Erica J Ambeba1, Lei Ye, Susan M Sereika, Mindi A Styn, Sushama D Acharya, Mary Ann Sevick, Linda J Ewing, Molly B Conroy, Karen Glanz, Yaguang Zheng, Rachel W Goode, Meghan Mattos, Lora E Burke. 1. Erica J. Ambeba, PhD School of Nursing and Graduate School of Public Health, Departments of Health and Community Systems and Epidemiology, University of Pittsburgh, Pennsylvania. Lei Ye, BMed Doctoral Student, School of Nursing and Graduate School of Public Health, Departments of Health and Community Systems and Biostatistics, University of Pittsburgh, Pennsylvania. Susan M. Sereika, PhD Professor, School of Nursing and Graduate School of Public Health, Departments of Health and Community Systems and Biostatistics, University of Pittsburgh, Pennsylvania. Mindi A. Styn, PhD Research Assistant Professor, School of Nursing and Graduate School of Public Health, Departments of Health and Community Systems and Epidemiology, University of Pittsburgh, Pennsylvania. Sushama D. Acharya, PhD Research Fellow, Community Guide Branch, Office of Surveillance, Epidemiology and Laboratory Services, Epidemiology and Analysis Program Office, Centers for Disease Control and Prevention, Atlanta, Georgia. Mary Ann Sevick, ScD Associate Professor, Veteran Affairs Pittsburgh Healthcare System, and School of Medicine, Department of Medicine, Center for Research on Healthcare, University of Pittsburgh, Pennsylvania. Linda J. Ewing, PhD Assistant Professor, School of Medicine, Department of Psychiatry, University of Pittsburgh, Pennsylvania. Molly B. Conroy, MD, MPH Assistant Professor, School of Medicine and Graduate School of Public Health, Departments of Medicine and Epidemiology, University of Pittsburgh, Pennsylvania. Karen Glanz, PhD, MPH Professor, Schools of Nursing and Medicine, University of Pennsylvania, Philadelphia. Yaguang Zheng, MSN Graduate Student Researcher, Department of Health and Community Systems, School of Nursing, University of Pittsburgh, Pennsylvania. Rachel W. Goode, MSW Graduate Student Researcher, School of Social Work and Graduate School of Public Health, University of Pittsburgh, Pennsylvania. Meghan Mattos, MSN Graduate Student Researcher, School of Nursing, De
Abstract
BACKGROUND: Evidence supports the role of feedback in reinforcing motivation for behavior change. Feedback that provides reinforcement has the potential to increase dietary self-monitoring and enhance attainment of recommended dietary intake. OBJECTIVE: The aim of this study was to examine the impact of daily feedback (DFB) messages, delivered remotely, on changes in dietary intake. METHODS: This was a secondary analysis of the Self- Monitoring And Recording using Technology (SMART) Trial, a single-center, 24-month randomized clinical trial of behavioral treatment for weight loss. Participants included 210 obese adults (mean body mass index, 34.0 kg/m²) who were randomized to either a paper diary (PD), personal digital assistant (PDA), or PDA plus daily tailored feedback messages (PDA + FB). To determine the role of daily tailored feedback in dietary intake, we compared the self-monitoring with DFBgroup (DFB group; n = 70) with the self-monitoring without DFB group (no-DFB group, n = 140). All participants received a standard behavioral intervention for weight loss. Self-reported changes in dietary intake were compared between the DFB and no-DFB groups and were measured at baseline and at 6, 12, 18, and 24 months. Linear mixed modeling was used to examine percentage changes in dietary intake from baseline. RESULTS: Compared with the no-DFB group, the DFB group achieved a larger reduction in energy (-22.8% vs -14.0%; P = .02) and saturated fat (-11.3% vs -0.5%; P = .03) intake and a trend toward a greater decrease in total fat intake (-10.4% vs -4.7%; P = .09). There were significant improvements over time in carbohydrate intake and total fat intake for both groups (P values < .05). CONCLUSION: Daily tailored feedback messages designed to target energy and fat intake and delivered remotely in real time using mobile devices may play an important role in the reduction of energy and fat intake.
RCT Entities:
BACKGROUND: Evidence supports the role of feedback in reinforcing motivation for behavior change. Feedback that provides reinforcement has the potential to increase dietary self-monitoring and enhance attainment of recommended dietary intake. OBJECTIVE: The aim of this study was to examine the impact of daily feedback (DFB) messages, delivered remotely, on changes in dietary intake. METHODS: This was a secondary analysis of the Self- Monitoring And Recording using Technology (SMART) Trial, a single-center, 24-month randomized clinical trial of behavioral treatment for weight loss. Participants included 210 obese adults (mean body mass index, 34.0 kg/m²) who were randomized to either a paper diary (PD), personal digital assistant (PDA), or PDA plus daily tailored feedback messages (PDA + FB). To determine the role of daily tailored feedback in dietary intake, we compared the self-monitoring with DFB group (DFB group; n = 70) with the self-monitoring without DFB group (no-DFB group, n = 140). All participants received a standard behavioral intervention for weight loss. Self-reported changes in dietary intake were compared between the DFB and no-DFB groups and were measured at baseline and at 6, 12, 18, and 24 months. Linear mixed modeling was used to examine percentage changes in dietary intake from baseline. RESULTS: Compared with the no-DFB group, the DFB group achieved a larger reduction in energy (-22.8% vs -14.0%; P = .02) and saturated fat (-11.3% vs -0.5%; P = .03) intake and a trend toward a greater decrease in total fat intake (-10.4% vs -4.7%; P = .09). There were significant improvements over time in carbohydrate intake and total fat intake for both groups (P values < .05). CONCLUSION: Daily tailored feedback messages designed to target energy and fat intake and delivered remotely in real time using mobile devices may play an important role in the reduction of energy and fat intake.
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