Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7333030 | Social Science & Medicine | 2015 | 8 Pages |
Abstract
Social networking sites such as Facebook provide a new way to seek and receive social support, a factor widely recognized as important for one's health. However, few studies have used actual conversations from social networking sites to study social support for health related matters. We studied 3,899 Facebook users, among a sample of 33,326 monitored adults, who initiated a conversation that referred to surgery on their Facebook Wall during a six-month period. We explored predictors of social support as measured by number of response posts from “friends.” Among our sample, we identified 8,343 Facebook conversation threads with the term “surgery” in the initial post with, on average, 5.7 response posts (SD 6.2). We used a variant of latent semantic analysis to explore the relationship between specific words in the posts that allowed us to develop three thematic categories of words related to family, immediacy of the surgery, and prayer. We used generalized linear mixed models to examine the association between characteristics of the Facebook user as well as the thematic categories on the likelihood of receiving response posts following the announcement of a surgery. Words from the three thematic categories were used in 32.5% (family), 39.5 (immediacy), and 50.7% (prayer) of root posts. Few user characteristics were associated with response in multivariate models [rate ratios, RR, 1.08 (95% CI 1.01, 1.15) for married/living with partner; 1.10 (95% CI 1.03, 1.19) for annual income > $75,000]. In multivariate models adjusted for Facebook user characteristics and network size, use of family and prayer words in the root post were associated with significantly higher number of response posts, RR 1.40 (95% CI 1.37, 1.43) and 2.07 (95% CI 2.02, 2.12) respectively. We found some evidence of social support on Facebook for surgery and that the language used in the root post of a conversation thread is predictive of overall response.
Keywords
Related Topics
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Public Health and Health Policy
Authors
Matthew A. Davis, Denise L. Anthony, Scott D. Pauls,