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Preventing Diabetes With Digital Health and Coaching

Preventing Diabetes With Digital Health and Coaching for Translation and Scalability (PREDICTS)

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03312764
Acronym
PREDICTS
Enrollment
598
Registered
2017-10-18
Start date
2017-11-01
Completion date
2020-08-31
Last updated
2021-02-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

PreDiabetes

Keywords

Prediabetes, Obesity, Intensive behavioral counseling, Type 2 Diabetes

Brief summary

The goal of this randomized controlled trial is to determine the efficacy of a digital diabetes prevention program for improving weight, glucose control, and secondary risk factors among people with prediabetes compared to an enhanced standard care plus wait-list control. Exploratory assessments of implementation facilitators and barriers will also be completed to determine strategies for integrating external diabetes-prevention interventions within healthcare settings.

Detailed description

Prediabetes is an increasingly prevalent condition, characterized by glucose levels that are above normal but below the threshold for diabetes. Previous studies have demonstrated that intensive lifestyle interventions targeting changes in diet, physical activity, sleep, and stress can reduce the risk of progressing from prediabetes to Type 2 diabetes. The Diabetes Prevention Recognition Program (DPRP) currently recognizes both in-person and online programs that meet requirements to deliver approved curriculum, provide health coaching and group support, and equip participants with behavioral skills and self-monitoring tools to support behavior change. While non-randomized trial data demonstrate that an online digital program was successful for producing meaningful weight loss and improved glucose control, the goal of this randomized, controlled trial is to definitively evaluate the efficacy of the program for improving weight, glucose control and secondary risk factors compared to current standard care for prediabetes. In addition, few trials have examined the implementation factors that could speed the uptake of efficacious diabetes prevention interventions for delivery in regular clinical practice. Qualitative information on key organizational stakeholders (e.g., physicians, office managers) will be gathered to provide information on perceptions of the online program characteristics, outcomes, and resources concurrently with strategies to promote adoption and implementation in health care settings.

Interventions

Digital delivery of Intensive behavioral counseling for diabetes prevention and healthy lifestyle management. Recipients have access to online curriculum, a live health coach, group-based communication forums, and connected technology to track weight and physical activity.

BEHAVIORALStandard Care

One-on-one or small group sessions with a dietitian or a trained health professional to advise on physical activity, healthful nutrition and risk reduction for diabetes.

Sponsors

University of Nebraska
CollaboratorOTHER
Wake Forest University Health Sciences
CollaboratorOTHER
Omada Health, Inc.
Lead SponsorINDUSTRY

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
DOUBLE (Investigator, Outcomes Assessor)

Masking description

All study investigators that collect data or analyze the data are prevented from knowing the interventions assigned to individual participants.

Intervention model description

Participants are randomly allocated to one of two groups for the duration of the study.

Eligibility

Sex/Gender
ALL
Age
19 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Receives care at University of Nebraska Medical Center or Nebraska Medicine * Age 19 years or older * HbA1c 5.7%-6.4% * Overweight (BMI 25+ or 22+ if Asian) * Planning to reside in recruitment area for next 12 months * Able to engage in moderate aerobic physical activity * Medically stable * Able to provide informed consent * Willing to accept random assignment to treatment

Exclusion criteria

* Not meeting all inclusion criteria * Diagnosed with Type I or II diabetes * Diagnosed with congestive heart failure, coronary artery disease, chronic obstructive pulmonary disease, pulmonary hypertension * Diagnosed with dementia or probable Alzheimer's disease * Taking oral hypoglycemic agents * Participating in a concurrent weight management program or interventional research protocol * Unable to engage in physical activity * On a prescribed medical diet * Had bariatric surgery within the past 3 years or planning surgery within the next 12 months * Anti-obesity or diabetes therapy within the preceding 4 months * Any mental health condition, including eating disorders or alcohol/substance use, which would preclude full participation * Self-report as currently pregnant or within 6 weeks of having given birth (or planning to become pregnant in the next 12 months) * Unstable cardiac disease (i.e. heart attack/failure or stroke in the last 6 months, or in cardiac rehabilitation) * On dialysis or an active organ transplant list * Chronic kidney disease * Untreated thyroid disease * Cancer within the last 5 years unless skin cancer (i.e. currently or within the last 5 years in chemotherapy or radiation treatment) * Unwilling to accept random assignment

Design outcomes

Primary

MeasureTime frameDescription
HbA1c reductionBaseline and 12 monthsChange in percent HbA1c

Secondary

MeasureTime frameDescription
Weight lossBaseline, 4 months, and 12 monthsReduction in percent of initial body weight
Decreased cardiovascular riskBaseline, 4 months, and 12 monthsAtherosclerotic Cardiovascular Disease (ASCVD) risk estimator algorithm will be used to assess cardiovascular risk. The tool uses a number of demographic and health characteristics to estimate risk.

Other

MeasureTime frameDescription
Implementation Context12 monthsThis qualitative assessment will identify the overall implementation climate for a digital DPP. Key informant interviews will be used to elicit stakeholder perceptions, which will be coded for meaning and grouped into categories. The categories will then be integrated to determine possible implementation strategies for this type of program. As such, there is a single assessment that will result in multiple categories. We identified the a priori hypothetical categories, but may find additional categories and may not find perceptions that align with the current categories. This is a single section since these qualitative outcomes may be variable. Physician, other health professional, and administrator perceptions of: 1. The value and practicality of integrating a new DPP within their facility 2. Barriers to DPP sustainability 3. Contextual readiness for a diabetes prevention initiative 4. Factors that would facilitate implementation 5. Indicators of successful implementation

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 19, 2026