A Smartphone App-Based Lifestyle Change Program for Prediabetes (D'LITE Study) in a Multiethnic Asian Population: A Randomized Controlled Trial

Abstract

IntroductionLandmark studies have established that lifestyle interventions focused on weight loss, diet modification and physical activity can prevent diabetes progression. However, the effectiveness of mobile health application among Asians with prediabetes remains largely unexamined. We aimed to assess whether a smartphone app-based lifestyle intervention program would lead to weight loss, normoglycemia and improved metabolic indices in a multiethnic Asian population with prediabetes.Research Design and MethodsThis multicentre prediabetes RCT is part of the Diabetes Lifestyle Intervention using Technology Empowerment (D'LITE) trial. Adults (n = 148) with prediabetes and BMI ≥ 23 kg/m2 were randomly allocated either to the intervention group (n = 72) empowered by self-monitoring features of the Nutritionist Buddy Diabetes app with in-app dietitian coaching for 6 months, or the control group (n = 76) receiving standard diet counseling at baseline. Primary outcome was defined as change in body weight at 6 months, while secondary outcomes included glycemic control and other metabolic indices analyzed using Generalized Linear Mixed Model analysis with intention-to-treat approach.ResultsIntervention group achieved a significantly greater weight loss of 4.2 vs. 1.3 kg [mean difference of −3.1 kg (95% CI −4.5 to −1.7), p < 0.001], and a 4.3-fold increased likelihood of achieving ≥ 5% weight loss, as compared to the control group at 6 months. The likelihood of achieving normoglycemia (defined as HbA1c < 5.7%) was 2.1 times higher in intervention group than in the control group (p < 0.018). Changes to blood pressure, total and LDL cholesterol were not statistically significant.ConclusionAn app-based lifestyle program led to clinically significant weight loss and improved glycemia, and can potentially augment current standard care in the prevention of diabetes among an Asian multiethnic population.Clinical Trial Registrationanzctr.org.au, identifier: ACTRN12617001112358.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

“…This systematic review was comprised of 19 studies with randomized trial designs [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 ] and 6 studies [ 55 , 56 , 57 , 58 , 59 , 60 ] with other types of trial designs (pragmatic trial and quasi-experimental). The features of the studies are detailed in Table 1 .…”

“…A total of thirteen studies [ 36 , 39 , 40 , 41 , 43 , 44 , 46 , 48 , 50 , 51 , 53 , 57 , 58 ] only used hbA1c as a diagnostic tool for prediabetes. Research conducted by Ramachandran [ 36 ] only used an oral glucose tolerance test (OGTT) as a diagnostic standard for prediabetes.…”

Association Between Mobile Health App Engagement and Weight Loss and Glycemic Control in Adults With Type 2 Diabetes and Prediabetes (D’LITE Study): Prospective Cohort Study

“…This prospective cohort study included prespecified subgroup analysis of all participants from the intervention arm of the D’LITE study (N=171) who were assigned the Nutritionist Buddy Diabetes (nBuddy Diabetes) app [ 11 , 12 ]. A full description of the D’LITE study and the intervention details for both diabetes and prediabetes groups have previously been published [ 11 , 12 ].…”

“…The primary Diabetes Lifestyle Intervention using Technology Empowerment (D’LITE) study has shown that both participants with prediabetes or diabetes achieved significant weight loss with a mean difference of −3.1 kg (95% CI −4.5 to −1.7; P <.001) and −2.4 kg (95% CI −3.5 to −1.3; P <.001) at 6 months, respectively, when compared with the control group [ 11 , 12 ]. The participants with prediabetes were 2.1 times likely to achieve normoglycemia (defined as HbA 1c <5.7%) than in the control group ( P <.018).…”

Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach

“…Mobile health apps, designed to support and reinforce health behaviors or to reduce risk behaviors, are among the most commonly downloaded apps, since they offer a novel and effective way for health professionals to engage users in the promotion and adoption of new behaviors (11,12). Several mobile apps have been designed and developed specifically to increase physical activity levels (13,14), encourage weight loss through personal coaching (15,16), boost healthy food choices (17)(18)(19)(20), reduce sedentary behavior (21,22), assess and track dietary intake (23), assess psychological distress (e.g., anxiety, depression) (24), support smoke cessation (25), and reduce alcohol consumption (26). Moreover, mobile apps developed based on behavior change models and theories, including the integration of different behavior change strategies (e.g., cognitive behavioral therapy, goal setting, real time feedback), are considered the most effective in securing behavior change in their users (27,28).…”