the University of Chicago Health Plan (UCHP) who largely reside in a working-class, urban African American community. Surveys were conducted at baseline, 3 months (mid-intervention), and 6 months (postintervention) to test the hypothesis that the intervention would be associated with improvements in self-efficacy, social support, health beliefs, and self-care. In addition, in-depth individual interviews were conducted with 14 participants and then analyzed using the constant comparative method to identify new behavioral constructs affected by the intervention.

RESULTS:

The intervention was associated with improvements in 5 of 6 domains of self-care (medication taking, glucose monitoring, foot care, exercise, and healthy eating) and improvements in 1 or more measures of self-efficacy, social support, and health beliefs (perceived control). Qualitatively, participants reported that knowledge, attitudes, and ownership were also affected by the program. Together these findings were used to construct a new behavioral model.

CONCLUSIONS:

This study's findings challenge the prevailing assumption that mobile phones largely affect behavior change through reminders and support the idea that behaviorally driven mobile health interventions can address multiple behavioral pathways associated with sustained behavior change.