Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: May 5, 2020
Date Accepted: Oct 2, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Mobile-based Interventions for Dietary and Exercise Behavior Change in Individuals at High-risk of Type 2 Diabetes Mellitus: Randomized Controlled Trial
ABSTRACT
Background:
The positive effects of intensive lifestyle modification to prevent type 2 diabetes mellitus (T2DM) have been demonstrated, yet the efficiency and effectiveness remain to be improved. Widespread use of mobile-based interventions has made it a promising health management assistant especially for chronic diseases. Furthermore, advanced behavioral change techniques like social media applets have enhanced the driving power of behavior change intention.
Objective:
To investigate the effect of mobile-based interventions on lifestyle change for T2DM prevention, we developed a mobile-based intervention applet, DHhealhBar, to facilitate dietary and exercise behavior change recording as well as health information delivery via social media. Based on Transtheoretical Model (TTM), we divided the process of behavior change into five stages: precontemplation, contemplation, preparation, action, and maintenance, meanwhile evaluate the intervention effects across the stages.
Methods:
This 6-month, paralleled, 2-group randomized controlled trial (RCT) included 76 participants in per-protocol analysis. Participants were randomized in (1) intervention group (n=36) to receive educational content via DHealthBar, or (2) control group (n=40) to learn the advice on lifestyle modification from handbook. Participants completed online self-administration assessments at three time points: baseline, month 3 and month 6. The study assessed (1) dietary behavior, including total calorie intake per day, three major nutrients intake (i.e., fat, carbohydrate and protein) per and their proportion for energy support, (2) exercise behavior, including the metabolic equivalent of task (MET) value of physical activities at low, medium and high levels and their total amount per week, (3) the stage of dietary and exercise behavior change, (4) and anthropometric measurements, including body mass index (BMI) and waist circumstance at each time point.
Results:
In this study, 39.5% (79/200) individuals were randomized, and 96.2% (76/79) completed the 6-month follow-up visit. Attrition rates did not differ significantly between two groups (χ²=0.004, P=.61). Equivalency was found on demographic characteristics and outcome measurements according to baseline assessment (P>.05). After 6-month DHealthBar intervention, reduction on mean levels of calorie and nutrients intake (P<.001) and enhancement of exercise behavior at all levels (P<.05) was reported statistically significant in the intervention group, but no statistical significance was demonstrated in the control group; meanwhile, individuals in the intervention group were significantly more likely to be at higher stage of dietary and exercise behavior modification (OR=32.65, 95%CI:4.58-232.60, P=.0007; OR=17.91, 95CI%:3.17-101.30, P=.001).
Conclusions:
DHealthBar was feasible and showed initial evidence of effectiveness in improving the dietary and exercise behaviors among high-risk individuals for diabetes, as well as allowed the enhancement of stage of behavior change. Future work would focus on identifying the effective components of intervention technologies contained in social media or behavior theory, which may contribute to the development of personalized health management. Furthermore, digital behavior trackers warrant extension in the ability to accurately capture the real-world data for objective and reliable assessments. Clinical Trial: Chictr.org.cn ChiCTR2000032323; http://www.chictr.org.cn/edit.aspx?pid=51946&htm=4
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