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Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study

BACKGROUND: Electronic self-monitoring technology has the potential to provide unique insights into important behaviors for inducing weight loss. OBJECTIVE: The aim of this study is to investigate the effects of electronic self-monitoring behavior (using the commercial Lose It! app) and weight loss...

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Autores principales: Farage, Gregory, Simmons, Courtney, Kocak, Mehmet, Klesges, Robert C, Talcott, G Wayne, Richey, Phyllis, Hare, Marion, Johnson, Karen C, Sen, Saunak, Krukowski, Rebecca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319781/
https://www.ncbi.nlm.nih.gov/pubmed/34259635
http://dx.doi.org/10.2196/18741
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author Farage, Gregory
Simmons, Courtney
Kocak, Mehmet
Klesges, Robert C
Talcott, G Wayne
Richey, Phyllis
Hare, Marion
Johnson, Karen C
Sen, Saunak
Krukowski, Rebecca
author_facet Farage, Gregory
Simmons, Courtney
Kocak, Mehmet
Klesges, Robert C
Talcott, G Wayne
Richey, Phyllis
Hare, Marion
Johnson, Karen C
Sen, Saunak
Krukowski, Rebecca
author_sort Farage, Gregory
collection PubMed
description BACKGROUND: Electronic self-monitoring technology has the potential to provide unique insights into important behaviors for inducing weight loss. OBJECTIVE: The aim of this study is to investigate the effects of electronic self-monitoring behavior (using the commercial Lose It! app) and weight loss interventions (with differing amounts of counselor feedback and support) on 4- and 12-month weight loss. METHODS: In this secondary analysis of the Fit Blue study, we compared the results of two interventions of a randomized controlled trial. Counselor-initiated participants received consistent support from the interventionists, and self-paced participants received assistance upon request. The participants (N=191), who were active duty military personnel, were encouraged to self-monitor their diet and exercise with the Lose It! app or website. We examined the associations between intervention assignment and self-monitoring behaviors. We conducted a mediation analysis of the intervention assignment for weight loss through multiple mediators—app use (calculated from the first principal component [PC] of electronically collected variables), number of weigh-ins, and 4-month weight change. We used linear regression to predict weight loss at 4 and 12 months, and the accuracy was measured using cross-validation. RESULTS: On average, the counselor-initiated–treatment participants used the app more frequently than the self-paced–treatment participants. The first PC represented app use frequencies, the second represented calories recorded, and the third represented reported exercise frequency and exercise caloric expenditure. We found that 4-month weight loss was partially mediated through app use (ie, the first PC; 60.3%) and the number of weigh-ins (55.8%). However, the 12-month weight loss was almost fully mediated by 4-month weight loss (94.8%). Linear regression using app data from the first 8 weeks, the number of self–weigh-ins at 8 weeks, and baseline data explained approximately 30% of the variance in 4-month weight loss. App use frequency (first PC; P=.001), self-monitored caloric intake (second PC; P=.001), and the frequency of self-weighing at 8 weeks (P=.008) were important predictors of 4-month weight loss. Predictions for 12-month weight with the same variables produced an R(2) value of 5%; only the number of self–weigh-ins was a significant predictor of 12-month weight loss. The R(2) value using 4-month weight loss as a predictor was 31%. Self-reported exercise did not contribute to either model (4 months: P=.77; 12 months: P=.15). CONCLUSIONS: We found that app use and daily reported caloric intake had a substantial impact on weight loss prediction at 4 months. Our analysis did not find evidence of an association between participant self-monitoring exercise information and weight loss. As 12-month weight loss was completely mediated by 4-month weight loss, intervention targets should focus on promoting early and frequent dietary intake self-monitoring and self-weighing to promote early weight loss, which leads to long-term success. TRIAL REGISTRATION: ClinicalTrials.gov NCT02063178; https://clinicaltrials.gov/ct2/show/NCT02063178
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spelling pubmed-83197812021-08-11 Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study Farage, Gregory Simmons, Courtney Kocak, Mehmet Klesges, Robert C Talcott, G Wayne Richey, Phyllis Hare, Marion Johnson, Karen C Sen, Saunak Krukowski, Rebecca JMIR Mhealth Uhealth Original Paper BACKGROUND: Electronic self-monitoring technology has the potential to provide unique insights into important behaviors for inducing weight loss. OBJECTIVE: The aim of this study is to investigate the effects of electronic self-monitoring behavior (using the commercial Lose It! app) and weight loss interventions (with differing amounts of counselor feedback and support) on 4- and 12-month weight loss. METHODS: In this secondary analysis of the Fit Blue study, we compared the results of two interventions of a randomized controlled trial. Counselor-initiated participants received consistent support from the interventionists, and self-paced participants received assistance upon request. The participants (N=191), who were active duty military personnel, were encouraged to self-monitor their diet and exercise with the Lose It! app or website. We examined the associations between intervention assignment and self-monitoring behaviors. We conducted a mediation analysis of the intervention assignment for weight loss through multiple mediators—app use (calculated from the first principal component [PC] of electronically collected variables), number of weigh-ins, and 4-month weight change. We used linear regression to predict weight loss at 4 and 12 months, and the accuracy was measured using cross-validation. RESULTS: On average, the counselor-initiated–treatment participants used the app more frequently than the self-paced–treatment participants. The first PC represented app use frequencies, the second represented calories recorded, and the third represented reported exercise frequency and exercise caloric expenditure. We found that 4-month weight loss was partially mediated through app use (ie, the first PC; 60.3%) and the number of weigh-ins (55.8%). However, the 12-month weight loss was almost fully mediated by 4-month weight loss (94.8%). Linear regression using app data from the first 8 weeks, the number of self–weigh-ins at 8 weeks, and baseline data explained approximately 30% of the variance in 4-month weight loss. App use frequency (first PC; P=.001), self-monitored caloric intake (second PC; P=.001), and the frequency of self-weighing at 8 weeks (P=.008) were important predictors of 4-month weight loss. Predictions for 12-month weight with the same variables produced an R(2) value of 5%; only the number of self–weigh-ins was a significant predictor of 12-month weight loss. The R(2) value using 4-month weight loss as a predictor was 31%. Self-reported exercise did not contribute to either model (4 months: P=.77; 12 months: P=.15). CONCLUSIONS: We found that app use and daily reported caloric intake had a substantial impact on weight loss prediction at 4 months. Our analysis did not find evidence of an association between participant self-monitoring exercise information and weight loss. As 12-month weight loss was completely mediated by 4-month weight loss, intervention targets should focus on promoting early and frequent dietary intake self-monitoring and self-weighing to promote early weight loss, which leads to long-term success. TRIAL REGISTRATION: ClinicalTrials.gov NCT02063178; https://clinicaltrials.gov/ct2/show/NCT02063178 JMIR Publications 2021-07-14 /pmc/articles/PMC8319781/ /pubmed/34259635 http://dx.doi.org/10.2196/18741 Text en ©Gregory Farage, Courtney Simmons, Mehmet Kocak, Robert C Klesges, G Wayne Talcott, Phyllis Richey, Marion Hare, Karen C Johnson, Saunak Sen, Rebecca Krukowski. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 14.07.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Farage, Gregory
Simmons, Courtney
Kocak, Mehmet
Klesges, Robert C
Talcott, G Wayne
Richey, Phyllis
Hare, Marion
Johnson, Karen C
Sen, Saunak
Krukowski, Rebecca
Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title_full Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title_fullStr Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title_full_unstemmed Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title_short Assessing the Contribution of Self-Monitoring Through a Commercial Weight Loss App: Mediation and Predictive Modeling Study
title_sort assessing the contribution of self-monitoring through a commercial weight loss app: mediation and predictive modeling study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8319781/
https://www.ncbi.nlm.nih.gov/pubmed/34259635
http://dx.doi.org/10.2196/18741
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