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Am J Health Behav. 2018 Mar 1;42(2):116-128. doi: 10.5993/AJHB.42.2.11.

Social Media Use and Depression and Anxiety Symptoms: A Cluster Analysis.

Author information

1
Center for Research on Media, Technology, and Health, Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
2
Departments of Psychiatry, Psychology, Epidemiology, and Biostatistics, University of Pittsburgh, Pittsburgh, PA.
3
Center for Research on Media, Technology, and Health, University Honors College, Division of Adolescent Medicine, Department of Pediatrics, Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA.

Abstract

OBJECTIVES:

Individuals use social media with varying quantity, emotional, and behavioral at- tachment that may have differential associations with mental health outcomes. In this study, we sought to identify distinct patterns of social media use (SMU) and to assess associations between those patterns and depression and anxiety symptoms.

METHODS:

In October 2014, a nationally-representative sample of 1730 US adults ages 19 to 32 completed an online survey. Cluster analysis was used to identify patterns of SMU. Depression and anxiety were measured using respective 4-item Patient-Reported Outcome Measurement Information System (PROMIS) scales. Multivariable logistic regression models were used to assess associations between clus- ter membership and depression and anxiety.

RESULTS:

Cluster analysis yielded a 5-cluster solu- tion. Participants were characterized as "Wired," "Connected," "Diffuse Dabblers," "Concentrated Dabblers," and "Unplugged." Membership in 2 clusters - "Wired" and "Connected" - increased the odds of elevated depression and anxiety symptoms (AOR = 2.7, 95% CI = 1.5-4.7; AOR = 3.7, 95% CI = 2.1-6.5, respectively, and AOR = 2.0, 95% CI = 1.3-3.2; AOR = 2.0, 95% CI = 1.3-3.1, respectively).

CONCLUSIONS:

SMU pattern characterization of a large population suggests 2 pat- terns are associated with risk for depression and anxiety. Developing educational interventions that address use patterns rather than single aspects of SMU (eg, quantity) would likely be useful.

PMID:
29458520
PMCID:
PMC5904786
DOI:
10.5993/AJHB.42.2.11
[Indexed for MEDLINE]
Free PMC Article

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