The relationship between self-monitoring, outcome expectancies, difficulties with eating and exercise, and physical activity and weight loss treatment outcomes

Carels, Robert A.; Darby, Lynn A.; Rydin, Sofia; Douglass, Olivia M.; Cacciapaglia, Holly; O’Brien, William H.

doi:10.1207/s15324796abm3003_2

Cited by 105 publications

(104 citation statements)

References 24 publications

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“…Self-monitoring exercise has been shown to be related to weight loss. 15 Most trials examining PA self-monitoring frequency have used paper journals for self-monitoring. 4 In one of the few behavioral weight loss studies examining mobile PA self-monitoring, researchers found that a wearable, mobile sensor to self-monitor PA enhanced a behavioral weight loss intervention over no electronic PA monitoring.…”

Section: Discussionmentioning

confidence: 99%

Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program

Turner‐McGrievy

Beets

Moore

et al. 2013

Journal of the American Medical Informatics Association

345

292

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Objective Self-monitoring of physical activity (PA) and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors. Materials and methods This study is a post hoc analysis of a 6-month randomized weight loss trial among 96 overweight men and women (body mass index (BMI) 25-45 kg/m 2 ) conducted from 2010 to 2011. Participants in both randomized groups were collapsed and categorized by their chosen selfmonitoring method for diet and PA. All participants received a behavioral weight loss intervention delivered via podcast and were encouraged to self-monitor dietary intake and PA. Results Adjusting for randomized group and demographics, PA app users self-monitored exercise more frequently over the 6-month study (2.6±0.5 days/week) and reported greater intentional PA (196.4±45.9 kcal/day) than non-app users (1.2±0.5 days/week PA self-monitoring, p<0.01; 100.9±45.1 kcal/day intentional PA, p=0.02). PA app users also had a significantly lower BMI at 6 months (31.5±0.5 kg/m 2 ) than non-users (32.5±0.5 kg/m 2 ; p=0.02). Frequency of self-monitoring did not differ by diet self-monitoring method ( p=0.63); however, app users consumed less energy (1437±188 kcal/day) than paper journal users (2049±175 kcal/day; p=0.01) at 6 months. BMI did not differ among the three diet monitoring methods ( p=0.20). Conclusions These findings point to potential benefits of mobile monitoring methods during behavioral weight loss trials. Future studies should examine ways to predict which self-monitoring method works best for an individual to increase adherence. BACKGROUND AND SIGNIFICANCE

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Section: Discussionmentioning

confidence: 99%

Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program

Turner‐McGrievy

Beets

Moore

et al. 2013

Journal of the American Medical Informatics Association

345

292

View full text Add to dashboard Cite

show abstract

“…These findings support several studies that have shown a positive association between self- monitoring and PA change. [58][59][60][61][62] In the present study, the Fitbit tracker allowed participants to access quick readings of their PA performance throughout the day. It is unclear as to why comparison participants were more engaged compared with those in the intervention.…”

Section: Self-monitoring (Fitbit One) Onlymentioning

confidence: 99%

Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial

Wang

Cadmus-Bertram

Natarajan

et al. 2015

Telemedicine and e-Health

286

266

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“…34,42 In conjunction with self-monitoring that allows AYAs to identify patterns of exercise and barriers to engagement, problem-solving skills training to generate solutions to identified barriers is also a well-supported strategy to improve health behavior engagement in several chronic illness groups. 63 Problem-solving skills training generally consists of the following components: defining the problem, generating alternative solutions, deciding on a solution, and implementing and evaluating the solution. Providing AYAs with the skills to systematically think through any barriers or issues they experience when attempting to exercise will not only allow them to work through these barriers, but it will provide them with the skills necessary to independently think through barriers that may arise in the future.…”

Section: Problem-solving Skills Trainingmentioning

confidence: 99%

Strategies to promote regular exercise in adolescent and young adult cancer survivors

Barnes

Casazza²,

Austin³

2015

COAYA

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Adolescents and young adults (AYAs) diagnosed with cancer are at increased risk for current and future health problems and premature death. Given the known risks for increased mortality and morbidity, fostering the development of exercise behaviors that may target the specific late effects experienced by AYA cancer survivors is crucial for healthy aging. Exercise is particularly important in the mitigation of late effects as it alters metabolic pathways that ultimately influence the development of chronic diseases associated with cancer treatment in AYAs. Despite the importance of exercise, a large proportion of AYA survivors do not meet recommended guidelines for exercise. The current review summarizes the beneficial effects of exercise in AYA survivors, evaluates strategies utilized in interventions that have been developed to address exercise engagement, and provides recommendations for psychosocial strategies on how to improve these behaviors in this population. A total of nine empirical articles examining exercise interventions in AYAs with a history of cancer were included for review. While several exercise strategies appear promising, more research is needed to evaluate long-term influence of strategies on exercise engagement, as well as the interactions these strategies have on AYA exercise maintenance and health outcomes as they continue into adulthood. Future interventions should evaluate key psychosocial strategies to increase both short-and long-term exercise adherence as well as overall health benefits.

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The relationship between self-monitoring, outcome expectancies, difficulties with eating and exercise, and physical activity and weight loss treatment outcomes

Abstract: Interventions that are targeted to increase self-monitoring and to improve transient difficulties with exercise and diminished outcome expectancies may improve BWLP treatment outcomes.

Cited by 105 publications

References 24 publications

Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program

Comparison of traditional versus mobile app self-monitoring of physical activity and dietary intake among overweight adults participating in an mHealth weight loss program

Wearable Sensor/Device (Fitbit One) and SMS Text-Messaging Prompts to Increase Physical Activity in Overweight and Obese Adults: A Randomized Controlled Trial

Strategies to promote regular exercise in adolescent and young adult cancer survivors

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