Coach access to digital self-monitoring data: an experimental test of short-term effects in behavioral weight-loss treatment.
Journal
Obesity (Silver Spring, Md.)
ISSN: 1930-739X
Titre abrégé: Obesity (Silver Spring)
Pays: United States
ID NLM: 101264860
Informations de publication
Date de publication:
02 Oct 2024
02 Oct 2024
Historique:
revised:
16
07
2024
received:
03
06
2024
accepted:
31
07
2024
medline:
3
10
2024
pubmed:
3
10
2024
entrez:
3
10
2024
Statut:
aheadofprint
Résumé
This study experimentally tested whether coach access to participants' digital self-monitoring data improved behavioral weight-loss outcomes. Participants (N = 322) received 12 weeks of group-based behavioral weight-loss sessions via videoconference and were instructed to engage in daily self-monitoring of weight, physical activity (PA), and dietary intake. For participants who were randomly assigned to Coach Share ON (n = 161), coaches regularly accessed a web-based portal that displayed data from the participants' scale, PA sensor, and food record. Weight loss at 12 weeks was significantly greater in Coach Share ON versus OFF (6.2% vs. 5.3%; p = 0.04). Self-monitoring of PA (98.70% vs. 97.40% of days; p = 0.006) and eating (98.05% vs. 93.51% of days; p = 0.007) was more frequent in Coach Share ON versus OFF. There were no significant differences by condition in PA (p = 0.57), attendance (p = 0.42), working alliance (p = 0.62), or self-monitoring of weight (p = 0.12). Perceived supportive accountability was significantly greater in Coach Share ON versus OFF (p < 0.001). The short-term efficacy of behavioral weight loss was greater when coaches had direct access to self-monitoring device data. Notably, there also was no evidence of iatrogenic effects of data sharing.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIDDK NIH HHS
ID : R01DK129300
Pays : United States
Informations de copyright
© 2024 The Obesity Society.
Références
Allman‐Farinelli M, Gemming L. Technology interventions to manage food intake: where are we now? Curr Diab Rep. 2017;17(11):103. doi:10.1007/s11892‐017‐0937‐5
Patel ML, Wakayama LN, Bennett GG. Self‐monitoring via digital health in weight loss interventions: a systematic review among adults with overweight or obesity. Obesity (Silver Spring). 2021;29(3):478‐499. doi:10.1002/oby.23088
Hutchesson MJ, Rollo ME, Krukowski R, et al. eHealth interventions for the prevention and treatment of overweight and obesity in adults: a systematic review with meta‐analysis. Obes Rev. 2015;16(5):376‐392. doi:10.1111/obr.12268
Cavero‐Redondo I, Martinez‐Vizcaino V, Fernandez‐Rodriguez R, Saz‐Lara A, Pascual‐Morena C, Álvarez‐Bueno C. Effect of behavioral weight management interventions using lifestyle mHealth self‐monitoring on weight loss: a systematic review and meta‐analysis. Nutrients. 2020;12(7):1977. doi:10.3390/nu12071977
Ufholz K, Bhargava D. A review of telemedicine interventions for weight loss. Curr Cardiovasc Risk Rep. 2021;15(9):17. doi:10.1007/s12170‐021‐00680‐w
Hu L, Illiano P, Pompeii ML, et al. Challenges of conducting a remote behavioral weight loss study: lessons learned and a practical guide. Contemp Clin Trials. 2021;108:106522. doi:10.1016/j.cct.2021.106522
Jain B, Bajaj SS, Stanford FC. Randomized clinical trials of weight loss: pragmatic and digital strategies and innovations. Contemp Clin Trials. 2022;114:106687. doi:10.1016/j.cct.2022.106687
Burke LE, Conroy MB, Sereika SM, et al. The effect of electronic self‐monitoring on weight loss and dietary intake: a randomized behavioral weight loss trial. Obesity (Silver Spring). 2011;19(2):338‐344. doi:10.1038/oby.2010.208
Spring B, Duncan JM, Janke EA, et al. Integrating technology into standard weight loss treatment: a randomized controlled trial. JAMA Intern Med. 2013;173(2):105‐111. doi:10.1001/jamainternmed.2013.1221
Stephens JD, Yager AM, Allen J. Smartphone technology and text messaging for weight loss in young adults: a randomized controlled trial. J Cardiovasc Nurs. 2017;32(1):39‐46. doi:10.1097/JCN.0000000000000307
Ross KM, Wing RR. Impact of newer self‐monitoring technology and brief phone‐based intervention on weight loss: a randomized pilot study. Obesity (Silver Spring). 2016;24(8):1653‐1659. doi:10.1002/oby.21536
Butryn ML, Godfrey KM, Martinelli MK, Roberts SR, Forman EM, Zhang F. Digital self‐monitoring: does adherence or association with outcomes differ by self‐monitoring target? Obes Sci Pract. 2019;6(2):126‐133. doi:10.1002/osp4.391
Miller NA, Ehmann MM, Hagerman CJ, et al. Sharing digital self‐monitoring data with others to enhance long‐term weight loss: a randomized controlled trial. Contemp Clin Trials. 2023;129:107201. doi:10.1016/j.cct.2023.107201
Jensen MD, Ryan DH, Apovian CM, et al. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association task force on practice guidelines and the Obesity Society. J Am Coll Cardiol. 2014;63(25):2985‐3023.
Withings. Scales accuracy in weight and body composition measurement. Accessed March 17, 2023. https://www.withings.com/us/en/health-insights/about-scales-accuracy
Forman EM, Chwyl C, Berry MP, et al. Evaluating the efficacy of mindfulness and acceptance‐based treatment components for weight loss: protocol for a multiphase optimization strategy trial. Contemp Clin Trials. 2021;110:106573. doi:10.1016/j.cct.2021.106573
Krukowski RA, Ross KM. Measuring weight with electronic scales in clinical and research settings during the coronavirus disease 2019 pandemic. Obesity (Silver Spring). 2020;28(7):1182‐1183. doi:10.1002/oby.22851
Vuorinen A, Helander E, Pietilä J, Korhonen I. Frequency of self‐weighing and weight change: cohort study with 10,000 smart scale users. J Med Internet Res. 2021;23(6):e25529. doi:10.2196/25529
Munder T, Wilmers F, Leonhart R, Linster HW, Barth J. Working Alliance Inventory‐Short Revised (WAI‐SR): psychometric properties in outpatients and inpatients. Clin Psychol Psychother. 2010;17(3):231‐239. doi:10.1002/cpp.658
Meyerhoff J, Haldar S, Mohr DC. The Supportive Accountability Inventory: psychometric properties of a measure of supportive accountability in coached digital interventions. Internet Interv. 2021;25:100399. doi:10.1016/j.invent.2021.100399
Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods. 2002;7(2):147‐177.
Graham JW. Missing data analysis: making it work in the real world. Annu Rev Psychol. 2009;60:549‐576. doi:10.1146/annurev.psych.58.110405.085530
Pearl RL, Puhl RM. Weight bias internalization and health: a systematic review. Obes Rev. 2018;19(8):1141‐1163. doi:10.1111/obr.12701
Mohr DC, Cuijpers P, Lehman K. Supportive accountability: a model for providing human support to enhance adherence to eHealth interventions. J Med Internet Res. 2011;13(1):e30. doi:10.2196/jmir.1602
Milsom VA, Malcolm RJ, Johnson GC, et al. Changes in cardiovascular risk factors with participation in a 12‐week weight loss trial using a commercial format. Eat Behav. 2014;15(1):68‐71. doi:10.1016/j.eatbeh.2013.10.004
O'Neil PM, Theim KR, Boeka A, Johnson G, Miller‐Kovach K. Changes in weight control behaviors and hedonic hunger during a 12‐week commercial weight loss program. Eat Behav. 2012;13(4):354‐360. doi:10.1016/j.eatbeh.2012.06.002
Richardson KM, Cota Aguirre G, Weiss R, et al. Abbreviated dietary self‐monitoring for type 2 diabetes management: mixed methods feasibility study. JMIR Diabetes. 2021;6(3):e28930. doi:10.2196/28930
Kwasnicka D, Dombrowski SU, White M, Sniehotta F. Theoretical explanations for maintenance of behaviour change: a systematic review of behaviour theories. Health Psychol Rev. 2016;10(3):277‐296. doi:10.1080/17437199.2016.1151372
Carpenter CA, Ugwoaba UA, Cardel MI, Ross KM. Using self‐monitoring technology for nutritional counseling and weight management. Digit Health. 2022;8:20552076221102774. doi:10.1177/20552076221102774