Perry Foley1, Dori Steinberg2, Erica Levine3, Sandy Askew4, Bryan C Batch5, Elaine M Puleo6, Laura P Svetkey7, Hayden B Bosworth8, Abigail DeVries9, Heather Miranda10, Gary G Bennett11. 1. Duke Global Digital Health Science Center, Duke Global Health Institute, 310 Trent Drive, Box 90519, Durham, NC 27710, USA. Electronic address: perry.foley@duke.edu. 2. Duke Global Digital Health Science Center, Duke Global Health Institute, 310 Trent Drive, Box 90519, Durham, NC 27710, USA. Electronic address: dori.steinberg@duke.edu. 3. Duke Global Digital Health Science Center, Duke Global Health Institute, 310 Trent Drive, Box 90519, Durham, NC 27710, USA. Electronic address: erica.levine@duke.edu. 4. Duke Global Digital Health Science Center, Duke Global Health Institute, 310 Trent Drive, Box 90519, Durham, NC 27710, USA. Electronic address: sandy.askew@duke.edu. 5. Department of Medicine, Division of Endocrinology, Duke University Medical Center, Durham, NC 27710, USA; Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC 27710, USA. Electronic address: bryan.batch@duke.edu. 6. School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003-9304, USA. Electronic address: epuleo@schoolph.umass.edu. 7. Department of Medicine, Division of Endocrinology, Duke University Medical Center, Durham, NC 27710, USA; Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, NC 27710, USA. Electronic address: laura.svetkey@duke.edu. 8. Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC 27705, USA. Electronic address: hayden.bosworth@dm.duke.edu. 9. Piedmont Health Services, Inc., Carrboro, NC 27510, USA. Electronic address: devriesa@piedmonthealth.org. 10. Piedmont Health Services, Inc., Carrboro, NC 27510, USA. Electronic address: mirandah@piedmonthealth.org. 11. Duke Global Digital Health Science Center, Duke Global Health Institute, 310 Trent Drive, Box 90519, Durham, NC 27710, USA; Department of Psychology and Neuroscience, Duke University, Durham, NC 27708, USA. Electronic address: gary.bennett@duke.edu.
Abstract
INTRODUCTION: Obesity continues to disproportionately affect medically vulnerable populations. Digital health interventions may be effective for delivering obesity treatment in low-resource primary care settings. METHODS:Track is a 12-month randomized controlled trial of a digital health weight loss intervention in a community health center system. Participants are 351 obese men and women aged 21 to 65years with an obesity-related comorbidity. Track participants are randomized to usual primary care or to a 12-month intervention consisting of algorithm-generated tailored behavior change goals, self-monitoring via mobile technologies, daily self-weighing using a network-connected scale, skills training materials, 18 counseling phone calls with a Track coach, and primary care provider counseling. Participants are followed over 12months, with study visits at baseline, 6, and 12months. Anthropometric data, blood pressure, fasting lipids, glucose and HbA1C and self-administered surveys are collected. Follow-up data will be collected from the medical record at 24months. RESULTS:Participants are 68% female and on average 50.7years old with a mean BMI of 35.9kg/m(2). Participants are mainly black (54%) or white (33%); 12.5% are Hispanic. Participants are mostly employed and low-income. Over 20% of the sample has hypertension, diabetes and hyperlipidemia. Almost 27% of participants currently smoke and almost 20% score above the clinical threshold for depression. CONCLUSIONS:Track utilizes an innovative, digital health approach to reduce obesity and chronic disease risk among medically vulnerable adults in the primary care setting. Baseline characteristics reflect a socioeconomically disadvantaged, high-risk patient population in need of evidence-based obesity treatment.
RCT Entities:
INTRODUCTION:Obesity continues to disproportionately affect medically vulnerable populations. Digital health interventions may be effective for delivering obesity treatment in low-resource primary care settings. METHODS: Track is a 12-month randomized controlled trial of a digital health weight loss intervention in a community health center system. Participants are 351 obesemen and women aged 21 to 65years with an obesity-related comorbidity. Track participants are randomized to usual primary care or to a 12-month intervention consisting of algorithm-generated tailored behavior change goals, self-monitoring via mobile technologies, daily self-weighing using a network-connected scale, skills training materials, 18 counseling phone calls with a Track coach, and primary care provider counseling. Participants are followed over 12months, with study visits at baseline, 6, and 12months. Anthropometric data, blood pressure, fasting lipids, glucose and HbA1C and self-administered surveys are collected. Follow-up data will be collected from the medical record at 24months. RESULTS:Participants are 68% female and on average 50.7years old with a mean BMI of 35.9kg/m(2). Participants are mainly black (54%) or white (33%); 12.5% are Hispanic. Participants are mostly employed and low-income. Over 20% of the sample has hypertension, diabetes and hyperlipidemia. Almost 27% of participants currently smoke and almost 20% score above the clinical threshold for depression. CONCLUSIONS: Track utilizes an innovative, digital health approach to reduce obesity and chronic disease risk among medically vulnerable adults in the primary care setting. Baseline characteristics reflect a socioeconomically disadvantaged, high-risk patient population in need of evidence-based obesity treatment.
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