Brooke T Nezami1, Carmina G Valle1,2, Alison K Nulty3, Mark Espeland4, Rena R Wing5, Deborah F Tate1,2,6. 1. Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 2. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 3. Department of Anthropology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 4. Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA. 5. Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Miriam Hospital, Providence, Rhode Island, USA. 6. Department of Health Behavior, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Abstract
OBJECTIVES: Self-monitoring is critical for weight management, but little is known about lapses in the use of digital self-monitoring. The objectives of this study were to examine whether lapses in self-weighing and wearing activity trackers are associated with weight and activity outcomes and to identify objective predictors of lapses. METHODS: Participants (N = 160, BMI = 25.5 ± 3.3 kg/m2 , 33.1 ± 4.6 years old) were drawn from a sample of young adults in the Study of Novel Approaches to Prevention-Extension (SNAP-E) weight gain prevention trial. Analyses evaluated associations between weighing and tracker lapses and changes in weight and steps/day during the first 90 days after receiving a smart scale and activity tracker. RESULTS: On average, participants self-weighed 49.6% of days and wore activity trackers 75.2% of days. Every 1-day increase in a weighing lapse was associated with a 0.06-lb gain. Lapses in tracker wear were not associated with changes in steps/day or weight between wear days. Weight gain predicted a higher likelihood of starting a lapse in weighing and tracker wear, whereas lower steps predicted a higher likelihood of a tracker lapse. CONCLUSIONS: Weight gain may discourage adherence to self-monitoring. Future research could examine just-in-time supports to anticipate and reduce the frequency or length of self-monitoring lapses.
OBJECTIVES: Self-monitoring is critical for weight management, but little is known about lapses in the use of digital self-monitoring. The objectives of this study were to examine whether lapses in self-weighing and wearing activity trackers are associated with weight and activity outcomes and to identify objective predictors of lapses. METHODS: Participants (N = 160, BMI = 25.5 ± 3.3 kg/m2 , 33.1 ± 4.6 years old) were drawn from a sample of young adults in the Study of Novel Approaches to Prevention-Extension (SNAP-E) weight gain prevention trial. Analyses evaluated associations between weighing and tracker lapses and changes in weight and steps/day during the first 90 days after receiving a smart scale and activity tracker. RESULTS: On average, participants self-weighed 49.6% of days and wore activity trackers 75.2% of days. Every 1-day increase in a weighing lapse was associated with a 0.06-lb gain. Lapses in tracker wear were not associated with changes in steps/day or weight between wear days. Weight gain predicted a higher likelihood of starting a lapse in weighing and tracker wear, whereas lower steps predicted a higher likelihood of a tracker lapse. CONCLUSIONS: Weight gain may discourage adherence to self-monitoring. Future research could examine just-in-time supports to anticipate and reduce the frequency or length of self-monitoring lapses.
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