Detecting Depression Signs on Social Media: A Systematic Literature Review

Affiliations.

  • 1 Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico.
  • 2 Tecnológico Nacional de México/I.T.S. Teziutlán, Fracción I y II S/N, Aire Libre, Teziutlán 73960, Puebla, Mexico.
  • 3 Centro de Investigación en Inteligencia Artificial/Universidad Veracruzana, Sebastián Camacho 5, Zona Centro, Centro, Xalapa-Enríquez 91000, Veracruz, Mexico.
  • 4 CONACYT-Tecnológico Nacional de México/I. T. Orizaba, Av. Oriente 9 No. 852, Col. Emiliano Zapata, Orizaba 94320, Veracruz, Mexico.
  • PMID: 35206905
  • PMCID: PMC8871802
  • DOI: 10.3390/healthcare10020291

Among mental health diseases, depression is one of the most severe, as it often leads to suicide; due to this, it is important to identify and summarize existing evidence concerning depression sign detection research on social media using the data provided by users. This review examines aspects of primary studies exploring depression detection from social media submissions (from 2016 to mid-2021). The search for primary studies was conducted in five digital libraries: ACM Digital Library, IEEE Xplore Digital Library, SpringerLink, Science Direct, and PubMed, as well as on the search engine Google Scholar to broaden the results. Extracting and synthesizing the data from each paper was the main activity of this work. Thirty-four primary studies were analyzed and evaluated. Twitter was the most studied social media for depression sign detection. Word embedding was the most prominent linguistic feature extraction method. Support vector machine (SVM) was the most used machine-learning algorithm. Similarly, the most popular computing tool was from Python libraries. Finally, cross-validation (CV) was the most common statistical analysis method used to evaluate the results obtained. Using social media along with computing tools and classification methods contributes to current efforts in public healthcare to detect signs of depression from sources close to patients.

Keywords: depression; sentiment analysis; social media.

Publication types

  • Open access
  • Published: 17 May 2022

Social media use and mental health during the COVID-19 pandemic in young adults: a meta-analysis of 14 cross-sectional studies

  • Youngrong Lee 1 ,
  • Ye Jin Jeon 2 ,
  • Sunghyuk Kang 2 , 3 ,
  • Jae Il Shin 4 ,
  • Young-Chul Jung 3 &
  • Sun Jae Jung 1 , 2  

BMC Public Health volume  22 , Article number:  995 ( 2022 ) Cite this article

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Public isolated due to the early quarantine regarding coronavirus disease 2019 (COVID-19) increasingly used more social media platforms. Contradictory claims regarding the effect of social media use on mental health needs to be resolved. The purpose of the study was to summarise the association between the time spent on social media platform during the COVID-19 quarantine and mental health outcomes (i.e., anxiety and depression).

Studies were screened from the PubMed, Embase, and Cochrane Library databases. Regarding eligibility criteria, studies conducted after the declaration of the pandemic, studies that measured mental health symptoms with validated tools, and studies that presented quantitative results were eligible. The studies after retrieval evaluated the association between time spent on social media platform and mental health outcomes (i.e. anxiety and depression). The pooled estimates of retrieved studies were summarised in odds ratios (ORs). Data analyses included a random-effect model and an assessment of inter-study heterogeneity. Quality assessment was conducted by two independent researchers using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS). This meta-analysis review was registered in PROSPERO ( https://www.crd.york.ac.uk/PROSPERO/ , registration No CRD42021260223, 15 June 2021).

Fourteen studies were included. The increase in the time spent using social media platforms were associated with anxiety symptoms in overall studies (pooled OR = 1.55, 95% CI: 1.30–1.85), and the heterogeneity between studies was mild (I 2  = 26.77%). Similarly, the increase in social media use time was also associated with depressive symptoms (pooled OR = 1.43, 95% CI: 1.30–1.85), and the heterogeneity between studies was moderate (I 2  = 67.16%). For sensitivity analysis, the results of analysis including only the “High quality” studies after quality assessment were similar to those of the overall study with low heterogeneity (anxiety: pooled OR = 1.45, 95% CI: 1.21–1.96, I 2  = 0.00%; depression: pooled OR = 1.42, 95% CI: 0.69–2.90, I 2  = 0.00%).

Conclusions

The analysis demonstrated that the excessive time spent on social media platform was associated with a greater likelihood of having symptoms of anxiety and depression.

Peer Review reports

Introduction

Despite the tremendous worldwide efforts including the introduction of vaccines, developing therapeutics and social distancing, the coronavirus outbreak is not expected to dampen due to the continuous emergence of new viral strains and difficulty in effective quarantine interventions. As a result of strong quarantine measures, private meetings, gatherings, and physical contact with intimate relatives have been reduced [ 1 ]. Prolonged social distancing and loss of intimate interpersonal contact increase feelings of frustration, boredom, anxiety, and potentially depression [ 2 ].

Studies have found that young, socially active populations or workers at high risk of infection, especially college students and frontline healthcare workers, bear a disproportionate burden of mental health problems worldwide (e.g., high levels of anxiety and depression), highlighting the need for appropriate intervention in these populations [ 3 , 4 ].

Social media in digital platforms is reportedly considered as a new channel of communication that could relieve aforementioned negative aspects of isolation through helping people escape negative emotions [ 5 ], projecting their personality as they desire, and evoking the impression of gaining back some control [ 6 ]. Social media may be helpful for relieving anxiety and depression by providing information regarding the pandemic [ 7 , 8 ].

However, prolonged use of social media by the isolated could be a double-edged sword that can adversely affect mental health due to sustained exposure to excessive information and misinformation [ 9 , 10 , 11 ]. While social media in digital platforms does help to promote social inclusion among adolescents and young adults, the risk associated with their excessive or problematic use cannot be overlooked [ 12 ]. Due to conflicting evidence and views regarding the effect of social media platform on the mental health, the recommendation for the use of social media in pandemic has been questioned.

Therefore, a meta-analysis was conducted to solve the contradictory effects of social media platform on anxiety and depression based on studies reporting an association between the use of social media and mental health outcomes (i.e., anxiety and depression) on the pandemic setting.

Eligibility criteria

Studies were included which met the following criteria: (1) use of the English language; (2) conducted after March 11, 2020 (date the WHO declared a pandemic) and published by December 20, 2020; (3) collected data using a validated tool of mental health symptoms (e.g., Patient Health Questionnaire: PHQ9, Generalized Anxiety Disorder-7 items: GAD-7); (4) full texts available; (5) measured time spent on social media platform in either continuous or categorical variable; (5) provided their results in OR, β, and/or Pearson’s r, and (6) studies measured mental health symptoms such as anxiety and depression.

Studies with the following characteristics were excluded: (1) Studies examined traditional social media (e.g., television and radio); (2) case reports, letters, comments, and narrative reviews without quantitative results, and (3) studies using a language other than English.

Studies investigating the association between time spent on social media and mental health outcomes (e.g., anxiety and depression) were summarised in Supplementary Material 1 . The pooled effect size of this meta-analysis was mainly presented in an odds ratio (Fig.  2 ).

Study selection

The search strategy principles were as follows: (1) “Social media” or individual names of social media in the title, keyword and abstract results; (2) Terms referring to mental health with COVID-19 specified in the title (e.g. depression, anxiety or blue).

A systematic literature search of the PubMed, Embase, and Cochrane Library databases was performed to identify studies. Publication date restrictions are from March 2020 to December 20, 2020. The search terms for a systematic search were as following: (1) (“COVID-19“ OR “corona“) AND (“mental health” OR depress* OR anxiety) AND (“social media” OR “Instagram” OR “Facebook” OR “twitter”) for PubMed, (2) (“coronavirus disease 2019’/exp/mj) AND (“mental health“/exp/mj OR “depression“/exp OR “anxiety“/exp) AND (“social media”/exp./mj OR “Facebook”/exp. OR “twitter”/exp. OR “Instagram“/exp) for Embase; (3) (“COVID-19″ OR “corona”) AND (“mental health“ OR depress* OR “anxiety”) AND (“social media“ OR ‘Instagram” OR “Facebook” OR “twitter”) for Cochrane Library.

Articles were first screened by reviewing titles, followed by a full-text review. Every selection stage involved three independent researchers (two medical doctors [SJJ and YRL] and one graduate student from the Epidemiology Department [YJJ]). Every article was independently evaluated by two researchers (YJJ and YRL) in first hand, and a third researcher (SJJ) mediated the final selection in case of differences in opinion.

Data extraction

Study data were extracted by two independent researchers (YRL and YJJ). A single author first extracted the information and a second author checked for accuracy. The extracted information is as follows: country of study, participant group sampled, age group of sample, date of data collection, mental health measures, effect size information, social media use time, and whether the adjustment was made for each analysis (see Supplementary Material 1 ). Studies were subdivided into categories according to the summary estimate of effect sizes (odds ratio [OR], beta estimate from multiple linear regression [β], and correlation coefficient [Pearson’s r]).

Exposure variables

The final studies after retrieval measured the amount of time spent on social media, which was either categorical or continuous variables (see Supplementary Material 1 ). It was measured based on the response to an item in the questionnaire: “How often were you exposed to social media? [categorical]” and “How long (in hours) were you exposed to social media? [continuous].” The measurement of exposure was expressed in different wordings as follows: “Less” vs. “Frequently,” “Less” vs. “Often”, “less than 1 hour” vs. “2 hours or more,” or “less than 3 hours” vs. “3 hours or more.” To calculate the overall effect, these individually measured exposure levels were operationally redefined (e.g., “Less” and “Few” were considered the same as “less than 2 hours;” “less than 1 hour,” “Frequently,” and “Often” were treated the same as “2 hours or more” and “3 hours or more”).

Outcome variables

The outcomes of included studies were “anxiety”, and “depression”. Anxiety was ascertained by using GAD-7 (cut-off: 10+), DASS-21, and PHQ-9, while depression was measured using PHQ-9 (cut-off: 10+), WHO-5 (cut-off: 13+), and GHQ-28 (cut-off: 24+). Anxiety and depression measured by using screening tools with cut-offs presented results in odds ratios (see Supplementary Material 1 ).

Statistical analysis

All statistical analyses and visualisations were performed with the “meta,” “metaphor,” and “dmeter” package of R version 3.6.3 ( https://cran.r-project.org/ ), using a random-effect model [ 13 , 14 , 15 ]. The effect measures were odds ratio, regression coefficient, and Pearson’s r, which calculated the association between the increase in social media use time and anxiety and depressive symptoms. In each study, the association with the mental health level of the social media frequent use group (compared to the low frequency group) was calculated as the odds ratio, and the association with the increase in the mental health level per hour increase was calculated as the regression coefficient (β) and Pearson’s r. Statistics used for calculating pooled effects (e.g., odds ratio, regression coefficient, and Pearson’s r) were utilized as its adjusted value with covariates from each study, not the unadjusted crude values.

The pooled effect sizes, Cochrane’s Q, and I 2 to assess heterogeneity were calculated. The pooled effect sizes, CIs, and prediction intervals were calculated by estimating the pooled effect and CIs using the Hartung-Knapp-Sidik-Jonkman method, which is known as the one of the most conservative methods [ 16 ]. The degree of heterogeneity was categorised as low, moderate, or high with threshold values of 25, 50, and 75%, respectively [ 17 ]. Possible causes of heterogeneity among study results were explored by statistical methods such as influential analysis, the Baujat plot, leave-one-out analysis, and Graphic Display of Heterogeneity analysis [ 18 ]. In addition, publication bias was assessed using funnel plots, Egger’s tests, and the trim-and-fill method [ 19 ].

Quality assessment

Quality assessment was conducted by two independent researchers, a psychiatrist (SHK) and an epidemiologist (YRL), using the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS), which can assess cross-sectional studies [ 20 ]. RoBANS has been validated with moderate reliability and good validity. RoBANS applies to cross-sectional studies and comprises six items: participant selection, confounding, exposure measurement, blinding of outcome assessments, missing outcomes, and selective reporting of outcomes. Each item is measured as having a “high risk of bias,” “low risk of bias,” or “uncertain.” For example, based on “participant selection,” each researcher marked an article as having a “high risk of bias” if, for example, the patient definitions of depression were generated by self-reported data. In cross-sectional studies, misclassification cases due to an unreliable self-contained questionnaire for categorizing depressive patients were rated as “high risk.” For the qualitative assessment, studies with two or more “high risk of bias” grades were then classified as “low quality”. The study was rated as “high quality” only if the evaluation of both raters was congruent. For sensitivity analysis, additional analysis including only “high quality” studies was conducted and it compared with the pooled estimates of overall results (see Table  1 ).

Ethical approval

The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines 2020 were followed for this study. No ethical approval and patient consent are required since this study data is based on published literature. This meta-analysis review was registered with PROSPERO ( https://www.crd.york.ac.uk/PROSPERO/ , registration No CRD42021260223, 15 June 2021).

Included and excluded studies

Total of 346 studies were selected from the database search (288 from PubMed, 34 from Embase, and 24 from the Cochrane Library). After removing 19 duplicate publications, 327 studies were included for the title and full-text review (see Fig.  1 ). Non-original studies and those conducted with irrelevant subjects ( n  = 218) were excluded. Another 95 studies were excluded finally due to inconsistent study estimates. As summarised in Supplementary material 1 and 8 , 13 papers studied anxiety as an outcome (6 studies in odds ratio, 3 in regression coefficient, 4 in Pearson’s r), and a total of 9 papers studied depression as an outcome (6 studies in odds ratio, 3 in regression coefficient). Each of the final distinct 14 studies (after excluding duplicate studies) measured multiple mental health outcome variables (i.e., anxiety and depression), and pooled effect sizes were calculated for each outcome. Six studies that dealt with anxiety symptoms and six with depression (Supplementary Material 1 –1-1, 1–2-1) reported ORs and their 95% confidence intervals (CIs) ( n  = 9579 and n  = 13,241 for anxiety and depressive symptoms, respectively). Three studies each on anxiety and depression (Supplementary Material 1 –1-2, 1–2-2) reported their findings in β ( n  = 2376 and n  = 2574 for anxiety and depression, respectively). All included studies were cross-sectional studies. The pooled effect size was presented in odds ratio.

figure 1

Flowchart of literature search and selection of the publications

Time spent on social media and mental health outcomes

Table 1 shows the result of the meta-analysis about the relationship between time spent on social media and mental health outcomes (i.e., anxiety and depression) of the selected cross-sectional studies. The increase in the time spent using social media platforms were associated with anxiety symptoms in overall studies (pooled OR = 1.55, 95% CI: 1.30–1.85, prediction intervals: [1.08–2.23]), and the heterogeneity between studies was mild (I 2  = 26.77%) (see Fig. 2 ). The three cross-sectional studies (presented in β) were insignificant (β = 0.05, 95% CI: − 0.32–0.15; a unit increment of each screening tool score per hour) with relatively high inter-study heterogeneity (I 2  = 76.07%). The overall estimate of the four cross-sectional studies (Pearson’s r) was 0.18 (95% CI: 0.10–0.27) with high inter-study heterogeneity (I 2  = 73.04%). The increase in social media use time was also associated with depressive symptoms (pooled OR = 1.43, 95% CI: 1.30–1.85, prediction intervals: [0.82–2.49]), and the heterogeneity between studies was moderate (I 2  = 67.16%) (see Fig. 2 ).

figure 2

Forest plot for social media exposure and symptoms of mental health (i.e. anxiety & depression) in cross-sectional studies. Estimates presented in odds ratios (OR)

As result of quality assessment analysis, pooled effect size of studies classified as “high quality” was presented in Table 1 . The results were similar to the overall outcome (anxiety: OR = 1.45, 95% CI: 1.21–1.96; depression: OR = 1.42, 95% CI: 0.69–2.90). High-quality studies had low inter-study heterogeneity (anxiety: I 2  = 0.00%; depression: I 2  = 0.00%). The kappa statistic (inter-rater agreement) was 33.3%, indicating fair agreement.

Publication bias

Publication bias was assessed by funnel plot analysis and Egger’s test (Supplementary Material 4 –1). Funnel-plot analyses revealed symmetrical results (Supplementary Material 4 –2). In addition, all results of the Egger test were statistically insignificant, indicating improbable publication bias. After applying the trim-and-fill method, the funnel plot revealed no asymmetry (Supplementary Material 5 ), indicating no significant publication bias.

The study aimed to present a comprehensive direction of relevance by analysing studies investigating the association between time spent on social media during the COVID-19 pandemic and mental health symptoms (i.e., anxiety and depressive) among the public. The increase in the time spent on social media in digital platforms was associated with symptoms of anxiety and depression.

The pooled results are in line with previous systematic reviews and meta-analysis performed before the pandemic. A systematic literature review before the COVID-19 outbreak (2019) found that the time spent by adolescents on social media was associated with depression, anxiety, and psychological distress [ 21 ]. A meta-analysis of 11 studies (2017) also reported a weak association between social media use and depressive symptoms in children [ 22 ]. A meta-analysis of 23 studies (2018) reported significant correlation between social media use and psychological distress [ 23 ]. Likewise, this study also observed a similar trend of a negative effect of social media on mental health outcomes in the COVID-19 pandemic. However, the estimates of inter-study heterogeneity of these meta-analysis were relatively high (meta-analysis of 11 studies: I 2  = 92.4%; meta-analysis of 23 studies: I 2  = 62.00% for anxiety, I 2  = 80.58% for depression) compared to the analysis, which implies relatively higher homogeneity of the study population and reliable results.

Unverified information and opinions can be easily disseminated on social media platform and perceived as facts without verification. There has been a stream of news regarding the pandemic, creating a sense of urgency and anxiety. Repeated exposure to the news may affect the construct of external reality and may lead to a delusion-like experience, which has been linked to anxiety and social media overuse [ 24 , 25 ].

Additionally, discrimination and stigma related to COVID-19 on social media can make people fearful of being infected and exacerbate depression and anxiety [ 26 ]. Fear of COVID-19 may be compounded by coexisting depression and anxiety disorders [ 27 ]. Due to the high accessibility of social media platform and the ease of socialisation in a controlled setting, individuals with underlying depression may be more drawn to social media interactions rather than face-to-face ones, more so in the pandemic era [ 28 ].

Also, implementation of social distancing mandates new norms limiting physical conducts in almost all sectors of life, including educational institutes and vocational venue. Rapid transition to the new remote educational environment and telecommuting may trigger mental health issues [ 29 ].

In interpreting the findings of this study, several limitations should be considered. First, all the studies included were cross-sectional design. The possibility of a reverse causal relationship cannot be ruled out. Further studies with longitudinal data are warranted. Second, the results do not represent the general population since most of the studies recruited participants through a web-based survey, which may have had a selection bias. Lastly, some of the analysis showed a relatively high inter-study heterogeneity (range: I 2  = 0.00–80.53%). The results of the statistical approaches to identify the cause of heterogeneity (i.e. influential analysis, Baujat plot, leave-one-out analysis, and GOSH analysis) were summarised in Supplementary Material 6 and 7 .

Despite these limitations, this study exhibits a number of strengths; to the best of our knowledge, the study is the first meta-analysis to examine the relationship between use of social media and mental health outcomes during the COVID-19 pandemic, to validate the results by various verification methods such as trim-and-fill methods, influential analysis, and heterogeneity analysis. In addition, sensitivity analysis was also conducted with unbiased “high quality” studies through quality assessment.

The analysis demonstrates that excessive time spent on social media platform is associated with increased anxiety and depressive symptoms in the pandemic. While social media may be considered as an alternative channel for people to connect with their peers in the pandemic, the findings suggest that excessive use of social media can be detrimental for mental health. Further observation studies with longitudinal design to determine the true effect of social media platform are required.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

Coronavirus disease 2019

Confidence interval

Patient Health Questionnaire-9

Shortened version of PHQ

General Health Questionnaire-28

Depression Anxiety and Stress Scales

World Health Organization-Five Well-Being Index

Generalized Anxiety Disorder-7

Shortened version of GAD

Risk of Bias Assessment Tool for Nonrandomized Studies

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Acknowledgements

The authors would like to thank the Editage ( www.editage.co.kr ) for English language editing.

This study was supported by the National Research Foundation of Korea, funded by the Ministry of Science and ICT (2020R1C1C1003502), awarded to SJJ.

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Ye Jin Jeon, Sunghyuk Kang & Sun Jae Jung

Department of Psychiatry, Yonsei University College of Medicine, Seoul, South Korea

Sunghyuk Kang & Young-Chul Jung

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Contributions

Conceptualization: YRL, SJJ. Data curation: SJJ, JIS, YCJ, YRL. Formal analysis: YRL, SJJ. Funding acquisition: SJJ. Methodology: JIS, YCJ, YRL, SJJ. Project administration: SJJ. Visualization: YRL. Writing – original draft: YRL, YJJ, SHK, SJJ. Writing – review & editing: YRL, YJJ, SHK, JIS, YCJ, SJJ. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. The author(s) read and approved the final manuscript.

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Correspondence to Sun Jae Jung .

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No ethical approval and patient consent are required since this study data is based on published literature. This meta-analysis review was registered with PROSPERO ( https://www.crd.york.ac.uk/PROSPERO/ , registration No CRD42021260223, 15 June 2021).

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Lee, Y., Jeon, Y.J., Kang, S. et al. Social media use and mental health during the COVID-19 pandemic in young adults: a meta-analysis of 14 cross-sectional studies. BMC Public Health 22 , 995 (2022). https://doi.org/10.1186/s12889-022-13409-0

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DOI : https://doi.org/10.1186/s12889-022-13409-0

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This paper analyzes the existing body of work on the relationship between depression and social media use in the information system field, including the impact of social media use on depression, the effect of depression on social media use and the association and interaction between depression and social media use.

Design/methodology/approach

Using the systematic review method, this study selected the Web of Science, Emerald, Science Direct, JSTOR, Wiley Online Library and Taylor and Francis Online as search databases and ended up with 29 papers that met all the authors' requirements.

This study identified five possible reasons for the inconsistencies between the findings of the selected studies. First, uses and gratifications theory has different influence mechanisms in evaluating the relationship between social media use and depression. Second, gender can moderate the impact of social media use on depression. Third, age moderates the association between social media use and depression. Fourth, for adolescents, the time spent on social media has a critical effect on their depression. Fifth, negative personality traits (e.g. rumination, envy, etc.) can play a significant role in mediating the relationship between passive social media use and depression.

Originality/value

This study conducted an evaluation of the relationship between depression and social media use. First, the authors summarized the research framework and main body of work covering the relationship between depression and social media use. Second, the authors proposed possible explanations for the inconsistencies between the findings. Third, the authors discussed and explained the possible influence mechanisms of the existing results.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0211 .

  • Social media use
  • Systematic review
  • Information system

Acknowledgements

This study was supported by research grants from the National Natural Science Foundation of China (grant no. 71973057).

Zhu, W. , Mou, J. , Benyoucef, M. , Kim, J. , Hong, T. and Chen, S. (2023), "Understanding the relationship between social media use and depression: a review of the literature", Online Information Review , Vol. 47 No. 6, pp. 1009-1035. https://doi.org/10.1108/OIR-04-2021-0211

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#Depression: Findings from a Literature Review of 10 Years of Social Media and Depression Research

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literature review on social media and depression

  • Julissa Murrieta 17 ,
  • Christopher C. Frye 18 ,
  • Linda Sun 18 ,
  • Linh G. Ly 19 ,
  • Courtney S. Cochancela 20 &
  • Elizabeth V. Eikey   ORCID: orcid.org/0000-0002-3099-8081 21  

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The purpose of our literature review was to understand the state of research related to social media and depression within the past 10 years. We were particularly interested in understanding what has been studied in relation to immigrant college students, as they are especially at risk for depression. Searching three databases, ACM Digital Library, PubMed, and IDEALS, we found 881 research articles. Based on our criteria, 78 research papers were included in our analysis. Although social media use is common among college students and depression is an issue for many immigrants and college students, we found few studies that focused specifically on college students, and we identified no studies on immigrant college students or college-aged immigrants. The research articles focused primarily on Twitter and general social media usage (rather than specific social media platforms) and commonly employed qualitative methods. We identify four gaps in the existing literature, why they matter, and how future research (our own included) can begin to address them.

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Murrieta, J., Frye, C.C., Sun, L., Ly, L.G., Cochancela, C.S., Eikey, E.V. (2018). #Depression: Findings from a Literature Review of 10 Years of Social Media and Depression Research. In: Chowdhury, G., McLeod, J., Gillet, V., Willett, P. (eds) Transforming Digital Worlds. iConference 2018. Lecture Notes in Computer Science(), vol 10766. Springer, Cham. https://doi.org/10.1007/978-3-319-78105-1_6

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Digital media use, depressive symptoms and support for violent radicalization among young Canadians: a latent profile analysis

  • Diana Miconi 1 ,
  • Tara Santavicca 2 ,
  • Rochelle L. Frounfelker 3 ,
  • Aoudou Njingouo Mounchingam 4 &
  • Cécile Rousseau 5  

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Despite the prominent role that digital media play in the lives and mental health of young people as well as in violent radicalization (VR) processes, empirical research aimed to investigate the association between Internet use, depressive symptoms and support for VR among young people is scant. We adopt a person-centered approach to investigate patterns of digital media use and their association with depressive symptoms and support for VR.

A sample of 2,324 Canadian young people (M age = 30.10; SD age = 5.44 ; 59% women) responded to an online questionnaire. We used latent profile analysis to identify patterns of digital media use and linear regression to estimate the associations between class membership, depressive symptoms and support for VR.

We identified four classes of individuals with regards to digital media use, named

Average Internet Use/Institutional trust, Average internet use/Undifferentiated Trust, Limited Internet Use/Low Trust and Online Relational and Political Engagement/Social Media Trust. Linear regression indicated that individuals in the Online Relational and Political Engagement/Social Media Trust and Average Internet Use/Institutional trust profiles reported the highest and lowest scores of both depression and support for VR, respectively.

Conclusions

It is essential to tailor prevention and intervention efforts to mitigate risks of VR to the specific needs and experiences of different groups in society, within a socio-ecological perspective. Prevention should consider both strengths and risks of digital media use and simulteaneously target both online and offline experiences and networks, with a focus on the sociopolitical and relational/emotional components of Internet use.

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The recent increase in support for – and direct engagement in – ideologically motivated violence among youth can be associated with the increase in social polarization in society [ 1 ] as well as the specificities of adolescence and early adulthood, a seminal period for the development of ideologies [ 2 , 3 ]. Violent radicalization (VR) is a complex and multidimensional phenomenon [ 4 ] defined as a process whereby an individual or a group increases support for violence as a legitimate means to reach a specific (e.g., political, social, religious) goal [ 5 ]. Noteably, VR processes are increasingly occurring online [ 6 , 7 ]. Internet use has been primarily investigated in the field of terrorism studies and with samples of radicalized individuals [ 6 , 8 ]. Less is known about the association of digital media use, social polarization and attitudes towards support for VR among young people. Although the association between attitudes and behaviors is not a linear one, positive attitudes towards VR can contribute to the creation of socially polarized environments that fuel conflicts and shatter social solidarities, resulting in some cases in extremist ideologies and the normalization of violence. In such contexts, vulnerable individuals - such as those experiencing significant social grievances - are at higher risk of engaging in violent acts and extremism. Thus, in a primary prevention perspective, a reduction in support of VR among youth can result in an overall decrease of violence in our societies in the short and long-term [ 9 , 10 , 11 ].

Although numerous interventions target online literacy and social media use as potential ways to counter violent extremism [ 7 ], empirical research on their effectiveness is scarce and the role that Internet use plays in the development of positive attitudes towards VR among young people is largely understudied. While depressive symptomatology, which has also been increasing among young people in the past decade [ 12 , 13 ], is associated with both digital media use and support for VR [ 14 , 15 , 16 , 17 ], empirical research has not yet examined the associations between these variables simultaneously in one study. The current study aims to fill this gap in the literature by empirically investigating if and how patterns of digital media use are differently associated with depressive symptoms and support for VR among a sample of Canadian young people via a person-centered approach. Given the prominent role that digital media use play in both VR processes and mental health among young people, a better understanding of risk and protective factors associated with digital media use is warranted to inform and tailor evidence-based prevention programs that could significantly help reduce social ruptures and the associated risk of violence.

Digital media use and support for VR

The online space has become a central developmental context for young people [ 18 , 19 ]. Empirical evidence remains mixed, suggesting that digital media use can be either a risk or protective factor across multiple developmental outcomes depending on a complex interplay between both online and offline factors [ 18 ]. A consensus is now emerging that the specific behaviors in which youth engage online, rather than overall digital media per se, are key determinants of well-being. Yet, gaps in knowledge remain [ 20 ].

On the one hand, digital media can be used to connect with peers and to counter isolation, thus extending or reinforcing one’s social support network and possibly one’s trust in institutions and in democracy. On the other hand, the Internet can provide instant and unfiltered access to content and groups that propagate fake news, extreme beliefs and encourage violent actions, representing one of the main settings that can facilitate disaffiliation phenomena and recruitment of young people by extremist groups [ 7 , 21 , 22 , 23 , 24 ]. Notably, whereas the majority of young people go online, only a minority of them get involved in VR processes. As such, it is likely that digital media use does not have a linear relationship with support for VR, but that specific constellations of digital media use are differentially associated with support for VR [ 8 , 25 ].

Young people’s use of digital media is complex and heterogeneous [ 18 ], making the measurement and conceptualization of digital media use a challenging area [ 26 , 27 ]. In this study, we focus on some aspects of digital media use that have been theoretically and/or empirically associated with VR, namely time on social media, reasons for Internet use (work, informational, entertainment, social), news literacy, trust in specific online sources of information (news, peers, influencers, government, youtube), preference for online social interactions and online political interactions.

The Internet can be used for multiple purposes, spanning from work or entertainment, to relational maintenance and social interaction [ 18 , 28 ]. Although spending more time online has been associated with increased exposure to extremist content [ 23 ], whether this exposure is associated with risks of VR is yet unclear [ 29 ]. Overall, the impact of time spent on social media on a variety of social and health outcomes including VR varies based on the specific online activities and experiences [ 8 , 18 , 20 ].

Of importance, the Internet is currently the most important source of information for young people [ 30 , 31 ], but trust on the validity of information from official governmental websites as well as from social media (e.g., Instagram, Twitter, Youtube) can vary between individuals. Misinformation and beliefs in conspiracy theories have been associated with higher support for VR [ 32 , 33 ]. News literacy is considered a potential avenue to countering both misinformation, social polarization and online extremism [ 34 , 35 ]. News literacy is defined as the ability to find/identify/recognize news, critically evaluate and produce them [ 36 ]. However, empirical research that examines the association between news literacy and support for VR is lacking.

Prior research has found that preference for online social interactions over face-to-face relationships represents a risk factor for support for VR [ 37 , 38 ]. Preference for online social interactions is characterized by beliefs that one is safer, more confident, more comfortable and appreciated when online as opposed to offline [ 39 ] and is considered a component of problematic Internet use as it implies problematic relational experiences offline.

Some studies suggest that actively seeking and engaging with extremist content online is associated with higher risk of VR [ 8 , 22 , 25 ]. Although online interactions with strangers have been associated with higher risk of psychological distress [ 17 , 40 ], the extent to which interactions with known and unknown people around political or current issues are associated, if at all, with support for VR has yet to be explored [ 23 ].

Given the variety in online experiences and type of digital media use, a person-centered approach via a latent profile analysis (LPA) facilitates examining different constellations of digital media use among young adults and associations between latent groups and support for VR. As VR is the result of complex and unique interplays between personal and social/contextual variables [ 4 , 41 , 42 ], identifying patterns of vulnerabilities online via a person-centered approach can inform the development of tailored VR prevention programs targeting digital media use.

The present study

The present study adopts a person-centered approach to investigate: 1) patterns of digital media use among young Canadians. Specifically we focus on reasons for digital media use (i.e., work, entertainment, socialization, information), reported trust in different sources of online information (i.e., official government and news websites and social media), news literacy, time on social media, preference for online social interactions and online political interactions (e.g., posting/discussing with peers vs strangers, having conflicts online about these issues); 2) the association between patterns of digital media use and levels of depressive symptoms; and 3) the association between patterns of digital media use and support for VR. We expect to identify at least two groups of young people who differ in their reported digital media use. Given that we do not have a priori knowledge of the class structure in the data, we did not have a priori hypotheses about the association between each profile and depressive symptoms. However, we anticipate that the group(s) that will report the highest levels of depressive symptoms will also be at higher risk of supporting VR.

Participants

A total of 2,695 participants answered an online survey; missing outcome data ( n =362) and individuals identifying as “other” gender ( n =9) were removed for methodological concerns given the very small sample size of this gender group. Final sample size was 2,324 participants (59.3% women; mean age = 30.10; SD = 5.44 ). Socio-demographic characteristics are presented in Table 1 .

Data were collected in November 2021, during the COVID-19 pandemic in Alberta, Ontario, and Quebec. Participants were recruited through the Leger360 online platform with over 500,0000 registered members and answered the survey in either English or French [ 43 ]. informed consent to participate was obtained electronically from all of the participants in the study, and response rate was 53.8%. Exclusion criteria were individuals under the age of 18 or above 41. Study protocol and procedures were approved by the Institutional Review Board of.

Support for VR

The Radicalism Intention Scale (RIS) is a 4-item subscale of the Activism and Radicalism Intention Scales (ARIS) [ 44 ]. It assesses an individual’s readiness to participate in illegal and violent behavior in the name of one’s group or organization. Respondents rated their agreement with four statements on a seven-point Likert scale, with higher scores indicating more support for VR (range 4-28). The scale has good psychometric properties among young adults [ 45 ] (α = .89; Ω = 0.89).

Time spent on social media (daily)

Participants were asked to identify how many hours they spend on social media on a typical day (i.e., less than 2 hours, 2-4 hours, 4-6 hours, and 6 hours or more).

Reasons for Internet use

Four statements on Internet use were presented (i.e., using Internet: for personal relationships, to actively search for information/news, for entertainment, and for work). Participants were asked to indicate on a 5-point Likert scale how much they used the Internet for each reason (not at all, a little, moderately, a lot, most of the time).

News literacy

Was measured as a subscale of the literacy scale by Jones-Jang et al. [ 36 ]. Participants were asked using a 5-point Likert scale how much they agreed with each statement (six items, from 1-strongly disagree to 5- strongly agree, range 6 - 30)(α = .80; Ω = 0.80).

Trust on online sources of information

Five statements around trusting different sources of online information were presented, namely trust in news, peers, influencers, government, and YouTube sources of information. Participants were asked to indicate how often they trust each source of information on a 4-point Likert scale (never, rarely, sometimes, often).

Preference for online social interactions

(PFOSI) was measured with the 13-item Social Comfort subscale of the Online Cognition Scale [ 46 ]. Participants rated on a 8-point Likert scale (range 0 – 91) how much they agreed with statements describing their relationships with people who they know primarily through the Internet (e.g., chat rooms, message boards, online gaming communities). Higher scores indicate more preference for online social interactions (α = .92; Ω = 0.92).

Online political interactions

Participants were asked to indicate on a 6-point Likert scale (from “None/No time at all”, to “Several times a day”) how often their online interactions were oriented around these four statements: posted information about politics/current affairs on social media, discussed politics/current affairs with people you know, discussed politics/current affairs with people you do not know, had verbal conflicts with known people around information shared/posted online.

Depressive symptoms

Depressive symptoms were measured by using the 15-item subscale of the Hopkins Symptom Checklist-25 (HSCL-25) [ 47 ]. Items are rated on a Likert scale from 1 (not at all) to 4 (extremely) based on how much discomfort that problem has caused them during the past seven days, and a total score is obtained by computing the mean of all items. The clinical cut-off is set at 1.75 (score range from 1 to 4) and scores have been recoded as below (0) or above (1) this cut-off. The HSCL-25’s psychometric qualities have been well established [ 48 ] (α = .94; Ω = 0.94).

Socio-demographic variables

Participants provided information on their age, gender (man or woman), education (None/Less than high school, High school graduate, Apprenticeship, technical institute, trade or vocational school, College, CEGEP or other non-university certificate or diploma or University certificate, diploma or degree), Income ($19,999 or less, $20,000- $39,999, $40,000- $59,999, $60,000 - $79,999, $80,000- $99,999, $100,000 or more), employment (not employed, employed -essential, employed – non-essential), generational status (first-generation immigrant, second-generation immigrant, and third generation or more immigrant/non-immigrant), province (Alberta, Ontario, Quebec), religious beliefs (no religion, religion), and age.

Statistical analyses

Analyses were conducted using R software [ 49 ]. Missing data were imputed using the Random Forest method via the mice package [ 50 , 51 ]. Sensitivity analysis suggested that missing data and multiple imputations did not alter the observed patterns of associations. First, we estimated the LPA model around variables related to digital media use via the tidyLPA package [ 52 ]. LPA is an analytic strategy that attempts to identify subgroups of people within a heterogeneous population who has a high degree of homogeneity in responses on a set of indicators. The appropriate number of latent profiles was selected based on the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Sample-size-adjusted BIC (SABIC), Bootstrap Likelihood Ratio Test (BLRT), characteristics of the profiles (interpretability of response profiles or uniqueness) and a conservative profile sample size (>10%) [ 53 , 54 , 55 , 56 ]. Lower AIC, BIC and SABIC values and a statistically significant BLRT indicate a better model fit [ 53 , 54 ]. Once the best LPA solution was identified, the level of entropy (acceptable if >.70) and Average Posterior Class Probability (AvePP; acceptable if >.70) were examined to determine the accuracy of classification [ 57 ].

Next, based on the predicted probabilities of profile membership made by the LPA, we assigned each participant to a specific profile. Analyses were then conducted on the univariable associations between sociodemographic characteristics and profile membership. Frequencies of profile membership by sociodemographic characteristics can be found in Table 3 .

Lastly, we conducted linear regression analyses that estimated support for VR as a function of profile membership. A sequential model building approach was used to evaluate the associations between profiles and support for VR. Model 1 presents the unadjusted association between profile and support for VR; model 2 adjusts for sociodemographic characteristics, and model 3 adjusts for sociodemographic characteristics and depression.

Latent Profile Structure

LPA models 2 through 6 are presented in Table 2 along associated BIC and log-likelihood values. The four-class solution was selected as the best fit for sample size of profiles (>10%) and interpretability of findings, despite not having the lowest BIC value. Figure 1 presents profile membership item response probabilities for digital media use. Participants in all profiles had a high probability of reporting average levels of news literacy. Unique class characteristics emerged around time spent on social media and overall Internet use preference for online social interactions, online political interactions and trusting multiple sources of information. Profile 1, named Average Internet use/Undifferentiated trust is characterized by individuals who demonstrated average Internet use yet infrequently used the Internet for interactions around politics/current affairs and showed undifferentiated trust towards information found on-line, regardless of the source. Participants in Profile 2, named Limited Internet use/Low Trust , infrequently used the Internet across the considered reasons and reported a low probability of trusting news and government sources compared to information from social media (e.g., peers, influencers, youtube). Profile 3, named Average Internet use/Institutional trust , is characterized by participants with average and undifferentiated internet use, who were more likely to report greater trust in institutional sources of online information (e.g., news, government) compared to other social media sources. Profile 4, named Online relational and political engagement/Social media trust , consists of individuals with a high probability of preferring online, as opposed to in person, social interactions and spending a large amount of time on social media on a daily basis. In addition, participants in Profile 4 had a high probability of using the Internet for discussing politics and other issues with both peers and strangers, actively posting on-line about politics, and were more likely to report conflicts online compared to all other profiles. Profile 4 participants had a lower probability of trusting news and government sources compared to other sources of information online (peers, influencers, youtube). Overall, Profile 1 and 3 included 46.8% and 27.9% of participants, respectively. Profile 2 was smaller and included 11.4% of participants, while Profile 4 included 13.9% of participants.

figure 1

Four-Profile Solution with Standardized Mean by Item Responses ( N = 2324)

Note. PFOSI Preference for online social interactions

Profile belonging, sociodemographic characteristics and depressive symptoms

Table 3 represents sociodemographic characteristics and depressive symptoms by profile for study participants. All variables were significantly associated ( p < 0.05) with profile belonging at the univariable level. The Average Internet use/Undifferentiated trust profile included a higher representation of women, non-immigrant, employed and non-religious participants, as well as participants who reported high education and income. A total of 45% of participants in this profile scored above the clinical cut-off for depressive symptoms. Participants in the Limited Internet use/Low Trust profile had a higher probability of being less educated, reporting a lower income and more unemployement. Participants in this profile were more likely to live in Alberta. Profile 3, Average Internet use/Institutional trust included participants who were highly educated, had high income, without an immigration background (third generation or more) and without a religion. Participants in this profile reported also the lowest levels of depression (37.5% above clinical cut-off) and more of them lived in Quebec. Finally, the Online relational and political engagement/Social media trust profile had an overrepresentation of men, immigrants, participants with a religion and who lived mainly in Ontario. In addition, participants in this group were overall educated but reported low income and high unemployment. A total of 70% of participants in this profile scored above the clinical cut-off to our measure of depressive symptoms.

Associations of profile membership with support for VR

Profile membership was associated with scores on the RIS ( p < 0.001). Participants in the Online relational and political engagement/Social media trust profile were more likely to report higher levels of support for VR compared to the other profiles in both unadjusted and adjusted models. Specifically, belonging to this profile was associated with a 0.91 ( SE = 0.06, p < 0.001) increase in support for VR compared to the Average Internet use/Undifferentiated trust profile when controlling for sociodemographic variables and depressive symptoms (Table 4 ). Belonging to the Average Internet use/Institutional trust profile was associated with a -0.267 ( SE = 0.046, p < 0.001) decrease in support for VR compared to the Average Internet use/Undifferentiated trust profile when controlling for sociodemographic variables and depression (Table 4 ). Gender, generation, province, age, and depressive symptoms were also associated with support for VR ( p < 0.05). Men, first generation immigrants, participants from Ontario, younger participants, and participants reporting more depressive symptoms were more likely to report higher support for VR. Religion, income and education were not significantly associated with support for VR (Table 4 ).

The current study investigated patterns of digital media use in a sample of young adults from three Canadian provinces. In addition, we examined whether these patterns were differentially associated with depressive symptoms and support for VR. Four profiles emerged from our LPA, confirming the pertinence of using a person-centered approach to shed light on the complex patterns of digital media use among young people. Overall, profiles differentiated participants mostly in terms of trust on specific sources of information and level and type of online engagement.

The two largest profiles ( Average Internet use/Undifferentiated trust and Average Internet use/Insitutional trust) differed primarily in their trust of online sources of information. Specifically, individuals in the Average Internet use/Insitutional trust profile reported to trust more frequently institutional sources of information (i.e., government and news) rather than social media (i.e., youtube, influencers, and peers), suggesting an overall acceptance of mainstream information and of the status quo. In contrast, the Average Internet use/Undifferentiated trust group showed average levels of trust to all sources of information alike. This group spent slightly more time online than the Average Internet use/Insitutional trust one , but overall these two groups did not differ much in their online social or political interactions. These two groups included 74.7% of participants, indicating a divide in the population mostly linked to what online sources to trust for information. The remaining participants were equally distributed between the Online relational and political engagement/Social media trust and the Low Internet use/Low trust profiles. Participants in both of these profiles trusted more frequently alternative social media sources of information compared to institutional ones, but they differed in overall levels of trust, with the Limited Internet use/Low trust group reporting overall low levels of trust, especially for institutional sources of information. Participants in the Online relational and political engagement/Social media trust profile reported high levels of trust in alternative social media sources of information and were more actively and politically engaged online with both peers and especially with strangers. They spent more time online and preferred online social interactions more compared to the other profiles. Taken together, these findings suggest that patterns of digital media use echo the increasing polarization in our societies [ 58 , 59 ] around issues of trust/distrust, engagement/disengagement as well as a variety of negative/positive online experiences. Indeed, the most important variables to differentiate the four profiles were related to the frequency of trusting different online sources of information as well as specific social and political interactions online, rather than reasons for Internet use or news literacy, which on the contrary did not seem to play a significant role in determining profile membership.

We suggest that the divide around trust in online information and engagement needs to be situated in the broader socio-political context, which can partly explain the socio-demographic differences we found across profiles.The Average Internet use/Insitutional trust and the Average Internet use/Undifferentiated trust profiles consisted of more affluent and more educated participants, mostly employed and without an immigration background. Participants in these profiles may benefit from more privileges in society, which can favor their trust in mainstream institutional sources of information online [ 60 , 61 , 62 ] . Indeed, participants in the Average Internet use/Institutional trust group were more likely to report the highest levels of education and income as well as the lowest levels of depressive symptoms followed by the Average Internet use/Undifferentiated trust profile. The difference in levels of depression between these two profiles can also be associated with the presence of younger participants and more women in the Average Internet use/Undifferentiated trust profile compared to the Average internet use/Institutional trust one. The Low Internet use/Low trust and Online relational and political engagement/Social media trust profiles included more participants reporting lower income. Participants in the Online relational and political engagement/Social media trust group included a higher percentage of men, participants with an immigration background and professing a religion – although participants in this profile reported an education level similar to the two larger profiles. This profile reported concerning levels of depression (70.2% above clinical cut-off). Relying on the internet for relational and political purposes combined with more frequent trust in alternative social media sources of information and less privileges in society can jeopardize young people’s mental health. Within a socio-ecological perspective, the fact that this profile is made up of primarily educated men with an immigrant background may represent a form of double-bind in which some groups may feel alienated because official discourses and stances about equity in Canada are contradicted by daily life experiences. This group’s pattern of digital media use may be related to the hardships, grievances and social deprivation experienced by minorities both online and offline. The combination of negative life experiences with high emotional distress may lead to experience overall negative and conflictual online social and political exchanges, subsequently legitimazing violence as an ultimate solution [ 16 , 17 , 63 ]. Besides reporting low income similarly to the Online relational and political engagement/Social media trust group, the Limited Internet use/Low trust profile included less educated and more unemployed participants compared to all other profiles, mostly without an immigration background. Participants in this group may not be content with their socio-political reality, and disengage from social and political issues, at least online. Noteworthy, our profiles suggest that digital media use is closely intertwined with social experiences offline. Interventions should consider this complex interaction and adopt a socio-ecological approach to both research and intervention, tailored not only to the different groups in society but also addressing the gap between them to mend the social fabric.

With regards to depressive symptoms and support for VR, the Online relational and political engagement/Social media trust reported the highest levels of depression and support for VR, followed by the Limited Internet use/Low trust profile. The fact that the two groups that reported less trust in institutional sources of information compared to alternative social media showed more depressive symptoms and support for VR indicates that issues of trust are important to address with young people in prevention and intervention efforts. Given that individuals in these groups had overall a lower status in society, compared to the other two profiles, it is possible that they may have been experiencing more social deprivation and grievances during the pandemic and have been more sensitive to the anti-system rhetoric which provided meaning to this perceived injustice [ 60 ]. This divide aligns with the emergence of polarized social movements in the whole of Canada (e.g., pro- and anti-vaxx groups during the pandemic). Promoting a sense of agency and belonging as well as ensuring that young people can express their opinions and have a purpose in life may help decrease depressive symptoms and reduce overall socio-political distrust and disengement both online and offline, which can in turn contribute to reduce the legitimation of violence. However, such interventions need to consider the social adversity and deprivation experienced by young people and be tailored to the specific needs and challenges that they face. Multi-level systemic interventions that target online and offline socio-political macro-determinants of mental health and injustices in our societies are needed above and beyond individual intervention programs.

The association between membership to the Online relational and political engagement/Social media trust profile and support for VR aligns with prior studies pointing to an association between active online political engagement and interactions and support for VR [ 8 , 23 , 35 ]. Noteworthy, this was a characteristic that clearly distinguished the Online active political engagement/Social media trust profile from all other profiles. Online relational and political engagement should be addressed in prevention and intervention, while also addressing possible isolation and injustices experienced offline. The association between membership to the Limited Internet use/Low trust and support for VR can be related to an overall distrust in society and especially in government and official institutions, which has been found to represent a risk factor for VR [ 32 ].

As expected, the group that was at higher risk of supporting VR was also the one that reported the highest level of depressive symptoms, which were significantly and positively associated with support for VR, confirming prior evidence [ 38 , 64 , 65 , 66 , 67 ]. Depressive symptoms do not necessarily lead to greater risk of VR [ 68 ]. Yet, multiple studies indicate a positive association between depressive symptoms and support for VR [ 38 , 64 , 65 , 66 , 67 ]. Although directionality of associations remain to be established, available evidence suggests that youth who interact more with strangers online [ 17 , 40 ], who prefer online social interactions [ 69 , 70 , 71 ] and who experience more social adversity [ 14 , 67 ] are at higher risk of depression, which can partly explain the higher scores of depressive symptoms found among the Online relational and political engagement/Social media trust profiles . Identifying as a man and being younger were also risk factors for support for VR, in line with prior studies [ 7 , 15 ], underlining the pertinence for future studies to focus on young people and to consider specificities by gender in VR studies [ 14 , 29 , 32 , 45 ].

Limitations

This study has several limitations. Most importantly, the cross-sectional design prevents us from drawing any conclusions about causality. Longitudinal studies are needed to shed light on the trajectories of associations between patterns of digital media use, depressive symptoms and support for VR. Second, our study is based on a convenience sample with a relatively high socio-economic level and education. This means that our results may not be generalizable to a larger, general population of young adults. Nonetheless, our online method of recruitment is appropriate given the sensitivity of the topic and the challenges of conducting research during a pandemic. Third, all data are based on young people’s self-reports and social desirability biases cannot be excluded. Fourth, our measures of digital media use were limited and not comprehensive of the broad range of possible online experiences. Given the rapidly evolving and dynamic aspects of the Internet, the availability of validated measures for different facets of Internet use remains a challenge for future studies. Last, our data were collected during the COVID-19 pandemic in three Canadian provinces, and results cannot be easily generalized to other provinces or countries, nor to a non-pandemic context.

Despite these limitations, our findings suggest that digital media use, psychological distress and their interaction play a role in processes of VR among young people and need to be situated and understood within a socio-ecological and social justice perspective. Specifically, trust in different sources of information and social and political experiences online are as relevant as the emotional and relational experiences of young people. The dynamic associations among these key elements have to be considered simultanously when reflecting on VR prevention and digital media use among young people. Prevention efforts should be adapted to the needs of specific populations and consider the diversity of their online/offline experiences. Indeed, our results suggests that online experiences are intertwined with offline experiences in society, in particular with grievances, and that an attention to the rapidly evolving socio-political scenario is warranted when designing intervention programs to prevent processes of VR among young people targeting their digital media use. The fact that self-reported news literacy did not differ across profiles questions the pertinence of VR prevention programs that target mainly news literacy skills among youth. Our findings support preliminary results that showed that media literacy did not protect youth from exposure to extremist content online [ 35 ] or risks of VR [ 25 ]. It has been argued that programs aimed to foster digital literacy may be associated with improved technical competence but leave participants “critically naïve” [ 72 ], failing to situate digital competence within the broader socio-political context. Although digital literacies may still be relevant skills to promote among young people, our findings suggest that, when it comes to the prevention of VR processes, critical thinking skills, supportive environments and a social justice approach to intervention may be equally important.

Availability of data and materials

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon request.

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Our work is funded by a Digital Citizen Contribution Program grant awarded to DM by Canadian Heritage and by a project grant awarded to CR by the Canadian Institute of Health Research (CIHR).

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Miconi, D., Santavicca, T., Frounfelker, R.L. et al. Digital media use, depressive symptoms and support for violent radicalization among young Canadians: a latent profile analysis. BMC Psychol 12 , 260 (2024). https://doi.org/10.1186/s40359-024-01739-0

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Social Networking Sites, Depression, and Anxiety: A Systematic Review

Elizabeth m seabrook.

1 Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, Australia

Margaret L Kern

2 Center for Positive Psychology, Melbourne School of Graduate Education, University of Melbourne, Melbourne, Australia

Nikki S Rickard

Associated data.

Summary of studies included in the systematic review.

Main results table: associations between depression, anxiety, and social networking site outcomes across the 70 reviewed studies.

Social networking sites (SNSs) have become a pervasive part of modern culture, which may also affect mental health.

The aim of this systematic review was to identify and summarize research examining depression and anxiety in the context of SNSs. It also aimed to identify studies that complement the assessment of mental illness with measures of well-being and examine moderators and mediators that add to the complexity of this environment.

A multidatabase search was performed. Papers published between January 2005 and June 2016 relevant to mental illness (depression and anxiety only) were extracted and reviewed.

Positive interactions, social support, and social connectedness on SNSs were consistently related to lower levels of depression and anxiety, whereas negative interaction and social comparisons on SNSs were related to higher levels of depression and anxiety. SNS use related to less loneliness and greater self-esteem and life satisfaction. Findings were mixed for frequency of SNS use and number of SNS friends. Different patterns in the way individuals with depression and individuals with social anxiety engage with SNSs are beginning to emerge.

Conclusions

The systematic review revealed many mixed findings between depression, anxiety, and SNS use. Methodology has predominantly focused on self-report cross-sectional approaches; future research will benefit from leveraging real-time SNS data over time. The evidence suggests that SNS use correlates with mental illness and well-being; however, whether this effect is beneficial or detrimental depends at least partly on the quality of social factors in the SNS environment. Understanding these relationships will lead to better utilization of SNSs in their potential to positively influence mental health.

Introduction

Social networking sites (SNSs) are Web-based platforms on which individuals connect with other users to generate and maintain social connections [ 1 ]. Considerable disagreement exists as to associations that SNS use may have with depression and anxiety [ 2 , 3 ]. On the one hand, SNSs may protect from mental illness, as they support and enable social interaction and connection [ 1 , 4 ], and allow users to reflect aspects of their identity and express emotion that may be relevant to their lived experience [ 5 ]. On the other hand, there are many opportunities for miscommunications and mismanaged expectations, and maladaptive tendencies can be exaggerated, leaving individuals feeling a greater sense of isolation [ 2 , 6 ]. As a whole, the SNS environment may be just as complex as face-to-face interactions. As SNS membership continues to rise [ 7 ], it is becoming increasingly important to address the possible benefits and detriments the use of SNSs may have on mental health.

Affective disorders such as depression and anxiety have been shown to have bidirectional interactions with the social environment that influence the path of illness onset and maintenance [ 8 ]. Depression and anxiety have an approximate prevalence of 4.7% and 7.3%, respectively, in the global population [ 9 , 10 ]. These disorders have high levels of comorbidity [ 11 ] and impact the quality of social relationships [ 12 , 13 ]. Depression and anxiety may be implicated in determining the size and structure of an individual’s social network [ 12 ], the quality of interactions within these networks, and how effectively social capital may be leveraged or developed to provide an individual with social support [ 8 , 14 ].

The social characteristics (both qualitative and structural) affected by depression or anxiety are also relevant to one’s sense of well-being. Current mental health theories suggest that the presence of well-being is not the same as the absence of mental illness; a complete model of mental health requires not just the absence of psychopathology, but also a focus on positive indices of functioning such as subjective well-being [ 15 ]. This is particularly pertinent when exploring how the social environment may affect an individual, as such environments may simultaneously confer a number of benefits to the individual and exaggerate deficits [ 16 - 18 ].

Social aspects of the Internet have been argued to augment social relationships and support mental health. SNSs in particular connect us to friends, family, colleagues, strangers, and celebrities and can help users to maintain and make new friendships, express thoughts and feelings, and express identity [ 1 , 4 , 19 ]. The primary social functions that SNSs perform may augment the benefits of engaging in face-to-face interaction by extending the reach and accessibility of our social networks [ 20 ]. Indeed, SNS use is associated with lower levels of loneliness and greater feelings of belonging (social connectedness), social capital, and actual and perceived access to social support and is generally associated with higher levels of life satisfaction and self-esteem [ 6 , 21 - 26 ].

As a whole, the positive social components of SNS use suggest a protective role against depression and anxiety. For instance, higher levels of self-esteem and life satisfaction may aid in attenuating depressive symptoms [ 27 ]. Kraut et al [ 28 ] found that frequent general Internet use did not increase depression over time, and, in a second study, communication activities on the Internet were shown to be associated with lower levels of depressive symptoms [ 29 ]. Computer-mediated communication (CMC; eg, email, instant messaging) allows users to express and interpret emotion in a similar way to face-to-face interaction [ 17 ]. CMC may therefore be beneficial for emotion regulation as has been demonstrated for offline forms of written emotional expression [ 30 , 31 ].

However, for individuals with depression or anxiety, the interpretation and frequent exposure to this emotion may have a negative impact [ 13 ]. SNS use may increase an individual’s exposure to negative social interactions (eg, cyberbullying), which may negatively impact mood and mental health [ 2 ]. For example, negative interaction quality was associated with decreases in self-esteem and life satisfaction [ 32 ]. Even passive exposure to the language used in SNS posts has been shown to influence the emotive language subsequently expressed by the receiving SNS user, where positive or negative emotions are argued to transfer via contagion [ 33 - 35 ]. As SNSs explicitly support a number of social features, the relationships and interactions between the user, their emotional experience, and Web-based technology are likely to be complex and may even accentuate differences between those who are doing well in life and those who are struggling.

Cognitive and social factors frequently emerge as both moderators and mediators of the relationships between offline social interactions or events and depression [ 36 - 38 ] and might also occur in Web-based environments. For instance, self-esteem mediates the pathway between relationship interactions and depressive symptoms [ 39 ], but it might also moderate how a person uses and is affected by the SNS. Rumination, a response style where an individual maintains a passive and repetitive focus on their distress [ 40 ], is one mechanism linking stressful life events and the development or maintenance of depression [ 41 ], and the SNS environment provides opportunity for a person to both internally ruminate on bad events and have an entire social network further accentuate shortcomings. Social support has additionally been shown to moderate relationships between stress and depression, with greater levels of social support acting as a buffer to depressive symptoms [ 42 ]. This is pertinent to SNSs as they present a potential intervention opportunity for developing and strengthening supportive social networks for vulnerable individuals.

Since the advent of SNSs, a number of articles have been published examining the relationship between SNS use and depression and anxiety. The interaction between SNSs and our mental health and well-being is clearly varied and complex. The objective of this paper was to provide a systematic review of literature examining SNSs and their relationship with depression and anxiety. It also considers links with well-being, as well as potential mediators and moderators to these relationships.

Search Strategy

Figure 1 summarizes the search strategy and article selection. A multidatabase search identified studies conducted between January 2005 and June 2016. The databases included were PsycINFO, MEDLINE (Ovid), Scopus, IEEE Xplore, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Education Resources Information Center, Social Sciences Citation Index, and Communication and Mass Media Complete. The inclusion of conference papers accessed through IEEE Xplore was intended to capture the research within the computer sciences and engineering fields that may have been relevant to the psychological literature.

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Overview of search strategy and selection process for the systematic review.

Search terms were selected in order to comprehensively capture the various ways mental health, mental illness, subjective well-being, and SNSs have been defined and explored in the existing literature.

SNSs were defined as conceptualized by Ellison and Boyd [ 1 ] as sites that are a Web-based communication platform with 3 distinct characteristics: (1) user profiles are unique and created through user-provided content and content provided by other users, (2) the network connections between individuals are visible and can be navigated through by other users, and (3) individuals can broadcast content and consume and interact with content contributed by others in a continuous stream of information. Prototypical examples of SNSs include Facebook, Twitter, Myspace, and Instagram.

For mental health, search terms specifically focused on depression and anxiety, as well as overall well-being (eg, subjective well-being, psychological well-being, wellness; see Figure 1 for full list of search terms).

Inclusion and Exclusion Criteria

Studies were included if they had a primary focus on SNS use as a behavior. As such, studies that referred to SNSs as a recruitment method only or used SNSs as a means for intervention delivery were excluded.

Articles were included if they provided results addressing anxiety or depression directly and were excluded if they were only referred to in the context of general psychological distress (or similar). As the primary focus of the review was on depression and anxiety, not the broader well-being construct, articles addressing well-being were only included if they also included specific reference to anxiety or depression.

The search was limited to articles published after 2005 to capture research on the prototypical examples of SNSs that include the basic features of modern networks. Studies that had a primary focus on the Internet, chat rooms, or online support forums were also excluded; although they may contain some of the features of SNSs, differences in the function they perform for users may exist [ 19 ].

Additionally, articles were restricted to English language, peer-reviewed journal or conference proceedings, and quantitative or mixed methodologies. Gray literature, commentary and editorial, qualitative research, literature reviews, and descriptive case studies were excluded.

Data Extraction and Data Synthesis

Two raters (the first author and a trained research assistant) reviewed all abstracts returned from the literature search and selected abstracts for full-text reading based on the inclusion and exclusion criteria. All articles that included measurement of depression, anxiety, or well-being were retained. The selected full-text articles were downloaded and reviewed by the first and third authors.

To provide some preliminary evaluation of the strength of the research, three risk of bias indicators were adapted from the Cochrane bias tool ( Cochrane Handbook for Systematic Reviews of Interventions [ 43 ]), which classifies methodology that may limit replicability or generalizability. Studies were rated to indicate whether the study (1) included psychometrically reliable and valid measures, (2) used an external measurement criterion for mental health, and (3) provided description of the sample demographics including some SNS activity statistics (eg, number of friends and/or use frequency). These were rated by the first and third authors from “0=No bias,” “1=Unclear risk of bias,” and “2=High risk of bias” and were summed to create a final score between 0 and 6. A linear weighted kappa statistic for interrater reliability (.78, SE=.06) indicated that there was very good agreement in applying the bias criteria. Consensus was reached on all ratings. Articles with a rating of 3 or above were excluded [ 44 - 52 ], resulting in the final set of 70 studies, as presented in Multimedia Appendix 1 .

From each article, the year of study, population of interest, type of SNS, and variables used (anxiety, depression, well-being) were noted, along with whether or not any formal mediators or moderators of these relationships were indicated. Information was then qualitatively synthesized to identify common themes.

Description of Studies

Figure 2 indicates the number of articles addressing SNSs, depression and anxiety, and well-being from 2005 through 2016, based on the 302 full-text articles initially reviewed. There were considerably more articles addressing well-being alone than articles only addressing depression and anxiety. Only 15 articles included both positive and negative aspects of mental health. This review includes the 70 articles that include depression or anxiety only or depression or anxiety and well-being.

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Publication frequency of research into well-being, depression or anxiety only, and depression or anxiety with well-being from 2005 to June 2016, based on the initial 302 full text articles reviewed, which included quantitative findings. Case studies, editorials, literature reviews, and gray literature were excluded.

A total of 22 studies addressed potential moderators or mediators in SNSs’ relationship with depression or anxiety (see Multimedia Appendix 1 ). Most articles obtained a bias rating of 0 to 1. Ratings of 1 or above were primarily due to the limited focus on reporting SNS activity statistics, such as the number of friends or average frequency of use, which help characterize the average SNS user in each sample. Facebook was the most commonly explored SNS followed by the measurement of SNS use as a general category (ie, no specific platform explored). The majority of studies examined young adults (late teens or early 20s).

Depression, Anxiety, and Social Networking Sites: Summary of Findings

Across the 70 articles, several general themes were apparent: frequency of use, size and structure of the SNS, language features and observable SNS activities, self-disclosure and expression, quality of interactions, social support, social connectivity, social comparison, addictive and problematic behaviors, and physiological associations. Findings are summarized in Multimedia Appendix 2 and are described below, with particular attention to moderators and possible mechanisms involved in the associations. As some articles were relevant to multiple themes, these articles appear in multiple sections. Studies that included well-being are also highlighted.

Frequency of Social Networking Site Use

Overall, total frequency or time spent on SNSs had mixed associations with depression and anxiety. Of the 30 studies examining these variables (see Multimedia Appendix 2 ) [ 53 - 81 ], 8 studies found a direct positive association with depression and 16 found a nonsignificant association. For anxiety (and social anxiety), 3 studies found direct positive associations and 7 found nonsignificant associations. With the exception of 1 study showing a significant negative association between Facebook-specific social anxiety and the frequency of SNS use [ 80 ], no studies supported an association between the frequent use of SNSs and a lower level of anxiety or depressive symptoms.

Several moderators appeared. In one study, the number of strangers followed moderated frequent Instagram use and greater depressive symptoms, where a significant relationship only occurred for those with high proportions of strangers in their social networks [ 68 ]. Similarly, time spent on Facebook was only a predictor of depression and anxiety for those individuals who have higher motives to use the site for social connection [ 73 ].

Associations may be affected by the study design. Studies utilizing an experience sampling method (ESM) to collect SNS use frequency over 1 to 2 weeks found no significant associations between SNS use frequency and depressive symptoms over time [ 61 , 63 , 77 ]. Indeed, across 2 studies, while Steers et al [ 77 ] found a positive association between the time spent on Facebook and depression when using a retrospective survey, this effect was nonsignificant when participants completed daily ESM diaries. In addition, 2 studies [ 54 , 56 ] conducted a 3-week follow-up and demonstrated no change in depressive or anxiety symptoms over time as a function of SNS use frequency.

Tendencies toward depressive rumination and corumination did not moderate associations, suggesting that the frequency of SNS use may not be a significant risk factor for depression even across varying cognitive styles [ 54 ]. Kross et al [ 63 ] additionally included depression as a moderator of the relationship between the frequency of daily SNS use and affective well-being (ratings of negative affect) and cognitive well-being (life satisfaction). Although more frequent SNS use was associated with more negative affect and lower life satisfaction across a 2-week period, depression did not moderate these associations.

A number of studies have made a more nuanced consideration of SNS use frequency by looking at the different functions of use of SNSs [ 54 , 56 , 69 , 74 - 76 , 78 ]. Table 1 presents how these broad functions have been defined in the literature and presents some example behaviors. It also provides the Cronbach alphas that have been reported for the measures of each function. The table shows a distinction between passive and active use (broad-level functions). Active use may further be divided into content production and interactive communication functions. The table also shows where behaviors may be enacted in public (entire SNS friend network audience) or in private (dyads or small selected audience).

Broad functions of social networking site use and example behaviors.

a Cronbach alphas indicating the internal consistency of measures defining functions of social networking site use as defined in the reviewed literature.

In general, passive uses of SNSs was not directly related to depression and anxiety, but there may be differential behavioral patterns for individuals high in depression or social anxiety [ 75 , 78 ]. Higher levels of social anxiety were significantly related to passive uses of Facebook but not to content production uses of Facebook [ 75 ]. Brooding, or anxious rumination, emerged as a mediator of the relationship between passive Facebook use and social anxiety and may be a cognitive risk factor for increasing social anxiety symptoms where passive Facebook use is frequent. Tandoc et al [ 78 ] found that Facebook envy mediated frequent passive Facebook use and depression, where lower levels of Facebook envy resulted in a direct effect of passive Facebook use reducing depressive symptoms and higher levels of envy led to greater depressive symptoms.

Active uses of SNSs demonstrate a more complex relationship. Shaw et al [ 75 ] found that depressive symptoms positively correlated with more frequent content production and interactive communications. McCord et al [ 69 ] showed that the frequency of social Facebook use did not predict social anxiety in the entire sample but was positively correlated with anxiety for a high anxiety group only.

Simoncic et al [ 76 ] suggested that personality and gender moderate the association of frequent active uses of Facebook (content production and interactive communication) and depression and may be protective. The study found a three-way interaction between gender, Facebook active uses, and neuroticism, such that lower depressive symptoms occurred in females who were high in neuroticism and actively used Facebook.

Size and Structure of Social Network on Social Networking Sites

The size of the SNS friendship network and its association with depression and anxiety has similarly yielded mixed findings. Fernandez et al [ 57 ] and Weidmann and Levinson [ 82 ] found significant negative relationships between social anxiety and the number of friends, and Park et al [ 83 ], Park et al [ 84 ], Rae and Lonborg [ 73 ], and Rosen et al [ 74 ] found this same relationship direction when examining depression. Rae and Lonborg [ 73 ] found that a greater number of friends on Facebook was associated with higher general positive affect and life satisfaction, when use of the site was motivated by maintaining friendships. The remaining studies demonstrated no significant relationship between the number of SNS friends, depression, or anxiety [ 53 , 57 , 64 , 67 , 71 , 73 , 78 , 79 , 85 , 86 ].

Specific friend categories have also been examined. Tsai et al [ 87 ] found that users accepting the friend request of an ex-partner tend to have higher levels of trait anxiety and depression severity than those who reject the request. Mota-Pereira [ 88 ] demonstrated that for individuals with treatment-resistant major depressive disorder (MDD) also currently taking antidepressants, the use of Facebook over a 3-month period significantly reduced depressive symptoms, compared with a no-Facebook control, and the addition of a “psychiatrist as a friend” showed significantly faster improvement in depressive symptoms. Such findings suggest a broad beneficial impact of SNS use when treatment is augmented by friends from a user’s network.

The structure of the network itself may make a difference. For instance, Homan et al [ 89 ] revealed significant differences in the network structures of individuals with depression and those without on an LGBTQ (lesbian, gay, bisexual, transgender, and queer) support SNS, TrevorSpace. Individuals without depression had significantly more integrated friendship networks on the SNS compared with depressed individuals, with their friends being more likely to know each other and also having a higher proportion of friends who do not know each other. For the depressed group this could indicate they have less diverse social networks. Peer-selected groups have the potential to offer social support to depressed individuals, whereas groups over which the user had less control may contribute further exposure to psychological distress [ 90 ].

Language Features and Observable Social Networking Site Activity

A number of articles have examined the language features in SNS posts, with the potential for identifying individuals with depression. SNS users with depression differ from users without depression in that they express negative affect more frequently, use more personal pronouns, and generally have lower frequencies of interaction with others in their SNS network [ 91 , 92 ]. Park et al [ 93 ] have shown that individuals with a diagnosis of MDD more frequently post negative sentiment than those who are not depressed, and Moreno and colleagues [ 85 , 94 ] demonstrated that depression could be identified in the language used in the Facebook posts of college students based on the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria for MDD.

Settani and Marengo [ 95 ] directly examined the expressed emotion in participant status updates and generated an automated word count from the emotion dictionaries of the Italian version of Linguistic Inquiry and Word Count ( LIWC ), which was also supplemented with emoticons. Providing face validity, the frequency of word use from the negative emotion and sadness LIWC subscales positively correlated with depression, while the anger subscale positively correlated with anxiety. Positive emotion was unrelated to depression or anxiety scores. Interestingly, only the relationship between the sadness subscale and anxiety remained statistically significant when examining individuals older than 25 years.

In addition to language features, the time of posting, relative volume of posts, and reciprocity (likes and comments, tweets and retweets) may also aid in describing individuals with and without depression, with depression correlating with more night activity and less volume and reciprocity than nondepressed peers [ 84 , 91 , 96 ]. Over multiple weeks, there may also be subtle variation across time [ 96 ]. Park et al [ 84 ] provided evidence indicating that, for individuals experiencing acute depression (or a relative increase in their symptom severity), there is an increase in their posting frequency over a 6-month period. This is consistent with Shaw and colleagues’ [ 75 ] findings indicating those with higher depressive symptoms engage in content production features on Facebook frequently.

The number of identity items on SNS users’ profile page have also been associated with both depression and social anxiety scores [ 57 , 82 , 97 ]. For example, listing a “Single” relationship status relates to higher levels of social anxiety [ 82 ]. This related to the quantity of information provided in specific areas of a user’s profile information (eg, TV, Books, Quotes, Music; [ 57 ]). Although some of the specific findings are mixed [ 57 , 82 , 98 ], studies generally suggest that social anxiety may be visible on SNSs through compensatory behaviors (increases in information disclosure) or through relative inactivity or social withdrawal [ 57 , 82 ].

Social Networking Sites for Self-Disclosure and Expression

At a broad level, it has been suggested that users of Facebook have lower levels of social anxiety than nonusers, suggesting that there might be a selection effect, such that SNS activities are unattractive to individuals high in social anxiety [ 99 ]. However, this depends on the social media platform. Baker and Moore [ 100 ] showed that, for new Myspace users, those who intended to use the site for blogging had higher mean depression and anxiety ratings than those who did not intend to blog. These individuals were also more likely than nonbloggers to feel dissatisfaction with their social networks and had a greater likelihood to use self-blame and venting coping strategies. Average levels of depression and anxiety among the bloggers were maintained across a 2-month period, although there was a trend in some symptoms being reduced and a significant increase in feelings of social integration and satisfaction with online and offline friendships [ 101 ]. Similarly, große Deters and Mehl [ 102 ] found that depressive symptoms remained stable through an intervention, although loneliness decreased via feelings of social connectedness.

Social anxiety is associated with an increased preference for SNS-mediated communication [ 103 ] and relates to differences in the depth of self-disclosure via public (status updates) or private (eg, messages) communication on SNSs. For individuals with higher levels of social anxiety, greater importance is placed on the need for reduced social cues and increased controllability of communication [ 59 , 104 ]. This leads to greater disinhibition and Facebook self-disclosure for private SNS communication only and not for public SNS communication [ 59 ]. Green et al [ 59 ] suggest that this may be related to the trust, audience size, and privacy differences between private and public communication on SNSs, which may position private SNS communication as more attractive and accessible for individuals high in social anxiety. Similarly, Baker and Jeske [ 80 ] suggested that assertiveness on Facebook (the ease with which an individual offers opinion or interacts with others) is lower for individuals high in social anxiety compared with those low in social anxiety.

A potential explanation for the self-disclosure activities of individuals with high social anxiety on SNSs may be related to motivations or perceived pressure to present an idealized self-image or to avoid presenting a negative image on SNSs [ 86 , 105 , 106 ]. Motivations to avoid presenting a negative self-image have been found to be a greater concern for individuals who had experienced high social anxiety the previous day and does not vary according to levels of perceived social competence [ 105 ]. Similarly, frequent impression management (including updating profile information) on SNSs is positively related with depression [ 74 ].

Frequently expressing positive or negative affect (emotional valence) in SNS status updates has also been shown to relate to depression and may be mediated by rumination [ 67 ]. In contrast, positive and negative expression appears to be unrelated to social anxiety [ 98 ]. Positive and negative self-disclosures may, instead, impact the quantity of social reciprocity an individual with social anxiety receives [ 98 ]. For example, when individuals higher in social anxiety post positive status updates, this generates more pronounced increase in social feedback (likes) than when positive posts are made by those low in social anxiety or when posts have low positive content [ 98 ].

Quality of Interactions

Considerable evidence suggests a link between the quality of interactions on SNSs and mental health. Studies have operationalized SNS interaction quality as either the perceived (when self-rated) or observed (when coded by experimenters) valence of interactions between friends and the user on SNSs. Items often refer to a global estimate of “How positive [or negative] are your interactions with people on Facebook” [ 54 ] or, where coded, the frequency of positive or negative sentiment expressed in comments on posts [ 103 ]. This differs from the frequency of social or interactive communication on SNSs, discussed above, which refers to the estimated frequency or total time spent engaging in these activities.

Depression is generally associated with fewer positive interactions and more negative interactions on SNSs [ 54 , 56 , 103 , 107 , 108 ]. Social and global anxiety similarly relate to the perception of negative quality interactions on SNSs [ 56 , 107 ]. Depressed individuals may use SNSs in a more problematic manner than do anxious individuals [ 56 ], thus creating negative interactions. For instance, symptoms recorded at the age of 13 years significantly predicted a reduced likelihood of receiving comments that contained deviancy talk from SNS peers at the age of 20 years; however, symptoms at the age of 20 years predicted a greater instance of verbally abusive comments from peers [ 103 ]. The findings of Frison et al [ 81 ] also suggest that depressive symptoms are a risk factor for peer victimization on Facebook. Moberg and Anestis [ 108 ] have additionally shown that, when controlling for the influence of depressive symptoms on perceived negative interactions on SNSs, greater ratings of negative interactions predict feelings of thwarted belongingness (disconnection), a potential risk factor for suicidal desire.

Depressive rumination and corumination may moderate associations between the perception of SNS interaction quality and depression. In 2 studies, Davila et al [ 54 ] showed that those with higher levels of depressive rumination exhibited a stronger relationship between the frequency of perceived negative interactions on SNSs and greater depressive symptoms. Although corumination (ie, “excessive discussion of problems within friendships”; [ 54 ] p73) did not emerge as a significant moderator, it did yield a number of relationships with other variables, notably, feeling down or depressed after interactions on SNSs and a greater frequency of SNS use. The quality of use also relates to intentions for continued SNS use. Belief that online communities are dangerous, including concerns about privacy and the potential to encounter hostile or negative interactions, has been shown to be a potential antecedent of online and general social anxiety and their link to reduced continuance intention of using Facebook for social communication [ 109 ].

Associations may depend in part on the methodologies used. When researchers have directly observed and coded the language of comments made to an SNS user by their friends, it has been shown that a greater level of social anxiety at age 20 years was a significant predictor of more positive supportive comments from SNS friends and fewer negative peer interactions [ 103 ]. This is in contrast with the research utilizing self-report survey methods that show more frequent reporting of negative interactions for those with high levels of depression and anxiety symptoms [ 54 , 56 , 107 ]. This discrepancy suggests there may be a role for perceptual bias in a participant’s interpretation of the quality of interactions to which they are exposed on SNSs. In this light, individuals with higher levels of depression and anxiety may be more inclined to interpret or perceive SNS interaction as more negative regardless of the communication content exchanged between users. The potential for such a perceptual bias in interpreting SNS interactions has also been suggested in reference to social support perceptions and is further discussed below (see Park et al [ 93 ]).

Social Support

Social support plays a mixed and varied role within the SNS environment. Studies suggest that individuals with higher depressive symptoms perceive their SNS friend networks as providing them with less social support than they actually receive [ 93 ] and that SNS social support seeking may exacerbate depressed mood for some individuals [ 110 ]. Perception of support appears to be more important than actual support. Across 2 studies, Park et al [ 93 ] showed that in the general population greater depressive symptoms were associated with more actual social support on status updates that contained negative emotion. In contrast, perceived support was negatively associated with depression, and higher depressive symptoms were associated with a greater discrepancy between actual and perceived social support. Frison and Eggermont [ 110 ] similarly found that depressed mood increased in adolescents when social support was sought on Facebook but perceived to not occur. Other research has also demonstrated the protective role of perceived social support in ameliorating the impact of SNS peer victimization on depression [ 81 ].

For anxiety, social support provided on SNSs may play a protective role. Indian and Grieve [ 111 ] found that perceptions of Facebook social support were only predictive of subjective well-being for individuals with high levels of social anxiety and not for those reporting low levels of social anxiety. Furthermore, in the high social anxiety group, perceived Facebook social support was the only significant predictor of subjective well-being, suggesting that SNS social support may provide unique benefits to individuals with high levels of social anxiety.

The nature of seeking social support on SNSs may differ from traditional face-to-face approaches [ 110 , 112 ]. Some evidence suggests that emotional support provided by Facebook can increase depressive symptoms and decrease quality of life [ 112 ]. It may depend in part on the characteristics of the user. For example, SNS users’ perceived communication competence—an overall evaluation of communication skills and behaviors—plays a role in determining the level of satisfaction they feel is generated from their SNS social support. Wright et al [ 79 ] demonstrated that better perceived communication competence predicted higher ratings of both face-to-face social support and Facebook social support satisfaction, which in turn were significantly negatively related to depression.

Social Connectedness

Facebook social connectedness encompasses subjective feelings of belonging and closeness to an individual’s social network [ 113 ]. Grieve et al [ 113 ] demonstrated that higher levels of Facebook social connectedness were related to lower levels of depression and anxiety and higher levels of subjective well-being (life satisfaction). Feelings of social connectedness may mediate the impact an increase in posting behavior has on decreasing loneliness [ 102 ].

Social Comparison

Social comparison on SNSs, where individuals compare themselves as having more positive (downward comparison) or negative (upward comparison) qualities than others, is a significant risk factor for depression and anxiety [ 68 , 77 , 114 , 115 ]. Several studies found that Facebook envy, a hostile evaluation of others from their social information on SNSs, is associated with higher ratings of depressive symptoms [ 78 , 116 ]. Lee [ 114 ] found that depression and anxiety were positively related to the frequency of social comparison on Facebook. Feinstein et al [ 115 ] extended these findings by revealing rumination as a mediator in the relationship between negative (upward) social comparison on Facebook and depressive symptoms. This relationship changed over time; at a 3-week follow up, more frequent negative social comparison on Facebook was associated with increases in rumination and a subsequent increase of depressive symptoms.

Appel et al [ 116 ] examined how depression may influence an SNS user’s interpretation of the profile information of other users. Individuals with depression were more likely to rate themselves as being unhappier (or inferior) in comparison with profiles of any type (attractive or unattractive) than those without depression. Individuals with depression also experienced greater envy than those without depression in response to viewing the unattractive profile, with this difference being greater after viewing the attractive profile.

Social comparison of any direction (upward, nondirectional, or downward) may also indirectly mediate the association between the time spent on Facebook and depression. Across 2 studies, as individuals spend more time on Facebook they engage in more frequent negative (upward) and nondirectional social comparison and less positive (downward) social comparison, which in turn relates to more depressive symptoms [ 77 ].

Envy potentially plays a destructive role in passive Facebook use (eg, viewing or browsing profiles; see Table 1 ). Where Facebook envy is high, greater frequency of passive Facebook use is associated with greater depressive symptoms, and where Facebook envy is low (or not present), passive Facebook use is associated with reduced depressive symptoms [ 78 ]. Indeed, research into Instagram (a photo-sharing SNS) [ 68 ] has shown that more positive (downward) social comparisons are associated with decreased depressive symptoms. Social network composition, additionally, may moderate the relationship between frequent Instagram use and increases in depressive symptoms via social comparison [ 68 ].

Addictive or Problematic Social Networking Site Use

“SNS addiction” and “problematic SNS use” are linked with depression and anxiety [ 58 , 60 , 62 , 65 , 104 , 106 , 117 - 121 ], although associations most likely are bidirectional in nature. It has been suggested that such maladaptive SNS use is only present for a small subset of users [ 62 , 106 ], although one study suggested that 41.9% of adolescents had a Facebook addiction [ 119 ]. While depression and social anxiety explain much of the variance in problematic SNS use or SNS addiction, other variables (younger age, male, and more frequent SNS or general Internet use) have also emerged as significant predictors [ 58 , 62 , 118 ]. Through cluster analysis, Moreau et al [ 120 ] showed that problematic Facebook use is most prevalent in individuals high in borderline personality traits and depressive and social anxiety symptoms compared with groups low in those symptoms or high in sensation seeking (but low in psychopathology). Their findings may indicate considerable comorbidity between psychopathological symptoms and SNS addiction.

Wegmann et al [ 121 ] suggested that depressive symptoms and social anxiety have both a significant direct relationship with SNS-specific addiction and a partially mediated pathway to SNS-specific addiction via 2 cognitive styles: self-regulation and Internet use expectancies. In these pathways, higher levels of depression and anxiety are related to lower levels of self-regulation, which are in turn related to higher SNS-specific addiction scores. Internet use expectancies, the perception that the Internet can aid in increasing pleasure and decreasing negativity, were greater for those with higher depression or anxiety symptoms, which again lead to greater vulnerability for SNS-specific addiction. They suggest that depression and social anxiety may predispose SNS users to these cognitive styles.

In contrast, Andreassen et al [ 117 ] found that while social anxiety was positively related to addictive SNS use, depression was negatively related to addictive SNS use. This was interpreted as reflecting social withdrawal characteristics of depression and CMC’s social compensation for individuals with social anxiety [ 117 ]. Indeed, addiction and the compensatory uses of SNSs have been demonstrated to be related to higher levels of social anxiety [ 106 ]. Some evidence suggests that the addictive use of SNSs arises from the need to compensate for the social functions affected by social anxiety symptoms. Casale and Fioravanti [ 104 ], for example, show that addressing unmet face-to-face social needs, such as the need to belong, to be perceived as socially competent, and to be assertive in communication, may drive problematic SNS use. However, associations may depend on gender. For males and females, a direct association between social anxiety and problematic SNS use has been demonstrated; however, a significant mediator (motivations for competent self-presentation) in this relationship only emerged for males [ 104 ]. Lee-Won et al [ 65 ] suggested that when the need for social reassurance (ie, motivations to seek social interactions and feelings of belonging) is high or moderate, the relationship between social anxiety and problematic SNS use is strengthened. Thus, social anxiety may only be a risk factor for problematic use of SNSs where the need for social connection is also high.

Physiology and Facebook

Finally, one study examined the impact of Facebook or face-to-face exposure as a primer for physiological arousal [ 122 ]. Arousal was greater for individuals when observing someone face-to-face after browsing their Facebook profile than for individuals exposed to a face-to-face encounter followed by the Facebook condition. Social anxiety was a significant moderator, with a more pronounced increase in arousal for those high in social anxiety, particularly in the Facebook than face-to-face exposure. The authors suggested that for the high social anxiety group, the initial exposure to Facebook may prime social comparison and self-presentation concerns for the subsequent face-to-face meeting. However, as emotional valence was not measured, it is unclear if the arousal experienced by participants was perceived as a positive or negative event.

Principal Findings

This systematic review examined associations between SNS use and anxiety and depression. Across 70 studies reviewed, a number of positive and negative correlates have been suggested, as well as moderators and mechanisms of these associations. On the basis of this review, it is likely that there are differing engagement and interactional styles on SNSs for users high in social anxiety and depression. These may be driven or defined by both symptoms and motives to compensate for needs that are not met face-to-face. Negative interactions, frequent social comparison, and SNS addiction or problematic use are related to higher levels of depression and anxiety. Furthermore, cognitive response styles such as rumination or brooding may exacerbate the negative interactions between SNS use, depression, or anxiety for some individuals.

While these potential risks exist for mental health, it is also clear that SNSs can provide considerable benefits to their users. Positive quality interactions, social support, and social connectedness most consistently related to lower levels of depression and anxiety. Social support and connectedness derived from SNS use may be uniquely beneficial to individuals with social anxiety who are unable to access these resources face-to-face. However, especially for those with depression, some evidence suggests that there is a discrepancy between the perceptions of interaction quality and social support and the actual content of their SNS communications, which may attenuate the potential positive impacts of SNS use.

Across a number of studies, observable SNS features such as language use and expressions of identity on user profiles have been demonstrated to provide insight into the depression and anxiety status of the SNS user. With continuing research these characteristics may be a useful tool for monitoring mental health. The content and quality of interactions on SNSs may provide the clearest candidates for monitoring depression and anxiety and may be potential intervention targets for improving mental health and well-being through engaging with SNSs.

Social Aspects of Social Networking Sites

Across studies, social aspects, including feelings of social support, social connectedness, and positive interaction quality, emerged as protective factors for SNS users. The SNS network structure itself may play an important role in supporting mental health, in that some platforms may better provide social resources to individuals with depression. Indeed, more integrated social networks on SNSs were associated with lower levels of depression [ 89 ]. Studies suggest that social support and social connectedness derived from SNSs are constructs distinct from general social support or connectedness [ 111 , 113 ]. SNSs may therefore be contributing additional benefit to their users by creating another domain in which individuals can access, or have greater perceived access to, social support, especially with individuals for whom face-to-face interaction is difficult [ 123 - 125 ]. The broad and visibly articulated social context on SNSs may contribute to the feeling of social connectedness derived from SNSs and its association with better mental health outcomes [ 126 ]. As such, SNSs may provide an environment where those already high in social skills and resources are benefiting from their cumulative sources of social support (“rich-get-richer”; see [ 28 ]) as well as augmenting social support access for those who have difficulties engaging face-to-face [ 111 , 123 - 125 ].

Consistent with offline research, the perception of social support appears to be more important than actual support [ 126 - 128 ]. Findings demonstrated that perceived social support was greater in those with lower depression scores and that perceived communication competence may contribute to this relationship [ 79 , 93 ]. Greater perceived positive interaction quality and greater reciprocity in interactions are also indicative of lower depression and anxiety. Similarly, Valkenburg et al [ 32 ] demonstrated higher levels of life satisfaction and self-esteem for those who frequently reported positive peer experiences on SNSs. However, aspects of the individual that drive depressive feelings and social anxiety, greater use of negative language, and cognitive aspects such as social comparison and rumination, can prevent the user from perceiving support that is actually there [ 93 ], further contributing to depressive or anxious symptoms.

Emotional Aspects of Social Networking Sites

The valence of posts on SNSs may both reflect and impact depression and anxiety. Individuals scoring higher on depression scales in the reviewed studies generally expressed more negative affect on SNSs and were more likely to perceive negative interactions. The way individuals interpret emotional and social content on SNSs may place depression as antecedent to maladaptive SNS use, which may, in turn, maintain depressive symptoms. For individuals who are already depressed, ambiguous interactions are often interpreted as negative [ 13 , 129 ], which may attenuate the potential benefits available through SNS use.

Evidence suggests that frequent positive expressions are associated with better mental health, and frequent negative expressions are associated with depression and poorer life satisfaction [ 67 , 91 , 96 ]. While therapeutic writing can provide some benefits in reducing distress and improving well-being [ 30 , 31 ], online writing may serve a different function, with Web-based expressions reflecting the lived experience of the individual (eg, [ 91 , 130 - 132 ]), rather than providing a therapeutic outlet. Indeed, relative increases in posting frequency were shown to be associated with greater depressive symptoms [ 84 ]. For others, the presence of social anxiety may hinder the use of posting functions for emotional disclosure on SNSs [ 59 ], which may decrease access to potential social interaction [ 98 ]. As emotional content can be effectively communicated on the Web [ 133 ], SNSs represent another space in which positive and negative interactions can be enacted and may provide key behavioral insights into the mental health and well-being of a SNS user. Alternatively, increases in self-expression on SNSs may be more beneficial to well-being domains (such as connectedness, social support, and life satisfaction) but may not have an impact on depression or anxiety. A direct comparison of these relationships has not been conducted, and might be an area to investigate in the future.

Cognitive Aspects as Mechanisms and Moderators

The prominent risk factors for depression and anxiety that emerged from this review included frequent SNS social comparison, negative perceived interaction quality, addictive or problematic SNS use, and rumination (or brooding). These factors represent cognitive and interactional styles that have well-established associations with depression and anxiety but may be enhanced by the enduring nature of social content on SNSs. Although the total frequency of SNS use does not appear to be directly related to either depression or anxiety, there are different moderating and mediating factors [ 68 , 73 , 77 , 78 ] and patterns in the functions of SNS use by individuals with higher depression or anxiety that may contribute to or exacerbate symptoms [ 69 , 74 - 76 , 78 ].

One of the risk factors for depression and an individual’s interaction with SNSs was rumination. Greater rumination is frequently associated with higher ratings of depression and also impacts well-being by maintaining a focus on negative affect [ 134 , 135 ]. Rumination is a likely mechanism for the relationship between negative interactions with SNSs and depression based on its role in SNS negative emotional expression [ 67 ] and social comparison [ 115 ]. There is considerable potential for SNSs to amplify and assist ruminative processes by exposing SNS users to a constant stream of rich social information that can be selectively reflected on as permanent content on a user’s profile [ 54 , 115 ].

Similar to depression, the cognitive risk factors for social anxiety include social comparison (via brooding) and the perception of frequent negative interactions. However, the pathway to and importance of these risk factors may differ from depression. In contrast to those with depression, those high in social anxiety mainly use SNSs for passive browsing and private communication, not for content production [ 75 ]. The passive uses of SNSs may place individuals at greater risk of more frequent social comparison, which may have negative mental health effects [ 114 ]. This differs from the relative benefit of content production on SNSs for an individual with social anxiety, as posts are often rated as being more appreciated by friends in the network [ 98 ], which may have a flow-on effect to the perception of SNS-derived social support [ 111 ] and may even reflect more positive interactions with peers [ 103 ].

The reduced social cues on SNSs may be attractive to individuals with social anxiety, as has previously been suggested in the general Internet literature [ 124 ]. However, the need to compensate for a lack of belonging and social reassurance in face-to-face interactions, in conjunction with lower self-regulation, may drive problematic SNS use for individuals with social anxiety [ 65 , 104 , 106 , 117 ]. Similarly, these motives may also contribute to individuals with social anxiety generating more content on their profile pages than others [ 57 ], and for those highest in social anxiety it may contribute to a higher frequency of SNS use [ 69 ]. On the whole, there appear to be a number of well-being benefits to using SNSs for individuals high in social anxiety that cannot be gained in face-to-face interactions; however, the pattern of SNS use may negatively affect other domains.

Mixed Results and Nonpredictors

The frequency of SNS use as a whole suggested no clear association with depression and anxiety. Longitudinal research suggests that depression and anxiety remain stable in the context of how frequently a user engages with SNSs [ 54 , 56 , 61 , 63 , 77 ] and the function of use holds clearer associations with depression and anxiety [ 75 ]. This is consistent with the literature examining general Internet use where total frequency of use is often not a predictor of depression, particularly when examining the social features of the Internet [ 28 , 125 ]. For example, when examining different functions on the Internet, Morgan and Cotten [ 29 ] showed that more hours spent using the Internet for social activities (IM’ing, chat rooms) are associated with decreased levels of depression and that informational uses and gaming are associated with increases in depression.

While total SNS use may not affect psychopathology, it may be related to subjective well-being. This was illustrated in the study by Kross et al [ 63 ], in which more frequent SNS use was related to experiencing more negative affect and reducing life satisfaction. As frequent experience of negative affect may contribute to the onset and maintenance of depression, it is likely that a pathway to poorer mental health outcomes exists via the impact SNS use has on the frequency of experiencing positive and negative emotions [ 54 , 63 , 67 ]. Additionally, other SNS features and cognitive processes (eg, network size, structure, and composition, tendency to ruminate, frequent social comparison) may be more informative in describing the impact frequent SNS use has on mental health.

In contrast with the literature examining social network size and structure offline [ 12 , 136 ], SNS friendship network size, on the whole, was not associated with depression or anxiety. However, some evidence has shown distinct network structure differences between individuals with depression and those without in terms of the interconnection between friends within a network [ 84 ]. Individuals with depression or anxiety have previously been shown to have more impoverished social networks, and changes in mental health are often associated with changes in an individual’s social network [ 12 , 137 ]. Impoverished social networks are often a risk factor for depression and anxiety by reducing access to “buffering” social support and increasing feelings of isolation [ 138 - 140 ]. They may also result from poor-quality social interactions, often typical of depression and anxiety [ 137 ].

The absence of a clear association between depression or anxiety and the number of friends on SNSs may be explained by one of the major differences between the offline and online social networks; that is, the way friendships are maintained over time. As SNSs do not necessitate direct social interaction to maintain the status of “friendship,” many users may not actively redefine their networks [ 141 ]. It is likely that the social pruning and the dissolution of social ties associated with mental illnesses such as depression and anxiety may not be visible on SNSs. Social pruning does occur for many SNS users (eg, 63% of American SNS users endorsed that they had removed friends from the “friends” list; [ 141 ]), but how comprehensively this behavior is performed remains unknown. Therefore, change in mental health status for SNS users may not be as accurately detected by a decreased social network size online as it may be when observing offline networks. Other metrics, such as communication output and reciprocity, may be more informative in describing the social network changes associated with depression and anxiety. For instance, De Choudhury et al [ 91 ] demonstrated that the volume of tweets and the associated replies were reduced in Twitter users with depression compared with those without.

Strengths and Limitations

As with any study, there are both strengths and limitations of this review. We included a basic criterion for bias that focused on evaluating the methodology of studies, which considered whether papers included (1) the use of psychometrically reliable and valid measures; (2) an external measurement criterion for mental health; and (3) description of sample demographics that included basic SNS user activity statistics. Only 9 studies were excluded for bias, suggesting that there is relative strength in defining the variables of interest in this field. However, a greater focus on defining the SNS characteristics of the sample is required.

The review attempted to characterize the research in terms of the populations and specific SNSs that have been studied. Studies have focused rather narrowly on the young adult population. While these individuals tend to represent the highest membership category of SNSs, recent estimates have suggested that SNS use is becoming more evenly represented across the life span, with more than 50% of older Internet users (65+ years) now also using SNSs [ 7 ]. This is an important consideration for future research as the social connection that may be gained through SNSs may provide more benefit for older users as quality of the interactions, particularly through language use, may vary significantly over the life span [ 142 ].

Despite the systematic approach to this review, the identified themes are not exhaustive. Other themes such as the differences between SNS users and nonusers and SNS use motives may have been extracted and more explicitly discussed. The discussion of results was limited to the depression or anxiety context and did not discuss findings outside this scope. Well-being, which clearly is becoming a growing area of interest ( Figure 1 ), was only included if there was also a focus on depression or anxiety. Future studies might extend to other aspects of mental illness and wellness.

Finally, although we identified some moderating characteristics, few studies have considered individual differences such as gender and personality and their interaction with SNS variables. Future studies might give greater attention to how characteristics of users impact the identified factors.

Implications and Future Directions

The results of this systematic review have revealed considerable support for the importance of examining the content and quality of the interactions a user has with SNSs. As such, the language used in interactions on SNSs could become a target of interest, particularly as it has been shown to be sensitive in identifying individuals with depression [ 91 , 92 , 94 , 143 ]. Further research should also focus on the interplay between the network structure components and dynamic interactions observable on SNSs. The SNS friend structure could be instrumental in defining the type and efficiency with which social resources may be accessed on SNSs. Examining network structure in concert with the quality of interactions, characteristics such as perceived social support, and mental health could provide rich explanations for why some people benefit from SNS use and others are placed at risk, echoing the detailed social network research that has occurred offline (eg, [ 12 ]).

Only a few studies in this review utilized SNS-derived data to answer their research questions. The majority focused on the use of self-report survey and relied on participant estimates of their SNS behaviors, which may have introduced considerable retrospective bias. This bias was addressed to some extent by including ESMs that more accurately sample a participant’s lived experience [ 144 ]. The studies directly observing SNS behaviors indicate that the mental health status of SNS users may be at least partly derived from their patterns of use, language expression, and profile information. These findings provide more weight to the potential of using computational science techniques within psychological research, particularly in characterizing well-being in large community samples [ 33 - 35 , 145 , 146 ], as well as predicting personality [ 147 ]; see also [ 148 ]. In reference to depression and anxiety, SNS data hold huge potential for early identification and time-sensitive monitoring of symptoms [ 143 ]. SNS data should be leveraged in future research as a part of ESMs to provide real-time, unobtrusive accounts of social behavior in a natural setting.

This systematic review examined the recent research on associations between SNSs and depression and anxiety. It examined findings in association with the suggested mediators and moderators and the links made with well-being. With more than 50% of adults using multiple SNSs [ 7 ], they permeate many aspects of daily life. For many, SNSs represent a way to socially connect with others. However, for others, SNSs may encourage and perpetuate maladaptive tendencies. SNSs maintain and reflect the complexities of the offline social environment and the risks and benefits it may pose to mental health. SNSs represent a novel, unobtrusive, real-time way to observe and leverage mental health and well-being information in a natural setting, with the ultimate potential to positively influence mental health.

Abbreviations

Multimedia appendix 1, multimedia appendix 2.

Conflicts of Interest: None declared.

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  25. Social Networking Sites, Depression, and Anxiety: A Systematic Review

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