Literature DB >> 27292942

Adherence as a predictor of weight loss in a commonly used smartphone application.

Stephanie Jacobs1, Cynthia Radnitz2, Tom Hildebrandt3.   

Abstract

As adherence to weight loss interventions has been shown in prior research to be crucial in achieving weight reduction, we were interested in examining whether this held true for individuals attempting to lose weight using smartphone applications. Archived data from an international community sample of 7633 overweight men and women using Noom, a smartphone-based behavioural weight loss program, were used to test the hypotheses that there would be significant weight loss after using the application for three months and that greater self-monitoring adherence would be positively associated with weight loss outcomes. An average 1.92 BMI points were lost after using Noom for three months, and for every 10% increase in adherence there was a decrease of 2.59 BMI points (β=-1.36kg, SE=.24, p<.001). Our results provide preliminary evidence suggesting that smartphone application use is linked to significant short-term weight loss and that this weight loss is associated with adherence.
Copyright © 2016 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Behavioural modification; Obesity; Smartphone; Technology; Weight loss

Mesh:

Year:  2016        PMID: 27292942     DOI: 10.1016/j.orcp.2016.05.001

Source DB:  PubMed          Journal:  Obes Res Clin Pract        ISSN: 1871-403X            Impact factor:   2.288


  14 in total

1.  Weight Loss Trajectories and Related Factors in a 16-Week Mobile Obesity Intervention Program: Retrospective Observational Study.

Authors:  Ho Heon Kim; Youngin Kim; Andreas Michaelides; Yu Rang Park
Journal:  J Med Internet Res       Date:  2022-04-15       Impact factor: 7.076

2.  Engagement and outcomes in a digital Diabetes Prevention Program: 3-year update.

Authors:  S Cameron Sepah; Luohua Jiang; Robert J Ellis; Kelly McDermott; Anne L Peters
Journal:  BMJ Open Diabetes Res Care       Date:  2017-09-07

3.  A Digital Health Weight Loss Program in 250,000 Individuals.

Authors:  Conor Senecal; Robert Jay Widmer; Beth R Larrabee; Mariza de Andrade; Lilach O Lerman; Amir Lerman; Francisco Lopez-Jimenez
Journal:  J Obes       Date:  2020-03-26

4.  Psychosocial Characteristics by Weight Loss and Engagement in a Digital Intervention Supporting Self-Management of Weight.

Authors:  Ellen S Mitchell; Qiuchen Yang; Heather Behr; Annabell Ho; Laura DeLuca; Christine N May; Andreas Michaelides
Journal:  Int J Environ Res Public Health       Date:  2021-02-10       Impact factor: 3.390

Review 5.  Efficacy of Interventions That Incorporate Mobile Apps in Facilitating Weight Loss and Health Behavior Change in the Asian Population: Systematic Review and Meta-analysis.

Authors:  Siew Min Ang; Juliana Chen; Jia Huan Liew; Jolyn Johal; Yock Young Dan; Margaret Allman-Farinelli; Su Lin Lim
Journal:  J Med Internet Res       Date:  2021-11-16       Impact factor: 5.428

6.  Cross-National Outcomes of a Digital Weight Loss Intervention in the United States, Canada, United Kingdom and Ireland, and Australia and New Zealand: A Retrospective Analysis.

Authors:  Qiuchen Yang; Ellen Siobhan Mitchell; Annabell S Ho; Laura DeLuca; Heather Behr; Andreas Michaelides
Journal:  Front Public Health       Date:  2021-06-10

Review 7.  Precision medicine in adult and pediatric obesity: a clinical perspective.

Authors:  Eric M Bomberg; Justin R Ryder; Richard C Brundage; Robert J Straka; Claudia K Fox; Amy C Gross; Megan M Oberle; Carolyn T Bramante; Shalamar D Sibley; Aaron S Kelly
Journal:  Ther Adv Endocrinol Metab       Date:  2019-07-27       Impact factor: 3.565

8.  Effect of mHealth With Offline Antiobesity Treatment in a Community-Based Weight Management Program: Cross-Sectional Study.

Authors:  Youngin Kim; Bumjo Oh; Hyun-Young Shin
Journal:  JMIR Mhealth Uhealth       Date:  2020-01-21       Impact factor: 4.773

9.  A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment.

Authors:  Julia A Schweiger; Ginger E Nicol; Amanda R Ricchio; Christopher L Metts; Michael D Yingling; Alex T Ramsey; J Philip Miller; Eric J Lenze
Journal:  JMIR Mhealth Uhealth       Date:  2020-11-13       Impact factor: 4.773

10.  Refining an algorithm-powered just-in-time adaptive weight control intervention: A randomized controlled trial evaluating model performance and behavioral outcomes.

Authors:  Stephanie P Goldstein; J Graham Thomas; Gary D Foster; Gabrielle Turner-McGrievy; Meghan L Butryn; James D Herbert; Gerald J Martin; Evan M Forman
Journal:  Health Informatics J       Date:  2020-02-06       Impact factor: 2.681

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