Study2018

Passive and Active Social Media Use and Depressive Symptoms Among United States Adults

Escobar-Viera CG, Shensa A, Bowman ND, Sidani JE, Knight J, James AE, Primack BA

Cyberpsychology, behavior and social networking · 133 citations

Review labels

Funding not disclosed

Neutral facts our review recorded about how this study was done. They describe method, never whether we like the result.

How it was studied

Design
Cross-sectional study (classified by our AI screen)
Studied in
People
Main outcome
Health markers and function

Who paid for it

Funding
Funding not disclosed

Publication

Published
2018-07-01 · Cyberpsychol Behav Soc Netw · vol. 21 · issue 7 · pp. 437–443
Publisher
Mary Ann Liebert, Inc.
Cited
361 citations · more than 100% of similar papers · 60.0× the field average
Impact
Top 10% most cited in its field
References
54 works
Access
Paywalled
Research areas
Impact of Technology on Adolescents · Digital Mental Health Interventions · Mental Health Research Topics
Keywords
social media use, passive social media use, active social media use, depressive symptoms, mental health, adolescents and young adults
MeSH
humans, logistic models, depression, anxiety, psychiatric status rating scales, adolescent, adult, middle aged, united states, female, male, young adult, social media, surveys and questionnaires

7 authors

From US

  • César G. Escobar-Viera · correspondingUniversity of Pittsburgh
  • Ariel S. ShensaUniversity of Pittsburgh
  • Nicholas David BowmanWest Virginia University
  • Jaime E. SidaniUniversity of Pittsburgh
  • Jennifer KnightWest Virginia University
  • Alton Everette JamesUniversity of Pittsburgh

Abstract

Social media allows users to explore self-identity and express emotions or thoughts. Research looking into the association between social media use (SMU) and mental health outcomes, such as anxiety or depressive symptoms, have produced mixed findings. These contradictions may best be addressed by examining different patterns of SMU as they relate to depressive symptomatology. We sought to assess the independent associations between active versus passive SMU and depressive symptoms. For this, we conducted an online survey of adults 18-49 of age. Depressive symptoms were measured using the Patient-Reported Outcomes Measurement Information System brief depression scale. We measured active and passive SMU with previously developed items. Factor analysis was used to explore the underlying factor structure. Then, we used ordered logistic regression to assess associations between both passive and active SMU and depressive symptoms while controlling for sociodemographic covariates. Complete data were received from 702 participants. Active and passive SMU items loaded on separate factors. In multivariable analyses that controlled for all covariates, each one-point increase in passive SMU was associated with a 33 percent increase in depressive symptoms (adjusted odds ratio [AOR] = 1.33, 95 percent confidence interval [CI] = 1.17-1.51). However, in the same multivariable model, each one-point increase in active SMU was associated with a 15 percent decrease in depressive symptoms (AOR = 0.85, 95 percent CI = 0.75-0.96). To inform interventions, future research should determine directionality of these associations and investigate related factors.

Abstract via Europe PMC. Copyright remains with the authors or publisher.

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