The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies
Open accessAbstract
Online social networking sites (SNSs) such as Facebook, Twitter, and MySpace are used by billions of people every day to communicate and interact with others. There has been increasing interest in the potential impact of online social networking on wellbeing, with a broadening body of new research into factors associated with both positive and negative mental health outcomes such as depression. This systematic review of empirical studies (n = 30) adds to existing research in this field by examining current quantitative studies focused on the relationship between online social networking and symptoms of depression. The academic databases PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE were searched systematically using terms related to online social networking and depression. Reporting quality was critically appraised and the findings discussed with reference to their wider implications. The findings suggest that the relationship between online social networking and symptoms of depression may be complex and associated with multiple psychological, social, behavioral, and individual factors. Furthermore, the impact of online social networking on wellbeing may be both positive and negative, highlighting the need for future research to determine the impact of candidate mediators and moderators underlying these heterogeneous outcomes across evolving networks.
AI snapshot
Written from the paper’s full text.
TL;DR
This systematic review of 30 quantitative studies found mixed evidence on the relationship between online social networking and depression, with most studies suggesting a complex relationship involving mediators and moderators. The authors conclude that how people use social networking sites and what they do online may matter more than frequency or duration alone.
Key findings
- Of 30 studies, 5 (16%) found a positive correlation between online social networking engagement and depressive symptoms, with small effect sizes (r = .15 to r = .26); 2 (6%) found a negative correlation (POR = 0.50, r = −.303); and 4 (13%) found no significant correlations.
- The majority suggested a complex relationship involving usage variables (frequency, quality, type of SNS use), individual differences (gender, personality), and social factors as candidate mediators or moderators; examples include positive correlations with negative interactions, Facebook addiction/intrusion, social comparison, and rumination, and negative correlations with Facebook social support satisfaction, positive social comparison, number of Facebook friends, and perceived connectedness.
- Reporting quality using STROBE ranged from 48% to 93%; sample size or power calculations were reported in only 5 of 30 studies, and funding sources in only 11 of 30.
- The review included 35,044 total participants across 14 countries, with participant age ranging from 15 to 88 years; 27 studies were cross-sectional and only 3 were longitudinal or had longitudinal components.
Methods
- Systematic review of empirical quantitative studies (n = 30) comparing measures of SNS use and depression; databases searched were PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE, with searches completed in April 2016.
- Eligibility required a quantitative design comparing SNS use and depression; articles were not excluded by age, gender, publication date, or country, but were excluded if unavailable in English. Search terms included “online social network*,” “online social media,” “Facebook*,” “Twitter,” “MySpace,” and “depression.”
- Reporting quality was appraised with the STROBE tool for cross-sectional studies; findings were synthesized narratively, and no meta-analytic pooling is described.
Limitations
- The paper states that conceptualizing online social networking was challenging due to evolving platforms; there was a significant bias toward Facebook research, limiting generalisability across platforms; the high prevalence of cross-sectional studies prevents determination of causation; and reporting issues included limited discussion of bias, selection bias, social desirability, confounding, and self-report measurement bias.
- Evident from the text: only 3 of 30 studies were longitudinal or had longitudinal components, so causal direction remains unclear; the review was also restricted to quantitative English-language studies, excluding qualitative evidence by design.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 39 cited sources checked · 0 supported · 0 flagged
- Findingown data
Possible sources of bias and efforts to reduce them were rarely discussed in the reviewed studies.
“Possible sources of bias and methodological efforts to minimise their effects were rarely discussed.”
Quote in the paperNot a substantial claim - Findingown data
Only 11 of the 30 reviewed studies reported sources of funding.
“Sources of funding were reported in only 11 out of 30 studies.”
Quote in the paperNot a substantial claim - Findingnone given
Overall, the findings of the review were mixed.
“Overall, the findings were mixed.”
Quote in the paperSubstantial claim - Findingcitation
Positive correlations were found between depression and negative social networking interactions.
“positive correlations were found between depression and negative social networking interactions, 34,39,40”
Quote in the paperSubstantial claim0 of 3 sources checked - Findingreasoning
Most reviewed studies suggested a complex relationship between online social networking and depression that involves factors which may mediate or moderate the relationship.
“The majority of studies suggested a complex relationship between online social networking and depression involving factors that may mediate or moderate this relationship, helping to explain the variability of findings.”
Quote in the paperSubstantial claim
- Findingcitation
Four reviewed studies (13%) found no significant correlations between online social networking and symptoms of depression.
“Thirteen percent (n = 4) found no significant correlations between online social networking and symptoms of depression.10,20,24,38”
Quote in the paperNot a substantial claim0 of 3 sources checked - Findingown data
In the reviewed studies, details of study design and methods such as point in time, setting, and eligibility criteria were usually implied rather than explicitly reported.
“For example, details of study design and methods such as the point in time, setting, and eligibility criteria were typically implied but not explicitly reported.”
Quote in the paperNot a substantial claim - Findingcitation
One reviewed study found a negative correlation between depression and addictive SNS use.
“although conversely one study found a negative correlation between depression and addictive SNS use.30”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [30] source
Not checked in the free run.
- Findingown data
Only 5 of the 30 reviewed studies reported clear information about sample size, such as power calculations.
“Clear information about sample size e.g.power calculations were reported in only 5 out of 30 studies.”
Quote in the paperNot a substantial claim - Findingnone given
Some studies reported analyses that controlled for confounding variables.
“whilst some studies reported analyses used to control for confounding variables”
Quote in the paperNot a substantial claim - Findingcitation
Significant associations between online social networking and depression remained after controlling for age, gender, socio-economic status, social networking usage variables, and offline behaviour.
“Significant associations between online social networking and depression remained after controlling for the effects of confounding such as age, gender, socio-economic status, social networking usage variables, and offline behaviour, highlighting variables of particular significance in this relationship.”
Quote in the paperSubstantial claim - Findingcitation
Reporting problems make it difficult to judge the validity of the findings.
“issues of reporting create difficulties in our ability to assess the validity of findings.59”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [59] source
Not checked in the free run.
- Findingreasoning
The survey methods used in all included studies had significant limitations.
“limitations in the survey methodology used within all of the studies in this review are significant.”
Quote in the paperSubstantial claim - Findingcitation
Negative comparison with others when using Facebook predicted depression via increased rumination even when a general tendency to engage in social comparison was controlled for.
“For example, negative comparison with others when using Facebook was found to predict depression via increased rumination even when a general tendency to engage in social comparison was controlled for.39”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [39] source
Not checked in the free run.
- Findingreasoning
A main problem was that the studies did not adequately report bias.
“A primary issue was a lack of reporting in relation to bias across the studies.”
Quote in the paperSubstantial claim - Findingown data
When participants were connected to the organisation running the research, the studies gave little attention to how social desirability might have affected responses.
“Similarly, where participants were linked to the organisation conducting the research, for example through their educational or healthcare institution, little consideration was given to the impact that social desirability may have had on some of the responses given.”
Quote in the paperNot a substantial claim - Findingcitation
Frequent posting on Facebook was associated with depression via rumination when gender and other variables such as length of time using a Facebook account, time spent using Facebook per day, and number of Facebook friends were controlled for.
“Similarly, frequent posting on Facebook was found to be associated with depression via rumination when gender and other variables such as length of time using a Facebook account, time spent using Facebook per day, and number of Facebook friends were controlled for.48”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [48] source
Not checked in the free run.
- Findingcitation
People scoring higher on measures of depression were more likely to use a Facebook application to read tips about depression.
“Park et al. 28 found that people scoring higher on measures of depression were more likely to use a Facebook application to read tips about depression, highlighting potential opportunities for online social networking as a mental health resource or intervention”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [28] source
Not checked in the free run.
- Findingown data
Many studies used student samples but gave little attention to selection bias, such as whether depressed students or those with particular online behaviours were more or less likely to participate.
“many studies recruited student populations into their sample; however, little consideration was given to selection bias i.e. whether students who may be depressed or engage in specific online behaviours were more or less likely to take part in research.”
Quote in the paperSubstantial claim - Findingown data
The review found problems in how the included studies reported their findings.
“issues were identified in the reporting of research findings.”
Quote in the paperSubstantial claim - Findingreasoning
Some included studies reported an association between using online social networking and depressive symptoms.
“whilst some studies have identified a relationship between engagement in online social networking and symptoms of depression”
Quote in the paperSubstantial claim - Interpretationreasoning
For some people, social networking may act as a resource in managing depression.
“Positive outcomes emerged as significant across a number of studies and findings suggest that for some social networking may act as a resource in managing depression.”
Quote in the paperSubstantial claim - Interpretationreasoning
The frequency, quality, and type of online social networking and depression appear to be intertwined in some ways.
“The frequency, quality, and type of online social networking and depression appear to be in some ways intertwined.”
Quote in the paperSubstantial claim - Interpretationreasoning
Online behaviours involving rumination or social comparison may be especially important in the relationship between online social networking and depression.
“Within this, online behaviours that lead to rumination or social comparison may be particularly important.”
Quote in the paperNot a substantial claim - Premisecitation
Self-report measures may not yield credible outcomes because of various biases.
“The use of self-report measures, whilst appropriate research tools in this context, may not produce credible outcomes due to various forms of bias.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [60]
Not checked in the free run.
- Interpretationcitation
The nature of online social network use may be more important in influencing symptoms of depression, or vice versa, than the frequency or duration of engagement alone.
“A key finding of this review, adding to those from internet and mental health research elsewhere, 7 is that the nature of online social network use may be more important in influencing symptoms of depression or vice versa than the frequency or duration of engagement alone.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [7]
Not checked in the free run.
- Interpretationreasoning
The review's findings suggest a complex relationship between online social networking and depression that can be influenced by mediating and moderating factors.
“The findings of this review suggest a complex relationship between online social networking and depression which can be influenced by a number of mediating and moderating factors.”
Quote in the paperSubstantial claim - Interpretationcitation
Because most included studies were cross-sectional, the review cannot establish that online social networking causes depression.
“due to the high prevalence of cross-sectional studies, it is not possible to determine causation.57”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [57] source
Not checked in the free run.
- Interpretationreasoning
Social comparison and rumination are likely candidate mediators in the relationship between SNS use and depression.
“A further finding of this review is that in the context of online social networking, social comparison and rumination are likely to be candidate mediators in the relationship between SNS use and depression.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 10
- May combine two claims. 23
- The quote only partly states this claim. 2
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataAcross all reviewed studies, the total number of participants was 35,044.
“The total number of participants across all reviewed studies was 35,044.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationTwo reviewed studies (6%) found a negative correlation between online social networking and depression, with POR = 0.50 and r = -.303.
“Six percent (n = 2) found a negative correlation (POR= 0.50, r=-.303), which authors argue may be a result of low motivation to engage in online social networking or of SNS use providing a coping tool to protect against mental health difficulties.22,33”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
FindingcitationPositive correlations were found between depression and Facebook impression management, envy triggered by Facebook surveillance, accepting former partners' invitations to become Facebook friends, producing more content or engaging in greater interactive communication on Facebook, social comparison with others, and frequent negative status updates or negative comparison with others leading to rumen
“In relation to type of online social networking behaviour, positive correlations were found between Facebook impression management, 32 envy triggered by Facebook surveillance, 31 accepting former partners' invitations to become Facebook friends, 45 producing more content or engaging in greater interactive communication on Facebook, 46 social comparison with others, 39,47 and frequent negative”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe systematic review included 30 empirical studies.
“This systematic review of empirical studies (n = 30) adds to existing research in this field by examining current quantitative studies focused on the relationship between online social networking and symptoms of depression.”
- Also stated in: § Study Characteristics · plain
“Table 1 provides an overview of the characteristics of the studies meeting the criteria of the review (n = 30).”
Quote in the paperNot a substantial claim- Also stated in: § Study Characteristics · plain
May combine two claims.
FindingreasoningCandidate mediators or moderators of the relationship between online social networking and depression include usage variables such as frequency, quality, and type of SNS use, as well as individual differences and social factors.
“These factors can be categorised”
- Also stated in: § ONLINE SOCIAL NETWORKING AND DEPRESSION ! 7 · plain
“usage variables”
- Also stated in: § ONLINE SOCIAL NETWORKING AND DEPRESSION ! 7 · hedged
“Individual differences and social factors were also found to be candidate mediators or moderators.”
Quote in the paperSubstantial claim- Also stated in: § ONLINE SOCIAL NETWORKING AND DEPRESSION ! 7 · plain
The quote only partly states this claim.
Findingown dataThe reporting quality of the reviewed studies, assessed with the STROBE tool, ranged from 48% to 93%.
“The quality of reporting based on the STROBE tool for cross-sectional studies ranged from 48% to 93%.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19]
Not checked in the free run.
- Rests on an assumption: The STROBE percentage score is a valid indicator of reporting quality for the reviewed studies.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataThe reviewed studies were conducted in 14 countries.
“Research was identified from 14 countries including the Philippines, 20,21 Turkey, 22,23 Serbia, 24,25 Australia, 26 Greece, 27 and Korea, 28 reflecting the global nature of the phenomenon under study.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataTwenty-seven reviewed studies were cross-sectional, while three were longitudinal or had longitudinal components.
“Twenty seven studies were cross-sectional in design and only three were longitudinal or had longitudinal components.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationPositive correlations were found between depression and Facebook addiction or pathological SNS use, and Facebook intrusion.
“positive correlations were found between depression and Facebook addiction or pathological SNS use, 23,42,43 and Facebook intrusion, 44”
Quote in the paperSubstantial claim0 of 3 sources checkedMay combine two claims.
FindingcitationNegative correlations were found between depression and Facebook social support satisfaction, positive social comparison, number of Facebook friends, and perceived Facebook social connectedness.
“negative correlations were found between depression and Facebook social support satisfaction, 36 positive social comparison, 41 number of Facebook friends, 32 and perceived Facebook social connectedness.26”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataSeven reviewed studies used only correlational analyses, and 23 included regression analyses.
“Seven studies used only correlational analyses and 23 included regression analyses.”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
FindingcitationFive reviewed studies (16%) found a positive correlation between engagement in online social networking and presence of depression symptoms, with small effect sizes ranging from r = .15 to r = .26.
“In total, 16% of the studies (n = 5) found a positive correlation between engagement in online social networking and pres-”
- Also stated in: § ONLINE SOCIAL NETWORKING AND DEPRESSION ! 7 · plain
“reflecting small effect sizes (correlations ranged between r=.15 to r=.26).21,25,27,36,37”
Quote in the paperSubstantial claim0 of 3 sources checked- Also stated in: § ONLINE SOCIAL NETWORKING AND DEPRESSION ! 7 · plain
May combine two claims.
FindingcitationParticipants higher in neuroticism had significantly higher levels of problematic SNS use and exhibited more depressive symptoms than those lower in neuroticism.
“For example, Giota & Kleftaras 27 found that participants higher in neuroticism had significantly higher levels of problematic SNS use and exhibited more depressive symptoms than those who scored lower on measures of neuroticism.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [27] source
Not checked in the free run.
May combine two claims.
FindingcitationNegative correlations were found between depression and location tagging, and frequent posting of positive Facebook status updates leading to reduced rumination.
“In contrast, negative correlations were found between depression and location tagging, 28 and frequent posting of positive Facebook status updates leading to reduced rumination.48”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
Findingown dataThe review found a marked overrepresentation of Facebook in the included studies, which may reduce how far the findings can be generalised to other platforms.
“This review identified a significant bias towards research into Facebook over other platforms, which, whilst not necessarily surprising given its user-base and media interest, could limit generalisability of findings across platforms.”
Quote in the paperNot a substantial claimMay combine two claims.
FindingcitationGender and personality were found to influence the relationship between online social networking and depression.
“Gender and personality were also found to influence the relationship between online social networking and depression, 27,34,35,45,47 highlighting the role of individual differences alongside usage variables cited above.”
Quote in the paperNot a substantial claim0 of 3 sources checkedMay combine two claims.
Findingnone givenIndirect social factors such as place of residence were found to influence problematic social network use, which in turn correlated with depression.
“Indirect social factors such as place of residence were also found to influence problematic social network use, which in turn correlated with depression.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe effect of social comparison on Facebook is inherently different from and may be more detrimental to psychological wellbeing than social comparison in real life.
“The fact that negative comparison with others when using Facebook was found to predict depression via increased rumination even when a general tendency to engage in social comparison offline was controlled for 39 suggests that the effect of social comparison on Facebook is inherently different and may be more detrimental to psychological wellbeing than social comparison in real life.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [39] source
Not checked in the free run.
May combine two claims.
PremisecitationCross-sectional designs have been criticised for assuming that variables stay stable over time and for not addressing chronological variability, which can produce biased estimates and incorrect inferences.
“cross-sectional designs have been criticised for an over-assumption on the idea that variables remain stable over time and for failing to address chronological variability, leading to biased estimates and incorrect inferences, 58”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [58]
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningThe idea of 'Facebook depression' may be too simplistic and may ignore the many factors that affect the relationship in both positive and negative ways.
“Whilst the concept of”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe evidence suggests that how people use online social networking and what they make of their interactions are likely to be important determinants of depression, or the reverse.
“The evidence suggests that the ways in which people use online social networking and the meanings they make of their interactions are likely to be important determinants of depression, or vice versa.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe review used the STROBE Statement tool for cross-sectional studies to assess reporting quality.
“To assess the quality of reporting, the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement tool for cross-sectional studies 19 was used.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [19]
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe impact of online social networking may be both positive and negative.
“The results reviewed here also suggest that the impact of online social networking may be both positive and negative.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningBecause social networking sites keep changing, whether the relationship between depression and older networks such as MySpace generalises to newer networks such as Instagram or Twitter requires further empirical study.
“as the functionality and nature of SNSs is in constant change, generalisability about the relationship between depression and previous networks such as MySpace to newer networks such as Instagram or Twitter needs further empirical consideration.”
Quote in the paperNot a substantial claim- Rests on an assumption: The functionality and nature of social networking sites is constantly changing.
May combine two claims.
PremisecitationSelf-report measures may be culturally sensitive, with people of Asian heritage potentially responding differently from those of European heritage, which further undermines reliability.
“Self-report measures may also be sensitive to culture, with participants of Asian heritage potentially responding differently to participants of European heritage, 61 further compromising the reliability of research findings.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [61]
Not checked in the free run.
Classified as probably not a substantial claim.
InterpretationreasoningWhen reporting quality was lower, the authors' conclusions deserve less weight.
“Where lower quality of reporting was identified, less weight can be attributed to authors' conclusions.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
InterpretationreasoningBecause research samples were culturally heterogeneous and sampling may have been problematic, validity and generalisability should be treated cautiously.
“However, due to the cultural heterogeneity of research samples and potential issues of sampling, validity and generalisability should also be treated with caution.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningFor some people, online social networking may be linked to more depressive symptoms, while for others it may be beneficial.
“the findings suggest that for some people online social networking may be associated with increased symptoms of depression whilst for others the activity may be beneficial.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe relationship between online social networking and depression appears to have complex influences, and suggestions of a unidirectional causal link are likely to be incorrect.
“The relationship between online social networking and depression appears to have complex influences and suggestions of a unidirectional causal link are likely to fall down under scrutiny.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductnone givenThe review systematically searched PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE using terms related to online social networking and depression.
“The academic databases PsycINFO, Web of Science, CINAHL, MEDLINE and EMBASE were searched systematically using terms related to online social networking and depression.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningBecause the research covered a wide scope, the findings may be representative of and relevant to many populations.
“due to the wide scope of research, findings are potentially representative of and relevant to a wide range of populations.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
The findings of the included studies are reliable enough to support the review's synthesis.
“All studies were interested in the relationship between depression and online social networking but some focused on specific variables such as time spent engaged in social networking, e.g.34 social networking features such as the number of Facebook friends, e.g.21 the frequency of social networking behaviours such as the number of self-portrait photographs shared on Facebook, e.g.24 or the impact”
The paper relies on this without support.
The STROBE percentage score is a valid indicator of reporting quality for the reviewed studies.
“Studies were scored on relevant items and assigned an overall percentage to indicate an appraisal of the reporting quality.”
The paper relies on this without support.
Depression is influenced by many variables.
“Depression was shown to be influenced by a large number of variables”
The paper relies on this without support.
The functionality and nature of social networking sites is constantly changing.
“as the functionality and nature of SNSs is in constant change”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Social media can benefit individuals through avenues such as teaching and developing socialization skills, allowing greater communication and access to resources, and helping with connection and belonging.
“other research has shown that social media can benefit individuals through a number of different avenues such as teaching and developing socialization skills, allowing greater communication and access to a greater wealth of resources, and helping with connection and belonging (American Psychological Association 2011; Baker and Algorta 2016; Marker et al. 2018).”
From The future of social media in marketing (2020) · cites this paper as Baker and Algorta 2016
The discussion (section ! 14) identifies social support and informational resources as potential benefits, and section ! 4 describes communication within extended social networks. The paper also reports that Facebook may help people maintain relationships (p. 11). These passages do not support the specific claim that social media teaches or develops socialization skills. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe remaining three reviews, which included adults and adolescents, found that cross-sectional designs, retrospective reporting, and small mixed associations were the norm and limited reliable conclusions.
“Conclusions were consistent with those summarized for the adolescent populations above in that cross-sectional research designs, retrospective reporting of symptoms and digital technology usage, and small and mixed patterns of associations were the norm and often limiting factors in drawing reliable conclusions in this area (Baker & Algorta, 2016; Seabrook et al., 2016).”
From Annual Research Review: Adolescent mental health in the digital age: facts, fears, and future directions. (2020) · cites this paper as Baker & Algorta, 2016
The study measured overall time spent on social media, not platform-specific or nature of use, which may limit the findings.
“A limitation of our study is that we measured overall time spent on social media; prior studies [30][31][32] have found that social media use may be positively or negatively associated with mental health depending on which platforms are used and how.”
From Associations Between Time Spent Using Social Media and Internalizing and Externalizing Problems Among US Youth. (2019) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Five of 30 studies is not 16%
MinorFive of 30 studies is 16.67%, which rounds to 17% at the reported precision, not 16%.
Reported 16 · recomputed 16.666667
“In total, 16% of the studies (n = 5) found a positive correlation”
Cites
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., Vandenbroucke, J. P., & Initiative, F. T. S. (2007) · PLoS Medicine · doi:10.1371/journal.pmed.0040296 · Cited by 23,020 · see citing works
von Elm, E., Altman, D. G., Egger, M., Pocock, S. J., Gøtzsche, P. C., & Vandenbroucke, J. P. (2008) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2007.11.008 · Cited by 17,893 · see citing works
Users of the world, unite! The challenges and opportunities of Social Media
Kaplan, A. M., & Haenlein, M. (2010) · Business Horizons · doi:10.1016/j.bushor.2009.09.003 · Cited by 17,875 · cited 1× · see citing works
“Kaplan and Haenlein 56 suggest that the classification of various forms of social media and SNSs is likely to require a systematic categorization scheme to distinguish them further.”
Social network sites: definition, history, and scholarship
boyd, D. M., & Ellison, N. B. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00393.x · Cited by 16,251 · see citing works
Ellison, N. B., Steinfield, C., & Lampe, C. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00367.x · Cited by 9,939 · see citing works
What is Twitter, a social network or a news media?
Kwak, H., Lee, C., Park, H., & Moon, S. (2010) · Proceedings of the 19th international conference on World wide web · doi:10.1145/1772690.1772751 · Cited by 6,652 · see citing works
Internet paradox: A social technology that reduces social involvement and psychological well-being?
Kraut, R. E., Patterson, M., Lundmark, V. A., Kiesler, S. B., Mukophadhyay, T., & Scherlis, W. L. (1998) · American Psychologist · doi:10.1037//0003-066x.53.9.1017 · Cited by 4,830 · see citing works
Internet paradox: A social technology that reduces social involvement and psychological well-being?
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998) · American Psychologist · doi:10.1037/0003-066x.53.9.1017 · Cited by 4,793 · see citing works
Handbook of research methods in personality psychology
(2007) · Choice Reviews Online · doi:10.5860/choice.45-2315 · Cited by 2,378 · see citing works
Andreassen, C. S., Billieux, J., Griffiths, M. D., Kuss, D. J., Demetrovics, Z., Mazzoni, E., & Pallesen, S. (2016) · Psychology of Addictive Behaviors · doi:10.1037/adb0000160 · Cited by 2,095 · cited 1× · see citing works
“30 In relation to type of online social networking behavior, positive correlations were found between Face-book impression management, 32 envy triggered by Facebook surveillance, 31 accepting former partners’ invitations to become Facebook friends, 45 producing more content or engaging in greater…”
Online Social Networking and Addiction—A Review of the Psychological Literature
Kuss, D. J., & Griffiths, M. D. (2011) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph8093528 · Cited by 2,038 · see citing works
Ambiguity and the process of knowledge transfer in strategic alliances
Simonin, B. L. (1999) · Strategic Management Journal · doi:10.1002/(sici)1097-0266(199907)20:7 · Cited by 1,967 · see citing works
Raacke, J., & Bonds-Raacke, J. (2008) · CyberPsychology & Behavior · doi:10.1089/cpb.2007.0056 · Cited by 1,577 · cited 1× · see citing works
“50 Simoncic et al. 35 suggest that the regulated social environment offered by Facebook, which allows users to carefully craft messages, may facilitate some to maintain relationships and promote their positive qualities in an adaptive way.”
Pathological Video Game Use Among Youths: A Two-Year Longitudinal Study
Gentile, D. A., Choo, H., Liau, A., Sim, T., Li, D., Fung, D., & Khoo, A. (2011) · Pediatrics · doi:10.1542/peds.2010-1353 · Cited by 1,314 · see citing works
Thomée, S., Härenstam, A., & Hagberg, M. (2011) · BMC Public Health · doi:10.1186/1471-2458-11-66 · Cited by 1,269 · see citing works
The Relationship Between Depression and Internet Addiction
YOUNG, K. S., & ROGERS, R. C. (1998) · CyberPsychology & Behavior · doi:10.1089/cpb.1998.1.25 · Cited by 1,198 · see citing works
Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness
Eysenbach, G. (2008) · Journal of Medical Internet Research · doi:10.2196/jmir.1030 · Cited by 1,143 · see citing works
Study design III: Cross-sectional studies
Levin, K. A. (2006) · Evidence-Based Dentistry · doi:10.1038/sj.ebd.6400375 · Cited by 1,134 · see citing works
Identifying and Avoiding Bias in Research
Pannucci, C. J., & Wilkins, E. G. (2010) · Plastic and Reconstructive Surgery · doi:10.1097/prs.0b013e3181de24bc · Cited by 1,079 · see citing works
Online communication, social media and adolescent wellbeing: A systematic narrative review
Best, P., Manktelow, R., & Taylor, B. (2014) · Children and Youth Services Review · doi:10.1016/j.childyouth.2014.03.001 · Cited by 1,067 · see citing works
Journal of the Medical Association of Thailand
(2020) · Journal of the Medical Association of Thailand · doi:10.35755/jmedassocthai · Cited by 963 · see citing works
Facebook use, envy, and depression among college students: is facebooking depressing?
Tandoc, E. C., Ferrucci, P., & Duffy, M. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.10.053 · Cited by 781 · see citing works
Social media definition and the governance challenge: An introduction to the special issue
Obar, J. A., & Wildman, S. (2015) · Telecommunications Policy · doi:10.1016/j.telpol.2015.07.014 · Cited by 650 · see citing works
Face-to-face or Facebook: Can social connectedness be derived online?
Grieve, R., Indian, M., Witteveen, K., Anne Tolan, G., & Marrington, J. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2012.11.017 · Cited by 609 · cited 2× · see citing works
“26 In terms of frequency, positive correlations were found between depression and Facebook addiction or pathological SNS use, 23,42,43 and Facebook intrusion, 44 although conversely one study found a negative correlation between depression and addictive SNS use.”
Online Social Networking and Mental Health
Pantic, I. V. (2014) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2014.0070 · Cited by 564 · see citing works
Seeing everyone else’s highlight reels: how Facebook usage is linked to depressive symptoms.
Steers, M.-L. N., Wickham, R. E., & Acitelli, L. K. (2014) · Journal of Social and Clinical Psychology · doi:10.1521/jscp.2014.33.8.701 · Cited by 535 · see citing works
Lup, K., Trub, L., & Rosenthal, L. (2015) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2014.0560 · Cited by 520 · see citing works
Negative social comparison on Facebook and depressive symptoms: Rumination as a mechanism.
Feinstein, B. A., Hershenberg, R., Bhatia, V., Latack, J. A., Meuwly, N., & Davila, J. (2013) · Psychology of Popular Media Culture · doi:10.1037/a0033111 · Cited by 500 · see citing works
Koc, M., & Gulyagci, S. (2013) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2012.0249 · Cited by 487 · see citing works
Rosen, L. D., Whaling, K., Rab, S., Carrier, L. M., & Cheever, N. A. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2012.11.012 · Cited by 472 · see citing works
“Facebook Depression?” Social Networking Site Use and Depression in Older Adolescents
Jelenchick, L. A., Eickhoff, J. C., & Moreno, M. A. (2013) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2012.05.008 · Cited by 445 · see citing works
Morrison, C. M., & Gore, H. (2010) · Psychopathology · doi:10.1159/000277001 · Cited by 437 · see citing works
(2020) · doi:10.36648/1791-809x · Cited by 424 · see citing works
(2012) · PubMed · Cited by 317 · see citing works
Cultural differences in response styles: The role of dialectical thinking
Hamamura, T., Heine, S. J., & Paulhus, D. L. (2008) · Personality and Individual Differences · doi:10.1016/j.paid.2007.10.034 · Cited by 306 · see citing works
A prospective study of individual-level social capital and major depression in the United States
Fujiwara, T., & Kawachi, I. (2008) · Journal of Epidemiology and Community Health · doi:10.1136/jech.2007.064261 · Cited by 300 · see citing works
Loneliness, Depression, and Computer Self-Efficacy as Predictors of Problematic Internet Use
Ceyhan, A. A., & Ceyhan, E. (2008) · CyberPsychology & Behavior · doi:10.1089/cpb.2007.0255 · Cited by 296 · see citing works
Shaw, A. M., Timpano, K. R., Tran, T. B., & Joormann, J. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.02.003 · Cited by 291 · see citing works
Thomée, S., Eklöf, M., Gustafsson, E., Nilsson, R., & Hagberg, M. (2007) · Computers in Human Behavior · doi:10.1016/j.chb.2004.12.007 · Cited by 284 · see citing works
Wright, K. B., Rosenberg, J., Egbert, N., Ploeger, N. A., Bernard, D. R., & King, S. (2013) · Journal of Health Communication · doi:10.1080/10810730.2012.688250 · Cited by 242 · cited 4× · see citing works
“…were found between depression and negative social networking interactions, 34,39,40 whereas negative correlations were found between depression and Facebook social support satisfaction, 36 positive social comparison, 41 number of Facebook friends, 32 and perceived Facebook social connectedness.”
InfluentialDavila, J., Hershenberg, R., Feinstein, B. A., Gorman, K., Bhatia, V., & Starr, L. R. (2012) · Psychology of Popular Media Culture · doi:10.1037/a0027512 · Cited by 237 · see citing works
Wegmann, E., Stodt, B., & Brand, M. (2015) · Journal of Behavioral Addictions · doi:10.1556/2006.4.2015.021 · Cited by 223 · see citing works
Banjanin, N., Banjanin, N., Dimitrijevic, I., & Pantic, I. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.11.013 · Cited by 215 · see citing works
Internet Use, Facebook Intrusion, and Depression: Results of a Cross-Sectional Study
Błachnio, A., Przepiórka, A., & Pantic, I. (2015) · European Psychiatry · doi:10.1016/j.eurpsy.2015.04.002 · Cited by 199 · see citing works
Rice, S. M., Goodall, J., Hetrick, S. E., Parker, A. G., Gilbertson, T., Amminger, G. P., Davey, C. G., McGorry, P. D., Gleeson, J., & Alvarez-Jimenez, M. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.3304 · Cited by 194 · see citing works
Activities on Facebook Reveal the Depressive State of Users
Park, S., Lee, S. W., Kwak, J.-A., Cha, M., & Jeong, B. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2718 · Cited by 128 · see citing works
Closing the Gap: Priorities for Essential Change in Mental Health
Social Care, L. G. A. C. P. D. (2014) · PsycEXTRA Dataset · doi:10.1037/e503762014-001 · Cited by 126 · see citing works
Simoncic, T. E., Kuhlman, K. R., Vargas, I., Houchins, S., & Lopez-Duran, N. L. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.07.039 · Cited by 123 · see citing works
Technology-Assisted Weight Loss Interventions in Primary Care: A Systematic Review
Levine, D. M., Savarimuthu, S., Squires, A., Nicholson, J., & Jay, M. (2015) · Journal of General Internal Medicine · doi:10.1007/s11606-014-2987-6 · Cited by 105 · see citing works
Facebook use and adolescents’ emotional states of depression, anxiety, and stress
Labrague, L. J. (2014) · ICUS and Nursing Web Journal · Cited by 100 · see citing works
Facebook behaviors associated with diurnal cortisol in adolescents: Is befriending stressful?
Morin-Major, J. K., Marin, M.-F., Durand, N., Wan, N., Juster, R.-P., & Lupien, S. J. (2016) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2015.10.005 · Cited by 90 · see citing works
(2015) · PubMed · Cited by 77 · see citing works
Facebook Use and the Tendency to Ruminate among College Students: Testing Mediational Hypotheses
Locatelli, S. M., Kluwe, K., & Bryant, F. (2012) · Journal of Educational Computing Research · doi:10.2190/ec.46.4.d · Cited by 73 · see citing works
The role of personality and depression in problematic use of social networking sites in Greece
Giota, K. G., & Kleftaras, G. (2013) · Cyberpsychology: Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2013-3-6 · Cited by 65 · see citing works
Afsar, B. (2013) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2013.05.001 · Cited by 46 · see citing works
Datu, J. A. D., Valdez, J. P. M., & Datu, N. D. (2012) · International Journal of Research Studies in Educational Technology · doi:10.5861/ijrset.2012.202 · Cited by 40 · see citing works
Pantic, I. V. (2013) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2013.10.199 · Cited by 31 · see citing works
Masedu, F., Mazza, M., Di Giovanni, C., Calvarese, A., Tiberti, S., Sconci, V., & Valenti, M. (2014) · Frontiers in Public Health · doi:10.3389/fpubh.2014.00286 · Cited by 28 · see citing works
Ringer, F. B., & Anestis, M. D. (2015) · Crisis · doi:10.1027/0227-5910/a000311 · Cited by 22 · see citing works
Meeting ex-partners on Facebook: users' anxiety and severity of depression
Tsai, C.-W., Shen, P.-D., & Chiang, Y.-C. (2015) · Behaviour & Information Technology · doi:10.1080/0144929x.2014.981585 · Cited by 14 · see citing works
Flagged first, then by citations
Research works printed but not linked: 6
- American Academy of Pediatrics, 2011, Pediatrics, 127, 802
- Eysenbach G, 2008, Journal of Medical Internet Research, 10
- Pantic I, 2012, Psychiatric Danubina, 24, 90
- 10.1016/j.eurpsy.2015.04.002 · DOI · Paper page
- Rice SM, 16, Journal of Medical Internet Research 2–14;, 190
- HM Government/Department of Health, 2011, No health without mental health: a cross-government mental health outcomes strategy for people of all ages
Cited by
Sorted by citations
Keles, B., McCrae, N., & Grealish, A. (2020) · International Journal of Adolescence and Youth · doi:10.1080/02673843.2019.1590851 · Cited by 1,909 · see citing works
“…systematic reviews included more studies since they have either focussed on a heterogeneous population including children, adolescents and adults (Baker & Algorta, 2016; Marino et al., 2018; Seabrook et al., 2016) or focussed on general mental well-being including both clinical outcomes and…”
BackgroundThe future of social media in marketing
Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00695-1 · Cited by 1,893 · see citing works
“…through a number of different avenues such as teaching and developing socialization skills, allowing greater communication and access to a greater wealth of resources, and helping with connection and belonging (American Psychological Association 2011; Baker and Algorta 2016; Marker et al. 2018).”
BackgroundBorghouts, J., Eikey, E., Mark, G., De Leon, C., Schueller, S. M., Schneider, M., Stadnick, N., Zheng, K., Mukamel, D., & Sorkin, D. H. (2021) · Journal of Medical Internet Research · doi:10.2196/24387 · Cited by 1,069 · see citing works
Odgers, C. L., & Jensen, M. R. (2020) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13190 · Cited by 1,189 · see citing works
“…above in that cross-sectional research designs, retrospective reporting of symptoms and digital technology usage, and small and mixed patterns of associations were the norm and often limiting factors in drawing reliable conclusions in this area (Baker & Algorta, 2016; Seabrook et al., 2016).”
Oberst, U., Wegmann, E., Stodt, B., Brand, M., & Chamarro, A. (2017) · Journal of Adolescence · doi:10.1016/j.adolescence.2016.12.008 · Cited by 894 · see citing works
“More specifically, a systematic review of quantitative studies revealed that the relationship between online social networking and depressive symptoms is highly complex, and the impact of online social networking onwellbeing can be both positive and negative (Baker & Algorta, 2016).”
BackgroundMeier, A., & Reinecke, L. (2021) · Communication Research · doi:10.1177/0093650220958224 · Cited by 534 · see citing works
Riehm, K. E., Feder, K. A., Tormohlen, K. N., Crum, R. M., Young, A. S., Green, K. M., Pacek, L. R., La Flair, L. N., & Mojtabai, R. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.2325 · Cited by 511 · see citing works
Time spent on social network sites and psychological well-being: a meta-analysis
Huang, C. (2017) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2016.0758 · Cited by 457 · see citing works
Media use and brain development during adolescence
Crone, E. A., & Konijn, E. A. (2018) · Nature Communications · doi:10.1038/s41467-018-03126-x · Cited by 464 · see citing works
Is social network site usage related to depression? A meta-analysis of Facebook–depression relations
Yoon, S., Kleinman, M., Mertz, J., & Brannick, M. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.01.026 · Cited by 355 · see citing works
A meta-analysis of the association between adolescent social media use and depressive symptoms
Ivie, E. J., Pettitt, A., Moses, L. J., & Allen, N. B. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.06.014 · Cited by 358 · see citing works
Passive and Active Social Media Use and Depressive Symptoms Among United States Adults
Escobar-Viera, C. G., Shensa, A., Bowman, N. D., Sidani, J. E., Knight, J., James, A. E., & Primack, B. A. (2018) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2017.0668 · Cited by 351 · see citing works
“18,19 For example, research has found increased odds of depression and related outcomes among individuals who used a greater number of SM platforms, 20 had a skewed distribution of their social network on SM, 21 experienced negative interactions on SM sites, 14,22,23 or exhibited problematic SMU.”
A comprehensive meta-analysis on Problematic Facebook Use
Marino, C., Gini, G., Vieno, A., & Spada, M. M. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.02.009 · Cited by 378 · see citing works
Reer, F., Tang, W. Y., & Quandt, T. (2019) · New Media & Society · doi:10.1177/1461444818823719 · Cited by 335 · see citing works
Social media and depression symptoms: a meta-analysis
Cunningham, S., Hudson, C. C., & Harkness, K. (2021) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-020-00715-7 · Cited by 308 · see citing works
Kretzschmar, K., Tyroll, H., Pavarini, G., Manzini, A., Singh, I., & NeurOx Young People’s Advisory Group (2019) · Biomedical Informatics Insights · doi:10.1177/1178222619829083 · Cited by 270 · see citing works
“In addition, although we are aware that the positive and negative effects that social media might have on people’s mental health still needs further exploration, 50 online platforms do sometimes contribute to the development of mental health difficulties in the first place.”
BackgroundMatthes, J., Karsay, K., Schmuck, D., & Stević, A. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.106217 · Cited by 280 · see citing works
Jensen, M., George, M. J., Russell, M. R., & Odgers, C. L. (2019) · Clinical Psychological Science · doi:10.1177/2167702619859336 · Cited by 242 · see citing works
“Across these reviews, cross-sectional designs using retrospective reporting and small effect sizes consistently stand out (Baker & Algorta, 2016; Seabrook, Kern, & Rickard, 2016).”
BackgroundSteele, R. G., Hall, J. A., & Christofferson, J. L. (2019) · Clinical Child and Family Psychology Review · doi:10.1007/s10567-019-00300-5 · Cited by 242 · see citing works
“Taken together, these results suggest that a more complex and complete account of the association between social media use and outcomes in adolescents and young adults is necessary (Baker and Algorta 2016; Nesi et al. 2018).”
BackgroundRohani, D. A., Faurholt-Jepsen, M., Kessing, L. V., & Bardram, J. E. (2017) · doi:10.2196/preprints.9691 · Cited by 195 · see citing works
“We did not find any research article that explains how social patterns change with depression, but the review article by Baker et al [27] on online social networks suggests a complex relation involving factors that mediate or moderate the correlation and increase the variability in the findings.”
BackgroundSocial Media Use and Self-Injurious Thoughts and Behaviors: A Systematic Review and Meta-Analysis
Nesi, J., Burke, T. A., Bettis, A. H., Kudinova, A. Y., Thompson, E. C., MacPherson, H. A., Fox, K. A., Lawrence, H. R., Thomas, S. A., Wolff, J. C., et al. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102038 · Cited by 186 · see citing works
The relationship between Instagram use and indicators of mental health: a systematic review
Faelens, L., Hoorelbeke, K., Cambier, R., van Put, J., Van de Putte, E., De Raedt, R., & Koster, E. H. W. (2021) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2021.100121 · Cited by 182 · see citing works
“Since every platform has its own functionalities, additional research is needed to further investigate if previous results regarding the impact of SNS use on mental well-being are generalizable to Instagram (e.g., Baker & Algorta, 2016).”
BackgroundProblematic Social Media Use and Perceived Social Isolation in Older Adults: A Cross-Sectional Study
Meshi, D., Cotten, S. R., & Bender, A. R. (2020) · Gerontology · doi:10.1159/000502577 · Cited by 173 · see citing works
Coyne, S. M., Stockdale, L., & Summers, K. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2019.02.014 · Cited by 156 · see citing works
Poon, L. Y. J., Tsang, H. W. H., Chan, T. Y. J., Man, S. W. T., Ng, L. Y., Wong, Y. L., Lin, C., Chien, C., Griffiths, M. D., Pontes, H. M., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/26821 · Cited by 160 · see citing works
“One of the potential reasons underpinning this phenomenon might be the fact that excessive use of the internet can result in social withdrawal when an individual engages in gaming with features encouraging social disconnection (eg, features that increase social comparison and rumination [60,61]), which may lead to poo…”
BackgroundHussain, Z., & Griffiths, M. D. (2021) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-019-00175-1 · Cited by 142 · see citing works
Pang, H. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101690 · Cited by 158 · see citing works
“A handful of researchers have associated compulsive use with diverse detrimental psychiatric and physical illnesses, such as emotional disturbance, social isolation, and impairment of academic achievement (Baker and Algorta, 2016; Chow and Wan, 2017; Tunc-Aksan & Akbay, 2019).”
BackgroundScreen time, social media use, and adolescent development
Odgers, C. L., Schueller, S. M., & Ito, M. (2020) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-121318-084815 · Cited by 137 · see citing works
Escobar-Viera, C. G., Whitfield, D. L., Wessel, C. B., Shensa, A. S., Sidani, J. E., Brown, A. L., Chandler, C. J., Hoffman, B. L., Marshal, M. P., & Primack, B. A. (2018) · JMIR Mental Health · doi:10.2196/10496 · Cited by 135 · see citing works
“A key finding from this review, adding to other research on the same topic [36,66], is that seeking social support and connectedness might be a potentially strong motivation to use social media among LGB individuals [60,62,63].”
ResultExperimentally manipulating social media abstinence: results of a four-week diary study
Hall, J. A., Xing, C., Ross, E. M., & Johnson, R. M. (2021) · Media Psychology · doi:10.1080/15213269.2019.1688171 · Cited by 120 · see citing works
“A systematic quantitative review suggests the association between SNS use and depression is positive though often moderated by the type of user and types of use (Baker & Algorta, 2016).”
BackgroundFear of Missing Out, online social networking and mobile phone addiction: A latent profile approach
Fúster, H., Lusar, A. C., & Oberst, U. E. (2017) · Aloma: revista de psicologia, ciències de l'educació i de l'esport Blanquerna · doi:10.51698/aloma.2017.35.1.22-30 · Cited by 125 · see citing works
Turel, O., Cavagnaro, D. R., & Meshi, D. (2018) · Psychiatry Research · doi:10.1016/j.psychres.2018.11.017 · Cited by 113 · see citing works
“One line of research in the literature thus far has examined various possibly stressful outcomes of excessive SNS use, including for example reduced wellbeing, mental health, and social and academic functioning (Baker and Algorta, 2016; Junco, 2012; Tromholt, 2016; Verduyn et al., 2017).”
Lambert, J. D., Barnstable, G., Minter, E., Cooper, J., & McEwan, D. (2022) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2021.0324 · Cited by 136 · see citing works
“27”
Social Media Use and Mental Health: A Global Analysis
Ulvi, O., Karamehic-Muratovic, A., Baghbanzadeh, M., Bashir, A., Smith, J., & Haque, U. (2022) · Epidemiologia · doi:10.3390/epidemiologia3010002 · Cited by 111 · see citing works
“The literature spanned vast geographical ranges including Italy [3], Thailand [15], Poland [16], The United States [11,14,17,20,22,28,30,33,38,40,42,43], Germany [18,41], Australia [20,26], Korea [13,29].”
BackgroundSocial Media Use and Depressive Symptoms-A Longitudinal Study from Early to Late Adolescence
Puukko, K., Hietajärvi, L., Maksniemi, E., Alho, K., & Salmela-Aro, K. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17165921 · Cited by 99 · see citing works
Biagianti, B., Quraishi, S. H., & Schlosser, D. A. (2018) · Psychiatric Services · doi:10.1176/appi.ps.201700283 · Cited by 90 · see citing works
Excessive social media users demonstrate impaired decision making in the Iowa Gambling Task
Meshi, D., Elizarova, A., Bender, A., & Verdejo-Garcia, A. (2019) · Journal of Behavioral Addictions · doi:10.1556/2006.7.2018.138 · Cited by 88 · see citing works
Vahedi, Z., & Zannella, L. (2021) · Current Psychology · doi:10.1007/s12144-019-0150-6 · Cited by 86 · see citing works
“…finding is supported by previous systematic reviews of this literature that also reported a qualitative difference in studies that assessed general frequency of SNS use versus those that investigated specific activities that were deemed detrimental (Baker and Algorta 2016; Seabrook et al. 2016).”
BackgroundResultInfluentialYuan, H. (2020) · Aging & Mental Health · doi:10.1080/13607863.2020.1711858 · Cited by 84 · see citing works
“Baker and Algorta (2016) argue that negative interactions and social comparisons on the Internet may exacerbate the rebellion of some Internet users against mainstream social values, promote loneliness and alienation, and cause Internet addiction, indifference and fear.”
BackgroundSocial comparisons: A potential mechanism linking problematic social media use with depression
Samra, A., Warburton, W. A., & Collins, A. M. (2022) · Journal of Behavioral Addictions · doi:10.1556/2006.2022.00023 · Cited by 82 · see citing works
The Welfare Effects of Social Media
Allcott, H., Braghieri, L., Eichmeyer, S., & Gentzkow, M. (2019) · doi:10.3386/w25514 · Cited by 81 · see citing works
Adolescent development and growing divides in the digital age
Odgers, C. L., & Jensen, M. R. (2020) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2020.22.2/codgers · Cited by 74 · see citing works
Balcı, Ş., & Baloğlu, E. (2018) · Galatasaray Üniversitesi İleti-ş-im Dergisi · doi:10.16878/gsuilet.500860 · Cited by 76 · see citing works
Lim, L. T. S., Regencia, Z. J. G., Cruz, J. R. C. D., Ho, F. D. V., Rodolfo, M. S., Ly-Uson, J. T., & Baja, E. S. (2022) · PLoS ONE · doi:10.1371/journal.pone.0267555 · Cited by 89 · see citing works
Hall, J. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108629935 · Cited by 68 · see citing works
Online media consumption and depression in young people: A systematic review and meta-analysis
Shin, M., Juventin, M., Chu, J. T. W., Manor, Y. D., & Kemps, E. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107129 · Cited by 65 · see citing works
Djafarova, E., & Trofimenko, O. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.021 · Cited by 76 · see citing works
“Baker and Algorta (2016) analyse the links between social networking and depression.”
BackgroundRozgonjuk, D., Schivinski, B., Pontes, H. M., & Montag, C. (2021) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-021-00590-3 · Cited by 69 · see citing works
Young Adult Depression and Anxiety Linked to Social Media Use: Assessment and Treatment
Bettmann, J. E., Anstadt, G., Casselman, B., & Ganesh, K. (2020) · Clinical social work journal · doi:10.1007/s10615-020-00752-1
Plackett, R., Sheringham, J., & Dykxhoorn, J. (2023) · Journal of Medical Internet Research · doi:10.2196/43213 · Cited by 57 · see citing works
“Therefore, self-esteem has been identified as a possible mediator of the relationship between social media use and mental health problems [10,20].”
BackgroundAzhari, A., Toms, Z., Pavlopoulou, G., Esposito, G., & Dimitriou, D. (2022) · Acta Psychologica · doi:10.1016/j.actpsy.2022.103706 · Cited by 70 · see citing works
“Social media usage has also been found to have a positive impact on mental health, including alleviating anxiogenic symptoms (Baker & Algorta, 2016; Grieve et al., 2013).”
How online self-presentation affects well-being and body image: A systematic review
de Vaate, A. B. D., Veldhuis, J., & Konijn, E. (2020) · Telematics and informatics · doi:10.1016/j.tele.2019.101316 · Cited by 60 · see citing works
“This paper systematically reviewed 55 studies (from 52 journal publications) to present an overview of the extent to which active self-presentation, versus passive lurking, enhances or diminishes individuals’ well-being and body image. First, the key concepts used in the studies appeared to be conceptualized and opera…”
BackgroundInfluentialRozgonjuk, D., Pruunsild, P., Jürimäe, K., Schwarz, R.-J., & Aru, J. (2020) · Mobile Media & Communication · doi:10.1177/2050157920910190 · Cited by 56 · see citing works
“…it has also been found that non-problematic use of SM could be associated with better psychological well-being, suggesting that the relationship between SM and psychological variables is more complex and possibly dependent on individual differences (Baker & Algorta, 2016; Seabrook et al., 2016).”
BackgroundDigital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews
Li, L., Novillo-Ortiz, D., Muscat, N. A., & Kostkova, P. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.645260 · Cited by 58 · see citing works
“Therefore, the results indicate that these data sources may pose a significant threat to the mental health of teenagers (104– 108), potentially contributing to anxiety, depression, and even suicide (109, 110), but the strength of these associations is still uncertain and needs more controlled trials to be proven (105,…”
BackgroundChan, R. C. H. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107531 · Cited by 67 · see citing works
Uncovering cyberincivility among nurses and nursing students on Twitter: A data mining study
Gagne, J. C. D., Hall, K. M., Conklin, J., Yamane, S. S., Roth, N. W., Chang, J., & Kim, S. S. (2018) · International Journal of Nursing Studies · doi:10.1016/j.ijnurstu.2018.09.009 · Cited by 54 · see citing works
Karaköse, T., Yıldırım, B., Tülübaş, T., & Kardas, A. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1126815 · Cited by 62 · see citing works
“…to this field through several reviews addressing the relationships between depression and a particular sub-type of digital addiction (e.g., Carli et al., 2013; Baker and Algorta, 2016; Seabrook et al., 2016; Frost and Rickwood, 2017; Elhai et al., 2017a, b; Sohn et al., 2019; Yoon et al., 2019).”
BackgroundBottaro, R., & Faraci, P. (2022) · Current Addiction Reports · doi:10.1007/s40429-022-00445-4 · Cited by 74 · see citing works
Young adult cancer caregivers' exposure to cancer misinformation on social media
Warner, E. L., Waters, A. R., Cloyes, K. G., Ellington, L., & Kirchhoff, A. C. (2020) · Cancer · doi:10.1002/cncr.33380 · Cited by 51 · see citing works
Depressive symptoms and upward social comparisons during Instagram use: A vicious circle
Aubry, R., Quiamzade, A., & Meier, L. L. (2023) · Personality and Individual Differences · doi:10.1016/j.paid.2023.112458 · Cited by 49 · see citing works
A Comprehensive Review of the Key Deterioration Factors of Concrete Bridge Decks
Ibrahim, A., Abdelkhalek, S., Zayed, T. M., Qureshi, A. H., & Abdelkader, E. M. (2024) · Buildings · doi:10.3390/buildings14113425 · Cited by 46 · see citing works
Social Media Use Is (Weakly) Related to Psychological Distress
Stronge, S., Mok, T., Ejova, A., Lee, C., Zubielevitch, E., Yogeeswaran, K., Hawi, D., Osborne, D., Bulbulia, J., & Sibley, C. G. (2019) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2019.0176 · Cited by 44 · see citing works
“1 In previous research, positive and active uses of social media (creating content and connecting with others) correlated negatively with depressive symptoms, 3,4,12 whereas negative and passive uses (social comparison and reading content without interaction) correlated positively with depression…”
Ibrahim, A., Zayed, T. M., & Lafhaj, Z. (2024) · Buildings · doi:10.3390/buildings14071988 · Cited by 44 · see citing works
Harkin, L. J., & Kuss, D. (2021) · Psychology of Popular Media · doi:10.1037/ppm0000278 · Cited by 43 · see citing works
Mobile App Use by Primary Care Patients to Manage Their Depressive Symptoms: Qualitative Study
Pung, A., Fletcher, S. L., & Gunn, J. M. (2018) · Journal of Medical Internet Research · doi:10.2196/10035 · Cited by 42 · see citing works
Christensen, J. F. (2017) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2016.2837 · Cited by 41 · see citing works
Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review
Fu, J., Li, C., Zhou, C., Li, W., Lai, J., Deng, S., Zhang, Y., Guo, Z., & Wu, Y. (2023) · Journal of Medical Internet Research · doi:10.2196/43349 · Cited by 46 · see citing works
Fan, S., & Yang, Y. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192013332 · Cited by 38 · see citing works
“comparisons may exacerbate the rebellion of some Internet users against mainstream social values, promote loneliness and alienation, and cause indifference and fear [25].”
BackgroundTwitter-based measures of neighborhood sentiment as predictors of residential population health
Gibbons, J., Malouf, R., Spitzberg, B. H., Martinez, L. S., Appleyard, B., Thompson, C. R., Nara, A., & Tsou, M.-H. (2019) · PLoS ONE · doi:10.1371/journal.pone.0219550 · Cited by 38 · see citing works
Psychological Distress and Emotional Expression on Facebook
Bazarova, N. N., Choi, Y. H., Whitlock, J. L., Cosley, D., & Sosik, V. S. (2017) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2016.0335 · Cited by 37 · see citing works
“This may be because the quality of interactions encompasses not only what users do on SNS but also, more importantly, their psychological experiences and perceptions of the positivity or negativity of interactions.(7,12) Thus, to understand the impact of social networking on mental health and to leverage SNS as resour…”
InfluentialSocial comparisons on Facebook and offline: The relationship to depressive symptoms
Faranda, M., & Roberts, L. D. (2018) · Personality and Individual Differences · doi:10.1016/j.paid.2018.12.012 · Cited by 36 · see citing works
Tibber, M., Zhao, J., & Butler, S. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106371 · Cited by 33 · see citing works
Hiding Instagram Likes: Effects on negative affect and loneliness
Wallace, E., & Buil, I. (2020) · Personality and Individual Differences · doi:10.1016/j.paid.2020.110509 · Cited by 38 · see citing works
‘She has like 4000 followers!’: the celebrification of self within school social networks.
MacIsaac, S., Kelly, J., & Gray, S. (2017) · Journal of Youth Studies · doi:10.1080/13676261.2017.1420764 · Cited by 36 · see citing works
“Given how new and ever-evolving these forms of social interaction are, we are yet to fully appreciate or understand the potential implications on, for example, mental health (Baker and Algorta 2016; Pantic 2014).”
BackgroundQiu, C., Liu, Q., Yu, C., Li, Z., & Nie, Y. (2021) · Addictive Behaviors · doi:10.1016/j.addbeh.2021.107199 · Cited by 36 · see citing works
Wrzus, C., Frenkel, M. O., & Schöne, B. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104485 · Cited by 38 · see citing works
Young adult cancer caregivers' use of social media for social support
Warner, E. L., Kirchhoff, A. C., Ellington, L., Waters, A. R., Sun, Y., Wilson, A. R., & Cloyes, K. G. (2020) · Psycho-Oncology · doi:10.1002/pon.5402 · Cited by 34 · see citing works
Satıcı, B., Kayiş, A. R., & Griffiths, M. D. (2021) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-021-00658-0 · Cited by 46 · see citing works
Peer Connectedness and Social Technology Use During COVID-19 Lockdown
James, K. M., Silk, J. S., Scott, L. N., Hutchinson, E., Wang, S., Sequeira, S. L., Lu, C., Oppenheimer, C. W., & Ladouceur, C. D. (2023) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-023-01040-5 · Cited by 42 · see citing works
“Social technologies may have positive effects on emotional health through enhanced social support and connectedness (Baker & Algorta, 2016; Best et al., 2014; Gilmour et al., 2020; Massing-Schaffer et al., 2022), potentially compensating for lost in-person experiences with peers.”
BackgroundResultCorrelations of online social network size with well-being and distress: a meta-analysis
Huang, C. (2021) · Cyberpsychology: Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2021-2-3 · Cited by 33 · see citing works
“The reference lists for all relevant articles as well as previous review articles (D. A. Baker & Algorta, 2016; Best et al., 2014; Dobrean & Păsărelu, 2016; Frost & Rickwood, 2017; Huang, 2017; Keles et al., 2020; D. Liu & Baumeister, 2016; Seabrook et al., 2016; Song et al., 2014; Vahedi &…”
BackgroundCan Depression Be Prevented? If So, How?
Hoare, E., Callaly, E., & Berk, M. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.1273 · Cited by 33 · see citing works
Marciano, L., Schulz, P. J., & Camerini, A.-L. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107390 · Cited by 36 · see citing works
Tsai, H.-Y. S., Hsu, P.-J., Chang, C.-L., Huang, C.-C., Ho, H.-F., & LaRose, R. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.12.034 · Cited by 32 · see citing works
Orsolini, L., Volpe, U., Albert, U., Carmassi, C., Carrà, G., Cirulli, F., Dell’Osso, B. M., Vecchio, V. D., Nicola, M. D., Giallonardo, V., et al. (2022) · Annals of General Psychiatry · doi:10.1186/s12991-022-00419-w · Cited by 36 · see citing works
Cudo, A., Szewczyk, M., Błachnio, A., Przepiórka, A., & Jarząbek-Cudo, A. (2019) · Psychiatric Quarterly · doi:10.1007/s11126-019-09685-6 · Cited by 31 · see citing works
Al-Busaidi, A. S., Dauletova, V., & Al-Wahaibi, I. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2075791 · Cited by 32 · see citing works
“The growing body of literature states that the most vulnerable and susceptible to the misuse of social media demographic groups are children and young adults (Baker and Algorta 2016; Lin et al. 2016; Oberst et al. 2016).”
BackgroundCole, D. A., Nick, E. A., Varga, G., Smith, D. K., Zelkowitz, R. L., Ford, M. A., & Lédeczi, Á. (2019) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2019.0035 · Cited by 29 · see citing works
“These results support Baker and Algorta’s observation that the effect of social media on depression-related outcomes is complicated by social, psychological, and behavioral moderators.(8) The current research provides longitudinal evidence that in-person social support may be one such moderator.”
ResultVijayabanu, C., Shanmugam, K., & Parayitam, S. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2046164 · Cited by 30 · see citing works
“Researchers addressed the antecedents and consequences of SN addiction (Baker and Algorta 2016; Kuss and Griffiths 2011; Manner 2017).”
BackgroundResultEpidemiology of Hikikomori: A systematic review and meta‐analysis of 19 studies
Zhang, W., Chen, M., Feng, Y., Su, Z., Cheung, T. C. C., Jackson, T., Zhang, Q., & Xiang, Y. (2025) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.13768 · Cited by 29 · see citing works
“…billions of people, particularly younger cohorts, use online social networks such as Facebook, X, Instagram, and WeChat to interact with others; 66 unfortunately, young adults with high social media usage report feeling more socially isolated and anxious compared to those with lower usage.”
Time perspective and Facebook addiction: The moderating role of neuroticism
Miceli, S., Cardaci, M., Scrima, F., & Caci, B. (2021) · Current Psychology · doi:10.1007/s12144-021-01355-w · Cited by 29 · see citing works
Lyu, J., Krasonikolakis, I. G., & Chen, C.-H. (2023) · Information & Management · doi:10.1016/j.im.2023.103818 · Cited by 32 · see citing works
“Despite positive support for smartphones ’ functions and assistance, excessive adoption of a technology may bring some limitations or negative effects especially in terms of anxiety [61] and its corresponding influence on purchasing behavior.”
Valentine, L., McEnery, C., D’Alfonso, S., Phillips, J., Bailey, E., & Alvarez-Jimenez, M. (2019) · Current Treatment Options in Psychiatry · doi:10.1007/s40501-019-00184-w · Cited by 26 · see citing works
Petalas, D. P., Konijn, E., Johnson, B. K., Veldhuis, J., de Vaate, N. A. J. D. B., Burgers, C., Droog, E., Miedzobrodzka, E., Bálint, K., & van de Schoot, R. (2021) · Social Media + Society · doi:10.1177/20563051211035353 · Cited by 20 · see citing works
“…SMU or more descriptive and non-pathological forms of SMU report primarily small, negative relationships between SMU and MH (Appel et al., 2020; Baker & Algorta, 2016; Best et al., 2014; Çikrıkci, 2016; Elhai et al., 2017; Glover & Fritsch, 2018; Huang, 2010, 2017; Keles et al., 2020; Liu et…”
InfluentialDoes trade reduce infant mortality? Evidence from sub-Saharan Africa
Panda, P. (2020) · World Development · doi:10.1016/j.worlddev.2019.104851 · Cited by 23 · see citing works
Aydın, O., Çökmüş, F. P., Balıkçı, K., Di̇ki̇ci̇, D. S., & Ünal‐Aydın, P. (2020) · International Journal of Social Psychiatry · doi:10.1177/0020764020919791 · Cited by 25 · see citing works
(2021) · doi:10.2196/24988 · Cited by 24 · see citing works
“For example, the extant literature on self-harm focuses primarily on a single challenge and its effect on public health and safety [15,21-23] or on how viewing content showing self-harm could lead to intentional self-harm by modeling the behavior of those we observe [24-26].”
Adeyanju, G. C., Solfa, R. P., Tran, T. L., Wohlfarth, S., Büttner, J., Osobajo, O. A., & Otitoju, A. (2021) · Translational Medicine Communications · doi:10.1186/s41231-021-00092-3 · Cited by 24 · see citing works
Park, H. J. (2022) · Telematics and Informatics · doi:10.1016/j.tele.2022.101878 · Cited by 24 · see citing works
Development and Maintenance of Self-Disclosure on Facebook: The Role of Personality Traits
Caci, B., Cardaci, M., & Miceli, S. (2019) · SAGE Open · doi:10.1177/2158244019856948 · Cited by 24 · see citing works
“While disclosing themselves on Facebook, people compare their lives with those of the others, also feeling quite depressed (Baker & Algorta, 2016).”
BackgroundProbing the digital exposome: associations of social media use patterns with youth mental health
Pagliaccio, D., Tran, K. T., Visoki, E., DiDomenico, G. E., Auerbach, R. P., & Barzilay, R. (2024) · NPP—Digital Psychiatry and Neuroscience · doi:10.1038/s44277-024-00006-9 · Cited by 23 · see citing works
- Authors
- Baker, D. A., & Algorta, G. P.
- Affiliations
- Lancaster University (GB)
- Spectrum Centre for Mental Health Research, Division of Health Research, Faculty of Health and Medicine, Lancaster University, Lancaster, United Kingdom.
- ORCID
- Baker, David A.
- Venue
- Cyberpsychology, Behavior, and Social Networking
- Publisher
- SAGE Publications
- Published
- 2016-11
- Volume
- 19
- Issue
- 11
- Pages
- 638-648
- ISSN
- 2152-2715 (ISSN-L)
- 2152-2723
- OpenAlex
- W2531561814
- Semantic Scholar
- 812f8d91109038313abddeef624b6bbff0d39828
- Cited by
- 286
- References
- 60
- Citations by year
- 2026: 12 · 2025: 20 · 2024: 33 · 2023: 28 · 2022: 43 · 2021: 32 · 2020: 51 · 2019: 36 · 2018: 17 · 2017: 12 · 2016: 1 · 2014: 1
- FWCI
- 8.30
- Type
- journal article
- Language
- en
- Open access
- green
- eprints.lancs.ac.uk
- Locations
- Cyberpsychology Behavior and Social Networking (publishedVersion)
- PubMed (publishedVersion)
- Lancaster EPrints (Lancaster University) (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Psychology › Social Psychology › Mental Health via Writing
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- online social networking, depression, depressive symptoms, Facebook, Twitter, MySpace, mental health, well-being, social media use, mediators and moderators
- MeSH terms
- Depression, Humans, Social Networking, Social Media
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