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Background: The evidence-based National Diabetes Prevention Program (NDPP) is now widely disseminated, yet strategies to increase its effectiveness are needed, especially for underserved populations. The yearlong program promotes lifestyle changes for weight loss and can be offered in-person, online, via distance learning, or a combination of modalities. Less is known about which delivery features are optimal and may help address disparities in outcomes for subgroups. We previously demonstrated the efficacy of a stand-alone text messaging intervention based on the NDPP (SMS4PreDM) in a randomized controlled trial in a safety net health care system. Upon broader dissemination, we then showed that SMS4PreDM demonstrated high retention and modest weight loss at a relatively low cost, suggesting the potential to improve in-person NDPP delivery.
Objective: In this study, we aim to compare the effectiveness of in-person NDPP classes with and without supplementary SMS4PreDM on attendance and weight loss outcomes to determine whether text messaging can enhance in-person NDPP delivery for a safety net patient population.
Methods: From 2015 to 2017, patients with diabetes risks were identified primarily from provider referrals and enrolled in NDPP classes, SMS4PreDM, or both per their preference and availability. Participants naturally formed three groups: in-person NDPP with SMS4PreDM (n=236), in-person NDPP alone (n=252), and SMS4PreDM alone (n=285). This analysis compares the first two groups to evaluate whether supplemental text messaging may improve in-person NDPP outcomes. Outcomes for SMS4PreDM-only participants were previously reported. NDPP classes followed standard delivery guidelines, including weekly-to-monthly classes over a year. SMS4PreDM delivery included messages promoting lifestyle change and modest weight loss, sent 6 days per week for 12 months. Differences in characteristics between intervention groups were assessed using chi-square and t tests. Differences in NDPP attendance and weight loss outcomes were analyzed with multivariable linear and logistic regressions.
Results: The mean age was 50.4 years (SD 13.9). Out of a total of 488 participants, 76.2% (n=372) were female and 59.0% (n=288) were Hispanic. An additional 17.2% (n=84) were non-Hispanic white and 12.9% (n=63) were non-Hispanic black. A total of 48.4% (n=236) of participants elected to receive supplemental text message support in addition to NDPP classes. Participants who chose supplemental text message support were on average 5.7 (SD 1.2) years younger (P<.001) than the 252 participants who preferred in-person classes alone. Relatively more women and Hispanic individuals enrolled in the NDPP with supplemental text messages than in NDPP classes alone, 83.9% (n=198) vs 69.0% (n=174, P<.001) and 68.6% (n=162) vs 50.0% (n=126, P=.001), respectively. Attendance and weight loss outcomes were comparable between groups.
Conclusions: Despite its appeal among priority populations, supplemental text messaging did not significantly increase attendance and weight loss for the in-person NDPP. Further research is needed to identify optimal strategies to improve the effectiveness of the NDPP.
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http://dx.doi.org/10.2196/15478 | DOI Listing |
Health Place
July 2025
University of Maryland School of Public Health, 4200 Valley Drive, 20742, College Park, MD, USA.
Background: Transportation issues are a significant barrier for accessing the National Diabetes Prevention Program (NDPP), which remains an effective intervention to prevent type 2 diabetes. Although the link between neighborhood socioeconomic disadvantage and access to health care resources has been widely studied, its impact on travel time and access to NDPP has been underexplored.
Methods: Medicaid and private claims data for 2019 from the Maryland Medical Care Data Base were linked to 2019 Social Deprivation Index (SDI) data to measure neighborhood socioeconomic disadvantage.
J Clin Transl Sci
February 2024
Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA.
Strategies are needed to ensure greater participation of underrepresented groups in diabetes research. We examined the impact of a remote study protocol on enrollment in diabetes research, specifically the Pre-NDPP clinical trial. Recruitment was conducted among 2807 diverse patients in a safety-net healthcare system.
View Article and Find Full Text PDFDiabetes Res Clin Pract
September 2023
Department of Internal Medicine, Division of Metabolism, Endocrinology, and Diabetes, University of Michigan, Ann Arbor, MI, USA.
Aims: To describe National Diabetes Prevention Program (NDPP) uptake, retention, and outcomes by enrollee characteristics and program type.
Methods: We studied 776 adult University of Michigan employees, dependents, and retirees with prediabetes and overweight or obesity who enrolled in one of four CDC-recognized NDPPs at no out-of-pocket cost. Programs included 1) an in-person classroom-based program led by certified diabetes educators in an endocrinology outpatient clinic; 2) an in-person classroom-based program led by trained peer instructors in community settings; 3) an in-person fitness-focused program led by trained lifestyle coaches; and 4) an online digital program led by personal health coaches with virtual group meetings.
Am J Health Promot
September 2022
School of Nursing, 8783University of California, Los Angeles, CA, USA.
Purpose: To describe Lifestyle Coach perceptions of dyads (i.e., family members and/or friends) in the National Diabetes Prevention Program (NDPP).
View Article and Find Full Text PDFPopul Health Manag
August 2022
Clinical Studies and Research, Lark Health, Mountain View, California, USA.
The National Diabetes Prevention Program (NDPP) offers lifestyle change education to adults at risk for diabetes across the United States, but its reach is curbed due, in part, to limitations of traditional in-person programs. Diabetes Prevention Programs (DPPs) that are fully digital may increase reach by overcoming these barriers. The aim of this research was to examine the reach of Lark's DPP, a fully digital artificial-intelligence-powered DPP.
View Article and Find Full Text PDF