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Research ArticleOriginal Research

DPPFit: Developing and Testing a Technology-Based Adaptation of the Diabetes Prevention Program (DPP) to Address Prediabetes in a Primary Care Setting

Jessica L. Stewart, Christos Hatzigeorgiou, Catherine L. Davis and Christy J. W. Ledford
The Journal of the American Board of Family Medicine May 2022, 35 (3) 548-558; DOI: https://doi.org/10.3122/jabfm.2022.03.210415
Jessica L. Stewart
From the Division of Epidemiology, Department of Population Health Sciences, Augusta University, Augusta, GA (JLS); General Internal Medicine, Department of Medicine, Medical College of Georgia, Augusta University (CH); Georgia Prevention Institute, Medical College of Georgia, Augusta University (CLD); Department of Family Medicine, Medical College of Georgia at Augusta University (CWL).
PhD, MPH
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Christos Hatzigeorgiou
From the Division of Epidemiology, Department of Population Health Sciences, Augusta University, Augusta, GA (JLS); General Internal Medicine, Department of Medicine, Medical College of Georgia, Augusta University (CH); Georgia Prevention Institute, Medical College of Georgia, Augusta University (CLD); Department of Family Medicine, Medical College of Georgia at Augusta University (CWL).
DO
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Catherine L. Davis
From the Division of Epidemiology, Department of Population Health Sciences, Augusta University, Augusta, GA (JLS); General Internal Medicine, Department of Medicine, Medical College of Georgia, Augusta University (CH); Georgia Prevention Institute, Medical College of Georgia, Augusta University (CLD); Department of Family Medicine, Medical College of Georgia at Augusta University (CWL).
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Christy J. W. Ledford
From the Division of Epidemiology, Department of Population Health Sciences, Augusta University, Augusta, GA (JLS); General Internal Medicine, Department of Medicine, Medical College of Georgia, Augusta University (CH); Georgia Prevention Institute, Medical College of Georgia, Augusta University (CLD); Department of Family Medicine, Medical College of Georgia at Augusta University (CWL).
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Article Figures & Data

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    Figure 1.

    Screenshot of messaging templates in project. Broadcast App.

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    Figure 2.

    Screenshot of DPPFit days 0 and 1 messages.

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    Figure 3.

    Timeline of the DPPFit intervention and the Covid-19 pandemic in the US.

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    Table 1.

    Behavioral Strategy Adaptations from National-Diabetes Prevention Program to DPPFit

    Behavioral StrategyN-DPP*DPPFit
    Setting and evaluating goalsSession 1 recorded into participant notebook. Revisited throughout 16 core sessions.Weight loss goal, PA daily/weekly goals (to be set in individual Fitbit® user application [app]); revisit through daily text at frequency of DPP
    Self-management strategies for behavioral changeSession 11Week 11 SMS/MMS texts
    Self-monitoring of dietCalorie counting, fat gram logs, food diaryFitbit® app – food log
    Self-monitoring of physical activityPhysical activity logFitbit® tracker and Fitbit® app
    AccountabilityLifestyle coach delivers 16 sessions over 6-monthnth period, in groups or 1 on 1.Daily SMS/MMS texts
    Problem solving, barriers to changeSession 9Week 9 SMS/MMS texts
    Addressing relapse in lifestyle changesSession 12Week 12 SMS texts
    Increasing self-efficacySession 11, session 16Week 11, week 16 SMS/MMS texts
    • Abbreviations: PA, physical activity; MMS, multimedia messaging service; N-DPP, National-Diabetes Prevention Program; SMS, short message service (in the present study, both SMS and MMS refer to text messages).

    • Session number refers to the 16 session-core of the DPP.

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    Table 2.

    Use of Technology and mHealth App to Deliver Behavioral Strategies*

    DPPFit ComponentDetailsBehavioral Strategy
    Week 1, day 3Cue to action: Use Fitbit® to track DPPFit goal of 150 activity minutes per weekSelf-monitoring of physical activity; cues to action
    Week 1, day 7Hyperlink: How to set goals in the Fitbit® application (app)Setting and evaluating goals; self-monitoring of physical activity
    Week 2, day 1Hyperlink: How to log and track food in Fitbit® appSelf-monitoring of diet
    Week 5, day 6Hyperlink: How to connect with friends in the Fitbit® communitySocial support; cues to action; self-efficacy
    Week 5, day 7Hyperlink: How to use Fitbit® to challenge yourself or other to be physical active.Cues to action; accountability; self-efficacy; self-monitoring of physical activity
    Week 7, day 4Cue to action: Use Fitbit® app to measure calorie balance.Cues to action; self-monitoring of diet and physical activity
    Week 13, day 3Hyperlink: Understanding heart rate tracking and aerobic fitness with Fitbit®.Self-monitoring of physical activity increasing self-efficacy
    Week 15, day 6Hyperlink: How to use Fitbit® for guided breathing exercise to relaxProblem-solving; perceived barriers; stress management; self-management strategies for behavioral change
    Week 16, day 4Hyperlink: Ways to stay motivated - Fitbit® app competitionsIncreasing self-efficacy; self-management strategies for behavioral change
    Using Fitbit® Tracker/AppLearning to use both the device and app to support healthy changes.Increasing self-efficacy; self-management strategies for behavioral change; social support
    • ↵* See Online Appendix for complete content of text messaging templates.

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    Table 3.

    Baseline Measures of Diabetes Risk, Demographics, and Socioeconomic Status

    VariableMean (SD)Variable% (n)
    Age in years44 (8.5)Sex
    FINDRISC (0 to 20)13.6 (2.6)    Male82 (27)
        Female18 (6)
    FINDRISC by Category, as % (n)Race
        Moderate risk: 9 to 1236.4 (12)    African American/Black48.5 (16)
        High risk: 13 to 2063.6 (21)    Asian8.6 (3)
    Clinical Measures    Caucasian/White39.4 (13)
        Multiracial3.0 (1)
        Glucose (FPG; mg/dL)99.3 (17.4)Education
        HbA1c (%)5.9 (0.28)    High school degree6.0 (2)
        Some university/College18.2 (6)
        Systolic BP (mm Hg)129.5 (13.5)    College degree45.5 (15)
        Diastolic BP (mm Hg)83.2 (10.4)    Graduate degree30.3 (10)
        Total cholesterol180.4 (43.4)Household Income
        Triglycerides (mg/dL)117.2 (65.1)    <$40,00021.2 (7)
        $40000-$80,00033.3 (11)
        LDL (mg/dL)110.9 (37.4)    > $80,00039.4 (13)
        HDL (mg/dL)50.5 (14.3)Employment Status
        HDL: females54 (12.7)    Employed (Part-time/Full-time)75.8 (25)
        Unemployed (< 1 year)3.0 (1)
        HDL: males37 (12.6)    Homemaker6.1 (2)
        Disabled
    Anthropometric measures    Student6.1 (2)
        Weight (kg)106.4 (26.7)9.1 (3)
        BMI (kg/m²)38.0 (8.9)Relationship Status
        Waist circumference (cm)113.7 (18.1)    Partnered/married72.7 (24)
        Dating/In relationship6.1 (2)
        Waist circumference: females112.4 (19.3)    Single18.2 (6)
        Waist circumference: males119.2 (10.4)    Widowed3.0 (1)
    • Abbreviations: BMI, body mass index; BP, blood pressure; cm-centimeters; FINDRISC, Finnish Diabetes Risk Test; FPG, fasting plasma glucose; Hb1Ac, hemoglobin A1c; HDL, high-density lipoproteins; LDL, low-density lipoproteins; SD, standard deviation.

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    Table 4.

    Pre- and Post-Intervention Effect: Biometrics and Self-Reported Physical Activity Outcome from the International Physical Activity Questionnaire

    Baseline Mean (SE)∼6 Months* Mean (SE)Difference† Mean difference (95% CI)F statisticp-value
    Weight (kg)108.6 (4.8)105.3 (4.9)−3.3 (−6.2 to −0.5)6.620.026
    BMI (kg/m2)38.8 (1.8)37.6 (1.9)−1.3 (−2.1 to −0.4)11.050.005
    Systolic BP (mm Hg)131.0 (2.9)129.1 (2.4)−1.9 (−7.2 to 3.5)0.540.470
    Diastolic BP (mm Hg)84.7 (2.2)77.9 (2.1)−6.8 (−10.3 to −3.3)16.8<0.001
    IPAQ
    Walk (days/week)2.9 (0.7)4.0 (0.8)1.1 (−1.0 to 3.2)1.150.297
    Moderate (days/week)0.8 (0.3)2.8 (0.7)2.0 (0.4 to 3.6)7.030.015
    Vigorous (days/week)0.6 (0.2)2.1 (0.6)1.5 (0.1 to 2.9)5.510.035
    Total PA (minutes/days)75.1 (14.5)137.5 (26.5)62.4 (3.5 to 121.3)5.010.039
    Sedentary (minutes/days)509.5 (48.7)389.9 (39.0)−121.6 (−206 to −37)9.070.007
    • ↵* Mean follow-up was 6 months, ranging from 4.5 to 8 months from baseline. Means and standard errors from model for baseline and follow-up values (time effect: 0 to 6 months).

    • ↵† Mean change with 95% CI. Analysis controlled for demographic and diabetes risk using the Finnish Diabetes Risk Test.

    • Abbreviations: BMI, body mass index; BP, blood pressure; CI, confidence interval; IPAQ, International Physical Activity Questionnaire; SE, standard error.

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The Journal of the American Board of Family Medicine: 35 (3)
The Journal of the American Board of Family Medicine
Vol. 35, Issue 3
May/June 2022
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DPPFit: Developing and Testing a Technology-Based Adaptation of the Diabetes Prevention Program (DPP) to Address Prediabetes in a Primary Care Setting
Jessica L. Stewart, Christos Hatzigeorgiou, Catherine L. Davis, Christy J. W. Ledford
The Journal of the American Board of Family Medicine May 2022, 35 (3) 548-558; DOI: 10.3122/jabfm.2022.03.210415

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DPPFit: Developing and Testing a Technology-Based Adaptation of the Diabetes Prevention Program (DPP) to Address Prediabetes in a Primary Care Setting
Jessica L. Stewart, Christos Hatzigeorgiou, Catherine L. Davis, Christy J. W. Ledford
The Journal of the American Board of Family Medicine May 2022, 35 (3) 548-558; DOI: 10.3122/jabfm.2022.03.210415
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