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

A healthcare social media research article published in Translational Behavioral Medicine, July 20, 2016

Title
Weight loss support seeking on twitter: the impact of weight on follow back rates and interactions
Authors (alpha)
Christine N. May, Effie Olendzki, Jennifer Carey, Jessica L. Oleski, Martinus Evans, Molly E. Waring, Sherry L. Pagoto, Stephanie Rodrigues
Published
July 20, 2016
Journal
Translational Behavioral Medicine
Impact Factor
2.189
DOI
10.1007/s13142-016-0429-1
Pubmed
27443643
Altmetric
A healthcare social media research article published in Translational Behavioral Medicine, July 20, 2016

Abstract

People seek weight loss support on online social networks, but little is known about how to build a supportive community. We created four Twitter accounts portraying women interested in weight loss (two obese, two normal weight/overweight) and followed health care professional and peer accounts for 2-5 weeks. We examined follow back rates, interactions, and organic follows from professionals and peers by weight status. Follow back rates did not differ by weight status when following professionals (6.8 % normal weight/overweight vs 11.0 % for obese; p = 0.4167) or peers (6.7 % for normal weight/overweight vs 10.8 % for obese; p = 0.1548). Number of interactions and organic followers also did not differ by weight status. Peers interacted with study accounts significantly more than professionals (p = 0.0138), but interactions were infrequent. Women seeking weight loss support on Twitter may need to be present for more than 5 weeks to build an interactive weight loss community.


Altmetric

The Altmetric Attention Score is based on the attention a research article gets on the internet. Each coloured thread in the circle represents a different type of online attention and the number in the centre is the Altmetric Attention Score. The score is calculated based on two main sources of online attention: social media and mainstream news media.

Healthcare Social Media Research

See the full list of healthcare social media research articles with data from or reference to Symplur.
#hcsmR is a collaboration between Stanford Medicine X and Symplur.