An interventional study of Digital Diabetes Prevention Program (dDPP) and Human Coach-based Diabetes Prevention Program (hDPP) in PreDiabetes, Hyperglycemia and Glucose, High Blood, sponsored by Johns Hopkins University. Completed at 2 sites in United States. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2026-11-05.
Sponsored by Johns Hopkins University · Not applicable, Interventional, and Prevention
The purpose of this research study is to compare the effectiveness of a fully automated digital diabetes prevention program to standard of care human coach-based diabetes prevention programs for promoting clinically meaningful lifestyle changes to reduce the risk of type 2 diabetes in adults with prediabetes.
After being informed about the study and potential risk, all participants giving written informed consent will undergo screening to determine eligibility for study entry. At baseline visit (month 0). Participants who meet the eligibility requirements will be randomly assigned in 1:1 ratio to human coach-based diabetes prevention program or digital diabetes prevention program. An equal number of participants will be randomly assigned to both groups (like flipping a coin).
If participants are randomly assigned to receive the human coach-based diabetes prevention program, the participants will be referred to a local Diabetes Prevention Program close to the participants' area. The Diabetes Prevention Program consists of 16 weekly sessions during months 1 to 6 and 6 sessions during months 7 to 12. These group sessions may be delivered in-person at the local program or remotely using video conferencing. During these sessions, participants will receive information about lifestyle change behaviors focusing on weight loss, physical activity, and nutrition from a trained lifestyle coach.
If participants are randomly assigned to receive the digital Diabetes Prevention Program, the participants will receive the Sweetch Digital Health Kit (Sweetch Health, Ltd.) in the mail within approximately 8-12 days of the participants' first study visit. The Sweetch digital health kit consists of a smartphone app and a digital body weight scale that is connected via Bluetooth to the app. The phone app also consists of brief Centers for Disease Control and Prevention (CDC) lessons on type 2 diabetes prevention, which participants will be encouraged to complete.
There will be a total of 3 study visits (baseline, 6 months, and 12 months), each visit includes fingerstick hemoglobin A1C measurement, weight measurement, and completion of several questionnaires. Height will be measured at the first visit. Throughout the 12-month study, participants will be asked to wear a device on the participants' wrist to measure physical activity for 7 consecutive days following the first visit and once every month thereafter.
918 studies on the registry are indexed under Prediabetic State; 232 are open to participants now.
This study's enrollment of 368 is above the median of 62 across 762 interventional studies indexed under Prediabetic State.
Browse Prediabetic State studies →Johns Hopkins University is the lead sponsor of 1,815 studies on the registry; 315 are open to participants now.
Of its 208 completed or terminated interventional studies of FDA-regulated products, 144 (69%) have results posted.
Counted across the registry records on this site, refreshed daily.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Laboratory evidence of prediabetes, defined as any of the following lab results, in the past year:
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
A blood test of average blood sugar over the past two to three months, given as a percentage or in mmol/mol. 6.5% (48 mmol/mol) or more is the usual threshold for diabetes, normally confirmed by a second test.
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
HbA1c
A blood test of average blood sugar over the past two to three months, given as a percentage or in mmol/mol. 6.5% (48 mmol/mol) or more is the usual threshold for diabetes, normally confirmed by a second test.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
BMI (body mass index)
Weight in kilograms divided by height in metres squared. Example: 70 kg and 1.75 m gives 70 ÷ (1.75 × 1.75) ≈ 22.9.
What counts as overweight or obesity differs between countries (some use lower cut-offs), so go by the range the study states.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Corticosteroids (steroids)
Anti-inflammatory medicines such as prednisone, prednisolone and dexamethasone — not the anabolic steroids used for muscle.
Studies differ in what they allow: check which steroid medicines, routes (tablets, injections, creams, inhalers, eye drops) and doses this study accepts.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Cancer (malignancy)
Malignancy means cancer. Criteria about another or earlier malignancy ask whether you have had a different cancer, usually within a set number of years.
Some are commonly allowed, such as treated skin cancers other than melanoma and early cancers removed completely — check the exceptions this study lists.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Participants will receive Sweetch Digital Diabetes Prevention Program consists of a smartphone app and bluetooth-enabled digital body weight scale that syncs with the app.
Behavioral: Digital Diabetes Prevention Program (dDPP)
Participants will attend a total of 16 weekly sessions during months 1 to 6 and 6 sessions during months 7 to 12. These group sessions may be delivered in-person at the local program or remotely using video conferencing. During these sessions, participants will receive information about lifestyle change behaviors focusing on weight loss, physical activity, and nutrition from a trained lifestyle coach.
Behavioral: Human Coach-based Diabetes Prevention Program (hDPP)
The Sweetch app is a hyper-personalized mobile digital coach that provides users with tailored recommendations to promote healthy lifestyle behaviors (150 minutes per week of physical activity, weight reduction, and healthy eating habits) to reduce the risk of type 2 diabetes. The Sweetch app uses self-tracking and multiple evidence-based persuasive eCoaching strategies. The Sweetch artificial intelligence algorithm delivers just-in-time support and/or adapt recommendations based on the user's response. For example, push notifications will be sent when the algorithm detects that the user is potentially available and able to act upon the recommendation, based on various parameters including location, previous response, calendar availability, and weather, etc.
The Human Coach-Based Diabetes Prevention Program will consist of a CDC recognized lifestyle change program. Participants will attend a total of 16 weekly sessions during months 1 to 6 and 6 sessions during months 7 to 12. These group sessions may be delivered in-person at the local program or remotely using video conferencing. During these sessions, participants will receive information about lifestyle change behaviors focusing on weight loss, physical activity, and nutrition from a trained lifestyle coach.
Achievement of CDC's Benchmark for Type 2 Diabetes Risk Reduction as a Binary Outcome (Yes/no)
The primary outcome was the CDC-defined diabetes risk reduction benchmark at 12 months (based on the 2021 standards), defined as at least one of the following: 1. Weight loss of ≥5%. 2. Weight loss of ≥4% combined with at least 150 weekly minutes of moderate-to-vigorous PA 3. An absolute decrease of ≥0.2 points in A1C (measured in %). The A1C endpoint was applicable only to participants with baseline A1C of 5.7% to 6.4%. Maintaining an A1C \<6.5% throughout the study was also a criterion for the primary outcome.
Time frame: 12 months
Absolute Weight Change
Absolute weight change (kilograms) from baseline to 12 months
Time frame: At 12 months
Cost-effectiveness as Assessed by the Markov Model
The investigators will compare the cost-effectiveness of the two interventions based on lifetime horizon by constructing a Markov model with model parameters populated from the trial results as well as other published literature. The model will estimate the incremental cost-effectiveness ratio between the two interventions.
Time frame: 12 months
Change in Hemoglobin A1C
Change in HbA1C (percentage points) from baseline to 12 months (among participants with baseline HbA1C of 5.7% - 6.4% who completed the 12-month study visit).
Time frame: At 12 months
Percentage Change in Weight
Percentage change in weight from baseline to 12 months
Time frame: At 12 months
Mean Weekly Moderate-to-vigorous Physical Activity (MVPA)
Average minutes/week of physical activity assessed using blinded Actigraphy (monthly serial consecutive 7-days wear period). If the participant did not wear their monitor for at least 5 of their 7 assigned days, they were considered noncompliant. In this case, the participant was assigned 0 minutes for physical activity for that week.To obtain the average MVPA minutes per week across the study period, the total MVPA minutes per week from all valid wear periods were summed and divided by the number of available wear periods (maximum of 11 post-baseline visits). Specifically, activity intensity was classified as MVPA if the vector magnitude of accelerometer counts per minute was equal to or greater than 3941 (Montoye's cut point).
Time frame: At 12 months
Incidence of Diabetes-range A1C
Number of individuals who had an AIC in the diabetes range (A1C ≥6.5%) at the 6-month or 12-month timepoint.
Time frame: At either 6 or 12 months
Acceptability as Assessed by the Diabetes Prevention Program Acceptability Scale (DPPAS)
Acceptability of the assigned intervention was assessed at 12 months using the Diabetes Prevention Program Acceptability Scale (DPPAS), Score range from 1 to 5; higher scores indicate greater acceptability (better outcome).
Time frame: 12 months
Correlation Between Self-reported and Measured Physical Activity
To evaluate the correlation between self-reported PA data collected using different methods: * Data collected and reported by hDPPs * Self-reported PA data collected by study team obtained at 1-month intervals * Objectively measured PA data (Actigraphy) obtained at 1-month intervals
Time frame: 6 months and 12 months
Program Initiation Rate
Program initiators were defined as participants who attended at least one in-person session (Human-DPP) or registered and used the Sweetch app (AI-DPP).
Time frame: At 12 months
Program Completion Rate
Program completers attended ≥8 sessions in months 1-6 and spanned ≥9 months (Human-DPP), or engaged with the app for ≥8 weeks during months 1-6 with a span of ≥9 months between initiation and last engagement (AI-DPP).
Time frame: At 12 months
| Milestone | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Started | 183 | 185 |
| Completed | 151 | 149 |
| Not completed | 32 | 36 |
The primary outcome was the CDC-defined diabetes risk reduction benchmark at 12 months (based on the 2021 standards), defined as at least one of the following: 1. Weight loss of ≥5%. 2. Weight loss of ≥4% combined with at least 150 weekly minutes of moderate-to-vigorous PA 3. An absolute decrease of ≥0.2 points in A1C (measured in %). The A1C endpoint was applicable only to participants with baseline A1C of 5.7% to 6.4%. Maintaining an A1C \<6.5% throughout the study was also a criterion for the primary outcome.
| Participants | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Achievement of CDC's Benchmark for Type 2 Diabetes Risk Reduction as a Binary Outcome (Yes/no) | 58 | 59 |
Absolute weight change (kilograms) from baseline to 12 months
| Kg | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Absolute Weight Change | -1.00 (-3.20 to 1.50) | -1.30 (-4.30 to 1.10) |
The investigators will compare the cost-effectiveness of the two interventions based on lifetime horizon by constructing a Markov model with model parameters populated from the trial results as well as other published literature. The model will estimate the incremental cost-effectiveness ratio between the two interventions.
Results for this outcome have not been posted.
Change in HbA1C (percentage points) from baseline to 12 months (among participants with baseline HbA1C of 5.7% - 6.4% who completed the 12-month study visit).
| Percentage of Total Hemoglobin | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Change in Hemoglobin A1C | 0.0 (-0.2 to 0.1) | -0.1 (-0.2 to 0.1) |
Percentage change in weight from baseline to 12 months
| percentage change | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Percentage Change in Weight | -1.03 (-3.73 to 1.46) | -1.43 (-4.03 to 1.14) |
Average minutes/week of physical activity assessed using blinded Actigraphy (monthly serial consecutive 7-days wear period). If the participant did not wear their monitor for at least 5 of their 7 assigned days, they were considered noncompliant. In this case, the participant was assigned 0 minutes for physical activity for that week.To obtain the average MVPA minutes per week across the study period, the total MVPA minutes per week from all valid wear periods were summed and divided by the number of available wear periods (maximum of 11 post-baseline visits). Specifically, activity intensity was classified as MVPA if the vector magnitude of accelerometer counts per minute was equal to or greater than 3941 (Montoye's cut point).
| Minutes per Week | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Mean Weekly Moderate-to-vigorous Physical Activity (MVPA) | 210.5 (134.5 to 344) | 174.4 (73.9 to 321.3) |
Number of individuals who had an AIC in the diabetes range (A1C ≥6.5%) at the 6-month or 12-month timepoint.
| Participants | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Incidence of Diabetes-range A1C | 8 | 7 |
Acceptability of the assigned intervention was assessed at 12 months using the Diabetes Prevention Program Acceptability Scale (DPPAS), Score range from 1 to 5; higher scores indicate greater acceptability (better outcome).
| score on a scale | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Acceptability as Assessed by the Diabetes Prevention Program Acceptability Scale (DPPAS) | 3.12 (2.98 to 3.26) | 3.95 (3.81 to 4.09) |
To evaluate the correlation between self-reported PA data collected using different methods: * Data collected and reported by hDPPs * Self-reported PA data collected by study team obtained at 1-month intervals * Objectively measured PA data (Actigraphy) obtained at 1-month intervals
Results for this outcome have not been posted.
Program initiators were defined as participants who attended at least one in-person session (Human-DPP) or registered and used the Sweetch app (AI-DPP).
| Participants | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Program Initiation Rate | 171 | 153 |
Program completers attended ≥8 sessions in months 1-6 and spanned ≥9 months (Human-DPP), or engaged with the app for ≥8 weeks during months 1-6 with a span of ≥9 months between initiation and last engagement (AI-DPP).
| Participants | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| Program Completion Rate | 117 | 93 |
Collected over From enrollment until the end of follow-up (12-month visit). Non-serious events are listed at a 0.5% frequency threshold.
| Group | Deaths | Serious | Other |
|---|---|---|---|
| Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | 0/183 (0%) | 36/183 (19.7%) | 10/183 (5.5%) |
| Human Coach-Based Diabetes Prevention Program (Human-DPP) | 0/185 (0%) | 6/185 (3.2%) | 3/185 (1.6%) |
| Event | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| COVID-19Infections and infestations | 4/183 | 1/185 |
| Chest PainCardiac disorders | 3/183 | 0/185 |
| Breast malignant tumorsNeoplasms benign, malignant and unspecified (incl cysts and polyps) | 2/183 | 1/185 |
| Flank painRenal and urinary disorders | 2/183 | 0/185 |
| Atrioventricular blockCardiac disorders | 1/183 | 0/185 |
| Fracture of ankleMusculoskeletal and connective tissue disorders | 1/183 | 0/185 |
| AppendicitisGastrointestinal disorders | 1/183 | 0/185 |
| PhacoemulsificationEye disorders | 1/183 | 0/185 |
| Diabetes mellitusEndocrine disorders | 1/183 | 0/185 |
| OtalgiaEar and labyrinth disorders | 1/183 | 0/185 |
| Event | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) |
|---|---|---|
| COVID-19Infections and infestations | 2/183 | 1/185 |
| ConcussionInjury, poisoning and procedural complications | 1/183 | 0/185 |
| Foreign body in earInjury, poisoning and procedural complications | 1/183 | 0/185 |
| Radius fractureInjury, poisoning and procedural complications | 1/183 | 0/185 |
| Generalized anxiety disorderPsychiatric disorders | 1/183 | 0/185 |
| MigraineNervous system disorders | 1/183 | 0/185 |
| Kidney stoneRenal and urinary disorders | 1/183 | 0/185 |
| OsteopeniaMusculoskeletal and connective tissue disorders | 1/183 | 0/185 |
| Neuropathy peripheralNervous system disorders | 1/183 | 0/185 |
| Plantar fasciitisMusculoskeletal and connective tissue disorders | 1/183 | 0/185 |
| Age, Continuous(Years) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Median | 60.0 (51.0 to 68.0) | 57.0 (50.0 to 63.0) | 58.0 (50.0 to 65.0) |
| Sex: Female, Male(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Female | 121 | 139 | 260 |
| Male | 62 | 46 | 108 |
| Race/Ethnicity, Customized(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Race — American Indian or Alaskan Native | 0 | 1 | 1 |
| Race — Asian | 11 | 16 | 27 |
| Race — Black or African American | 51 | 49 | 100 |
| Race — White or Caucasian | 114 | 111 | 225 |
| Race — More than One Race | 3 | 5 | 8 |
| Race — Other | 4 | 2 | 6 |
| Race — Declined to Answer | 0 | 1 | 1 |
| Race/Ethnicity, Customized(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Ethnicity — Not Hispanic or Latino | 176 | 167 | 343 |
| Ethnicity — Hispanic or Latino | 5 | 15 | 20 |
| Ethnicity — Declined to Answer | 1 | 1 | 2 |
| Ethnicity — Unknown | 1 | 2 | 3 |
| Marital Status(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Married/Partnered | 120 | 121 | 241 |
| Previously Married | 27 | 26 | 53 |
| Single/Other | 36 | 38 | 74 |
| Educational Attainment(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| High School or Less | 23 | 19 | 42 |
| Some College/Associate's Degree | 38 | 36 | 74 |
| Bachelor's Degree | 53 | 55 | 108 |
| Graduate/Professional Degree | 69 | 74 | 143 |
| Declined to Answer | 0 | 1 | 1 |
| Body Mass Index (BMI)(Kg/m^2) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Median | 32.2 (28.2 to 35.9) | 32.5 (29.3 to 37.7) | 32.3 (28.5 to 37.1) |
| Dyslipidemia(Participants) | Artificial Intelligence-Based Diabetes Prevention Program (AI-DPP) | Human Coach-Based Diabetes Prevention Program (Human-DPP) | Total |
|---|---|---|---|
| Count of participants | 85 | 86 | 171 |
10 further baseline measures are reported on the registry.
PDFs hosted by the registry, ClinicalTrials.gov.
Plan to share: Yes — The Data Coordinating Center (Johns Hopkins University) will prepare a de-identified database that is consistent with HIPAA requirements. The de-identified database will include all study research data and will be stored in a repository at Johns Hopkins University (archive.data.jhu.edu) at a time that will coincide with the online publication of the study primary endpoint paper. The repository will contain documentation designed to facilitate use of the database. The documentation prepared for the repository will include a list and timetable for secondary and exploratory papers planned by the study investigators. Access to the database will be restricted to qualified users. Qualified users will include those investigators who submit valid pre-specified hypotheses and certify that they will not use the data for commercial purposes.
Supporting information: Study protocol
Time frame: The study protocol will be submitted for publication within 1 year of the start of enrollment.
Ran from Oct 2021 to primary completion in Dec 2024, 38 months.
Results were first posted in Dec 2025, 1 year after primary completion.
Of 378 non-industry interventional studies with no phase under Prediabetic State, half reached primary completion within 25 months of starting (the median), counting those still running; a quarter within 12 and three quarters within 39. This study's 38 months is above that.
Counting every sponsor, half of 424 studies reached it within 23 months; a quarter within 11 and three quarters within 37.
How these figures are worked out, and which studies are left out of them.
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
This study is completed, as verified in Nov 2026. You cannot join it, but the record below documents what was studied.
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