Jiyoung Park1, David Seungjae Lee2, Holly Shablack2, Philippe Verduyn3, Patricia Deldin2, Oscar Ybarra2, John Jonides2, Ethan Kross4. 1. Department of Psychological and Brain Sciences, University of Massachusetts, Amherst, 135 Hicks way, Amherst, MA 01003, United States. Electronic address: j.park@umass.edu. 2. Department of Psychology, University of Michigan, 530 Church Street, Ann Arbor, MI 48109, United States. 3. Faculty of Psychology and Educational Sciences, University of Leuven, Belgium; Faculty of Psychology and Neuroscience, Maastricht University, Netherlands. 4. Department of Psychology, University of Michigan, 530 Church Street, Ann Arbor, MI 48109, United States. Electronic address: ekross@umich.edu.
Abstract
BACKGROUND: Although the relationship between depression and "offline" social support is well established, numerous questions surround the relationship between "online" social support and depression. We explored this issue by examining the social support dynamics that characterize the way individuals with varying levels of depression (Study 1) and SCID-diagnosed clinically depressed and non-depressed individuals (Study 2) interact with Facebook, the world's largest online social network. METHOD: Using a novel methodology, we examined how disclosing positive or negative information on Facebook influences the amount of social support depressed individuals (a) actually receive (based on actual social support transactions recorded on Facebook walls) and (b) think they receive (based on subjective assessments) from their Facebook network. RESULTS: Contrary to prior research indicating that depression correlates with less actual social support from "offline" networks, across both studies depression was positively correlated with social support from Facebook networks when participants disclosed negative information (p=.02 in Study 1 and p=.06 in Study 2). Yet, depression was negatively correlated with how much social support participants thought they received from their Facebook networks (p=.005 in Study 1 and p=.001 in Study 2). LIMITATIONS: The sample size was relatively small in Study 2, reflecting difficulties of recruiting individuals with Major Depressive Disorder. CONCLUSIONS: These results demonstrate that an asymmetry characterizes the relationship between depression and different types of Facebook social support and further identify perceptions of Facebook social support as a potential intervention target. (243 words; 250 max).
BACKGROUND: Although the relationship between depression and "offline" social support is well established, numerous questions surround the relationship between "online" social support and depression. We explored this issue by examining the social support dynamics that characterize the way individuals with varying levels of depression (Study 1) and SCID-diagnosed clinically depressed and non-depressed individuals (Study 2) interact with Facebook, the world's largest online social network. METHOD: Using a novel methodology, we examined how disclosing positive or negative information on Facebook influences the amount of social support depressed individuals (a) actually receive (based on actual social support transactions recorded on Facebook walls) and (b) think they receive (based on subjective assessments) from their Facebook network. RESULTS: Contrary to prior research indicating that depression correlates with less actual social support from "offline" networks, across both studies depression was positively correlated with social support from Facebook networks when participants disclosed negative information (p=.02 in Study 1 and p=.06 in Study 2). Yet, depression was negatively correlated with how much social support participants thought they received from their Facebook networks (p=.005 in Study 1 and p=.001 in Study 2). LIMITATIONS: The sample size was relatively small in Study 2, reflecting difficulties of recruiting individuals with Major Depressive Disorder. CONCLUSIONS: These results demonstrate that an asymmetry characterizes the relationship between depression and different types of Facebook social support and further identify perceptions of Facebook social support as a potential intervention target. (243 words; 250 max).
Authors: Christopher Tufts; Daniel Polsky; Kevin G Volpp; Peter W Groeneveld; Lyle Ungar; Raina M Merchant; Arthur P Pelullo Journal: JMIR Public Health Surveill Date: 2018-12-06
Authors: Alan R Teo; Heather E Marsh; Samuel B L Liebow; Jason I Chen; Christopher W Forsberg; Christina Nicolaidis; Somnath Saha; Steven K Dobscha Journal: J Med Internet Res Date: 2018-02-26 Impact factor: 5.428