Sonya Negriff1. 1. Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California. Electronic address: Sonya.X.Negriff@kp.org.
Abstract
PURPOSE: There is a substantial body of literature that examines depression or well-being as outcomes of social media use, but there are fewer studies that seek to understand how mental health may lead to different patterns of online interactions. The purpose of the present study was to examine how depressive symptoms may predict subsequent structural characteristics of the online social network. METHODS: Data came from Time 3 and Time 5 of a longitudinal study on the effects of maltreatment on adolescent development. At Time 3, adolescents reported on their depressive symptoms (n = 319), and at Time 5, a subsample was enrolled in the Facebook data collection (n = 133). An application downloaded the friend list, and network metrics were computed. Path models examined the main effect of depressive symptoms at Time 3 on Facebook social network measures. RESULTS: The coefficients indicated that higher levels of depressive symptoms at Time 3 predicted fewer Facebook friends (smaller size), fewer ties between friends (lower average degree), more components, and fewer friends in the main component of the network. CONCLUSIONS: Depression may alter how youth form and maintain online friendships. Using social network characteristics may help identify youth at risk for serious mental illness.
PURPOSE: There is a substantial body of literature that examines depression or well-being as outcomes of social media use, but there are fewer studies that seek to understand how mental health may lead to different patterns of online interactions. The purpose of the present study was to examine how depressive symptoms may predict subsequent structural characteristics of the online social network. METHODS: Data came from Time 3 and Time 5 of a longitudinal study on the effects of maltreatment on adolescent development. At Time 3, adolescents reported on their depressive symptoms (n = 319), and at Time 5, a subsample was enrolled in the Facebook data collection (n = 133). An application downloaded the friend list, and network metrics were computed. Path models examined the main effect of depressive symptoms at Time 3 on Facebook social network measures. RESULTS: The coefficients indicated that higher levels of depressive symptoms at Time 3 predicted fewer Facebook friends (smaller size), fewer ties between friends (lower average degree), more components, and fewer friends in the main component of the network. CONCLUSIONS:Depression may alter how youth form and maintain online friendships. Using social network characteristics may help identify youth at risk for serious mental illness.
Authors: Allison L Groom; Thanh-Huyen T Vu; Robyn L Landry; Anshula Kesh; Joy L Hart; Kandi L Walker; Lindsey A Wood; Rose Marie Robertson; Thomas J Payne Journal: Int J Environ Res Public Health Date: 2021-06-24 Impact factor: 3.390