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Digital therapeutics are evidence-based behavioral treatments delivered online that can increase accessibility and effectiveness of health care. However, few studies have examined long-term clinical outcomes of digital therapeutics.
The objective of this study was to conduct a 2-year follow-up on participants in the Internet-based
A quasi-experimental research design was used, including a single-arm pre- and post-intervention assessment of outcomes. Participants underwent a 16-week weight loss intervention and an ongoing weight maintenance intervention. As part of the program, participants received a wireless scale, which was used to collect body weight data on an ongoing basis. Participants also received A1c test kits at baseline, 0.5 year, 1 year, and 2-year time points.
Participants previously diagnosed with prediabetes (n=220) were originally enrolled in the pilot study. A subset of participants (n=187) met Centers for Disease Control and Prevention (CDC) criteria for starting the program (starters), and a further subset (n=155) met CDC criteria for completing the program (completers) and were both included in analyses. Program starters lost an average of 4.7% (SD 0.4) of baseline body weight after 1 year and 4.2% (SD 0.8) after 2 years, and reduced A1c by mean 0.38% (SD 0.07) after 1 year and 0.43% (SD 0.08) after 2 years. Program completers lost mean 4.9% (SD 0.5) of baseline body weight after 1 year and 4.3% (SD 0.8) after 2 years, and reduced A1c by 0.40% (SD 0.07) after 1 year and 0.46% (SD 0.08) after 2 years. For both groups, neither 2-year weight loss nor A1c results were significantly different from 1-year results.
Users of the
Prediabetes, the clinical precursor to type 2 diabetes, continues to grow to epidemic levels. Recent estimates by the Centers for Disease Control and Prevention (CDC) indicate that prevalence increased 8% in the last decade—from 29% in 1999-2002 to 37% in 2009-2012—amounting to 86 million Americans over age 20 with prediabetes [
One of the most established digital therapeutics is
Previous published research showed that
Furthermore, a critique of DPP studies by Kahn and Davidson noted that weight loss results of DPP translations have often been low (a meta-analysis of 22 studies showing 2.4% weight loss at 1 year) [
Thus, the current study seeks to make an original contribution to the scientific literature by addressing such points through investigating the long-term outcomes and sustainability of an Internet-based DPP.
A quasi-experimental research design was used, including a single-arm pre- and post-intervention assessment of body weight, A1c, and program engagement outcomes [
Patients were recruited via craigslist advertisements seeking participants for an Internet-based diabetes prevention program. Patients were screened for a self-reported clinical diagnosis of prediabetes within the past year and meeting CDC DPRP eligibility criteria: 18 years of age or older, have a body mass index (BMI) of ≥24 kg/m2 (≥22 kg/m2 if Asian), and able to engage in light physical activity [
Eligible participants completed an online account set-up process, in which they provided consent and completed health and demographic questionnaires, and then enrolled in the
A full description of the program components has been previously published [
Prevent starts with a 16-week “Core” curriculum focusing on weight loss and continues with a 36-week post-core “Sustain” curriculum focusing on weight maintenance, with this “active” intervention totaling 12 months. During this time, participants also engage with health coaching, small group discussion, and tracking of body weight/food/physical activity. After 12 months, participants continue with an ongoing intervention that is more proactive, in which they continue to have access to past curriculum, a larger
Baseline demographic and health information were collected prior to program start using an Internet-based questionnaire self-completed by the subject. Body weight, the study’s primary outcome, was measured serially in pounds using a validated, wireless-enabled scale that was mailed to participants [
A1c was measured in percent (NGSP/DCCT units) using self-administered AccuBase A1c test kits by DTI laboratories, an FDA-cleared whole blood test that uses a capillary tube blood collection method. This allows for reliable home-based data collection and valid lab testing using high-performance liquid chromatography (HPLC-IE/HPLC-BA), including abnormal hemoglobin screening [
Results were analyzed for two subgroups based on CDC DPRP standards: “program starters” were those who completed at least 4 core lessons, and “program completers” were those who completed as least 9 core lessons.
Results were analyzed using SPSS Statistics 21.0 and SAS 9.3. Baseline characteristics were compared between subgroups using chi-square tests or Fisher’s exact test for categorical variables and two-sample
Models used an autoregressive-moving-average covariance structure to statistically account for the correlation of frequently measured weight data. Repeated A1c measures were also correlated but not measured on a daily basis. Therefore a spatial power covariance structure (with time as the distance measure) was used to account for the correlation among repeated measures of A1c from the same participant.
As shown in
Participant recruitment and retention flow chart.
Baseline demographic characteristics of participants.
Characteristics | Total (N=220) | Non-starters (0-3 lessons) (n=33) | Starters (4+ lessons) (n=187) | Non-starters vs Starters, |
Non-completers (4-8 lessons) (n=32) | Completers (9+ lessons) (n=155) | Non-completers vs Completers, |
|
Age, mean (SD) | 43.6 (12.4) | 42.0 (12.6) | 43.9 (12.4) | .43a | 39.0 (9.4) | 44.9 (12.8) | .004a | |
Weight, mean (SD) | 223.1 (47.9) | 226.1 (53.5) | 222.5 (47.0) | .69a | 229.8 (45.9) | 221.0 (47.2) | .34a | |
BMI, mean (SD) | 36.6 (7.5) | 35.9 (6.6) | 36.7 (7.6) | .56a | 38.3 (7.5) | 36.4 (7.6) | .21a | |
Gender (male), n (%) | 38 (17.3) | 10 (30.3) | 28 (15.0) | .03b | 3 (9.4) | 25 (16.1) | .42c | |
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|
|
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.28b |
|
|
.89c | |
|
White | 108 (50.2) | 15 (45.5) | 93 (51.1) |
|
15 (48.4) | 78 (51.7) |
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|
Black | 63 (29.3) | 10 (30.3 | 53 (29.1) |
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11 (35.5) | 42 (27.8) |
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Hispanic | 23 (10.7) | 2 (6.1) | 21 (11.5) |
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3 (9.7) | 18 (11.9) |
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Other | 21 (9.8) | 6 (18.2) | 15 (8.2) |
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2 (6.5) | 13 (8.6) |
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|
|
|
|
.13c |
|
|
.68c | |
|
Married/live with a partner | 87 (57.6) | 9 (50.0) | 78 (58.6) |
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15 (68.2) | 63 (56.8) |
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|
Divorced/separated/widowed | 25 (16.6) | 1 (5.6) | 24 (18.1) |
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3 (13.6) | 21 (18.9) |
|
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Never married | 39 (25.8) | 8 (44.4) | 31 (23.3) |
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4 (18.2) | 27 (24.3) |
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|
|
|
|
.01b |
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|
.13b | |
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< College graduate | 72 (48.3) | 14 (77.8) | 58 (44.3) |
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13(59.1) | 45 (41.3) |
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≥ College graduate | 77 (51.7) | 4 (22.2) | 73 (55.7) |
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9 (40.9) | 64 (58.7) |
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|
|
|
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.92b |
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.52b | |
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<$50,000 | 69 (48.3) | 8 (47.1) | 61 (48.4) |
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11 (55.0) | 50 (47.2) |
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$50,000 or higher | 74 (51.8) | 9 (52.9) | 65 (51.6) |
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9 (45.0) | 56 (52.8) |
|
a
b
c
As reported in a previous publication, during the first year of the program, program starters completed an average of 13.8 and 3.2 lessons during the core and post-core phases (CDC DPRP benchmark is 9 and 3 lessons), documented body weight at 90% and 67% of weeks and months in which core and post-core lessons were completed (benchmark is 80% and 60%), and documented physical activity at 85% of weeks in which core lessons were completed (benchmark is 80%) [
Because lessons are limited to the first year, no engagement benchmarks exist beyond 1 year. However, participants continued to weigh in an average of 6.2 (SD 0.3) of 12 months and logged in an average of 3.5 (SD 0.3) of 12 months between years 1 and 2. In order to evenly compare engagement rates between years 1 and 2, the last 8 months of the year 1 (ie, the Sustain post-core period) was compared to the first 8 months of year 2.
Among program starters, 100% (187/187) had an initial baseline weight measurement, 78.6% (147/187) had at least one weight measurement between 15 and 17 weeks, 79.1% (148/187) had at least one weight measurement between 11 and 13 months, and 70.1% (131/187) had at least one weight measurement between 22 and 26 months.
Changes in body weight and A1c after 16 weeks and 1 year were reported in a previous publication and reported here alongside 2-year data in
Because A1c measurement was optional, compliance was lower. Among program starters, 75.4% (141/187) had an initial baseline A1c measurement, 36.4% (68/187) had an A1c measurement between months 6-8 (due to A1c being a lagging measurement), 55.6% (104/187) had an A1c measurement between months 12-14, and 52.9% (99/187) had an A1c measurement between months 24-28.
As shown in
Body weight and A1c of participants over time.
|
Starters (4+ lessons) | Completers (9+ lessons) | ||
Weight (lbs), mean (SE)a | A1c (%), mean (SE)a | Weight (lbs), mean (SE)a | A1c (%), mean (SE)a | |
Baseline | 221.6 (3.5) | 5.99 (0.07) | 220.2 (3.9) | 6.02 (0.08) |
16 weeks | 210.5 (3.5) | 6.02 (0.08) | 208.6 (3.9) | 6.04 (0.09) |
Year 1 | 211.3 (3.4) | 5.61 (0.08) | 209.5 (3.8) | 5.62 (0.08) |
Year 2 | 212.3 (3.5) | 5.55 (0.08) | 210.7 (3.9) | 5.56 (0.08) |
aAdjusted means from linear mixed models.
Changes in body weight and A1c of participants over time.
|
Starters (4+ lessons) | Completers (9+ lessons) | ||||||
Weight loss, % change (SE)a |
|
A1c, change (SE)a |
|
Weight loss, % change (SE)a |
|
A1c, change (SE)a |
|
|
16 weeks-Baseline | 5.0 (0.3) | <.001 | 0.03 (0.06) | .55 | 5.2 (0.3) | <.001 | 0.03 (0.06) | .62 |
Year 1-Baseline | 4.7 (0.4) | <.001 | -0.38 (0.07) | <.001 | 4.9 (0.5) | <.001 | -0.40 (0.07) | <.001 |
Year 2-Baseline | 4.2 (0.8) | <.001 | -0.43 (0.08) | <.001 | 4.3 (0.8) | <.001 | -0.46 (0.08) | <.001 |
Year 2-Year 1 | -0.5 (-0.4) | .25 | -0.06 (0.07) | .39 | -0.5 (-0.5) | .20 | -0.06 (0.07) | .38 |
aAdjusted means from linear mixed models.
Results indicate that the
Furthermore, A1c continued to show an average reduction from within the prediabetes range (5.7%-6.4%) to the normal range (<5.7%), in contrast to an expected annual rate of progression of approximately 4% from prediabetes to type 2 diabetes [
The ability of
Although
Study strengths include longitudinal collection of body weight and A1c data and statistical analysis using linear mixed models, which allow for more robust estimation over time and missing data. Furthermore, recruitment, intervention, and assessment were done exclusively remotely, in contrast to most digital health studies that require in-person orientation or follow-up assessment. This enhances the generalizability of the findings to “real-world” commercial deployments that must be done remotely.
Study limitations include a non-randomized, uncontrolled single-arm design with a self-selected sample, which precludes causal inference of the intervention to outcomes. However, this also better approximates how commercial programs enroll real-world populations. Fewer males participated in the study, but this is typical of behavioral weight loss interventions. Furthermore, 70% of program starters had weight data at year 2 and 53% had A1c data at year 2, which limits generalizability regarding outcomes on all participants. Thus, conclusions regarding weight loss and A1c reductions are limited to program starters and completers. In addition, while adherence to program behaviors (eg, lesson completion, tracking of weight and physical activity) were assessed according to CDC DPRP standards, adherence to health behaviors (eg, diet and exercise goals) were not, which limits causal inference.
Results of this study suggest that the
Body Mass Index
Centers for Disease Control and Prevention
Diabetes Prevention Program
Diabetes Prevention Recognition Program
High-Performance Liquid Chromatography
Institutional Review Board
US Preventive Services Task Force
The authors wish to acknowledge Dr Ann Albright and Dr Ed Gregg at the CDC for their support of this work, and the Diabetes Prevention Program Research Group for performing the original DPP trial, on which the
Data were collected by SCS and provided unmodified to LJ, who independently conducted data analysis and wrote the results section. ALP provided consultation and editing of the paper for accuracy.
This work was funded by Omada Health, a company that makes and owns online behavior change programs, including the