Open AccessSocial Support and Connectedness as Predictors of Weight Control Behaviors in Online Communications
Author(s) -
Paul Branscum,
Chen Ling,
Xiaoqian Wang
Publication year - 2020
Publication title -
american journal of health studies
Language(s) - English
Resource type - Journals
eISSN - 1945-4511
pISSN - 1090-0500
DOI - 10.47779/ajhs.2014.210
Subject(s) - social connectedness , social support , overweight , weight control , consumption (sociology) , psychology , control (management) , weight loss , obesity , gerontology , environmental health , social psychology , medicine , computer science , sociology , social science , artificial intelligence
The purpose of this study was to evaluate the role of social support and social connectedness for five weight control behaviors among overweight/obese adults (N=118) participating in an online weightloss community. The five weight control behaviors investigated were physical activity, screen time, and the consumption of sugar-free drinks, sugar-sweetened drinks, and fruits and vegetables. Step-wise multiple regression was used to predict each weight control behavior with constructs of social support and social connectedness. Social support was highly predictive of all behaviors under investigation. Furthermore, interactions within the community (active or passive users) were significant for two behaviors (screen time and fruit and vegetable consumption), and number of minutes engaged in the community per week was significant for fruit and vegetable consumption only. These results suggest that promoting social support is likely the most important feature for online weight loss communities.