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SYSTEMATIC REVIEW article

Front. Psychiatry, 14 December 2018
Sec. Addictive Disorders

Problematic Social Networking Site Use and Comorbid Psychiatric Disorders: A Systematic Review of Recent Large-Scale Studies

  • 1School of Human Sciences, College of Life and Natural Sciences, University of Derby, Derby, United Kingdom
  • 2International Gaming Research Unit, Psychology Department, Nottingham Trent University, Nottingham, United Kingdom

Background and Aims: Research has shown a potential association between problematic social networking site (SNS) use and psychiatric disorders. The primary objective of this systematic review was to identify and evaluate studies examining the association between problematic SNS use and comorbid psychiatric disorders.

Sampling and Methods: A literature search was conducted using the following databases: PsychInfo, PsycArticles, Medline, Web of Science, and Google Scholar. Problematic SNS use (PSNSU) and its synonyms were included in the search. Information was extracted based on problematic SNS use and psychiatric disorders, including attention deficit and hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), depression, anxiety, and stress. The inclusion criteria for papers to be reviewed were (i) being published since 2014 onwards, (ii) being published in English, (iii) having population-based studies with sample sizes >500 participants, (iv) having specific criteria for problematic SNS use (typically validated psychometric scales), and (v) containing empirical primary data reporting on the correlation between PSNSU and psychiatric variables. A total of nine studies met the predetermined inclusion and exclusion criteria.

Results: The findings of the systematic review demonstrated that most research has been conducted in Europe and all comprised cross-sectional survey designs. In eight (of the nine) studies, problematic SNS use was correlated with psychiatric disorder symptoms. Of the nine studies (some of which examined more than one psychiatric symptom), there was a positive association between PSNSU and depression (seven studies), anxiety (six studies), stress (two studies), ADHD (one study), and OCD (one study).

Conclusions: Overall, the studies reviewed showed associations between PSNSU and psychiatric disorder symptoms, particularly in adolescents. Most associations were found between PSNSU, depression, and anxiety.

Introduction

Global use of social networking sites (SNSs) is growing with over 2 billion users worldwide. North America and Europe rank highest in terms of SNS usage with 70% and 66% social media penetration rates, respectively (1). Research has shown that amongst American teenagers, YouTube, Instagram, and Snapchat are the most popular SNSs, and 45% of teenagers stated that they are online almost constantly (2). Given the broad spectrum of SNS use, it is important to understand the potential risks involved in problematic SNS use. Public health concerns have been voiced by the World Health Organization (3) regarding the propensity of problematic SNS behaviors associated with addiction among a minority of users. Empirical studies have shown that problematic internet users spend more time online than non-problematic users (4, 5). Problematic SNS use (PSNSU) has been conceptually defined as a disorder that does not involve ingestion of a psychoactive substance and shares qualities related to a behavioral addiction (6). Other researchers (7) have used the term SNS addiction. Andreassen and Pallesen (7) define SNS addiction as being overly concerned about SNSs, driven by a strong motivation to log on to or use SNSs, and to devote so much time and effort to SNSs that it impairs other social activities, education and/or occupation, interpersonal relationships, and/or psychological health and well-being. Behavioral addictions, as defined by Griffiths (6, 8), are behaviors that comprise six components: salience, mood modification, tolerance, withdrawal symptoms, conflict, and relapse. These components have been reported among SNS users in several studies [e.g., (911)]. The prevalence of PSNSU varies among populations ranging from 1.6% in Nigeria (12), 4.5% in Hungary (13), 8.6% in Peru (14), and 12% in China (15), although only the study by Banyai et al. (13) used a nationally representative sample. These findings show that PSNSU is an increasing concern across cultures.

SNSs allow users to communicate with individuals around the world, to keep in touch with family and friends providing a feeling of connection (16) and increased online social well-being (17). Research has demonstrated that connectivity on SNSs can facilitate well-being offline (18). However, increased monitoring, compulsive checking, and excessive engagement with these websites may be leading to the emergence of psychiatric disorder symptoms among a minority of individuals (19). Maladaptive SNS use has been identified as a potential mental health problem (20) with such claims being supported by empirical findings showing that PSNSU is associated with health-related, interpersonal, and educational problems (7, 21). Empirical research has also shown PSNSU to be negatively associated with life satisfaction (22, 23) and low quality of life (24). Recent research (25, 26) has shown that narcissistic individuals spend more time on SNSs, and those individuals who possess high levels of Dark Triad personality traits may employ SNSs to execute “cheater strategies” that help them achieve their interpersonal and social goals despite their anti-social personality traits (26, 27). Halpern et al. (28) reported that narcissistic individuals take “selfies” (self-portraits uploaded and shared on social media) more frequently over time which leads to increased levels of narcissism. In a comprehensive study examining worldwide selfie-related accidental mortality, Jain and Mavani (29) reported that between 2014 to mid-2016, 75 individuals died while attempting a selfie in 52 incidents worldwide, with the mean age of the victims being 23.3 years and 82% were male. Research by Nesi and Prinstein (30) examined longitudinal associations between adolescents' digital status seeking (an investment of significant effort into the accumulation of online indicators of peer status and approval) and health-risk behaviors. The results showed that digital status seekers engaged in higher levels of substance use and sexual risk behavior 1 year later. Sarabia and Estévez (31) examined sexualized behaviors displayed by Spanish adolescents on their Facebook profiles, and results showed that girls tried to please others via seduction to obtain social approval while boys presented themselves as seducers. Taken as a whole, research is beginning to show how SNSs may influence behavior which is concerning given the wide usage and popularity of these websites.

Due to the widespread use of SNSs, research concerning its implications for mental health necessitates scientific review. There may be severe mental health implications for the minority of individuals experiencing PSNSU. Previous systematic reviews have focused on pathological internet use and psychopathology (32), problematic internet use (33, 34), and problematic smartphone use and anxiety and depression symptoms (35). However, there are no recent review papers overviewing PSNSU and psychiatric symptoms. A focused systematic review examining the associations between PSNSU and psychiatric disorder symptoms is therefore warranted and is necessary for prevention and treatment work. It is important to examine and highlight the symptoms of psychiatric disorder before they become fully developed disorders. The main aims of this focused review were to (i) review the scientific literature concerning SNSs and psychiatric disorders, (ii) identify and evaluate studies performed on the correlation between PSNSU and comorbid psychiatric disorders, (iii) to map the geographical distribution of studies, and (iv) assess the quality of the studies. Based on previous literature, the following psychiatric disorders were included: attention deficit and hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), depression, anxiety, and stress.

Methods

The preferred reporting items for systematic reviews and met-analysis [PRISMA; (36)] were closely adhered to during the review process (see Figure 1). A comprehensive literature search was conducted using PsychInfo, PsycArticles, Medline, Web of Science, and Google Scholar databases. Reference lists of retrieved articles and review papers were also examined for any further studies. The main keywords used in the search were “problematic social networking site,” “problematic social media use” or “social networking site addiction,” “social media addiction,” “social networking site dependence,” “social media dependence,” “pathological social networking site use,” “pathological social media use,” “compulsive social networking site use,” “compulsive social media use,” “excessive social networking site use” and “excessive social media use” combined with the keywords of “attention deficit and hyperactivity disorder/ADHD” or “obsessive compulsive disorder/OCD,” “depression” or “anxiety” or “stress.”

FIGURE 1
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Figure 1. Flow diagram of review process.

Studies were systematically and independently reviewed by the authors and assessed regarding the study type, study population, methodology, measures used, and interpretation of results. The inclusion criteria for papers to be reviewed were (i) being published since 2014 onwards, (ii) being published in English (the native language of the present authors), (iii) having population-based studies with sample sizes >500 participants, (iv) having specific criteria for PSNSU (typically validated psychometric scales), and (v) containing empirical primary data reporting on the correlation between PSNSU and psychiatric variables. Studies were excluded if they comprised case studies and/or comprised treatment assessment. Papers were screened based on the titles and abstracts reporting on the topics of interest. Thereafter, papers were selected based on scientific relevance of the study and included following full text assessment. Studies were evaluated if there was an observation of a full association and significance level. Full association was considered when a correlation was found for PSNSU and specific psychiatric disorder symptoms following bivariate or multivariate analysis. The geographical distribution of studies was also mapped.

After deleting duplicate studies, a total of 100 papers were screened and identified via the systematic search strategy employed. As a result, 91 papers were excluded because they (i) were based on other internet-related topics and not social media use, (ii) did not assess psychiatric disorder symptoms, and (iii) did not meet the inclusion criteria (see Figure 1 for a flow diagram of the review process). Thus, there were nine papers included in the present review. The characteristics of the studies included in the review (see Table 1) are discussed below. Some studies are referred to in more than one section due to assessing more than one psychiatric disorder symptom. The results section also briefly reports the key findings of a further nine studies that met all the inclusion criteria apart from sample size.

TABLE 1
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Table 1. Study details and results.

Results

Description of Included Studies and Geographical Distribution

All nine of the studies were cross-sectional survey studies. Most studies (n = 7) targeted adolescent and/or emerging adult groups (13, 39, 41, 43, 4547), while two studies had a mainly adult sample (37, 42). Only two studies used a nationally representative population [i.e., (13, 42)]. All studies examined both genders and the sample sizes ranged from 509 to 23,533. The majority of studies (n = 7) were carried out in European countries (Hungary, Netherlands, Norway, Poland, Portugal, Turkey, United Kingdom), one study was carried out in the United States [i.e., (42)], and one in India [i.e., (47)]. Table 1 summarizes further information about the included studies.

Methods of Assessing Problematic Social Networking Site Use

Most studies (n = 7) assessed PSNSU using the Bergen Social Media Addiction Scale [BSMAS; (37)] or its predecessor, the Bergen Facebook Addiction Scale [BFAS; (38)]. The BSMAS contains six items reflecting the core components of addiction (6). The six BSMAS questions were modified by replacing the word “Facebook” in the original BFAS with the words “social media.” Participants rate all items on a 5-point Likert scale (where 1 = very rarely, 2 = rarely, 3 = sometimes, 4 = often, 5 = very often). Example adapted questions include: “How often during the last year have you felt an urge to use social media more and more?” and “How often during the last year have you used social media in order to forget about personal problems?” Various studies have reported that the BFAS and adapted BSMAS have good psychometric properties [e.g., (4851)]. The two remaining studies used the Social Media Use Questionnaire (40) and the Compulsive Internet Use Scale [CIUS; (44)], the latter of which does not specifically assess problematic social media use. Table 1 provides details of measurement instruments used by studies to assess PSNSU.

Problematic Social Networking Site Use and ADHD

Only one study [i.e., (37)] examined the associations between PSNSU and ADHD. The authors assessed ADHD using the Adult ADHD Self-Report Scale [ASRS-Version 1.1; (52)]. Significant and positive associations between PSNSU and ADHD were reported. The bivariate correlation was r = 0.41, and the multivariate association was β = 0.268.

Problematic Social Networking Site Use and OCD

Only one study (37) examined the associations between PSNSU and OCD. The authors assessed OCD using the Obsessive-Compulsive Inventory-Revised [OCI-R; (53)]. The results showed a significant and positive association between PSNSU and OCD. The bivariate correlation was r = 0.33, and the significant multivariate association was β = 0.147.

Problematic Social Networking Site Use and Depression

Seven studies examined the associations between PSNSU and depression [i.e., (37, 39, 4143, 45, 47)]. A significant and positive association between PSNSU and depression was reported in six studies [i.e., (37, 39, 4143, 45)]. One study [i.e., (47)] reported an indirect positive association between PSNSU and depression. Bivariate correlations were typically in the range of 0.19–0.45. Multivariate associations showed betas ranging from −0.018 to 0.32. Each of these studies finding a positive association between PSNSU and depression used different scales to assess depression: (i) Andreassen et al. (37) used the depression scale of the Hospital Anxiety and Depression Scale (HADS; 53); (ii) Dhir et al. (47) used the Depression Scale [DEPS; (54)]; (iii) Kircaburun et al. (55) used the depression sub-scale of the Short Depression-Happiness Scale [SDHS; (56)]; (iv) Pontes (41) used the depression scale of the Depression Anxiety and Stress Scales−21 [DASS-21; (57)]; (v) Shensa et al. (42) used the Patient-Reported Outcomes Measurement Information System depression scale [PROMIS; (58)]; (vi) Van Rooij et al. (43) used the six-item Depressive Mood List (59, 60); and (vii) Worsley et al. (45) used the Patient Health Questionnaire [PHQ-9; (61)]. One study (13) reported high levels of depression among participants who displayed PSNSU but no bivariate or multivariate associations were reported in the results. Bányai et al. (13) used the Center of Epidemiological Studies Depression-Scale [CES-D; (62)].

Problematic Social Networking Site Use and Anxiety

Six studies [i.e., (37, 41, 43, 4547)] examined the associations between PSNSU and anxiety. A significant and positive association between PSNSU and anxiety was reported in five studies [i.e., (37, 41, 43, 45, 46)]. One study [i.e., (47)] reported an indirect positive association between PSNSU and anxiety. When examining the bivariate correlations, they were typically in the range of 0.15–0.34. Multivariate associations showed betas that ranged from 0.05 to 0.074. The studies assessed anxiety with different scales: (i) Andreassen et al. (37) used the anxiety scale of the Hospital Anxiety and Depression Scale [HADS; (63)]; (ii) Atroszko et al. (46) used the shortened Polish version of Liebowitz Social Anxiety Scale [LSAS; (64, 65)]; (iii) Dhir et al. (47) used the Social Anxiety Scale for Adolescents [SAS-A; (66)]; (iv) Pontes (41) used the anxiety scale of the DASS-21 (57); (v) Van Rooij et al. (43) used the social anxiety scale (67); and (vi) Worsley et al. (45) used the anxiety dimension of the Relationship Questionnaire [RQ; (68)].

Problematic Social Networking Site Use and Stress

Two studies [i.e., (41, 46)] examined the associations between PSNSU and stress with a significant and positive association between PSNSU and stress being reported in both of them. The bivariate correlations ranged from 0.22 to 0.36, and multivariate associations showed betas ranging from 0.16 to 0.26. Atroszko et al. (46) assessed stress using the Perceived Stress Scale [PSS-4; (69)], and Pontes (41) assessed stress by using the stress scale of the DASS-21 (57).

Problematic Social Networking Site Use in Other Studies (Sample Sizes < 500 Participants)

During the initial literature search, nine studies were found that met all the inclusion criteria apart from having sample sizes above 500 participants. Most of these studies' findings concurred with those outlined in the previous sections. Two studies {i.e., (70) [n = 289]; (71) [n = 283]} examined the associations between PSNSU and ADHD. Significant and positive associations between PSNSU and ADHD were reported in both studies. Seven studies {e.g., (72) [n = 253]; (73) [n = 442]; (74) [n = 374]; (55) [n = 344]; (75) [n = 197]; (76) [n = 365]; (77) [n = 334]} examined the associations between PSNSU and depression with significant and positive associations being reported in all seven studies. Five studies {(78) [n = 207]; (79) [n = 451]; (80) [n = 243]; (75) [n = 197]; (77) [n = 334]} examined the associations between PSNSU and anxiety with a significant and positive association being reported in all the studies. Two studies {(81) [n = 499]; (75) [n = 197]} examined the associations between PSNSU and stress with a significant and positive association being reported in both of them. Finally, one study {i.e., (82) [n = 215]} reported a negative association between PSNSU and depression.

Discussion

The present systematic review examined the associations between PSNSU and psychiatric disorder symptoms in nine studies that met the inclusion criteria. Of the nine studies, there was a positive association between PSNSU and depression (seven studies), anxiety (six studies), stress (two studies), ADHD (one study), and OCD (one study). The general findings of the review suggest that PSNSU co-occurs with all psychiatric disorders that have been examined (i.e., ADHD, OCD, depression, anxiety, and stress). Similar results were also found in the nine studies that met all the criteria for inclusion apart from having samples < 500 participants. The review showed that depression was significantly associated with PSNSU in seven of the reviewed studies. Based on the effect size conventions (83), these relationships generally had small to medium bivariate effect sizes across the studies. The review also showed that anxiety was significantly associated with PSNSU in six of the studies, and that the relationships generally had small bivariate effect sizes across the studies. It is important to note that only a small number of studies have examined the relationship between PSNSU and symptoms of psychiatric disorder. The association between the variables will need to be re-assessed in the near future once there are further empirical studies. Based on the studies reviewed, it is plausible to suggest that participants with PSNSU are at higher risk of psychiatric disorders. However, it is also possible that those with psychiatric illness symptoms may be more prone to PSNSU. Different measurement instruments were used to assess PSNSU with the BSMAS (and its predecessor, the BFAS) being the most utilized psychometrically validated measure. The review also showed that adolescent samples were the most utilized group with only two studies targeting the general population. This shows that future research needs to examine SNS use in the general adult population.

Explanations for Psychiatric Disorder Symptoms Relations With PSNSU

The reviewed studies provided some explanations for the relationship between PSNSU and psychiatric disorder symptoms. Andreassen et al. (37) suggested individuals over-using SNSs may experience a constant urge to check their social networks for new information and updates because of the fear of missing out (8487). Andreassen et al. (33) also suggest that those with ADHD symptoms may use SNSs excessively due to the constant updates from these platforms and beeping and vibrating smartphones [SNSs are now typically accessed via smartphones; (88)]. Shensa et al. (42) suggest that individuals with greater PSNSU levels neglect other constructive aspects of their lives which could contribute to depression symptoms. Also, it may be that individuals experiencing depressive symptoms are more prone to PSNSU. It is important to note that Shensa et al. (42) found that social media use frequency (but not social media time) was significantly and independently associated with depressive symptoms. This suggests that it may be how individuals use social media (and not how much) that is associated with depressive symptoms. Atroszko et al. (46) concluded that Facebook dependent individuals crave social interactions and self-validation, and that compulsive Facebook activity may generate stress. Worsley et al. (45) inferred that young users may be excessively using SNSs in order to avoid or reduce depression and anxiety. This provides support for the work of Seabrook et al. (89) who claimed that there is a possibility that the relationship between PSNSU and depression symptoms may be bi-directional. Taken together, these findings provide interesting insights into the mechanisms of SNS use and the influence they have on the individual user (especially those who are susceptible to psychiatric disorders). Some of the studies suggest that the experiences of SNS users and how they respond to the rewarding aspects of SNS use may be a defining factor in the occurrence of PSNSU. Furthermore, the studies pave the way for future research to investigate specific cognitive factors (e.g., fear of missing out) and motivational factors (e.g., escapism) associated with PSNSU. Brand et al. (90) have argued that future studies should explicitly address the personality profiles among different forms of Internet-related disorders because this may reveal common and unique correlates of dysfunctional use of SNSs.

External factors (such as work/home environments) that may affect the relationship between SNS use and psychiatric disorder symptoms should be taken into consideration. SNSs can serve as a platform with positive and/or negative effects on users' psychological health and well-being. Given that adolescents are using SNSs at a high rate worldwide, as a specific group they are more likely to experience co-morbid psychiatric symptoms (42). Research evidence suggests that increased levels of internet use can cause the types of psychiatric symptoms included in the present review among a minority of individuals (34). For instance, problematic technology use (internet use, social media use, computer use, mobile phone use, and smartphone use) have all been associated with greater subsequent levels of depression, stress, anxiety and sleep disturbance among a minority of individuals (34, 9194). Future research should focus on prevention programs and interventions to ameliorate the potential adverse consequences among this minority of problematic SNS users. The findings from this review benefits researchers and clinicians in helping pinpoint symptoms of psychiatric disorders during intervention programs and consultations.

Limitations

The limitations of the studies covered in the review is that all of them were cross-sectional surveys. Although this type of study design is arguably reliable in determining such associations (despite well-known biases such as memory recall and social desirability), it is not possible to ascertain causality. Longitudinal study data is required to assess causal interactions between variables examined in the present review. Most of the studies were based on European samples (and even then, only data from seven countries was collected) which limits the generalizability of the findings. Consequently, the results cannot be interpreted in the context of other cultures and continents. Although the present review only included large scale studies, only two studies had very large sample sizes over 5,000 participants [i.e., (13, 37)], and only two studies collected data from representative populations [i.e., (13, 42)]. Further research is therefore needed using much larger and representative samples. Overall, the studies reviewed here showed associations between PSNSU and psychiatric disorder symptoms, particularly in adolescents. Most associations were found between PSNSU, depression, and anxiety. Future research should focus on other psychiatric disorder symptoms using different study methods. Future studies should also focus on the potential negative consequences of SNS use and psychiatric disorders by implementing methodologies other than cross-sectional surveys. An interesting angle for future research would be to assess associations between different behavioral addictions because there may be common etiologies and psychopathologies.

Conclusions

This systematic review demonstrates that PSNSU and psychiatric disorder symptoms co-occur, particularly in adolescents. Most associations were found between PSNSU, depression, and anxiety. Future research using different methods (other than cross-sectional surveys) and representative samples is required.

Author Contributions

ZH and MG: Paper concept and design; writing and finalization of the manuscript; approved the final manuscript. ZH: Literature searches, initial analyses of studies, and initial drafting of the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

1. Statista.com. Number of Social Media Users Worldwide From 2010 to 2021 (in billions) (2018). Available online at: https://www.statista.com/statistics/278414/number-of-worldwide-social-network-users/ (Accessed September 26, 2018).

2. Pew Research Center. Teens, Social Media, and Technology 2018 (2018). Available online at: http://www.pewinternet.org/2018/05/31/teens-social-media-technology-2018/50/ (Accessed September 26, 2018).

3. World Health Organization. Public Health Implications of Excessive Use of the Internet, Computers, Smartphones and Similar Electronic Devices: Meeting Report. Foundation for Promotion of Cancer Research, National Cancer Research Centre, Tokyo, Japan. Geneva: WHO (2014).

4. Niemz K, Griffiths M, Banyard P. Prevalence of pathological Internet use among university students and correlations with self-esteem, the general health questionnaire (GHQ), and disinhibition. Cyberpsychol Behav. (2005) 8:562–70. doi: 10.1089/cpb.2005.8.562

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Tsitsika A, Critselis E, Kormas G, Filippopoulou A, Tounissidou D, Freskou A, et al. Internet use and misuse: a multivariate regression analysis of the predictive factors of Internet use among Greek adolescents. Eur J Pediatr. (2009) 168:655–65. doi: 10.1007/s00431-008-0811-1

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Griffiths M. A “components” model of addiction within a biopsychosocial framework. J Subst Use (2005) 10:191–7. doi: 10.1080/14659890412331318930

CrossRef Full Text | Google Scholar

7. Andreassen CS, Pallesen S. Social network site addiction - An overview. Curr Pharm Design (2014) 20:4053–61. doi: 10.2174/13816128113199990616

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Griffiths M. Behavioural addiction: an issue for everybody? Employee Counsel Today (1996) 8:19–25. doi: 10.1108/13665629610116872

CrossRef Full Text

9. Cam E, Isbulan O. A new addiction for teacher candidates: social networks. Turk Online J Educ Technol. (2012) 11:14–9.

Google Scholar

10. Koc M, Gulyagci S. Facebook addiction among Turkish college students: the role of psychological health, demographic, and usage characteristics. Cyberpsychol Behav Soc Netw. (2013) 16:279–84. doi: 10.1089/cyber.2012.0249

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Malik S, Khan M. Impact of Facebook addiction on narcissistic behavior and self-esteem among students. J Pak Med Assoc. (2015) 65:260–3.

PubMed Abstract | Google Scholar

12. Alabi OF. A survey of Facebook addiction level among selected Nigerian university undergraduates. N Media Mass Commun. (2013) 10:70–80.

Google Scholar

13. Bányai F, Zsila Á, Király O, Maraz A, Elekes Z, Griffiths MD, et al. Problematic social media use: results from a large-scale nationally representative adolescent sample. PLoS ONE (2017) 12:e0169839. doi: 10.1371/journal.pone.0169839

PubMed Abstract | CrossRef Full Text | Google Scholar

14. Wolniczak I, Caceres-DelAguila JA, Palma-Ardiles G, Arroyo KJ, Solís-Visscher R, Paredes-Yauri S, et al. Association between Facebook dependence and poor sleep quality: a study in a sample of undergraduate students in Peru. PLoS ONE (2013) 8:e59087. doi: 10.1371/journal.pone.0059087

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Wu AM, Cheung VI, Ku L, Hung EP. Psychological risk factors of addiction to social networking sites among Chinese smartphone users. J Behav Addict. (2013) 2:160–6. doi: 10.1556/JBA.2.2013.006

PubMed Abstract | CrossRef Full Text | Google Scholar

16. Utz S. The function of self-disclosure on social network sites: not only intimate, but also positive and entertaining self-disclosures increase the feeling of connection. Comput Hum Behav. (2015) 45:1–10. doi: 10.1016/j.chb.2014.11.076

CrossRef Full Text | Google Scholar

17. Huang HY. Examining the beneficial effects of individual's self-disclosure on the social network site. Comput Hum Behav. (2016) 57:122–32. doi: 10.1016/j.chb.2015.12.030

CrossRef Full Text | Google Scholar

18. Nabi RL, Prestin A, So J. Facebook friends with (health) benefits? Exploring social network site use and perceptions of social support, stress, and well-Being. Cyberpsychol Behav Soc Netw. (2013) 16:721–7. doi: 10.1089/cyber.2012.0521

PubMed Abstract | CrossRef Full Text | Google Scholar

19. Oberst U, Wegmann E, Stodt B, Brand M, Chamarro A. Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out. J Adolesc. (2017) 55:51–60. doi: 10.1016/j.adolescence.2016.12.008

PubMed Abstract | CrossRef Full Text | Google Scholar

20. Kuss DJ, Griffiths MD. Online social networking and addiction – A review of the psychological literature. Int J Environ Res Public Health (2011) 8:3528–52. doi: 10.3390/ijerph8093528

PubMed Abstract | CrossRef Full Text | Google Scholar

21. Kirschner PA, Karpinski AC. Facebook® and academic performance. Comput Hum Behav. (2010) 26:1237–45. doi: 10.1016/j.chb.2010.03.024

CrossRef Full Text | Google Scholar

22. Błachnio A, Przepiorka A, Pantic I. Association between Facebook addiction, self-esteem and life satisfaction: a cross-sectional study. Comput Hum Behav. (2016) 55:701–5. doi: 10.1016/j.chb.2015.10.026

CrossRef Full Text | Google Scholar

23. Satici SA, Uysal R. Well-being and problematic Facebook use. Comput Hum Behav. (2015) 49:185–90. doi: 10.1016/j.chb.2015.03.005

CrossRef Full Text | Google Scholar

24. Chen W, Lee K-H. Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychol Behav Soc Netw. (2013) 16:728–34. doi: 10.1089/cyber.2012.0272

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Andreassen CS, Pallesen S, Griffiths MD. The relationship between excessive online social networking, narcissism, and self-esteem: findings from a large national survey. Addict Behav. (2017) 64:287–93. doi: 10.1016/j.addbeh.2016.03.006

CrossRef Full Text | Google Scholar

26. Fox J, Rooney MC. The Dark Triad and trait self-objectification as predictors of men's use and self-presentation behaviors on social networking sites. Pers Individ Differ. (2015) 76:161–5. doi: 10.1016/j.paid.2014.12.017

CrossRef Full Text | Google Scholar

27. Kircaburun K, Griffiths MD. The dark side of internet: preliminary evidence for the associations of dark personality traits with specific online activities and problematic internet use. J Behav Addict. (2018). doi: 10.1556/2006.7.2018.109. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

28. Halpern D, Valenzuela S, Katz JE. “Selfie-ists” or “Narci-selfiers”?: a cross-lagged panel analysis of selfie taking and narcissism. Pers Individ Differ. (2016) 97:98–101. doi: 10.1016/j.paid.2016.03.019

CrossRef Full Text | Google Scholar

29. Jain MJ, Mavani KJ. A comprehensive study of worldwide selfie-related accidental mortality: a growing problem of the modern society. Int J Injury Control Safety Promot. (2017) 24:544–9. doi: 10.1080/17457300.2016.1278240

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Nesi J, Prinstein MJ. In search of likes: longitudinal associations between adolescents' digital status seeking and health-risk behaviors. J Clin Child Adolesc Psychol. (2018). doi: 10.1080/15374416.2018.1437733. [Epub ahead of print].

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Sarabia I, Estévez A. Sexualized behaviors on Facebook. Comput Hum Behav. (2016) 61:219–26. doi: 10.1016/j.chb.2016.03.037

CrossRef Full Text | Google Scholar

32. Carli V, Durkee T, Wasserman D, Hadlaczky G, Despalins R, Kramarz E, et al. The association between pathological internet use and comorbid psychopathology: a systematic review. Psychopathology (2013) 46:1–13. doi: 10.1159/000337971

PubMed Abstract | CrossRef Full Text | Google Scholar

33. Anderson EL, Steen E, Stavropoulos V. Internet use and problematic internet use: a systematic review of longitudinal research trends in adolescence and emergent adulthood. Int J Adolesc Youth (2016) 22:430–54. doi: 10.1080/02673843.2016.1227716

CrossRef Full Text | Google Scholar

34. Kuss DJ, Griffiths MD, Karila L, Billieux J. Internet addiction: a systematic review of epidemiological research for the last decade. Curr Pharm Design (2014) 20:4026–52. doi: 10.2174/13816128113199990617

PubMed Abstract | CrossRef Full Text | Google Scholar

35. Elhai JD, Dvorak RD, Levine JC, Hall BJ. Problematic smartphone use: a conceptual overview and systematic review of relations with anxiety and depression psychopathology. J Affect Disord. (2017) 207:251–9. doi: 10.1016/j.jad.2016.08.030

PubMed Abstract | CrossRef Full Text | Google Scholar

36. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int J Surg. (2010) 8:336–41. doi: 10.1016/j.ijsu.2010.02.007

PubMed Abstract | CrossRef Full Text | Google Scholar

37. Andreassen CS, Billieux J, Griffiths MD, Kuss DJ, Demetrovics Z, Mazzoni E, et al. The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav. (2016) 30:252–62. doi: 10.1037/adb0000160

CrossRef Full Text | Google Scholar

38. Andreassen CS, 1Torsheim T, Brunborg GS, Pallesen S. Development of a Facebook Addiction Scale. Psychol Rep. (2012) 110:501–17. doi: 10.2466/02.09.18.PR0.110.2.501-517

PubMed Abstract | CrossRef Full Text | Google Scholar

39. Kircaburun K, Kokkinos CM, Demetrovics Z, Király O, Griffiths MD, Çolak TS. Problematic online behaviors among adolescents and emerging adults: associations between cyberbullying perpetration, problematic social media use, and psychosocial factors. Int J Mental Health Addict. (2018) 1–19–8. doi: 10.1007/s11469-018-9894-8

CrossRef Full Text | Google Scholar

40. Xanidis N, Brignell CM. The association between the use of social network sites, sleep quality and cognitive function during the day. Comput Hum Behav. (2016) 55:121–6. doi: 10.1016/j.chb.2015.09.004

CrossRef Full Text | Google Scholar

41. Pontes HM. Investigating the differential effects of social networking site addiction and Internet gaming disorder on psychological health. J Behav Addict. (2017) 6:601–10. doi: 10.1556/2006.6.2017.075

PubMed Abstract | CrossRef Full Text | Google Scholar

42. Shensa A, Escobar-Viera CG, Sidani JE, Bowman ND, Marshal MP, Primack BA. Problematic social media use and depressive symptoms among US young adults: a nationally-representative study. Soc Sci Med. (2017) 182:150–7. doi: 10.1016/j.socscimed.2017.03.061

CrossRef Full Text | Google Scholar

43. Van Rooij AJ, Ferguson CJ, Van de Mheen D, Schoenmakers TM. Time to abandon internet addiction? Predicting problematic Internet, game, and social media use from psychosocial well-being and application use. Clin Neuropsychiatry (2017) 14:113–21.

Google Scholar

44. Meerkerk GJ, van Den Eijnden RJ, Vermulst AA, Garretsen HF. The compulsive internet use scale (CIUS): some psychometric properties. CyberPsychol Behav. (2009) 12:1–6. doi: 10.1089/cpb.2008.0181

PubMed Abstract | CrossRef Full Text | Google Scholar

45. Worsley JD, McIntyre JC, Bentall RP, Corcoran R. Childhood maltreatment and problematic social media use: the role of attachment and depression. Psychiatry Res. (2018) 267:88–93. doi: 10.1016/j.psychres.2018.05.023

PubMed Abstract | CrossRef Full Text | Google Scholar

46. Atroszko PA, Balcerowska JM, Bereznowski P, Biernatowska A, Pallesen S, Andreassen CS. Facebook addiction among Polish undergraduate students: validity of measurement and relationship with personality and well-being. Comput Hum Behav. (2018) 85:329–38. doi: 10.1016/j.chb.2018.04.001

CrossRef Full Text | Google Scholar

47. Dhir A, Yossatorn Y, Kaur P, Chen S. Online social media fatigue and psychological wellbeing – A study of compulsive use, fear of missing out, fatigue, anxiety and depression. Int J Inform Manag. (2018) 40:141–52. doi: 10.1016/j.ijinfomgt.2018.01.012

CrossRef Full Text | Google Scholar

48. Andreassen CS, Griffiths MD, Gjertsen SR, Krossbakken E, Kvam S, Pallesen S. The relationships between behavioral addictions and the five-factor model of personality. J Behav Addict. (2013) 2:90–9. doi: 10.1556/JBA.2.2013.003

PubMed Abstract | CrossRef Full Text | Google Scholar

49. Monacis L, De Palo V, Griffiths MD, Sinatra M. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale. J Behav Addict. (2017) 6:178–86. doi: 10.1556/2006.6.2017.023

PubMed Abstract | CrossRef Full Text | Google Scholar

50. Lin CY, Broström A, Nilsen P, Griffiths MD, Pakpour AH. Psychometric validation of the Persian Bergen Social Media Addiction Scale using classic test theory and Rasch models. J Behav Addict. (2017) 6:620–9. doi: 10.1556/2006.6.2017.071

PubMed Abstract | CrossRef Full Text | Google Scholar

51. Pontes HM, Andreassen CS, Griffiths MD. Portuguese validation of the Bergen Facebook Addiction Scale: an empirical study. Int J Mental Health Addict. (2016) 14:1062–73. doi: 10.1007/s11469-016-9694-y

CrossRef Full Text | Google Scholar

52. Kessler RC, Adler L, Ames M, Demler O, Faraone S, Hiripi EVA, et al. The World Health Organization Adult ADHD Self-Report Scale (ASRS): a short screening scale for use in the general population. Psychol Med. (2005) 35:245–56. doi: 10.1017/S0033291704002892

PubMed Abstract | CrossRef Full Text | Google Scholar

53. Foa EB, Huppert JD, Leiberg S, Langner R, Kichic R, Hajcak G, et al. The obsessive-compulsive inventory: development and validation of a short version. Psychol Assess. (2002) 14:485–96. doi: 10.1037//1040-3590.14.4.485

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Salokangas RKR, Poutanen O, Stengård E. Screening for depression in primary care: development and validation of the Depression Scale, a screening instrument for depression. Acta Psychiatr Scand. (1995) 92:10–6. doi: 10.1111/j.1600-0447.1995.tb09536.x

PubMed Abstract | CrossRef Full Text | Google Scholar

55. Kircaburun K, Demetrovics Z, Király O, Griffiths MD. Childhood emotional trauma and cyberbullying perpetration among emerging adults: a multiple mediation model of the role of problematic social media use and psychopathology. Int J Mental Health Addict. (2018) 1–19. doi: 10.1007/s11469-018-9941-5

CrossRef Full Text | Google Scholar

56. Joseph S, Linley PA, Harwood J, Lewis CA, McCollam P. Rapid assessment of well-being: the Short Depression-Happiness Scale (SDHS). Psychol Psychother. (2004) 77:463–78. doi: 10.1348/1476083042555406

PubMed Abstract | CrossRef Full Text | Google Scholar

57. Lovibond PF, Lovibond SH. The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the beck depression and anxiety inventories. Behav Res Ther. (1995) 33:335–43. doi: 10.1016/0005-7967(94)00075-U

PubMed Abstract | CrossRef Full Text | Google Scholar

58. Cella D, Riley W, Stone A, Rothrock N, Reeve B, Yount S, et al. The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. J Clin Epidemiol. (2010) 63:1179–94. doi: 10.1016/j.jclinepi.2010.04.011

PubMed Abstract | CrossRef Full Text | Google Scholar

59. Kandel DB, Davies M. Epidemiology of depressive mood in adolescents: an empirical study. Arch Gen Psychiatry (1982) 39:1205–12. doi: 10.1001/archpsyc.1982.04290100065011

PubMed Abstract | CrossRef Full Text | Google Scholar

60. Kandel DB, Davies M. Adult sequelae of adolescent depressive symptoms. Arch Gen Psychiatry (1986) 43:255–62. doi: 10.1001/archpsyc.1986.01800030073007

PubMed Abstract | CrossRef Full Text | Google Scholar

61. Kroenke K, Spitzer RL. The PHQ-9: a new depression diagnostic and severity measure. Psychiatr Ann. (2002) 32:509–15. doi: 10.3928/0048-5713-20020901-06

CrossRef Full Text | Google Scholar

62. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Measur. (1977) 1:385–401. doi: 10.1177/014662167700100306

CrossRef Full Text | Google Scholar

63. Zigmond AS, Snaith RP. The hospital anxiety and depression scale. Acta Psychiatr Scand. (1983) 67:361–70. doi: 10.1111/j.1600-0447.1983.tb09716.x

PubMed Abstract | CrossRef Full Text | Google Scholar

64. Dabkowska M. Some aspects of anxiety in victims of domestic abuse. Psychiatria (2008) 5:91–8.

Google Scholar

65. Liebowitz MR. Social phobia. Mod Trends Pharmacopsychiatry (1987) 22:141–73. doi: 10.1159/000414022

PubMed Abstract | CrossRef Full Text | Google Scholar

66. La Greca AM, Lopez N. Social anxiety amongst adolescents: linkages with peer relations and friendships. J Abnorm Child Psychol. (1998) 26:83–94. doi: 10.1023/a:1022684520514

CrossRef Full Text | Google Scholar

67. La Greca AM, Stone WL. Social anxiety scale for children-revised: factor structure and concurrent validity. J Clin Child Psychol. (1993) 22:17–27. doi: 10.1207/s15374424jccp2201_2

CrossRef Full Text | Google Scholar

68. Bartholomew K, Horowitz LM. Attachment styles among young adults: a test of a four-category model. J Pers Soc Psychol. (1991) 61:226. doi: 10.1037//0022-3514.61.2.226

PubMed Abstract | CrossRef Full Text | Google Scholar

69. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. (1983) 24:385–96. doi: 10.2307/2136404

PubMed Abstract | CrossRef Full Text | Google Scholar

70. Gul H, Yurumez Solmaz E, Gul A, Oner O. Facebook overuse and addiction among Turkish adolescents: are ADHD and ADHD-related problems risk factors? Psychiatry Clin Psychopharmacol. (2018) 28:80–90. doi: 10.1080/24750573.2017.1383706

CrossRef Full Text | Google Scholar

71. Settanni M, Marengo D, Fabris MA, Longobardi C. The interplay between ADHD symptoms and time perspective in addictive social media use: a study on adolescent Facebook users. Child Youth Serv Rev. (2018) 89:165–70. doi: 10.1016/j.childyouth.2018.04.031

CrossRef Full Text | Google Scholar

72. Chae D, Kim H, Kim YA. Sex differences in the factors influencing Korean college students' addictive tendency toward social networking sites. Int J Mental Health Addict. (2018) 16:339–50. doi: 10.1007/s11469-017-9778-3

CrossRef Full Text | Google Scholar

73. Holmgren HG, Coyne SM. Can't stop scrolling!: pathological use of social networking sites in emerging adulthood. Addict Res Theory (2017) 25:375–82. doi: 10.1080/16066359.2017.1294164

CrossRef Full Text | Google Scholar

74. Jasso-Medrano JL, López-Rosales F. Measuring the relationship between social media use and addictive behavior and depression and suicide ideation among university students. Comput Hum Behav. (2018) 87:183–91. doi: 10.1016/j.chb.2018.05.003

CrossRef Full Text | Google Scholar

75. Meena PS, Soni R, Jain M, Paliwal S. Social networking sites addiction and associated psychological problems among young adults: a study from North India. Sri Lanka J Psychiatry (2015) 6:14–6. doi: 10.4038/sljpsyc.v6i1.8055

CrossRef Full Text | Google Scholar

76. Wang P, Wang X, Wu Y, Xie X, Wang X, Zhao F, et al. Social networking sites addiction and adolescent depression: a moderated mediation model of rumination and self-esteem. Pers Individ Differ. (2018) 127:162–7. doi: 10.1016/j.paid.2018.02.008

CrossRef Full Text | Google Scholar

77. Wegmann E, Stodt B, Brand M. Addictive use of social networking sites can be explained by the interaction of Internet use expectancies, Internet literacy, and psychopathological symptoms. J Behav Addict. (2015) 4:155–62. doi: 10.1556/2006.4.2015.021

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Pers Individ Differ. (2017) 116:69–72. doi: 10.1016/j.paid.2017.04.039

CrossRef Full Text | Google Scholar

79. Durak HY. Modeling of variables related to problematic internet usage and problematic social media usage in adolescents. Curr Psychol. (2018) 1–13. doi: 10.1007/s12144-018-9840-8

CrossRef Full Text | Google Scholar

80. Lee-Won RJ, Herzog L, Park SG. Hooked on Facebook: the role of social anxiety and need for social assurance in problematic use of Facebook. Cyberpsychol Behav Soc Netw. (2015) 18:567–74. doi: 10.1089/cyber.2015.0002

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Hou XL, Wang HZ, Guo C, Gaskin J, Rost DH, Wang JL. Psychological resilience can help combat the effect of stress on problematic social networking site usage. Pers Individ Differ. (2017) 109:61–6. doi: 10.1016/j.paid.2016.12.048

CrossRef Full Text | Google Scholar

82. Turel O, Poppa N, Gil-Or O. Neuroticism magnifies the detrimental association between social media addiction symptoms and wellbeing in women, but not in men: a three-way moderation model. Psychiatr Q. (2018) 89:605–19. doi: 10.1007/s11126-018-9563-x

CrossRef Full Text | Google Scholar

83. Cohen J. Statistical Power Analysis for the Behavioral Sciences, 2nd Edn. Hillsdale, NJ: Lawrence Erlbaum Associates (1988).

Google Scholar

84. Andreassen CS. Online social network site addiction: a comprehensive review. Curr Addict Rep. (2015) 2:175–84. doi: 10.1007/s40429-015-0056-9

CrossRef Full Text | Google Scholar

85. Lee SJ, Kim B, Choi TK, Lee SH, Yook KH. Associations between smartphone addiction proneness and psychopathology. Korean J Biol Psychiatry (2014) 21:161–7.

Google Scholar

86. Lee YK, Chang CT, Lin Y, Cheng ZH. The dark side of smartphone usage: psychological traits, compulsive behavior and technostress. Comput Hum Behav. (2014) 31:373–83. doi: 10.1016/j.chb.2013.10.047

CrossRef Full Text | Google Scholar

87. Przybylski AK, Murayama K, DeHaan CR, Gladwell V. Motivational, emotional, and behavioral correlates of fear of missing out. Comput Hum Behav. (2013) 29:1841–8. doi: 10.1016/j.chb.2013.02.014

CrossRef Full Text | Google Scholar

88. Kuss DJ, Griffiths MD. Social networking sites and addiction: ten lessons learned. Int J Environ Res Public Health (2017) 14:311. doi: 10.3390/ijerph14030311

PubMed Abstract | CrossRef Full Text | Google Scholar

89. Seabrook EM, Kern ML, Rickard NS. Social networking sites, depression, and anxiety: a systematic review. JMIR Mental Health (2016) 3:e50. doi: 10.2196/mental.5842

PubMed Abstract | CrossRef Full Text | Google Scholar

90. Brand M, Young KS, Laier C, Wölfling K, Potenza MN. Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: an Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neurosci Biobehav Rev. (2016) 71:252–66. doi: 10.1016/j.neubiorev.2016.08.033

PubMed Abstract | CrossRef Full Text | Google Scholar

91. Leménager T, Hoffmann S, Dieter J, Reinhard I, Mann K, Kiefer F. The links between healthy, problematic, and addicted Internet use regarding comorbidities and self-concept-related characteristics. J Behav Addict. (2018) 7:31–43. doi: 10.1556/2006.7.2018.13

PubMed Abstract | CrossRef Full Text | Google Scholar

92. Mitchell L, Hussain Z. Predictors of problematic smartphone use: an examination of the Integrative Pathways Model and the role of age, gender, impulsiveness, excessive reassurance seeking, extraversion, and depression. Behav Sci. (2018) 8:74. doi: 10.3390/bs8080074

PubMed Abstract | CrossRef Full Text | Google Scholar

93. Thomée S, Eklöf M, Gustafsson E, Nilsson R, Hagberg M. Prevalence of perceived stress, symptoms of depression and sleep disturbances in relation to information and communication technology (ICT) use among young adults–an explorative prospective study. Comput Hum Behav. (2007) 23:1300–21. doi: 10.1016/j.chb.2004.12.007

CrossRef Full Text | Google Scholar

94. Hussain Z, Griffiths MD, Sheffield D. An investigation into problematic smartphone use: the role of narcissism, anxiety, and personality factors. J Behav Addict. (2017) 6:378–86. doi: 10.1556/2006.6.2017.052

PubMed Abstract | CrossRef Full Text | Google Scholar

Keywords: attention deficit and hyperactivity disorder, obsessive compulsive disorder, depression, anxiety, problematic social media use, social media addiction

Citation: Hussain Z and Griffiths MD (2018) Problematic Social Networking Site Use and Comorbid Psychiatric Disorders: A Systematic Review of Recent Large-Scale Studies. Front. Psychiatry 9:686. doi: 10.3389/fpsyt.2018.00686

Received: 08 October 2018; Accepted: 26 November 2018;
Published: 14 December 2018.

Edited by:

Yasser Khazaal, Université de Genève, Switzerland

Reviewed by:

Giuseppe Carrà, Università degli Studi di Milano Bicocca, Italy
Rita Santacroce, Università degli Studi G. d'Annunzio Chieti e Pescara, Italy
Lucia Romo, Université Paris Nanterre, France

Copyright © 2018 Hussain and Griffiths. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zaheer Hussain, z.hussain@derby.ac.uk

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