Christine A Pellegrini1, David E Conroy2, Siobhan M Phillips3, Angela Fidler Pfammatter3, H Gene McFadden3, Bonnie Spring3. 1. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL. Electronic address: c-pellegrini@northwestern.edu. 2. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; Department of Kinesiology and Human Development and Family Studies, Pennsylvania State University, University Park, PA. 3. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Abstract
OBJECTIVE: To examine within-person variation in dietary self-monitoring during a 6-month technology-supported weight loss trial as a function of time-varying factors including time in the study, day of the week, and month of the year. METHODS: Smartphone self-monitoring data were examined from 31 obese adults (aged 18-60 years) who participated in a 6-month technology-supported weight loss program. Multilevel regression modeling was used to examine within-person variation in dietary self-monitoring. RESULTS: Participants recorded less as time in the study progressed. Fewer foods were reported on the weekends compared with weekdays. More foods were self-monitored in January compared with October; however, a seasonal effect was not observed. CONCLUSIONS AND IMPLICATIONS: The amount of time in a study and day of the week were associated with dietary self-monitoring but not season. Future studies should examine factors that influence variations in self-monitoring and identify methods to improve technology-supported dietary self-monitoring adherence.
RCT Entities:
OBJECTIVE: To examine within-person variation in dietary self-monitoring during a 6-month technology-supported weight loss trial as a function of time-varying factors including time in the study, day of the week, and month of the year. METHODS: Smartphone self-monitoring data were examined from 31 obese adults (aged 18-60 years) who participated in a 6-month technology-supported weight loss program. Multilevel regression modeling was used to examine within-person variation in dietary self-monitoring. RESULTS:Participants recorded less as time in the study progressed. Fewer foods were reported on the weekends compared with weekdays. More foods were self-monitored in January compared with October; however, a seasonal effect was not observed. CONCLUSIONS AND IMPLICATIONS: The amount of time in a study and day of the week were associated with dietary self-monitoring but not season. Future studies should examine factors that influence variations in self-monitoring and identify methods to improve technology-supported dietary self-monitoring adherence.
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