Literature DB >> 25631561

Social embeddedness in an online weight management programme is linked to greater weight loss.

Julia Poncela-Casasnovas1, Bonnie Spring2, Daniel McClary1, Arlen C Moller3, Rufaro Mukogo4, Christine A Pellegrini2, Michael J Coons2, Miriam Davidson2, Satyam Mukherjee5, Luis A Nunes Amaral6.   

Abstract

The obesity epidemic is heightening chronic disease risk globally. Online weight management (OWM) communities could potentially promote weight loss among large numbers of people at low cost. Because little is known about the impact of these online communities, we examined the relationship between individual and social network variables, and weight loss in a large, international OWM programme. We studied the online activity and weight change of 22,419 members of an OWM system during a six-month period, focusing especially on the 2033 members with at least one friend within the community. Using Heckman's sample-selection procedure to account for potential selection bias and data censoring, we found that initial body mass index, adherence to self-monitoring and social networking were significantly correlated with weight loss. Remarkably, greater embeddedness in the network was the variable with the highest statistical significance in our model for weight loss. Average per cent weight loss at six months increased in a graded manner from 4.1% for non-networked members, to 5.2% for those with a few (two to nine) friends, to 6.8% for those connected to the giant component of the network, to 8.3% for those with high social embeddedness. Social networking within an OWM community, and particularly when highly embedded, may offer a potent, scalable way to curb the obesity epidemic and other disorders that could benefit from behavioural changes.
© 2015 The Author(s) Published by the Royal Society. All rights reserved.

Entities:  

Keywords:  complex networks; modelling; obesity; weight loss

Mesh:

Year:  2015        PMID: 25631561      PMCID: PMC4345465          DOI: 10.1098/rsif.2014.0686

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  29 in total

1.  An experimental study of homophily in the adoption of health behavior.

Authors:  Damon Centola
Journal:  Science       Date:  2011-12-02       Impact factor: 47.728

Review 2.  The impact of Internet use for weight loss.

Authors:  S L Saperstein; N L Atkinson; R S Gold
Journal:  Obes Rev       Date:  2007-09       Impact factor: 9.213

3.  The Diabetes Prevention Program. Design and methods for a clinical trial in the prevention of type 2 diabetes.

Authors: 
Journal:  Diabetes Care       Date:  1999-04       Impact factor: 19.112

4.  Effect of length of treatment on weight loss.

Authors:  M G Perri; A M Nezu; E T Patti; K L McCann
Journal:  J Consult Clin Psychol       Date:  1989-06

5.  Exploiting social networks to mitigate the obesity epidemic.

Authors:  David B Bahr; Raymond C Browning; Holly R Wyatt; James O Hill
Journal:  Obesity (Silver Spring)       Date:  2009-01-15       Impact factor: 5.002

Review 6.  Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up.

Authors:  Marion J Franz; Jeffrey J VanWormer; A Lauren Crain; Jackie L Boucher; Trina Histon; William Caplan; Jill D Bowman; Nicolas P Pronk
Journal:  J Am Diet Assoc       Date:  2007-10

7.  Does using the Internet facilitate the maintenance of weight loss?

Authors:  J Harvey-Berino; S Pintauro; P Buzzell; M DiGiulio; B Casey Gold; C Moldovan; E Ramirez
Journal:  Int J Obes Relat Metab Disord       Date:  2002-09

8.  Collective behavior in the spatial spreading of obesity.

Authors:  Lazaros K Gallos; Pablo Barttfeld; Shlomo Havlin; Mariano Sigman; Hernán A Makse
Journal:  Sci Rep       Date:  2012-06-14       Impact factor: 4.379

9.  Searching for superspreaders of information in real-world social media.

Authors:  Sen Pei; Lev Muchnik; José S Andrade; Zhiming Zheng; Hernán A Makse
Journal:  Sci Rep       Date:  2014-07-03       Impact factor: 4.379

10.  Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers.

Authors:  Sushama D Acharya; Okan U Elci; Susan M Sereika; Edvin Music; Mindi A Styn; Melanie Warziski Turk; Lora E Burke
Journal:  Patient Prefer Adherence       Date:  2009-11-03       Impact factor: 2.711

View more
  10 in total

1.  Factors associated with long-term wearable physical activity monitor user engagement.

Authors:  Ciarán P Friel; Talea Cornelius; Keith M Diaz
Journal:  Transl Behav Med       Date:  2021-02-11       Impact factor: 3.046

Review 2.  Do weight management interventions delivered by online social networks effectively improve body weight, body composition, and chronic disease risk factors? A systematic review.

Authors:  Erik A Willis; Amanda N Szabo-Reed; Lauren T Ptomey; Felicia L Steger; Jeffery J Honas; Richard A Washburn; Joseph E Donnelly
Journal:  J Telemed Telecare       Date:  2016-07-09       Impact factor: 6.184

3.  Utilizing Digital Health Technologies for Patient Education in Lifestyle Medicine.

Authors:  Anne Kuwabara; Sharlene Su; Jeffrey Krauss
Journal:  Am J Lifestyle Med       Date:  2019-12-13

4.  Applying and advancing behavior change theories and techniques in the context of a digital health revolution: proposals for more effectively realizing untapped potential.

Authors:  Arlen C Moller; Gina Merchant; David E Conroy; Robert West; Eric Hekler; Kari C Kugler; Susan Michie
Journal:  J Behav Med       Date:  2017-01-05

5.  The statistical mechanics of human weight change.

Authors:  John C Lang; Hans De Sterck; Daniel M Abrams
Journal:  PLoS One       Date:  2017-12-18       Impact factor: 3.240

6.  Effects of an abbreviated obesity intervention supported by mobile technology: The ENGAGED randomized clinical trial.

Authors:  Bonnie Spring; Christine A Pellegrini; Angela Pfammatter; Jennifer M Duncan; Alex Pictor; H Gene McFadden; Juned Siddique; Donald Hedeker
Journal:  Obesity (Silver Spring)       Date:  2017-05-11       Impact factor: 5.002

7.  Health and Wellness Coaching Implemented by Trainees: Impact in Worksite Wellness.

Authors:  Jared Blackwell; Karen Gregory-Mercado; Michael Collins; Jose Guillen; Christina Scribner; Karen Moses
Journal:  Glob Adv Health Med       Date:  2019-02-27

8.  The first step is recognizing there is a problem: a methodology for adjusting for variability in disease severity when estimating clinician performance.

Authors:  Meagan Bechel; Adam R Pah; Stephen D Persell; Curtis H Weiss; Luís A Nunes Amaral
Journal:  BMC Med Res Methodol       Date:  2022-03-16       Impact factor: 4.615

9.  Development of a Weight Loss Mobile App Linked With an Accelerometer for Use in the Clinic: Usability, Acceptability, and Early Testing of its Impact on the Patient-Doctor Relationship.

Authors:  Seryung Choo; Ju Young Kim; Se Young Jung; Sarah Kim; Jeong Eun Kim; Jong Soo Han; Sohye Kim; Jeong Hyun Kim; Jeehye Kim; Yongseok Kim; Dongouk Kim; Steve Steinhubl
Journal:  JMIR Mhealth Uhealth       Date:  2016-03-31       Impact factor: 4.773

10.  Adapting Behavioral Interventions for Social Media Delivery.

Authors:  Sherry Pagoto; Molly E Waring; Christine N May; Eric Y Ding; Werner H Kunz; Rashelle Hayes; Jessica L Oleski
Journal:  J Med Internet Res       Date:  2016-01-29       Impact factor: 5.428

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.