A Novel Diabetes Prevention Intervention Using a Mobile App

Abstract

Introduction Mobile phone technology may be a cost-effective and convenient way to deliver proven weight-loss interventions and thereby prevent or delay onset of type 2 diabetes. The purpose of this study was to examine the feasibility and efficacy of a diabetes prevention intervention combined with a mobile app and pedometer in English-speaking overweight adults at risk for type 2 diabetes. Design RCT. Participants Participants included 61 overweight adults with a mean age (SD) of 55.2 (9.0) years. Seventy-seven percent were women, 48% were racial/ethnic minorities, and baseline BMI was 33.3 (6.0). Intervention The curriculum was adapted from the Diabetes Prevention Program, with the frequency of in-person sessions reduced from 16 to six sessions and group exercise sessions replaced by a home-based exercise program. A study-developed mobile phone app and pedometer augmented the intervention and provided self-monitoring tools. Main outcome measure Weight loss. Results Data were collected in 2012 and 2013 and were analyzed in 2014. In intention-to-treat analyses, the intervention group (n=30) lost an average of 6.2 (5.9) kg (−6.8% [5.7%]) between baseline and 5-month follow-up compared to the control group’s (n=31) gain of 0.3 (3.0) kg (0.3% [5.7%]) (p<0.001). The intervention group’s steps per day increased by 2,551 (4,712) compared to the control group’s decrease of 734 (3,308) steps per day (p<0.001). In comparison, the intervention group had greater reductions in hip circumference (p<0.001); blood pressure (p<0.05); and intake of saturated fat (p=0.007) and sugar-sweetened beverages (p=0.02). The intervention had no significant effect on fasting lipid or glucose levels. Conclusions The significant weight loss resulting from this modified combined mobile app and pedometer intervention for overweight adults warrants further investigation in a larger trial.

mHealth Physical Activity Intervention: A Randomized Pilot Study in Physically Inactive Pregnant Women

“…Second, due to their physically inactive lifestyle prior to pregnancy, the goal for daily steps and the pace to achieve the goal were cautiously set, based on prior PA intervention studies in pregnant women. For this study, 8500 steps/day as a final goal and a weekly increase of 10 % from baseline steps were used, in contrast to the daily goal of 10,000–12,000 steps and 20 % used for other populations, including physically inactive women [25] and pre-diabetic populations [26]. In addition, the active control condition, including a wearable activity monitor and the same final goal steps as the intervention group, may itself have had substantial effects, although our results suggest that this effect may not be long-lasting.…”

The Effectiveness and Cost of Lifestyle Interventions Including Nutrition Education for Diabetes Prevention: A Systematic Review and Meta-Analysis

“…Technology-based approaches also have the potential advantage of reducing personnel resource demand, and can overcome transportation barriers to reach geographically disparate population groups. 15 Therefore, there is a need to investigate the relative effectiveness of technology-based interventions, compared to traditional in-person interventions. Having these data available could inform decision-making related to organizational selection, adaptation, and implementation of diabetes preventions programs.…”

A Novel Approach for Fully Automated, Personalized Health Coaching for Adults with Prediabetes: Pilot Clinical Trial (Preprint)

“…A smartphone/web-based DPP (Alive-PD) that included tailored goal setting, weekly tracking, human-based phone coaching, and twice-weekly DPP curriculum achieved A1C reductions of 0.26% and 3.3 kg weight loss at 6 months [14]. Another intervention that included in-person DPP curriculum sessions and a mobile app for selfmonitoring of weight, activity, and diet resulted in 6.2 kg weight loss at 5 months, but failed to demonstrate any significant change in glycemic measures [15]. A hybrid program combining human coaching and digital tools, Noom Coach, (Noom, Inc., New York) demonstrated significant weight loss but did not report glycemic data [16].…”

“…While these have shown promise for diabetes prevention, most of these programs have required either active learning on the part of the user [14] (e.g. on-line curriculum), in-person training [15], or have a major component of human coaching [16,17], which limits scalability and longterm adherence, as interventions that rely on human coaching require substantial human resources and professional training as well as sustained commitment on the part of participants.…”