Literature DB >> 22212418

Structural social support predicts functional social support in an online weight loss programme.

Kevin O Hwang1, Jason M Etchegaray, Christopher N Sciamanna, Elmer V Bernstam, Eric J Thomas.   

Abstract

BACKGROUND: Online weight loss programmes allow members to use social media tools to give and receive social support for weight loss. However, little is known about the relationship between the use of social media tools and the perception of specific types of support.
OBJECTIVE: To test the hypothesis that the frequency of using social media tools (structural support) is directly related to perceptions of Encouragement, Information and Shared Experiences support (functional support).
DESIGN: Online survey. PARTICIPANTS: Members of an online weight loss programme.
METHODS: The outcome was the perception of Encouragement (motivation, congratulations), Information (advice, tips) and Shared Experiences (belonging to a group) social support. The predictor was a social media scale based on the frequency of using forums and blogs within the online weight loss programme (alpha = 0.91). The relationship between predictor and outcomes was evaluated with structural equation modelling (SEM) and logistic regression, adjusted for sociodemographic characteristics, BMI and duration of website membership.
RESULTS: The 187 participants were mostly female (95%) and white (91%), with mean (SD) age 37 (12) years and mean (SD) BMI 31 (8). SEM produced a model in which social media use predicted Encouragement support, but not Information or Shared Experiences support. Participants who used the social media tools at least weekly were almost five times as likely to experience Encouragement support compared to those who used the features less frequently [adjusted OR 4.8 (95% CI 1.8-12.8)].
CONCLUSIONS: Using the social media tools of an online weight loss programme at least once per week is strongly associated with receiving Encouragement for weight loss behaviours.
© 2011 John Wiley & Sons Ltd.

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Year:  2012        PMID: 22212418      PMCID: PMC5060736          DOI: 10.1111/j.1369-7625.2011.00759.x

Source DB:  PubMed          Journal:  Health Expect        ISSN: 1369-6513            Impact factor:   3.377


  21 in total

1.  Measuring social support for weight loss in an internet weight loss community.

Authors:  Kevin O Hwang; Allison J Ottenbacher; Joseph F Lucke; Jason M Etchegaray; Amanda L Graham; Eric J Thomas; Elmer V Bernstam
Journal:  J Health Commun       Date:  2011-02

2.  Weight loss on the web: A pilot study comparing a structured behavioral intervention to a commercial program.

Authors:  Beth Casey Gold; Susan Burke; Stephen Pintauro; Paul Buzzell; Jean Harvey-Berino
Journal:  Obesity (Silver Spring)       Date:  2007-01       Impact factor: 5.002

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4.  Using Internet technology to deliver a behavioral weight loss program.

Authors:  D F Tate; R R Wing; R A Winett
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Journal:  Obes Rev       Date:  2005-02       Impact factor: 9.213

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Authors:  Janice F Bell; Frederick J Zimmerman; David E Arterburn; Matthew L Maciejewski
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7.  Minimal in-person support as an adjunct to internet obesity treatment.

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Journal:  Ann Behav Med       Date:  2007-02

8.  Associations of internet website use with weight change in a long-term weight loss maintenance program.

Authors:  Kristine L Funk; Victor J Stevens; Lawrence J Appel; Alan Bauck; Phillip J Brantley; Catherine M Champagne; Janelle Coughlin; Arlene T Dalcin; Jean Harvey-Berino; Jack F Hollis; Gerald J Jerome; Betty M Kennedy; Lillian F Lien; Valerie H Myers; Carmen Samuel-Hodge; Laura P Svetkey; William M Vollmer
Journal:  J Med Internet Res       Date:  2010-07-27       Impact factor: 5.428

9.  Social support in an Internet weight loss community.

Authors:  Kevin O Hwang; Allison J Ottenbacher; Angela P Green; M Roseann Cannon-Diehl; Oneka Richardson; Elmer V Bernstam; Eric J Thomas
Journal:  Int J Med Inform       Date:  2009-11-27       Impact factor: 4.046

10.  Web-based weight loss in primary care: a randomized controlled trial.

Authors:  Gary G Bennett; Sharon J Herring; Elaine Puleo; Evelyn K Stein; Karen M Emmons; Matthew W Gillman
Journal:  Obesity (Silver Spring)       Date:  2009-08-20       Impact factor: 5.002

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2.  Obesity in social media: a mixed methods analysis.

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Journal:  Transl Behav Med       Date:  2014-09       Impact factor: 3.046

3.  Weight loss support seeking on twitter: the impact of weight on follow back rates and interactions.

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Review 4.  The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness.

Authors:  Panos Balatsoukas; Catriona M Kennedy; Iain Buchan; John Powell; John Ainsworth
Journal:  J Med Internet Res       Date:  2015-06-11       Impact factor: 5.428

5.  Website usage and weight loss in a free commercial online weight loss program: retrospective cohort study.

Authors:  Kevin O Hwang; Jing Ning; Amber W Trickey; Christopher N Sciamanna
Journal:  J Med Internet Res       Date:  2013-01-15       Impact factor: 5.428

6.  Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

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Journal:  J Med Internet Res       Date:  2018-02-22       Impact factor: 5.428

Review 7.  A systematic review of the behaviour change techniques and digital features in technology-driven type 2 diabetes prevention interventions.

Authors:  Luke Van Rhoon; Molly Byrne; Eimear Morrissey; Jane Murphy; Jenny McSharry
Journal:  Digit Health       Date:  2020-03-24
  7 in total

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