Diabetes imposes a significant economic burden on society in the form of higher medical costs, lost productivity, premature mortality, and additional costs in the form of disability-adjusted life years [1]. Diabetes is largely attributed to modifiable lifestyle factors such as diet, physical activity, and sleep [2]. There is a need for those at risk of developing type 2 diabetes to engage in health-promoting behaviors to reduce their risk. Specifically, individuals can utilize lifestyle modification programs to reduce weight and increase physical activity [3]. Several published studies suggest that smartphones can deliver effective behavioral interventions among various age groups and for different diseases [4-6]. The purpose of this study was to investigate the effects of a novel digital therapeutic diabetes prevention program (Transform) on weight loss, body mass index (BMI), exercise frequency, and work absenteeism.

In 2017, the International Diabetes Federation (IDF) [7] estimated that, worldwide, approximately 425 million adults, aged 20-79 years, were living with diabetes. By 2045, this number is expected to increase to 629 million. In the United States, it is estimated that more than 30 million adults are living with diabetes [7]. Lin et al [8] projected that the number of adults diagnosed with diabetes in the United States would significantly increase to almost 40 million in 2030 and to more than 60 million in 2060. Based on 79,535 death certificates, diabetes was the seventh leading cause of death in the United States in 2015 [9].

Diabetes imposes a significant economic burden on society. The American Diabetes Association estimated that the total cost of diagnosed diabetes has increased to US $327 billion in 2017 from US $245 billion in 2012 in the United States alone [10]. Indirect costs linked to diabetes in the United States include increased absenteeism (US $3.3 billion) and reduced productivity while at work (US $26.9 billion) [10].

Diabetes is a complex, chronic illness requiring ongoing medical care. It is managed by multifactorial risk-reduction strategies that go beyond glycemic control. Diabetes is caused by several factors including modifiable health behaviors and, in many cases, it is preventable. At-risk individuals can use lifestyle modification programs to reduce weight and increase physical activity [3]. A recent systematic review concluded that lifestyle modifications among individuals with prediabetes reduced the incidence of diabetes development more than standard treatment [11].

Blue Mesa Health, a global digital health company based in New York City, adapted the CDC’s DPP to a digital model to enable a scalable, convenient, and flexible delivery of the evidence-based program. Transform integrates interactive mobile computing (eg, smartphone app), wearable tracking devices (eg, activity tracker), remote health monitoring hardware (eg, digital scale), and professional health coaches to effectively address the complex factors that impact behavior. Transform is a 12-month intervention that uses the same two-phase program structure as the CDC’s program: a 16-week high-frequency core intervention followed by 8 months of complimentary maintenance programming to support the new health behaviors. The program components are described in detail below and outlined in Figure 1.

In this study, we aimed to examine the effectiveness of a novel digital DPP (Transform) on weight, BMI, exercise frequency, and work absenteeism in a sample of adults with prediabetes.

The study is a secondary analysis of data collected via the Transform DPP. Deidentified data that were collected at baseline and 4 months were analyzed. Transform participants were recruited via a marketing channel partner. Participants completed an online eligibility survey that was adapted from the CDC prediabetes screening survey [23]. Eligible participants completed a baseline questionnaire and a 4-month follow-up questionnaire. The questionnaires were adapted from the World Health Organization Health and Work Performance Questionnaire [29] and the National Health and Nutrition Examination Survey [30]. The end of the fourth month was a relevant time point because it marked the end of the first phase (core) of the 12-month DPP.

Participants were eligible for the study if they met the following inclusion criteria: score≥9 on the online survey adapted from the CDC prediabetes screening tool [23] or indication of prediabetes diagnosis through a recent blood test (within the last 12 months); BMI≥25 kg/m² or ≥23 kg/m² if self-identified as Asian; age≥18 years; indication of readiness to change based on additional survey questions [31]; and completion of the 4-month follow-up survey and record of body weight during week 16 of the Transform program.

Participants were excluded from the study if they had a BMI<25 kg/m²; were <18 years of age; failed to meet at least one of the following criteria: (a) screened as high-risk according to the American Diabetes Association [32] or CDC prediabetes screening tool [23] or (b) self-reported as positive for prediabetes, according to a blood test within the last 12 months; or did not consent for their data to be used for research.

Once the participants were accepted into the program, they completed an online baseline health behavior survey to assess their current physical activity, diet, sleep, work performance, and general health status. Participants received a series of onboarding emails and were mailed packages to introduce them to the program. The packages included a wireless scale by BodyTrace, Inc, and a wearable activity tracker by Fitbit, Inc (model: Flex 2). Weight was measured by the wireless scale and height was self-reported; weight and height were both used to calculate BMI. After 4 months, participants completed an online follow-up survey. Four outcomes were assessed: weight, BMI, exercise frequency, and work absenteeism. Work absenteeism was adapted from the World Health Organization Health and Work Performance Questionnaire [29]. Subjects answered the following question: “Think of your work experience over the past 4 weeks (28 days). In the space provided below, type the number of entire workdays missed because of problems with your physical or mental health.” Each measure was calculated as the difference between scores at baseline and 4 months. Participants did not receive an incentive to complete the follow-up survey.

Solutions Institutional Review Board, an independent ethics review company (Little Rock, AR and Yarnell, AZ), reviewed and approved this study.

Descriptive statistics (mean and SD for continuous variables; frequency and percentage for categorical variables) were used to describe participant demographics. Four paired-samples t tests were used to compare the baseline mean BMI, exercise frequency, and work absenteeism with the means at the 4-month follow-up. Analyses were conducted using IBM SPSS Statistics, version 23 (IBM Corp, NY). A P value <.05 was considered statistically significant for all tests.

Of the 1183 individuals who enrolled in the Transform program and completed the baseline survey, 27 participants did not give consent for their data to be used for research purposes. From the participants’ interaction with their coach data, 10.5% (124/1183) of the participants were lost to follow-up. Approximately 23% (n=273) of the participants completed the online follow-up survey at 4 months. This response rate is consistent with other studies using online surveys [33].

The current analysis included all participants that completed the 4-month follow-up survey. A total of 273 subjects were included in the analysis. Of these, 70.3% were female. The mean age of the sample was 54.01 (SD 11.33) years. Participants were primarily white (74%; Table 1).

This secondary analysis demonstrates that adults with prediabetes who used a novel and individualized digital diabetes prevention program had significant reductions in BMI, weight, and work absenteeism. They also demonstrated a significant increase in exercise frequency at the end of the 4-month study period. This strongly suggests that the Transform digital DPP is an effective tool to drive positive changes in lifestyle behaviors associated with prevention of diabetes.

The Finnish National Diabetes Prevention Program implemented its DPP program in-person through clinics [34]. They were able to achieve an average weight loss of 1.2% among 919 participants, which is less than the weight loss recorded in our study. Although this study supports the findings of other digital interventions targeting diabetic patients [35,36], the current study utilizes a comprehensive digital DPP targeting adults with prediabetes.

Among participants with prediabetes using the Transform DPP, the mean weight declined by 6.5%. This amount of weight loss can be interpreted as a clinically significant reduction in diabetes risk. According to Knowler et al, 5% to 7% of body weight loss reduces the risk of developing type 2 diabetes by 58% in adults with prediabetes and by 71% for people over 60 years old [21]. Additionally, Hamman et al [22] stated that for every kilogram of weight loss, there was a 16% reduction in diabetes risk. Colditz et al [37] noted that loss of 1 kg of weight was associated with a 10% reduction in diabetes risk.

This study was observational and not experimental. It lacks a control group, which may help in addressing possible confounders. This study does not investigate the individual contribution of each program component on the outcome variables. Another limitation was the reliance on self-reports of exercise frequency and work absenteeism. Bias in self-reported physical activity can be avoided in the future by using data from an activity tracker.

The main strength of this study is that it is a secondary analysis of real-world implementation of the intervention. Participants did not receive an incentive to complete the follow-up survey. A benefit of real-world evidence is the generalizability of the outcomes.

Data on outcome sustainability after 4 months were not collected in this analysis. Future studies should examine 12-24 months of follow-up data to address the sustainability of behavior change following the intervention. Future research should include an experimental study to assess possible confounding variables including ethnic origin, education, socioeconomic factors, gender, and other factors related to the outcomes such as reduction in hemoglobin A1c levels. Future research would benefit from the inclusion of an economic analysis of the impact of the Transform DPP and should consider both the direct and indirect costs.

Transform, a digital DPP adapted from the National Diabetes Prevention Program, was developed to prevent or delay the onset of type 2 diabetes in adults with prediabetes. Transform incorporates interactive mobile computing, remote monitoring, health coaching, evidence-based curriculum, behavior tracking tools, health coaching, and online peer support to prevent or delay the onset of type 2 diabetes. We observed that the Transform DPP significantly reduces BMI, body weight, and work absenteeism and increases exercise frequency. The study findings highlight the effectiveness of the Transform program.