Elsevier

Journal of Affective Disorders

Volume 248, 1 April 2019, Pages 65-72
Journal of Affective Disorders

Review article
Is social network site usage related to depression? A meta-analysis of Facebook–depression relations

https://doi.org/10.1016/j.jad.2019.01.026Get rights and content

Highlights

  • Significant correlations between SNS-usage variables (i.e., time spent on social networking sites (SNS) and SNS checking frequency) and depression were found.

  • Significant correlations were found between social comparisons made on SNS (i.e., general and upward comparisons) and depression was found.

  • Social comparisons on SNS were more strongly related to depression than was time spent on SNS.

Abstract

Background

Facebook depression is defined as feeling depressed upon too much exposure to Social networking sites (SNS). Researchers have argued that upward social comparisons made on SNS are the key to the Facebook depression phenomenon. To examine the relations between SNS usage and depression, we conducted 4 separate meta-analyses relating depression to: (1) time spent on SNS, (2) SNS checking frequency, (3) general and (4) upward social comparisons on SNS. We compared the four mean effect sizes in terms of magnitude.

Methods

Our literature search yielded 33 articles with a sample of 15,881 for time spent on SNS, 12 articles with a sample of 8041 for SNS checking frequency, and 5 articles with a sample of 1715 and 2298 for the general and the upward social comparison analyses, respectively.

Results

In both SNS-usage analyses, greater time spent on SNS and frequency of checking SNS were associated with higher levels of depression with a small effect size. Further, higher levels of depression were associated with greater general social comparisons on SNS with a small to medium effect, and greater upward social comparisons on SNS with a medium effect. Both social comparisons on SNS were more strongly related to depression than was time spent on SNS.

Limitations

Limitations include heterogeneity in effect sizes and a small number of samples for social comparison analyses.

Conclusions

Our results are consistent with the notion of ‘Facebook depression phenomenon’ and with the theoretical importance of social comparisons as an explanation.

Section snippets

Search process1

Articles published by February 2018 were retrieved, using PsychInfo, PubMed, and ProQuest dissertations & Theses Global. In addition, a supplemental search was conducted using Google Scholar. The following keywords were searched with depress or depression or depressive (within all text fields): social media or online social networks or Facebook or Snapchat or Instagram or Twitter (within abstract in PsychInfo and within titles in ProQuest). For the SNS usage analyses (aims 1 and 2), studies

SNS usage analyses

For the time spent on SNS analysis, 33 studies with 37 effect sizes were included. The total sample was 15,881 (mean sample size = 429.22, range = 26–2073). Three studies did not report the mean age and three studies reported an age range. The mean age across samples was 21.89, and the mean female participant ratio was approximately 59%. For the SNS checking frequency analysis, 12 studies with 14 effect sizes were included. The total sample of participants was 8041 (mean sample size = 574.36,

Discussion

This study conducted four meta-analyses relating SNS usage and depression. The first two analyses investigated the Facebook depression phenomenon by examining the relationships between depression and the time spent on SNS and SNS checking frequency. To further extend the literature and examine whether social comparisons made on SNS might help explain the Facebook depression phenomenon, two additional meta-analyses were conducted on general and upward social comparisons made by participants on

Acknowledgments

None.

Role of funding sources

This research received no specific grants from any funding agencies in the public, commercial, or not-for-profit sectors.

Contributors

Sunkyung Yoon conducted literature searches, statistical analysis, and wrote the first draft of the manuscript. Mary Kleinman and Jessica Mertz conducted literature searches, contributed to writing the introduction section, and assisted in proof-reading the manuscript. Michael T. Brannick contributed to statistical analysis and writing. All authors contributed to and have approved the final manuscript.

Conflict of interest

We declare that there is no conflict of interest.

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