JMIR Publications

ABSTRACT

Background:

Introduction: Type 2 diabetes is a major public health concern in older adults. Healthy lifestyles such as engaging in physical activity and adopting healthy eating are effective strategies in diabetes self-management for controlling glucose and improving physical function. Increasing evidence shows that health technologies could promote healthy lifestyles for type 2 diabetes management. However, few such studies have been conducted in older adults. Given the low digital literacy among older adults, this study assessed the feasibility of using health technology to self-monitor lifestyles for diabetes management, test the preliminary efficacy of lifestyle self-monitoring on health outcomes in older adults with type 2 diabetes, and Explore participants’ experiences with health technologies and identify strategies needed to support lifestyle changes for diabetes management.

Objective:

Given the low digital literacy among older adults, this study aimed to assess the feasibility of using health technology to self-monitor lifestyles for diabetes management, test the preliminary efficacy of lifestyle self-monitoring on health outcomes in older adults with type 2 diabetes, and explore participants’ experiences with health technologies and identify strategies needed to support lifestyle changes for diabetes management.

Methods:

This 12-week pilot study used a pre- and post-test design. Fitbit fitness trackers paired with smart phone applications were used to track physical activity and food intake over 12 weeks in 15 overweight/obese older adults with type 2 diabetes (Mean age=70.5±4.8). Baseline and 12-week health outcomes (e.g., HbA1c and physical function) were compared using paired t-tests; effect sizes were calculated using Cohen’s D. The associations with HbA1c and physical function (assessed by the Short Physical Performance Battery) of percentage of days with tracked steps (PDWTS), average daily steps, and percentage of days with food logs (PDWFL) were examined using Pearson Correlation analysis. Semi-structured qualitative interviews were conducted with participants at the end of the study. Facilitators and barriers of self-monitoring and lifestyle behaviors were collected and analyzed using thematic analysis.

Results:

HbA1c decreased significantly from baseline to 12-weeks (effect size=-0.49, p=0.036). Weight (effect size=-0.83), BMI (effect size=-0.61), and physical function (effect size=0.20) trended toward improvement (p>0.05). PDWFL showed a significant inverse correlation with HbA1c (r=-0.53, P<0.05) at 12-week follow-up. Qualitative data revealed that barriers and facilitators of self-monitoring of lifestyle and diabetes management through lifestyle modifications exist across multiple levels, including the individual, interpersonal, organizational/community, and societal levels in older adults with type 2 diabetes. Factors at one level could influence those at another level. For example, health technology not tailored to older adults may present challenges due to limited technological proficiency, while support from others can help mitigate these difficulties.

Conclusions:

Technology-assisted self-monitoring of lifestyle behaviors may support glycemic control and related health outcomes in older adults with type 2 diabetes. In designing future diabetes management interventions, it is essential to address interconnected factors at multiple levels that address older adults’ unique needs and capacities in diabetes self-management.