A review of theories and models applied in studies of social media addiction and implications for future research


  • 1 School of Information, The University of Texas at Austin, USA. Electronic address: [email protected].
  • 2 School of Information, The University of Texas at Austin, USA. Electronic address: [email protected].
  • PMID: 33268185
  • DOI: 10.1016/j.addbeh.2020.106699

With the increasing use of social media, the addictive use of this new technology also grows. Previous studies found that addictive social media use is associated with negative consequences such as reduced productivity, unhealthy social relationships, and reduced life-satisfaction. However, a holistic theoretical understanding of how social media addiction develops is still lacking, which impedes practical research that aims at designing educational and other intervention programs to prevent social media addiction. In this study, we reviewed 25 distinct theories/models that guided the research design of 55 empirical studies of social media addiction to identify theoretical perspectives and constructs that have been examined to explain the development of social media addiction. Limitations of the existing theoretical frameworks were identified, and future research areas are proposed.

Keywords: Facebook addiction; Internet addiction; Literature review; Problematic use; Social media addiction; Theoretical framework.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Publication types

  • Behavior, Addictive*
  • Internet Addiction Disorder
  • Interpersonal Relations
  • Social Media*

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Research Article

Hooked on virtual social life. Problematic social media use and associations with mental distress and addictive disorders

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Affiliations Faculty of Medicine, Dept of Clinical Sciences Lund, Psychiatry, Lund University, Lund, Sweden, Malmö Addiction Center, Region Skåne, Malmö, Sweden

Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Writing – review & editing

* E-mail: [email protected]

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  • Vincent Henzel, 
  • Anders Håkansson


  • Published: April 8, 2021
  • https://doi.org/10.1371/journal.pone.0248406
  • Reader Comments

Table 1

Social media is an important and growing part of the lives of the vast majority of the global population, especially in the young. Although still a young and scarce subject, research has revealed that social media has addictive potential. The aim of this cross-sectional study was to explore the associations between problematic use of social media and mental distress, problematic gaming and gambling, within the Swedish general population.

Data from 2,118 respondents was collected through self-report questions on demographics and validated scales measuring addiction-like experiences of social media, problem gaming, problem gambling, and mental distress. Associations were analyzed in unadjusted analyses and–for variables not exceedingly inter-correlated–in adjusted logistic regression analyses.

In adjusted analyses, problematic use of social media demonstrated a relationship with younger age, time using instant messaging services, and mental distress, but not with education level, occupational status, or with treatment needs for alcohol or drug problems. Behavioral addictions (internet, gaming and gambling) were substantially inter-correlated, and all were associated with problematic use of social media in unadjusted analyses.


Social media use is associated with other addictive behaviors and mental distress. While factors of causality remain to be studied, these insights can motivate healthcare professionals to assess social media habits, for example in individuals suffering from issues concerning gambling, gaming or mental health.

Citation: Henzel V, Håkansson A (2021) Hooked on virtual social life. Problematic social media use and associations with mental distress and addictive disorders. PLoS ONE 16(4): e0248406. https://doi.org/10.1371/journal.pone.0248406

Editor: Simone N. Rodda, University of Auckland, NEW ZEALAND

Received: March 18, 2020; Accepted: February 25, 2021; Published: April 8, 2021

Copyright: © 2021 Henzel, Håkansson. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data set cannot automatically be shared publicly, because that is not consistent with the data handling statement made in the original ethics application. These restrictions have been imposed by the Swedish Ethical Review Authority, Uppsala, Sweden. Requests for data access would have to be formally reviewed by the ethics review board. Data access requests may be directed to the Swedish Ethical Review Authority (contact via [email protected] ), to the Corresponding Author (contact via [email protected] ), or to Åsa Westrin (contact via [email protected] ).

Funding: The authors received no specific funding for this work.

Competing interests: AH holds a position as a professor at Lund University. His research funding includes funding from the Swedish state-owned gambling operator (Svenska Spel), the regional hospital system, and funding from the Swedish enforcement agency. However, these sponsorships are unrelated to this specific study.


There is a growing body of research indicating that using modern technologies, such as the Internet, video games, smart phones and social media platforms, has the potential of being addictive [ 1 – 3 ]. Social media addiction is not yet an established diagnosis, although it is one of many suggested behavioral addictions [ 4 ]. Among these, the gambling disorder is the only one recognized in the Diagnostic and Statistical Manual for Mental Disorders, while Internet gaming disorder is listed in its appendix as a condition which requires further research [ 5 ].

Worldwide, the number of people with an active Facebook account is predicted to surpass three billion [ 6 ] in the year 2021. Other popular platforms such as YouTube, Snapchat, and Instagram are also attracting an increasing number of users, especially from younger populations [ 7 ]. Constant online presence and availability has become something of a status quo in the lives of the vast majority, made possible with the rise of highly accessible and user-friendly laptops and smartphones. Using social media is one of the most common activities on the Internet [ 8 ], with daily use reported by nine out of ten youths worldwide [ 9 ]. Social media presents users with a broad spectrum of activities, ranging from maintenance of real life relationships through chats and calls, sharing one’s own or others’ creative content and opinions, partaking in communities, playing games, gambling, and passing time looking through the activities of other users [ 3 ]. This diversity of activities is a scientific challenge concerning whether social media can be considered addictive as a whole, or if it is rather a question of which parts of it that are potentially negative, as well as beneficial for the individual.

Academic work in this field has been criticized for its inconsistencies of defining normal and problematic usage, as well as using non-standardized measurement tools, subsequently rendering comparison of results and prevalence rates difficult. Confusion also surrounds what social media actually entails, and whether it is synonymous to social networking or not, as it is sometimes referred as [ 4 , 10 ]. In fact, the existent literature is inconsistent on labeling this issue; social media addiction, excessive, problematic, and at-risk use are applied both separately and homogeneously. Moreover, online activities such as sharing photos, engaging in communities, and communicating with real life friends can be associated with lower degree of loneliness and less psychological distress [ 11 , 12 ]. These particular activities are also believed to be mediators of shaping and maintaining the user’s sense of identity and belonging, safety and competence, satisfying basic psychological needs [ 13 ], as well as bringing higher psychosocial wellbeing, which apparently is the case particularly for young users [ 14 – 16 ].

Studies have demonstrated that interrelationships between different behavioral addictions exist, suggesting common underlying risk factors, together with associations with addictive use of psychoactive substances [ 17 ]. This has bred a widely used matrix of characteristics, first proposed by Griffiths as a ‘components model of addiction’ [ 18 ], involving a number of key components; salience (typically defined as the preoccupation in thoughts, and the vast amount of time and energy spent on either thinking of or carrying out the behavior), mood modification, tolerance, withdrawal, loss of control, and conflicts [ 18 , 19 ]. Some authors [ 20 , 21 ] have proposed socio-cognitive mechanisms for how Internet-related addictions develop. These revolve around negative beliefs about the self and the world, with thoughts such as ‘I’m nobody offline, but online I am someone’ or ‘the online world is safer than the real one’. This could reasonably lead to a preference for online interaction, an overreliance to the services provided by the Internet and social media, thus giving rise to an addictive state for the individual. With the component model as background, problematic use of social media has been suggested to consist of an exaggerated concern about social media, a strong motivation to use it, and the devotion of time and effort to social media to the extent that it negatively impacts on other social activities, studies, work, interpersonal relationships, and/or mental health and well-being [ 22 ].

There is a lack of reviews on the subject, and agreed-upon definitions or gold standard measurements and cutoffs have not been established. One part of this research gap is that–apart from differing definitions–prevalence rates reported also derive from different populations and in very different settings; prevalence figures reported have differed widely from a low of 1.6% in a study carried out in Nigeria, and a high of 34% in a study from China. When including general Internet addiction as well as Facebook addiction specifically, rates of 2–12% have been reported from various literature reviews [ 23 – 25 ]. Even though anyone with access to social media can become addicted to it, this holds true especially for young people, a group that has been increasingly exposed to technology, and consistently reported to use and abuse social media to a larger degree than adults [ 26 ]. From Europe and the US [ 27 , 28 ], recent studies and reports have found high rates of technology use among the young. A large proportion of children as young as 8 months use a screen daily, with the majority of 11-year-olds owning a smartphone, and 8-12-year-olds using screens for entertainment purposes almost five hours per day.

There are also associations to being single, as well as to low education level and lower monthly income, and although evidence is somewhat inconclusive for gender differences, several findings point to a slight overrepresentation among female users [ 29 – 31 ]. Suffering from mental disorders such as depression and anxiety has been long known to increase the risk for, and be exacerbated by, behavioral and substance addictions alike [ 32 , 33 ]. Numerous studies, including comprehensive reviews, have shown that addictive use of social media is associated with depression, anxiety and mental distress [ 26 , 34 – 37 ].

There have been discoveries regarding associations and interrelationships between addictive online behavior and use of psychoactive substances, in a number of European countries. Problematic use of video games and social media have displayed a small but significant relationship [ 23 ], while multidirectional associations between problematic gaming, gambling, and internet use have been observed as well [ 38 ]. Excessive use of the Internet has been shown to increase likelihood for use [ 39 – 42 ] and abuse [ 43 , 44 ] of alcohol and other substances. A relationship between time spent on social media and episodic heavy drinking has also been found [ 45 ].

There is a scarcity of studies on prevention or treatment for technology-related addictions. Mindfulness techniques [ 46 ], and psychotherapeutic interventions, have shown improvement of symptoms in some patients, but more controlled trials are needed to develop any standardized treatment regimens [ 47 – 49 ]. Thus, altogether, the overall understanding of addictive social media behavior is hitherto limited, with respect to topics ranging from risk factors and prevalence to the clinical picture and treatment possibilities. Based on this research gap, more knowledge is needed in the basic understanding of the existence and correlates of this construct in the population.

Altogether, based on the relative novelty of research in the area of social media addiction, large research gaps remain in the area. For example, considerably more information is needed about the correlates of problematic social media use, both in the population as a whole and in younger individuals specifically. Also, given the uncertainty so far about the definition of social media, there is reason to study if and how the present construct is association with other behavioral addictions often related to online platforms, such as gaming, gambling and the overall use of the internet. In addition, it is of importance to study and to control for the time spent in typically occurring instant messaging services, when also considering other types of possible risk factors.

Thus, the present study aimed to assess problematic use of social media as the primary outcome of the study, and exemplifying it mentioning some brand names representing the most common social media reported (Facebook and Instagram) [ 50 ], as well as one of the social media somewhat less common but often referred to in the media (Twitter). Also, the study aimed to outline the possible correlations of problematic social media use with demographics, mental distress, and other behavioral addictions, in the general population as a whole, as well as in the sub-population of adolescents/younger adults. The present study hypothesized that addictive social media behavior, in the general population, may be related to symptoms of psychological distress, and to a history of treatment needs for problematic alcohol or drug use.

Study design

A cross-sectional self-reported online survey design was utilized, targeting the general Swedish population. The questionnaire assessed a spectrum of behavioral addictions, of which problematic use of social media was the main outcome variable. In the present analyses, problematic social media use was treated as the outcome variable, testing it against a number of factors suggested in the literature to be associated with this behavior.

Participants and procedures

Data collection from a general Swedish population sample was conducted with the help of a marketing survey company (Userneeds AB), who administered a self-report online questionnaire via e-mail to their web panel members in six age groups ranging from 16 to 80 years, aiming for a nationally representative sample. Potential participants included members of the web panel of Userneeds, who typically receive offers to participate in market surveys for commercial products and similar. Each completed survey grants the respondent a reward of approximately 1€.

Electronic written consent was required in order for the questionnaire to open. To ensure anonymity and confidentiality, the IP-address of each respondent was hidden from the researchers. To complete and thereby send the filled questionnaire to the researchers, every single question had to be answered, and though they could not be skipped, some items had an optional answer reading “do not wish to answer”. The target was to reach a sample of 2000 individuals, equally divided regarding gender, and stratified by age. The full sample was reached in October, 2019, totaling 2118 partial and 2002 completed surveys, ending four weeks of data collection.

The National Ethical Review Board, Sweden, approved the study in August, 2019, and stated it was not subject to Swedish ethics legislation as it does not involved identified personal data. The present study is based on data from the same overall online survey data collection as a different scientific publication in a separate line of research, a paper assessing history of voluntary self-exclusion in gambling through a novel multi-operator self-exclusion service in the present setting [ 51 ].

Instruments and measures

For the primary outcome measure of social media addiction, the study used the Bergen Social Media Addiction Scale (BSMAS) includes six Likert scale items, graded 1–5 (‘Never’–‘Very often’) about the following experiences, during the last 12 months: spending a lot of time thinking of social media or planning what to do there; desiring to use social media more and more; using social media to forget about personal issues; tried to cut down use without success; becomes restless or anxious when unable to access social media; used social media to such a degree that it has impacted your work or studies negatively. Scoring ranges from 6–30, with 19 or above indicating problematic use of social media, and the scale has been validated and shown to have a Cronbach alpha of 0.86 [ 52 , 53 ]. As in recent years, the authors behind the present scale have recommended a score of 19 as the cut-off indicating problematic social media use [ 52 – 54 ], the present study used a dichotomous classification of respondents as either above or below cut-off, rather than using the instrument in a dimensional way.

The start of the social media item was that the questions were to deal with the respondent’s use of social media (Facebook, Twitter, Instagram and similar) during the past 12 months. The social media given as examples here, as well as the ‘and similar’ wording, were provided in order to mention the most common ones, i.e. Facebook and Instagram, as well as Twitter as an example of a service also being relatively common but which may also appear in somewhat different contexts, such as in reports in the professional life and in business and traditional media [ 50 ].

In order to study potential correlates of social media addiction, related to problematic internet use, problem gambling, problem gaming and psychological distress, the study used the following screening tools:

  • The Problematic and Risky Internet Use Screening Scale-3 (PRIUSS), is made up of three items grading Internet behavior with a five-point Likert scale ranging from never to very often. This scale has no time frame, rather it assesses current symptoms. The questions evaluated to what degree the subject had experienced increased anxiety because of Internet use, felt anxious when not using the Internet, and how often they felt a loss of motivation for more important tasks. Score range is 0–12, with a cutoff at 9 points for risky Internet use [ 55 ]. Cronbach-alpha value has been reported to be 0.81.
  • The Gaming Addiction Scale (GAS), also a five-point Likert scale ranging from 1–5 (‘Never’ to ‘Very often’), was developed and validated by Lemmens et. al [ 56 ]. It begins with the phrase ‘How often during the last six months…’, followed by seven questions: did you think about playing a game all day long; did you spend an increasing amount of time on games; did you play games to forget about real life; have others unsuccessfully tried to reduce your game use; have you felt bad when you were unable to play; did you have fights with others (e.g., family, friends) over your time spent on games, and; have you neglected other important activities(work, school, exercise) to play games. The cutoff for at-risk gaming behavior is 21 out of a total of 35 points, and the internal validity of this tool has repeatedly demonstrated a Cronbach-alpha above 0.7 [ 57 ].
  • The Problem Gambling Severity Index (PGSI), developed in Canada [ 58 ], consists of nine items corresponding to the diagnostic criteria for Gambling Disorder in the DSM-5. Assessing gambling behavior during the recent twelve month period, the scale grades loss of control, increased urges, returning to reclaim losses, whether they had borrowed money or sold something to gamble, self-awareness of problematic gambling, receiving criticism from others, feelings of guilt, gambling had caused any health issues, and lastly any financial problems. In this research paper, which does not seek to screen for or subdivide gambling behavior, scoring 9 or higher out of 27 possible points is regarded problematic [ 59 , 60 ]. The Cronbach-alpha has been shown to be 0.77 [ 60 ].
  • The Kessler Psychological Distress Scale (Kessler-6), a six-item questionnaire with a 5-point Likert scale on each one (‘Not at all’ to ‘Almost constantly’), assessing non-specific mental distress during the past six months. It is widely used both clinically and academically as a tool for severity or screening [ 61 ]. With questions inspired from the symptomatology of depression and anxiety, it asks how often the respondent had been nervous, restless or fidgety, so depressed that nothing could cheer him/her up, felt that everything was an effort, and had felt worthlessness. A cut-off at 13 out of 24 possible points indicates severe mental distress. It includes an option to answer ‘Do not wish to answer’ on each item, although these were excluded from statistical analyses. The Cronbach-alpha of the Kessler-6 scale has been reported to be 0.89 [ 61 ]

In addition, study variables included sociodemographic data; age (in age groups), gender (male, female, or do not wish to answer), marital status, occupational status, level of education, and monthly income in discrete intervals. The five categories of occupational status were merged into two categories; working (59.8%), or not working (40.2%) which covered studying, seeking employment, being retired, or being on sick leave ( Table 1 ).


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All individuals included (N = 2,002).


Given the previous literature on likely associations between social media behavior and substance use, the study included items describing problematic substance use. These variables included one dichotomous item about whether the respondent had ever felt the need to seek treatment for alcohol problems, and one variable about having felt the need to seek treatment for drug problems (defining drugs as illicit drugs and addictive prescription drugs such as prescription sedatives or strong analgesics). Also, a corresponding item assessed whether respondents had ever felt the need to seek treatment for mental distress. These items included the possibility to refuse to answer. Moreover, the quantity of time spent on online messaging services was included, with examples of such use being instant messaging services such as Facebook Messenger, Instagram Direct Messaging, as well as WhatsApp and regular phone texting. Here, options ranged from below one hour daily, to more than four hours daily ( Table 1 ).

Statistical methods

SPSS was used for statistical observations and analyses. A total of 2118 questionnaires were initiated, of which 116 were excluded because of incomplete status. Subsequently, descriptive characteristics were observed, and the primary outcome was characterized as problematic or non-problematic use of social media. In a first univariate comparison of respondents with problematic or non-problematic social media use, these groups were compared using the chi-square test for categorical data, and the Mann-Whitney U-test for continuous variables. Thereafter, in order to adjust variables for one another, logistic regression analyses were performed.

In a binary correlation matrix run for each pairwise combination of variables, some variables displayed relatively pronounced correlations; the association reaching the highest level of correlation (a Pearson correlation of 0.65) was between gaming (GAS) and gambling (PGSI), and three further associations were above a correlation of 0.50 (PRIUSS and GAS, 0.56, the Kessler score and having felt a need to seek treatment for mental health, 0.54, and PRIUSS and the Kessler score, 0.53). Time on instant messaging services and PRIUSS had a correlation of 0.43, and PRIUSS and PGSI 0.41, age and GAS 0.40, age and the Kessler score 0.40, and GAS and time on instant messaging 0.40, whereas all other correlations were below 0.40. Thus, in the logistic regression, data for behavioral addictions (PRIUSS, GAS and PGSI) were not assessed, due to the high statistical overlap between them, and these were therefore only reported in univariate analyses. Finally, in addition, due to the close correlation (and conceptual similarity) between the Kessler-6 score and the item describing the need to seek help for mental health, only the Kessler-6 score was included in the logistic regression. Finally, these regression analyses therefore included age group, gender, occupational status (working vs not working), level of education, number of hours spent in instant messaging services, the Kessler-6 score for mental health, and ever having felt a need to seek treatment for alcohol problems, and for drug problems, respectively). The adjusted logistic regression analyses carried out included one for the whole sample (n = 1,863, after exclusion of 139 individuals with missing data for any of the variables assessed), and one including only the youngest age groups (>40 years, n = 677, after exclusion of 59 cases with missing data).

Descriptive observations

The number of initiated questionnaires was 2118, of which 116 were not completed and thus not included in statistical analysis. Of the remaining 2002 entries, demographics were distributed almost evenly regarding gender (1009 female, 989 male). Age distribution was skewed with the youngest groups being in minority compared to the older ones ( Table 1 ). Educational level was split into five categories, with distribution percentages (%) presenting at 5.5 for primary school, 34.7 for high school, 16.6 for an incomplete university degree, 38.7 for a complete degree, and lastly 4.4 per cent for the category labeled ‘Other’. Having experienced a need for help seeking was reported by 36.6, 4.2 and 2.1 percent for mental distress, alcohol problems, and drug problems, respectively.

Five percent of the total sample reached scores of 19 or above of the BSMAS, indicating problematic use of social media. Of the six symptomatic components of the BSMAS scale, the most common complaint in the sample was salience (18.1%), the least common being usage leading to negative consequences (3.8%). A majority of individuals spent up to two hours (83.4%) communicating with instant messaging services, with 16.6 percent spending two hours or more. The medians for the PRIUSS, GAS, PGSI, and Kessler-6, were 2, 7, 0, and 4 respectively. A history of having felt the need to seek help for mental distress, and alcohol and drug use, were reported by 37, four and two percent, respectively.

Associations with problematic use of social media

The univariate analysis showed no significant difference between men and women in regards to problematic use of social media, while there was a clear difference across age groups, with the highest percentages of problem users found in the younger groups (16–39 years), and a steep decrease was observed in the two older groups (40 years and above). Working or not revealed no significant difference, while educational level did, with individuals finishing high school having the highest percentage of social media addiction (7.2%), while the category of ‘other’ education showed the lowest (1.1%). Time spent chatting, as well as medians for each psychometric scale measured, were significantly associated with problematic use of social media ( Table 2 ).



In logistic regression, age displayed a negative associations with problematic social media use (OR 0.66 [0.55–0.78]), whereas the level of time spent in instant messaging services (OR 2.15 [1.79–2.58]), as well as the Kessler-6 score (OR 1.11 [1.05–1.17]), were positively associated with problematic social media use. Occupational status, level of education, as well as having felt a need to seek help for alcohol and drug use were not significantly correlated to the outcome ( Table 3 ). In the second logistic regression, including only respondents below 40 years of age, the association with age was no longer statistically significant, whereas the outcome variable remained significantly associated with time using instant messaging services (OR 2.03 [1.65–2.49]), and with the Kessler-6 score (OR 1.09 [1.03–1.16], Table 4 ).


Analyses after exclusion of 139 cases with non-complete for included variables.



Age groups 39 years and younger (N = 677). Analyses after exclusion of 59 individuals with incomplete data for included variables.


Among measures of behavioral addiction, the problematic social media group had markedly higher scores for both problem internet use (PRIUSS, p<0.001), problem gaming (GAS, p<0.001), and problem gambling (PGSI, p<0.001). In addition, individuals with problematic social media use were markedly more likely to score above cut-off for problem internet use (29% vs 1% in the non-problem social media group, p<0.001), problem gaming (38% vs 3%, p<0.001), and problem gambling (56% vs 5%, p<0.001). Problem gambling, problem gaming and problem internet use were closely linked to one another; the risk of meeting established criteria of problem gambling was markedly increased with an increasing GAS score (OR 1.45 [1.38–1.52], p<0.001), or an increasing PRIUSS score (OR 1.73 [1.59–1.88], p<0.001).

In the present study, using a web survey addressing the general population, problematic use of social media was significantly associated with younger age, time using instant messaging, and general mental distress, and, in unadjusted analyses, also with each of the behavioral addictions including problem internet use, problematic gaming, and problematic gambling,. No independent associations were found for gender, educational level, occupational status, or having felt a need to seek help for drug or alcohol problems. The is one of few studies hitherto examining the symptoms of problematic social media use, and its correlates, in the population.

Gender did not turn out to be an independent correlate of problematic social media use. The lack of an association with female gender, when adjusting for a number of variables, is in contrast to the findings of previous studies [ 3 , 31 ], although one comprehensive review [ 1 ] gathered a few studies demonstrating an association with male gender, or no association to gender at all. Speculations on the tendency of female over-representation often refer to what type of online activities are engaged in by the two genders. Women spend more Internet time on social media [ 30 ], but tend to use it for mainly for communication purposes and maintenance of already established real life relationships [ 23 ]. Conversely, results show that even though they too spend a lot of time on social media sites, men use the Internet more for gaming or gathering information compared to women, and when they engage in social media, they use it for forming new relationships and seeking communities with similar interests [ 23 , 62 ].

Age was inversely correlated with problematic use of social media addiction, an observation supported by previous research [ 1 , 3 , 23 ]. This unsurprising find might be derived from several factors. In contrast to the childhoods of older generations, children today are increasingly exposed to technology during their formative years, at an age that seems to be steadily decreasing [ 27 , 28 ]. They are taught in schools and at home how to handle technologies otherwise regarded as complex to introduce to older people, who rely more on traditional means of communication, as well as managing work and everyday life.

As children grow into teen age, they can experience increased peer pressure and a stronger need to achieve a sense of community, belonging and identity [ 15 ], which can evidently be satisfied by the various services of social media [ 3 ]. Furthermore, the fear of missing out has been proposed as another motivator for youths to constantly check their social media applications, adding to the need of constant online presence [ 63 ]. Although it remains to be seen whether higher age will be a protective factor for the addictive use of technology in the future, this current finding can be considered expected and in line with previous literature. However, despite the overall idea that problematic social media behavior may be more pronounced in the young, in the present sub-analysis of younger individuals only, the same correlates of problematic social media use remained statistically significant, except that within this narrower age group, age itself was no longer a significant correlate of the outcome variable.

Our data shows that educational level was not related to problematic use of social media, where all education categories, including the alternative ‘Other’, were separately tested against the first category, i.e. primary school. Andreasen and colleagues [ 23 ] demonstrated a relationship with lower level of education, but argued that it might be due to age rather than the education level itself. Despite the categorical features of the variable used here, and the weakness of a non-negligible number of respondents answering the alternative ‘other’, the results can be regarded as consistent with the findings of Andreasen and colleagues, although more research may be needed in order to fully shed light on the potential link between level of education and social media use. Moreover, our results showed no associations between problematic social media use and occupational status. To the researchers’ knowledge, this is an under-researched area, and findings may so far be hard to interpret.

Our study explored the relationship of problematic use of social media in relation to three commonly discussed non-substance-related addictive behaviors; problematic internet use, problem gaming, and problem gaming. Here, the analyses of the present paper are limited by the fact that these variables, between one another, tended to be too closely correlated for them to fit into the same logistic regression analysis. In particular, this holds true for the link between gambling and gaming, which displayed a relatively high degree of inter-correlation. However, it was evident that the outcome measure assessed in the present study was closely related to each of these three behavioral addictions.

For example, problematic use of social media was closely associated with the score of the Gaming Addiction Scale. In a similarly designed study, Karlsson and colleagues showed that there was a relationship between problematic gaming and addictive use of the Internet as a whole, measured by the GAS and PRIUSS scales [ 38 ], as in the present study. Despite not explicitly measuring use of social media, those results are somewhat comparable to the ones of this paper, since visiting social media sites is highly common while online [ 8 ]. Gaming and social networking may be rewarding to people in partly the same way; both channels share a potential to provide users with instant gratifications, a sense of purpose and identity, as well as satisfying social needs through online interaction [ 64 ]. Players can instantly message and talk with one another, as well as creating and being part of communities, motivating some players to use games primarily for social fulfillment. Also, probably, both gaming and social networking may even fill a purpose of personal or professional development, such as through a sports career in e-sports, or the professional and commercial value of marketing in both sectors. For example, the use of social media for professional development may apply to sectors as diverse as health professionals [ 65 ], or even information or disinformation in public health issues [ 66 ]. Likewise, gaming may range from a recreational habit to a professional career path, such as in e-sports [ 67 ]. Adding to the question of gender differences, research has shown that young men use social media sites to play games provided there, sometimes in excess, possibly making the boundaries between risky social media behavior and problematic gaming less obvious.

In addition, the present study indicated that problematic use of social media and problem gambling may correlate with one another. To the researchers’ knowledge, this is the first study assessing this relationship, thus making comparison with previous results somewhat challenging. There are however studies indicating a relationship between gambling and other technological addictions such as problematic mobile phone use, gaming and general Internet addiction [ 38 , 68 ]. Some scholars have noticed similarities in design between certain aspects of casinos and social media sites. Many gambling types deliver rewards at variable ratios, a psychological mechanism notorious for being the most reinforcing type of conditioning, therefore regarded as highly addictive [ 69 ]. An example of this is slot machines, which deliver rewards at irregular intervals, making gamblers unknowing of when to expect cash payback, but expecting it nonetheless. The same can be said about some aspects of technology. The buzz of the smartphone in one’s pocket could be rewarding, a Facebook notification could be a like or a reply to a comment, but is usually something irrelevant. Together with infinite scroll, a function automatically loading more content, these functions may contribute to the addictive mechanisms of social media.

With both problematic gaming and gambling being associated with problematic use of social media, this study indicates that behavioral addictions are connected. It further supports the idea that some individuals might have a general tendency, though not always willingly or voluntarily, to do things in excess and suffer as a consequence.

Although not explicitly asking whether the individual has symptoms of addiction, the questions on having felt the need of seeking help for alcohol or drug use showed no associations with problematic use of social media. These observations may be seen as somewhat surprising, as other studies [ 40 – 42 , 45 ] have reported associations between misusing these substances with regular and the problematic use of smartphones, the Internet and social media, findings supporting the general idea of an interrelationship between addictive conditions. The present study’s variables were brief, in the context of a web survey, and could therefore, at best, be considered a brief screening for substance use problems. Still, however, more research may be needed in order to highlight whether a problematic social media behavior may demonstrate an unexpectedly negative association with more traditional types of addictive behaviors, and importantly, this will require more in-depth screening or diagnostic instruments.

Even though addictions and mental distress are often seen together, it cannot be said with certainty where one issue starts and the other one ends. They may be different in their expressions, but could they share some core origin, a primal human drive for a sense of purpose and belonging? Addressing problematic social media use as a facet of mental health issues could help health care professionals treat their patients synergistically from multiple angles. For example, while an association was demonstrated between problematic social media use and poor mental health, this association does not imply causality. As a large review on Facebook-related depression studies demonstrated, the strongest predictor of depression was not the time spent on Facebook or how frequently it was checked for updates, but rather how much the user compared their life situation with the appearances and activities of others [ 70 ]. This could possibly create and strengthen any perceived social and cultural pressure to be happy and successful, bringing more shame over one’s cognitions, emotions and behaviors.

Moreover, it can be used to strengthen the screening for problematic social media habits in clinical settings where patients with mental health problems are assessed, and likewise, in case of an assessment for an exaggerated social media use, an individual’s mental health should be assessed. Thus, even while demonstrating only cross-sectional associations without further evidence of causality, there may be implications of relevance for routine clinical settings.

Five percent of our total sample had a score of 19 or higher on the Bergen Social Media Addiction Scale, indicating problematic social media use. One interesting finding was the distribution of component symptomatology of social media use. By observing what proportions of our sample answered ‘Often’ or ‘Very often’ on any item, we saw that 18.1 percent were highly preoccupied with social media. This might be affected by several factors, one being that scales measuring addictions generally go from mild to severe experiences, where sole preoccupation is rarely seen without any other symptoms or experiences in addictions. Another factor could be that social needs are increasingly fulfilled online, and just as real-life social situations, people go about their days thinking a lot about what they said to somebody or what they are planning to do with friends, without substantial complaints. Adding to this, the question was phrased as how much time one spent thinking about social media, not how much they worried about it.

The uneven proportion of social media related experiences might indicate that some components contribute more to a state of suffering and addiction than others. This is reflected in the less reported withdrawal symptoms and social media use leading to adverse consequences in real life, whereas the item describing salience was markedly more commonly reported. Such experiences are especially relevant in the context of mental health, where some symptoms emerge as more probable contributors, maintainers and consequences of mental unease. Suffering frequent withdrawal symptoms such as anxiety and irritability might increase existent mental distress. If the individual then finds these moods being alleviated through social media, the component of mood modification emerges as an important element. For individuals without manifest mental disorders, times of stress and tension can lead to escapism for the same reasons. If psychosocial needs are better met online, addiction can manifest as an overreliance on virtual interactions. The difficulty to control use, or stopping it completely, may contribute to general stress and feeling a lack of free will, as well as shame and guilt, two common features of depression. These mind states could in turn be distracted from, but also exaggerated by, using social media. Anxious people may resort to Facebook, Instagram, Snapchat or YouTube if it can provide them with more control over social situations. For example, choosing with greater freedom who to interact with, or dare to express opinions more readily, especially if their anxiety revolves around social situations. Be it depression or anxiety, symptoms might be further exacerbated should social media absorb enough time and energy to damage relationships, work or studies, a potentially serious and debilitating consequence of any addiction. Naturally, the magnitude of these consequences is likely to be smaller than those seen in severe addictions to gambling or substances.

Although there was a significant difference between the groups studied with respect to the amount of time spent communicating in instant messaging services, our results also show that the majority of those who spent more than four hours chatting did not qualify for problematic use. Naturally, this is not equal to them never experiencing distress. However, it indicates that users might well use online chats as their main channel of communication, and in that context, the terminology of ‘addiction’ may present a risk to pathologize and stigmatize common behaviors, especially when they consume a lot of time. Among its many young users, a number of benefits are reported, such as a sense of belonging, establishment of identity, learning skills, as well as improve relationships with virtual and real-world friends. Moreover, attitudes differ between technology when used excessively by children; they themselves regard it as less of a problem or an addiction for that matter, compared to their parents who more often see screen time as negative [ 3 ]. In a debate paper, Kardefeldt and co-workers argue that many behaviors can be performed in excess without being perceived as addictive for the individual. Working eight hours per day is commonplace and can come out of necessity and duty, enjoyment and a sense of purpose, rather than escapism, compulsiveness, or cravings. Professionals of arts or sports, including e-sports, may well compromise other life areas or experience distress when unable to do what they like [ 10 ], although the concept of an addictive condition may be less applicable to these situations.

Also utilizing the BSMAS, in their large study Andreassen and co-workers found that excessive use of social media was linked to symptoms of ADHD and OCD, as well as narcissistic and extraversion personality traits [ 23 , 29 ]. Even though these respondents scored higher on the social media addiction scale, it does not necessarily translate into addiction. The paths to excessive use and addiction-like behavior are thought to be different for people with these traits, with decreased executive functioning or compulsiveness leading to loss of the control that technology has on these individuals, while they might not experience cravings or withdrawal. Such potential associations also should be borne in mind when assessing whether a description of an addiction is appropriate or not.

Strengths and limitations

Most empirical studies into addictive technological behaviors rely on small and/or non-representative samples [ 25 , 71 – 73 ], often surveying students form primary school to university. The sample used in the present study was moderately sized, comprising 2002 respondents including individuals of 16 years and above. However, our sample has a skewed age distribution and is therefore not completely nationally representative, despite an overall ambition to reach representativity. Consequently, any conclusions for prevalence rates of problematic social media cannot be made from our results.

An obvious limitation of the present finding is the fact that all data were self-reported, and although using established scales for the measure of several constructs included here, the self-report of several measures means that the individual’s own perception of one’s behavior may affect the reporting. This could, for example, apply to the reporting of the number of days spent in social messaging services per day; a person with an impression of being more preoccupied than desired with these services, could possibly lead to lower her/his reporting.

Using a market survey company made it possible to disidentify respondents’ IP-addresses, while simultaneously enabling detection of duplicates. Had the same respondent filled the questionnaire more than once from different IPs, the design could not account for that. The length of the questionnaire may, however, reasonably make such an attempt unappealing.

The choice to omit some variables is motivated by initially weak hypotheses, and retrospectively discovered correlational overlap. The reason for including the demographic variables of gross monthly income and living situation is mostly that previous studies carried out by the same research department as this study have included them as well. One could argue that they needed not to be part of the questionnaire only for this reason. Seeking help for mental distress and PRIUSS scoring were found to skew the correlational data of the logistic regression analyses, which might question the choice to include them from the beginning.

One flaw of the addiction scales is that they assess symptomatology for different time frames, rendering them less intercomparable to each other. They range from the past 30 days to the past 12 months, and while PRIUSS is measuring momentaneous experience of Internet use, it is a factor not taken into consideration since it was omitted from regression analysis. The scales are validated and cross-validated across languages, justifying them as tools and comparing them with other studies using them. Naturally, comparing with results stemming from other tools is more speculative. An agreed upon research method would diminish this issue.

It is important to note that all scales are screening tools and not diagnostic instruments, meaning that the demonstrated relationships are based on scores and cutoffs of these scales. Therefore, it is not possible to draw conclusions on if, and to which degree the actual diagnoses co-occur. While this is a limitation of the study with respect to the lack of formal diagnostic information, the use of brief screening tools was based on the need to maintain a relatively brief total survey content, in the format of an online survey.

Study implications

Defined treatment strategies specifically targeting social media addiction are lacking, although extensive work by Young [ 49 ] laid a fundament for cognitive behavioral therapy for general Internet addiction. Since neither the Internet nor social media can reasonably be taken away from people, abstinence protocols such as those used for substances cannot reasonably be applied. Rather, approaches focus on restriction. Managing Internet use in general has traditionally equaled to self-blocking of various websites more prone to addiction, such as pornography or shopping sites. In a social media context, this kind of selective restriction may be hindered by the fact that potentially beneficial and dangerous services exist on the same web page. Limiting access to specific functions on Facebook, Instagram or any other platform might hopefully be enabled by the companies themselves or third parties in the near future. In fact, some appliances have already implemented regulators of use such as app-stop timers, screen time tracking, and proposals to remove the infinite scroll function as well as limiting like-buttons have been made.

Being that problematic use of social is associated with mental distress as well as with problematic gaming and problem gambling, this could motivate health care professionals meeting patients suffering from these associated disorders to also ask them about their social media habits and experiences. One implication is that more research is needed in order to establish possible causality, which cannot be concluded from the present study, but still, there may be implications for routine screening and assessment in clinical settings where any of these conditions are treated, and where other potentially addictive behaviors, or poor mental health, also may be present.

The present study demonstrated a complex interrelationship between problematic use of social media and mental distress, with time spent in instant messaging services, as well as with other behavioral addictions, but not with a history of treatment needs for substance use. Young age was also associated with problematic social media use, while no associations were observed for educational level or occupational status. Conclusions cannot be drawn for the general population as our sample was somewhat skewed in regard to age. Since the measuring tools used are for screening purposes, we cannot conclude whether any corresponding disorders are related either, but rather that higher scores on the scales are seen with one another.

To further expand the emerging field of technology-related addictions, agreed upon definitions and measurement tools, as well as more studies are needed. With longitudinal data, it will be very interesting to see how the use, abuse, or restricted use of social media will contribute to functioning and perception of the individual. Because of their early exposure and norms of technology, observing young generations as they age would be especially fascinating. Given the results of the present study, mental health and social media use will be important to detect and follow in preventive work and in clinical settings.

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Social Media Addiction in High School Students: A Cross-Sectional Study Examining Its Relationship with Sleep Quality and Psychological Problems

  • Published: 03 August 2021
  • Volume 14 , pages 2265–2283, ( 2021 )
  • Adem Sümen   ORCID: orcid.org/0000-0002-8876-400X 1 &
  • Derya Evgin 2  

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The aim of this study was to examine the relationship of social media addiction with sleep quality and psychological problems in high school students. The study is a cross-sectional, correlational type. The study was conducted with 1,274 students receiving education in a district located in the western region of Turkey. For the collection of the data, a Descriptive Information Form, the Social Media Addiction Scale for Adolescents (SMASA), the Strengths and Difficulties Questionnaire (SDQ), the Sleep Quality Scale (SQS) and the Sleep Variables Questionnaire (SVQ) were used. Among the high school students who participated in the research, 49.3% stated that they had been using social media for 1–3 years, 53.9% reported that they spent 1–3 h per day on social media, and 42.8% stated that they placed their telephone under their pillow or beside their bed while sleeping. Students’ mean scores were 16.59 ± 6.79 (range: 9–45) for the SMASA, 16.54 ± 4.27 (range: 0–40) for total difficulties, and 14.18 ± 1.56 (range: 7–21) for the SQS, while their sleep efficiency value was 97.9%. According to the research model, difficulties experienced by high school students increase their social media addiction, while they decrease prosocial behaviours. Social media addiction in high school students decreases students’ sleep efficiency (p < 0.05). It is considered important to conduct further public health studies for children and adolescents related to the risks caused by the excessive use of technology, the consequences of social media addiction, measures to protect psychological health, sleep programmes and the importance of sleep quality.

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1 Introduction

Together with the very rapid digitalization in our age, the use of social media is increasing in our country and in the world (Ersöz & Kahraman, 2020 ; Singh et al., 2020 ). According to the Digital 2021: Global Overview Report, the time spent on social media has increased 1.5 times in the last 5 years. The most widely used social networks are listed as: Facebook, YouTube, WhatsApp, FB Messenger, Instagram, WeChat, TikTok and QQ (DataReportal, 2021a ). As for Turkey, the use of social media has increased by 11.1% in the past year, and YouTube, Instagram, WhatsApp, Facebook, Twitter and FB Messenger are the most frequently used social networks (DataReportal, 2021b ). When the way of dealing with social media addiction is examined, it can be said that nowadays, social media addiction has ceased to be an ordinary problem and become a disease associated with a global epidemic. People all over the world can show excessive interest in social media and spend a great deal of time using social media. For this reason, social media has a negative effect on the lives of millions of people in the world (Andreassen, 2015 ; Singh et al., 2020 ).

In a study by Drahošová and Balco ( 2017 ), in which they investigated the advantages and disadvantages of social media use, 97.7% of participants stated that the advantages of using social media were communication and the exchange of information, while 72.2% stated that the biggest disadvantage was internet addiction. It is known that among users, especially the younger age group faces the risk of addiction. Although social media is regarded as a new area of socialization and that this situation is an advantage (Savcı & Aysan, 2017 ), it is also reported that social media has a negative effect on interpersonal relationships (Çalışır, 2015 ), psychological health (Chen et al., 2020 ) and private life (Acılar & Mersin, 2015 ), increases levels of depression (Haand & Shuwang, 2020 ), and leads to social media addiction. Indeed, it has been determined that in the case of adolescent users, excessive levels of use are associated with paranoid thoughts, phobic anxiety and feelings of anger and hostility (Bilgin, 2018 ). Moreover, an increase in periods of social media use can cause a reduction in sleep quality (Eroğlu & Yıldırım, 2017 ). Poor sleep quality can lead to daytime sleepiness in students and to negative effects on their performance, school achievement, activities and energy (Güneş et al., 2018 ).

Due to the coronavirus pandemic, the switch to the distance education process was made in line with the restrictions implemented for protecting public health. The extension of periods spent at home by adolescents has led to long periods of exposure to screens, a restriction of outdoor activities, a reduction in peer interactions, unhealthy sleep patterns, and increases in stress and anxiety levels (Liu et al., 2021 ; Wang et al., 2020 ). Based on this, the aim of this study is to examine the relationship of social media addiction with sleep quality and psychological problems in high school students.

2.1 Study Design

This is a cross-sectional, correlational type of research. In this study, which was conducted in order to determine the relationship of social media addiction with sleep quality and psychological problems in high school students, a path analysis study was made in line with the examined literature and the aim, and the theoretical model is shown in Fig.  1 . The model consists of four hypotheses, and the correlations between the variables in these hypotheses are included in the model.

H 1 : Difficulties experienced by high school students (emotional problems, conduct problems, attention deficit and hyperactivity, and peer problems) increase social media addiction.

H 2 : Prosocial behaviours in high school students decrease social media addiction.

H 3 : Social media addiction in high school students increases poor sleep quality.

H 4 : Social media addiction in high school students decreases sleep efficiency.

figure 1

Path diagram of the research model. SMASA: Social Media Addiction Scale for Adolescents, SQS: Sleep Quality Scale

2.2 Participants

The study was conducted in 15 high schools affiliated to a District National Education Directorate in the south of Turkey. A total of 4,602 students are registered at these high schools in the 2020–2021 academic year. Since education at the schools is carried out in the form of distance education within the scope of the COVID-19 measures, the research was carried out online via the District National Education Directorate and the school principals. The study was completed between 01–30 December 2020 with a total of 1,274 people with the aim of reaching all students. Students registered at high school and volunteering to participate in the study were included in the research. A 99% error rate and 3.07% confidence interval originating from the sample number of the research were found.

2.3 Data Collection Tools

A Descriptive Information Form prepared by the researchers by examining the literature, the Social Media Addiction Scale for Adolescents, the Strengths and Difficulties Questionnaire, the Sleep Quality Scale, and the Sleep Variables Questionnaire were used for data collection.

Descriptive Information Form

This was prepared in line with the literature, and consists of questions related to adolescents’ socio-demographic characteristics, school achievement, family, friend relationships, sleep status, and extent of using social media. School achievement and relationship levels were classified as “good”, “average” or “poor” depending on the students’ own statements.

Social Media Addiction Scale for Adolescents (SMASA)

This scale was developed by Özgenel et al. ( 2019 ) with the aim of determining adolescents’ levels of social media addiction. The scale consists of a single factor and includes nine items. The highest score that can be obtained from the five-point Likert-type scale is 45, while the lowest score is 9. It can be said that adolescents’ social media addiction is greater as scores obtained in the scale increase, while as scores decrease, their level of addiction is lower. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.904. In this study, however, the Cronbach alpha value was found to be 0.880.

Strengths and Difficulties Questionnaire (SDQ)

Developed by Goodman ( 1997 ), this scale is extensively used all over the world to examine children’s and adolescents’ psychological and behavioural problems. The scale was adapted to Turkish by Güvenir et al. ( 2008 ). Consisting of a total of 25 questions, the scale is scored with a three-point Likert-type rating, and the questions are scored as “0”, “1” and “2” according to their degree of accuracy. The scale includes subscales of emotional problems, conduct problems, attention deficit and hyperactivity, peer problems, and prosocial behaviours, each containing five questions. Although each subscale can be evaluated in itself, the total of the first four subscales gives a total difficulty score. While high scores for prosocial behaviours reflect an individual’s strengths in the social domain, high scores in the other four domains indicate that the problem areas are severe. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.73, while in this study, the Cronbach alpha value was found to be 0.776.

Sleep Quality Scale and Sleep Variables Questionnaire (SQS-SVQ)

This scale was developed by Meijer and van den Wittenboer ( 2004 ), and the Turkish validity and reliability study was carried out by Önder et al. ( 2016 ). Seven scale items that measure sleep quality and eight questionnaire items that identify parental control, total sleep time, midpoint of sleep, and sleep efficiency are included in the SQS-SVQ. Each of the SQS items have three categories scored from 1 to 3. Scores that can be obtained from the scale range between 7 and 21. A high score obtained from the scale indicates poor sleep quality, while a low score indicates good sleep quality. Among the SVQ items, however, only sleep efficiency was calculated and used. The Cronbach alpha internal consistency reliability coefficient of the scale is 0.72. In this study, however, the Cronbach alpha value was calculated as 0.714.

2.4 Data Collection

The data were collected by using an online web-based questionnaire via Google Forms. The questionnaire was sent to the students through social media networks via the District National Education Directorate and the school principals. Before beginning the study, the study aim and method were explained to the students and their families, and it was stated that the data would be used only for scientific purposes, that the data would be kept confidential, that the study would be conducted based on the principle of voluntariness, and that participants were free to take part in the research or not. After the students who agreed to take part in the study had confirmed that they were volunteers in an electronic environment, they began to reply to the questions. It took an average of 15–20 min to respond to the questionnaires. A total of 1,366 students filled in the form. When the forms were examined after the study, 92 forms were not evaluated due to missing data. Therefore, the data collection process was completed with 1,274 students.

2.5 Data Evaluation

The statistical analyses of the data were made using the SPSS Statistics Base V 23 version of Statistical Package for the Social Sciences and AMOS 21.0 software. For evaluating the data of the study, descriptive statistical methods (frequency, percentage, mean and standard deviation) were used; to test the differences between groups, t-test for independent variables and one-way variance analysis were performed; for comparisons between groups, the post-hoc Bonferroni and Tukey tests for multiple comparisons were utilised. In the research, the path analysis method was applied to test the hypotheses of the model created to determine the relationship of social media addiction with psychological problems and sleep quality. The results were evaluated at a 95% confidence interval and at p < 0.05, p < 0.01 and p < 0.001 significance levels.

2.6 Ethical Aspect of the Research

To be able to conduct the research, institutional permission was obtained from Antalya Provincial Directorate of Education (date: 25/09.2020, No: E.13536854), while ethical approval was obtained from Akdeniz University Clinical Research Ethics Committee (date: 19/02/2020, No: KAEK-174). Meetings were held with school principals of all the schools, and the research aim, content and method were explained to them. Participants’ consent was obtained by making an announcement about the study on the first page of the online link of the data collection tools.

Among the high school students participating in the research, 70.0% were girls, and their average age was 15.36 ± 1.22. Approximately half of the students were studying in first grade (45.4%), while over half of them (61.9%) stated that their school achievement level was average. The majority of students reported that they had good relationships with their mothers (85.2%), fathers (77.1%), siblings (72.2%) and friends (77.5%). It was revealed that 75.1% of students decided when to go to bed themselves, 65.6% did not turn off their telephones while sleeping, 44.6% kept their telephones away from the bed, and 42.8% placed their telephones under their pillow or beside their bed. The majority of students stated that they had been using social media for 1–3 years (49.3%), and that they spent 1–3 h per day on social media (53.9%), while 35.9% checked their social media as soon as a notification came. 10.3% of students considered themselves to be social media addicts, while 72.7% believed that society was addicted to social media (Table 1 ).

The high school students’ mean SMASA score was determined to be 16.59 ± 6.79. For the SDQ, their mean score for total difficulties was calculated as 16.54 ± 4.27. Among the SDQ subscales, the highest mean score was for prosocial behaviours with 7.94 ± 1.88, while the lowest was for conduct problems with 2.23 ± 1.49. The total SQS mean score was calculated as 14.18 ± 1.56, while the sleep efficiency value was calculated as 97.9% (Fig.  2 ).

figure 2

Participants’ SMASA, SQS-SVQ and SDQ total and subscale mean scores (n: 1274)

Mean SMASA scores of female students (p < 0.001), students with poor school achievement (p < 0.001), students who had poor relationships with their mothers (p < 0.001), fathers (p < 0.001), siblings (p < 0.001) and friends (p < 0.05), whose parents decided on their bedtime (p < 0.05), who did not turn off their telephones while sleeping (p < 0.001), who had been using social media for more than seven years (p < 0.001), who spent more than seven hours on social media per day (p < 0.001), who checked their social media notifications at every spare moment (p < 0.001), and who considered themselves (p < 0.001) and society (p < 0.001) to be social media addicts were found to be higher. Female students (p < 0.05), students who had poor relationships with their mothers (p < 0.01) and siblings (p < 0.05), and those who did not turn off their telephones while sleeping (p < 0.01) were determined to have higher mean SQS scores. It was revealed that female students (p < 0.001), students with poor school achievement (p < 0.001), students who had poor relationships with their mothers (p < 0.001), fathers (p < 0.001), siblings (p < 0.001) and friends (p < 0.001), who had used social media for more than seven years (p < 0.005), who spent more than seven hours on social media per day (p < 0.001), who checked their social media notifications at every spare moment (p < 0.001), and who considered themselves (p < 0.001) and society (p < 0.001) to be social media addicts had higher mean SDQ scores (Table 1 ).

In the study, a positive correlation of students’ mean SMASA scores with SDQ-conduct problems, SDQ-attention deficit, SDQ-emotional problems, SDQ-peer problems, SDQ-total difficulties index and total SQS mean scores was found, while a negative correlation was found with SDQ-prosocial behaviours and SVQ-sleep efficiency mean scores (p < 0.01) (Table 2 ).

The standardised estimates related to the research model drawn within the scope of the study are given in Table 3 . According to the research model, difficulties experienced by high school students have a positive effect on social media addiction (β = 0.293), while prosocial behaviours have a negative effect on social media addiction (β = -0.159) (p < 0.05). Social media addiction in high school students has a negative effect on sleep efficiency (β = -0.094, p < 0.05). As a result of the path analysis, it was determined that the goodness-of-fit indices of the model had acceptable values and that model-data fit was achieved (İlhan & Çetin, 2014 ; Kline, 2011 ). Accordingly, hypotheses H 1 , H 2 ve H 4 relating to the model were accepted, while hypothesis H 3 was not accepted (Table 3 ).

4 Discussion

Social media use by individuals has steadily increased in recent years (Dong et al., 2020 ; Fernandes et al., 2020 ; Kashif & Aziz-Ur-Rehman, 2020 ; Lemenager et al., 2021 ). Especially young people increasingly use social media and the internet, which is an easily and rapidly accessible means of mass communication, frequently for academic and other purposes. These tools are not merely a source of information, their use is also sought for other purposes such as social interaction, games and entertainment (Singh & Barmola, 2015 ). The decrease seen in individuals’ interaction in social life and the increase in the time they spend at home due to the COVID-19 pandemic have increased the use of online communication tools (Benke et al., 2020 ; King et al., 2020 ; Oliviero et al., 2021 ). The steady increase in internet and social media addiction among young people in recent years has already been reported (Fernandes et al., 2020 ; Kashif & Aziz-Ur-Rehman, 2020 ; Orben et al., 2020 ; Scott et al., 2019 ). However, in this study, it was seen that high school students’ mean social media addiction scores (16.59 ± 6.79) were below average.

In the Addiction Prevention Training Programme of Turkey implemented by Green Crescent ( 2017 ), certain criteria were defined concerning the case of whether or not high school students’ are addicted to social media. Accordingly, it is stated that if social media is the first choice that comes to mind in cases of boredom, if it takes precedence over real life, if it leads to disruption of daily life and negligence of responsibilities, if it takes up an excessive amount of time and creates anxiety when it cannot be accessed, if the need is felt to constantly share things, then adolescents may be addicted to social media. The majority of students included in the scope of the study stated that they had been using social media for 1–3 years (49.3%), and that they spent 1–3 h on social media per day (53.9%), while 35.9% checked their social media whenever a notification came. Therefore, it can be said that students taking part in the study were at risk of social media use disorder. However, another important finding of the study is that while one in ten students regarded themselves as social media addicts, around three-quarters of them considered that society was addicted to social media. This situation in fact shows that the students had awareness regarding social media addiction, but that they did not accept addiction for themselves. In a study conducted by Fernandes et al. ( 2020 ) on adolescents in India, Malaysia, Mexico and Great Britain, it was found that during the pandemic, periods of social media use, playing online games, and watching video content increased significantly compared to before the pandemic. In other conducted studies, it is also seen that the period spent on social media has increased during the pandemic compared to before the pandemic (71.4%) (Lemenager et al., 2021 ), and that people frequently spend their free time on social media during the pandemic (67%) (Kashif & Aziz-Ur-Rehman, 2020 ).

In the study, it was revealed that social media addiction scores were higher in students who had poor relationships with their mothers, fathers, siblings and friends. Social media prevents adolescents from forming close personal relationships with their families and immediate environment. Social media use disorder also causes weak family and friend relationships in adolescents (Moreno & Uhls, 2019 ). Numerous problems emerge due to the misuse of social media. In the study, it was determined that mean SQS scores were higher in students who had poor relationships with their mothers and siblings, and those who did not switch off their telephones while sleeping. It has been found that adolescents with high levels of problematic internet use and of social media use suffer from depression, loneliness, lower sleep quality and high anxiety levels (Bányai et al., 2017 ; Alonzo et al., 2020 ; Fernandes et al., 2020 ; Orben et al., 2020 ). In some studies, a statistically significant correlation between social media use and adolescent sleep patterns, especially delayed sleep onset, has been determined (Alimoradi et al., 2019 ; Gradisar et al., 2013 ; Scott et al., 2019 ). In the study, students’ total sleep quality mean score (14.18 ± 1.56) was revealed to be poor, and their sleep efficiency value was calculated as 97.9%. This shows that the adolescents included in the sample were unable to sleep efficiently and that their sleep quality was low. This situation may be the result of changes in sleep habits of adolescents due to remaining at home because of the coronavirus pandemic. Similarly, in a study carried out in Italy, it was determined that as a result of the isolation measures taken against the coronavirus, a big delay in children’ sleeping/waking schedules and an increase in sleep disorders occurred in all age groups (Oliviero et al., 2021 ). In another study, it was revealed that problems occurred in adolescents during the pandemic, such as delay in falling asleep, reduction in length of sleep, respiratory impairment during sleep, and sleepiness during the day, and that sleep routines were disrupted (Becker & Gregory, 2020 ). The problem of lack of sleep is very common in adolescents, and is an important public health problem that needs intervention in several aspects, such as mental health, obesity and academic performance (Owens, 2014 ; Sampasa-Kanyinga et al., 2020 ).

In the study, the high school students’ mean total difficulties score in the SDQ was calculated as medium level (16.54 ± 4.27). Among the SDQ subscales, the highest mean score was found to be for prosocial behaviours, while the lowest was for conduct problems. The high level of prosocial behaviours and low level of conduct problems in the sample group indicates that the research group were able to cope with difficulties. A negative correlation was found between SDQ-prosocial behaviours and SVQ-sleep efficiency mean scores in the study. This situation can be interpreted to say that social media use can lead to lack of sleep in students, and that students’ prosocial behaviours can decrease. Pandemic adolescents showed higher levels of other problems and a more problematic social media usage than peers before the pandemic (Muzi et al., 2021 ). Moreover, significant increases are seen in individuals’ rates of problematic internet use and of social media use due to the pandemic, and it is stated that this situation creates negative effects in terms of individuals’ psychological health (Baltacı et al., 2021 ; Oliviero et al., 2021 ). In a qualitative study conducted by Baltacı et al., ( 2020 ), it was stated that students experienced difficulties in controlling their internet use during the pandemic, and that since they were unable to control this, they experienced negative emotions and regarded themselves as internet addicts due to this situation.

Evidence suggests that problematic use of gaming, the internet, and social media among adolescents is on the rise, affecting multiple psycho-emotional domains. Moreover, excessive use of digital activities and smartphones may result in multiple mental and physical problems, such as behavioural addiction, cognitive impairment, and emotional distress (Ophir et al., 2020 ). It was found that as students’ mean social media scores increased, their mean scores for attention deficit, conduct problems, emotional problems, peer problems and total difficulties index also increased. In addition, it has been determined that the difficulties experienced by high school students (emotional problems, conduct problems, attention deficit and hyperactivity, and peer problems) increase social media addiction (H 1 ). It is emphasized that spending a long time on the Internet increases the possibility of exposure to risks and pathological tendencies, and that the time spent using social media is harmful to mental health (Alonzo et al., 2020 ; Coyne et al., 2020 ; Stockdale & Coyne, 2020 ; Twigg et al., 2020 ). It is known that during the pandemic, missing the daily routines that school brings and absence of time spent with peers causes adolescents to experience a great number of problems. These problems can be listed as increase in monotonous time spent at home, disrupted sleep habits, increased exposure to screens, intensive internet use, increased eating habits, decreased physical activity, increased attention and concentration problems, loss of academic achievement due to reduced motivation, increased domestic conflicts, inability to cope with negative emotions such as aggression, boredom, anger and anxiety, increased emotional activity, and deterioration of emotion regulation skills (Ghosh et al., 2020 ; Lee, 2020 ; Oliviero et al., 2021 ). In support of the literature, in this study, too, it was seen that especially during these difficult times that we have been going through, the high school students’ social relationships were weakened, their school achievement decreased, the frequency and length of their social media use increased, and there was an increase in the psychological problems and social media addiction that they experienced. This situation reveals that adolescents are at risk biopsychosocially in terms of healthy development and acquiring identity, and with regard to other risks (cyber violence, obesity, loneliness, depression, anxiety, etc.) that the digital environment will bring (Orben et al., 2020 ). Especially the greater amount of time that adolescents spend using social media has increased the negative effects on adolescents’ general health and wellbeing, including sleep (Dong et al., 2020 ).

Another important result of the study is the finding that prosocial behaviors reduce social media addiction in high school students (H 2 ). Some studies showed that there were short comings in social skills associated with social interactions and internet and social media addiction (Chua et al., 2020 ; Dalvi-Esfahani et al., 2021 ). While the effective use of the internet creates an opportunity for the adolescent, its excessive use may negatively affect the adolescent's physical, psychological, social and cognitive development (Hou et al., 2019 ). A study found that depression, bullying, loneliness, and sleep quality are among the most common health problems that arise from social media use (Royal Society for Public Health, 2020 ). Kurulan araştırma modelinde, sosyal medya bağımlılığının lise öğrencilerinde kötü uyku kalitesini etkilemediği (H 3 ) fakat uyku verimliliğini (H 4 ) azalttığı sonucuna varılmıştır. There are studies showing that social media addiction is positively associated with poor sleep quality (Alfaya et al., 2021 ; Ho, 2021 ; Tandon et al., 2020 ; Wong et al., 2020 ). According to Garett et al. ( 2018 ), using social media for longer periods of time and spending more time with social media causes the quality of sleep of users to decrease. Wong et al. ( 2020 ) determined that both the severity of internet gaming disorder and social media addiction were positively related to psychological distress and sleep disorder. In a study on social media use, sleep quality, and well-being in 467 adolescents, it was found that social media use was associated with poor sleep, anxiety, depression, and low self-esteem. Poor sleep was most strongly associated with nighttime social media use (Woods & Scott, 2016 ). It is important for the development of a healthy generation to educate adolescents about conscious social media and smart phone use and to emphasize the importance of sleep habits (Gıca, 2020 ).

5 Conclusions

According to the results obtained in the study, the students’ scores for social media addiction and psychological problems were found to be below average, while their sleep quality scores were negatively above. Although it is known that sleep is very important for adolescent health, it was determined that increased social media addiction in the students in the sample group increased the potential for the emergence of health and sleep problems. It should be borne in mind that the social distancing, recommendations to stay at home, and distance education implemented due to the pandemic can lead to greater flexibility in sleeping and waking times, and can cause an increase in the use of technology for long periods and in social media addiction. It was seen that social media addiction in students was positively correlated with conduct and emotional problems, attention deficit/hyperactivity, peer problems and poor sleep quality, and negatively correlated with prosocial behaviours and sleep efficiency. Based on this, school health nurses should plan and implement appropriate intervention methods in collaboration with other healthcare personnel (psychologists, school counsellors, social workers, etc.). Enabling high school students’ access to the correct information sources, open and transparent sharing of information, planning daily routines at home such as meals, sleep and homework, increasing physical activities, expanding intelligent internet use that will support personal and social development, enabling adolescents’ return to the peer and school environment by creating safe school environments in as short a time as possible, creating alternative means and support groups for peer interaction by reducing isolation and loneliness, and appropriate therapeutic interventions such as sleep education and interventions can be listed among these measures and precautions.

Data Availability

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

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Sümen, A., Evgin, D. Social Media Addiction in High School Students: A Cross-Sectional Study Examining Its Relationship with Sleep Quality and Psychological Problems. Child Ind Res 14 , 2265–2283 (2021). https://doi.org/10.1007/s12187-021-09838-9

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Accepted : 01 July 2021

Published : 03 August 2021

Issue Date : December 2021

DOI : https://doi.org/10.1007/s12187-021-09838-9

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Social media use and depression in adolescents: a scoping review

There have been increases in adolescent depression and suicidal behaviour over the last two decades that coincide with the advent of social media (SM) (platforms that allow communication via digital media), which is widely used among adolescents. This scoping review examined the bi-directional association between the use of SM, specifically social networking sites (SNS), and depression and suicidality among adolescents. The studies reviewed yielded four main themes in SM use through thematic analysis: quantity of SM use, quality of SM use, social aspects associated with SM use, and disclosure of mental health symptoms. Research in this field would benefit from use of longitudinal designs, objective and timely measures of SM use, research on the mechanisms of the association between SM use and depression and suicidality, and research in clinical populations to inform clinical practice.


Over the past several decades, adolescent depression and suicidal behaviours have increased considerably. In the USA, depression diagnoses among youth increased from 8.7% in 2005 to 11.3% in 2014 ( Mojtabai, Olfson, & Han, 2016 ). Additionally, suicide is the second leading cause of death among youth between the ages of 10 and 34 ( Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, 2017 ), with a 47.5% increase since 2000 ( Miron, Yu, Wilf-Miron, & Kohane, 2019 ). One suggested cause for this rise in adolescent depression and suicide is the advent of social media (SM) ( McCrae, Gettings, & Purssell, 2017 ; Twenge, Joiner, Rogers, & Martin, 2018 ).

The term ‘social media’ describes types of media that involve digital platforms and interactive participation. SM includes forms such as email, text, blogs, message boards, connection sites (online dating), games and entertainment, apps, and social networking sites (SNS) ( Manning, 2014 ). Over the past decade, SNS platforms designed to help people communicate and share information online have become ubiquitous. Among youth, 97% of all adolescents between the ages of 13 and 17 use at least one of the following seven SNS platforms: YouTube (85% of adolescents), Instagram (72%), Snapchat (69%), Facebook (51%), Twitter (32%), Tumblr (9%) or Reddit (7%) ( Pew Research Center, 2018a ).

Concerns have arisen around the effects of SM on adolescents’ mental health, due to SM’s association with decreased face-to-face interpersonal interactions ( Baym, 2010 ; Kraut et al., 1998 ; Nie, Hillygus, & Erbring, 2002 ; Robinson, Kestnbaum, Neustadtl, & Alvarez, 2002 ), addiction-like behaviours ( Anderson, Steen, & Stavropoulos, 2017 ), online bullying ( Kowalski, Limber, & Agatston, 2012 ), social pressure through increased social comparisons ( Guernsey, 2014 ), and contagion effect through increased exposure to suicide stories on SM ( Bell, 2014 ).

Conversely, others have described potential benefits of SM use in adolescents such as feelings of greater connection to friends and interactions with more diverse groups of people who can provide support ( Pew Research Center, 2018b ). In fact, higher internet use has been associated with positive social well-being, higher use of communication tools, and increased face-to-face conversations and social contacts in college students ( Baym, Zhang, & Lin, 2004 ; Kraut et al., 2002 ; Wang & Wellman, 2010 ). These findings suggest that internet use, including SM, may provide opportunities for social connection and access to information ( Reid Chassiakos et al., 2016 ).

Recent systematic reviews examining the association between online technologies and depression have found a ‘general correlation’ between SM use and depression in adolescents, but with conflicting findings in some domains (e.g. the association between time spent on SM and mental health problems), overall limited quality of the evidence ( Keles, McCrae, & Grealish, 2019 ), and a relative absence of studies designed to show causal effects ( Best, Manktelow, & Taylor, 2014 ). The scope of search in these reviews is broader in topic, including online technologies other than SM ( Best et al., 2014 ) or focussed on a select number of studies in order to meet the requirements of a systematic review ( Keles et al., 2019 ). With this scoping review, we aim to expand the inclusion of studies with a range of designs, while narrowing the scope of the topic of SM to those studies that specifically included SNS use. Additionally, we aim to expand the understanding and potential research gaps on the bi-directional association between SM and depression and suicidal behaviours in adolescents, including studies that consider SM use as a predictor as well as an outcome. A better understanding of this relationship can inform interventions and screenings related to SM use in clinical settings.

This scoping review was initiated by a research team including 3 mental health professionals with clinical expertise in treating depression and suicidality in adolescents. We followed the framework suggested by Arksey and O’Malley (2005) for scoping reviews. The review included five steps: (1) identifying the research question; (2) identifying relevant studies; (3) study selection; (4) charting the data; and (5) collating, summarizing and reporting the results.

Research question

The review was guided by the question: What is known from the existing literature about the association between depression and suicidality and use of SNS among adolescents? Given that much of the literature used SM and SNS interchangeably, this review used the term ‘social media’ or ‘SM’ when it was difficult to discern if the authors were referring exclusively to SNS.

Data sources and search strategy

The team conceived the research question through a series of discussions, and the first author (CV) consulted an informationist to identify the appropriate search terms and databases. A search of the database PsychINFO limited to peer-reviewed articles was conducted on 5 June 2019 (see Table 1 for search strategy). No additional methods were identified through other sources. The search was broad to include articles measuring depression as an outcome variable, and as a co-variate or independent variable. There was no restriction on the type of study design included, and English and Spanish language articles were included in the search. Articles were organized using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia).

Search strategy.

Eligibility criteria

(1) The study examined SM (versus internet use in general) and made specific mention of SNS; (2) participants were between the ages of 10 and 18. If adults were included, the majority of the study population was between 10–18 years of age, or the mean participant age was 18 or younger; (3) the study examined the association between SM use and depression and/or suicidality; (4) the study included at least one measure of depression; and (5) if the focus of the study was on SM addiction or cyberbullying, it included mention and a measure of depressive symptoms. We did not include articles in which: (1) the study primarily focussed on media use other than SM, or that did not specifically mention inclusion of SNS (e.g. studies that focussed only on TV, video game, smartphone use, blogging, email); (2) included primarily adult population; (3) was not an original study, but a case report, review, commentary, erratum, or letter to the editor; (4) focussed on addiction and cyberbullying exclusively without a depression measure; and (5) the method used was content analysis of SM posts without specification of the population age range.

Title and abstract relevance screening

The search yielded 728 articles of which six duplicates were removed. One author (CV) screened the remainder of the articles by title and abstract and a second author (TL) reviewed every 25th article for agreement. All authors screened full-text articles and extracted data from those that met the inclusion criteria. The authors met over the course of the full-text review process to resolve conflicts and maintain consistency among the authors themselves and with the research question. Of the total number of studies included for full-text review, 505 articles were excluded. Out of the 223 full-text studies assessed for eligibility, 175 were excluded. A total of 42 articles were eligible for review (see Figure 1 : PRISMA flow chart for details). A form was developed to extract the characteristics of each study that included author and year of publication, objectives of the study, study method, country where the study was conducted, depression scale used, number of participants, participant age, and results (see Table 2 for details).

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PRISMA flow chart of data selection process.

Data charting form including author and year of publication, objectives of the study, method used, country where the study was conducted, depression scale used, number of participants, participant age, results and main social media focus.

AIU = Addictive internet Use; BIU = Borderline Addictive Internet Use; BSMAS = Bergen Social Media Addiction Scale; BIU = Borderline addictive internet use; CBP = Cyberbullying Perpetration; CERM = Cuestionario de Experiencias Relacionadas con el móvil (Questionnaire of Experiences Related to the cellphone); DIB = Dysfunctional Internet Behaviour; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders (4th edition, Text Revision); FOMO = Fear of Missing Out; HVSM = Highly Visual Social Media; SNI = Intensity of social network use; IA = Internet Addiction; IAB = Internet Addictive Behaviour; OSNA = Online social networking addiction; PSMU = Problematic Social Media Use; RADS-2 = Reynolds Adolescent Depression Scale - Version 2; SITBs = self-injurious thoughts and behaviours; SNS = social networking sites.

Data summary and synthesis

After reviewing the table, each study was labelled according to the main focus of research related to SM, based on the objectives, variables used, and results of the study. The topics were classified into nine different categories based on the main SM focus of the article; categories were discussed and reviewed by two authors (TL and CV) ( Table 2 ). All authors then discussed the categories and grouped them into four main themes of studies looking at SM and depression in adolescents.

A total of 42 studies published between 2011 and 2019 met the inclusion criteria. Of the studies included, 16 were conducted in European Countries, 14 in the USA, 5 in Asia, 3 in Canada, 2 in Australia, and 2 in Latin American Countries. The number of participants per study ranged from 23 in a qualitative study (94 in the smallest quantitative study) to 118,545 participants in the largest study ( Table 2 ).

The studies reviewed were grouped into four themes with nine categories according to the main focus of the research. The themes and categories were: (1) quantity of SNS use: effects of the frequency of SM use and problematic SM use (or evidence of addictive engagement with SM); (2) quality of SM use: characteristics of SNS use and social comparisons; (3) social aspects of SM use: cyberbullying, social support, and parental involvement; and (4) disclosure of mental health symptoms: online disclosure and prediction of symptoms and suicide contagion effect ( Figure 2 ).

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Number of studies by theme (quantity, quality, social and disclosure) and time period (2011–2012, 2013–2014, 2015–2016 and 2017–2018).

Quantity of SM use

The majority of studies ( n = 24) examined quantity of SM use by measuring either frequency or time spent on SM ( n = 17), or problematic or addictive engagement with SM ( n = 7).

Frequency of use

The majority of studies found a positive correlation between time spent on SNS and higher levels of The majority of studies found a positive correlation between time spent on SNS and higher levels of depression ( Akkın Gürbüz, Demir, Gökalp Özcan, Kadak, & Poyraz, 2017 ; Marengo, Longobardi, Fabris & Settanni, 2018 ; Pantic et al., 2012 ; Twenge et al., 2018 ; Woods & Scott, 2016 ). Higher frequency of SM use (≥2 h a day) was also found to be positively associated with suicidal ideation ( Sampasa-Kanyinga & Lewis, 2015 ) and attempts ( Sampasa-Kanyinga & Hamilton, 2015 ), in addition to deficits in self-regulation ( Lee, Ho, & Lwin, 2017 ). Factors such as the number of SM accounts and the frequency of checking SM ( Barry, Sidoti, Briggs, Reiter, & Lindsey, 2017 ) were associated with a variety of symptoms, including depression.

A study ( Oberst, Wegmann, Stodt, Brand, & Chamarro, 2017 ) examining SM use as an outcome suggested that depression may affect SM use both directly, and indirectly, mediated by the Fear of Missing Out (or the apprehension of missing rewarding experiences that others might be enjoying) ( Przybylski, Murayama, DeHaan, & Gladwell, 2013 ). Adolescents with depression were also found to have more difficulty regulating their SM use ( Lee et al., 2017 ).

Longitudinal studies suggested a reciprocal relationship between quantity of SM use and depression. Frison and Eggermont (2017) found that frequency of Instagram browsing at baseline predicted depressed mood six months later and depressed mood at baseline predicted later frequency of photo posting. Additionally, heavy use (>4 h per day) of the internet to communicate (including social networking) and play games (gaming) predicted depressive symptoms a year later ( Romer, Bagdasarov, & More, 2013 ). Further, depressive symptoms predicted increased internet use and decreased participation in non-screen activities (e.g. sports). Finally, Salmela-Aro, Upadyaya, Hakkarainen, Lonka, and Alho (2017) found that school burnout increased the risk for later excessive internet use and depressive symptoms. Conversely, Houghton et al. (2018) found small, positive bi-directional associations between depressive symptoms and screen use 1 year later, but their final model did not support a longitudinal association.

Yet, not all studies found a positive association between frequency of use and depressed mood. While Blomfield-Neira and Barber (2014) reported a link between adolescents having a SM profile and depressed mood, they found no correlation between SM frequency of use and depressed mood. Rather, investment in SM (a measure of how important SM is to an adolescent) was linked to poorer adjustment, lower self-esteem and depressed mood. Moderate SM use (a stable trend in the time spent on SM during adolescence and into early adulthood that did not interfere with functioning) was associated with better emotional self-regulation ( Coyne, Padilla-Walker, Holmgren, & Stockdale, 2018 ) and healthier development, especially when used to acquire information ( Romer et al., 2013 ). Finally, Rodriguez Puentes and Parra (2014) found a positive association between SM and externalizing behaviours, but no significant association between SM use and depression.

Additionally, age moderated the effects of frequency of use on depression. For example, in one study, older adolescents with higher SM use had higher ‘offline’ social competence, while younger adolescents with higher SM use had more internalizing problems and diminished academics and activities ( Tsitsika, Janikian, et al., 2014 ).

Problematic SM use

Seven studies explored problematic use or engagement with SM or the internet in an addictive manner (a dysfunctional pattern of behaviour similar to that of impulse control disorders, which causes distress and/or functional impairment) ( Critselis et al., 2014 ).

An addiction-like pattern of internet use (including SM use) was associated with emotional maladjustment ( Critselis et al., 2014 ), internalizing and externalizing symptoms ( Tsitsika, Tzavela, et al., 2014 ), and depressive mood ( Van Rooij, Ferguson, Van de Mheen, & Schoenmakers, 2017 ). Further, depressive mood predicted problematic internet use (both SM and gaming, independently) ( Kırcaburun et al., 2018 ; Van Rooij et al., 2017 ).

Bányai et al. (2017) assessed the prevalence of problematic internet use conducting a latent profile analysis to describe classes of users and found that the class described as ‘at risk’ for problematic internet and SM use tended to be female, use the internet for longer periods, and have lower self-esteem and more depressive symptoms. Yet, while Banjanin, Banjanin, Dimitrijevic, and Pantic (2015) found a positive correlation between internet addiction and depression in high school students (particularly for females), no such correlation was found with engagement with SM (measured by number of pictures posted).

Several studies examined mediators of the association of problematic SM use and depression. Wang et al. (2018) found that rumination mediated the relationship between SM addiction and adolescent depression, with a stronger effect among adolescents with low self-esteem. Additionally, insomnia partially mediated the association between SM addiction and depressive symptoms ( Li et al., 2017 ). Woods and Scott (2016) found that nighttime-specific SM use (in addition to overall use and emotional investment in SM) was associated with poorer sleep quality, anxiety and depressive symptoms. Finally, problematic SM use mediated the association between depressive symptoms and cyberbullying perpetration ( Kırcaburun et al., 2018 ).

Quality of SNS use

In addition to the frequency of adolescents’ engagement with SM, another focus of research has been the ways in which adolescents engage with SM. Of the studies selected, four primarily examined engagement styles with SM and two specifically examined social comparisons with other users.

Characteristics of SM use

The ways in which adolescents use SM may also have an effect on depression. One study ( Frison & Eggermont, 2016 ) characterized SM use as public (e.g. updating one’s status on a profile) vs private (e.g. messaging), and active (e.g. interacting with others on SM) vs passive (e.g. browsing on SM) and found that public Facebook use was associated with adolescent depressed mood. Among girls, passive use of Facebook yielded negative outcomes such as depressed mood, while active use yielded positive outcomes such as perceived social support ( Frison & Eggermont, 2016 ). A longitudinal study of Flemish adolescents by the same group ( Frison & Eggermont, 2017 ) found passive SM use at baseline to predict depressive symptoms 7 months later, while depressive symptoms predicted active use of SM. Interestingly, there was no association between depressive symptoms and Facebook use (frequency of use, network size, self-presentation, and peer interaction) in a study conducted among healthy adolescents ( Morin-Major et al., 2016 ).

Romer et al. (2013) found that the types of internet activities utilized (e.g. SNS, blogs, etc.) were associated with the frequency of self-reported depression-like symptoms. Additionally, using the internet for information searching was associated with higher grades, more frequent participation in clubs, and lower reports of depressive symptoms, while using the internet more than 4 h per day to communicate or play games was associated with greater depression-like symptoms, suggesting that Internet use for acquiring information is associated with healthy development.

A qualitative study further explored positive and negative aspects of SM use among adolescents diagnosed with clinical depression ( Radovic, Gmelin, Stein, & Miller, 2017 ). Participants described positive SM use as including searching for positive content (e.g. entertainment, humour, content creation) or social connection, while they described negative SM use as sharing risky behaviours, cyberbullying, or making self-denigrating comparisons with others. Furthermore, this study found that adolescents’ use of SM shifted from negative to positive during the course of treatment.

Social comparisons

Two studies examined social comparisons made through SM and the association with depression. Nesi and Prinstein (2015) found that technology-based social comparison and feedback-seeking were associated with depressive symptoms, even when controlling for the effects of overall frequency of technology use, offline excessive reassurance-seeking, and prior depressive symptoms. This association was strongest among females and adolescents low in popularity (as measured by peer report). Niu et al. (2018) found that negative social comparisons mediated the association between Qzone use (a Chinese SM site) and depression, and that the association between Qzone use and negative social comparisons was stronger among individuals with low self-esteem. However, there was no direct effect of Qzone use on depression. An additional study that primarily focussed on studying frequency of use ( Marengo et al., 2018 ) found that increased use of highly visual SM (e.g. Instagram) predicted internalizing symptoms and body image concerns in a student sample. Moreover, in this study, the effect of highly visual SM on internalizing symptoms was mediated by body image concerns.

Social aspects of SM use

Several studies looked at the social aspects of engagement with SM, either by evaluating the effects of cybervictimization ( n = 4) on depression, parental involvement both through monitoring of SM use or direct engagement with the adolescent ( n = 3), and aspects of social support received by the adolescent within and outside of SNS ( n = 2).


Four studies examined cyberbullying via SM and depressive symptoms. Duarte, Pittman, Thorsen, Cunningham, and Ranney (2018) found that symptoms of depression, post-traumatic stress disorder, and suicidal ideation were more prevalent among participants who reported any past-year cyberbullying (either victimization or perpetration). After adjusting for a range of demographic factors, only lesbian, gay, and bisexual status correlated with cyberbullying involvement or adverse mental health outcomes. Another study found that cyberbullying victimization fully mediated the association between SM use and psychological distress and suicide attempts ( Sampasa-Kanyinga & Hamilton, 2015 ). Furthermore, a 12-month longitudinal study found that cybervictimization predicted later depressive symptoms ( Cole et al., 2016 ). Depressive symptoms have also been shown to be a risk factor (rather than an outcome) for cybervictimization on Facebook ( Frison, Subrahmanyam, & Eggermont, 2016 ), showing evidence of the bi-directionality of this association.

Social support

While many studies examined potential negative effects of SM use, some studies examined the positive effects of SM use on youth outcomes, including social support. Frison and Eggermont (2015) found that adolescents seeking social support through Facebook had improved depressive symptoms if support was received, but worsened symptoms if support was not received. This pattern was not found in non-virtual social support contexts, suggesting differences in online and traditional social support contexts. A later study that primarily focussed on the characteristics of SM use ( Frison & Eggermont, 2016 ) found that perception of online support was particularly protective against depressive symptoms in girls with ‘active’ Facebook use (e.g. those who update their status or instant message on Facebook). Finally, Frison et al. (2016) showed that support from friends can be a protective factor of Facebook victimization.

Parental involvement/parental monitoring

Studies examining parent and family role in adolescent SM use and its outcomes were heterogeneous. One study ( Coyne, Padilla-Walker, Day, Harper, & Stockdale, 2014 ) explored adolescent use of SM with parents and found lower internalizing behaviours in participants who used SNS with their parents (mediated by feelings of parent/child connection). Another study ( Fardouly, Magson, Johnco, Oar, & Rapee, 2018 ) examined parent control over preadolescents’ time spent on SM and found no association between parental control and preadolescent depressive symptoms.

Family relationships offline were also associated with adolescent outcomes. Isarabhakdi and Pewnil (2016) examined adolescents’ engagement with offline relationships and found improved mental health outcomes with higher involvement in family activities and with peers, while internet use did not significantly improve mental well-being. This finding suggests that in-person support systems were more effective for the promotion of mental well-being. Interestingly, in Szwedo, Mikami, and Allen (2011) , negative interactions with mothers during early adolescence were associated with youth preferring online versus face-to-face communication, experiencing more negative interactions on webpages, and forming close friendships with someone they met online 7 years later. An additional study that primarily focussed on suicide contagion ( Tseng & Yang, 2015 ) found that family support was protective for both males and females, while friend support was protective only for females. However, ‘significant other’ support was a risk factor for suicidal plans among females.

Disclosure of mental health symptoms on SM

A few of the studies selected focussed on studying the disclosure of depressive symptoms on SM and explored the potential of disclosure of symptoms of distress on SM to predict depression and suicide, in addition to the phenomenon of suicide contagion.

Online disclosure and prediction of mental health symptoms

Although content analysis is a method theorized to have potential to predict and prevent non-suicidal and suicidal self-injurious behaviours, the data are mixed. Ophir, Asterhan, and Schwarz (2019) examined the predictive validity of explicit references to personal distress in adolescents’ Facebook postings, comparing these postings with external, self-report measures of psychological distress (e.g. depression) and found that most depressed adolescents did not publish explicit references to depression. Additionally, adolescents published less verbal content than adult users of SNS. Conversely, Akkın Gürbüz et al. (2017) found that while disclosures of depressed mood were frequent among both depressed and non-depressed adolescents, those who were depressed shared more negative feelings, anhedonia, and suicidal thoughts on SM than those who were not depressed.

Suicide contagion effect

One longitudinal study examined suicide contagion effects ( Dunlop, More, & Romer, 2011 ) finding that even though traditional SNS (e.g. Facebook or MySpace) were a significant source of exposure to suicide stories, this exposure was not associated with increases in suicidal ideation one year later. On the other hand, exposure to online discussion forums (including self-help forums) did predict increases in suicidal ideation over time. Notably, this study found that in a quarter of the sample, the exposure to suicide stories took place through SM. Another study ( Tseng & Yang, 2015 ) found that higher importance attributed to web communication (e.g. chatting or making friends online) was associated with increased risk of self-injurious thoughts and behaviours in boys.

The recent rise in the prevalence of depression and suicide among adolescents has coincided with an increase in screen-related activities, including SM use ( Twenge et al., 2018 ), sparking an interest in investigating the effects of SM use on adolescent mental health. This interest has given rise to a broad scope of research, ranging from observational to experimental and qualitative studies through interviews or analysis of SM content, and systematic studies. This scoping review aimed to understand the breadth of research in the area of depression and SM (with a focus on SNS) and to identify the existing research gaps.

We identified four main themes of research, including (1) the quantity of SM use; (2) the quality of SM use; (3) social aspects associated with SM use; and (4) SM as a tool for disclosure of mental health symptoms and potential for prediction and prevention of depression and suicide outcomes.

Most research on SM and depressive symptoms has focussed on the effects of frequency of SM use and problematic SM use. The majority of articles included in this review demonstrated a positive and bi-directional association between frequency of SM use and depression and in some instances even suicidality. Yet some questions remain to be determined, including to what degree adolescents’ personal vulnerabilities and characteristics of SM use moderate the association between SM use and depression or suicidality, and whether other environmental factors, such as family support and/or monitoring, or cultural differences influence this association. Although moderate SM use may be associated with better self-regulation, it is unclear if this is due to moderate users being better at self-regulation.

Findings from the studies examining problematic SM use were consistent with prior studies linking problematic internet use with a variety of psychosocial outcomes including depressive symptoms ( Reid Chassiakos et al., 2016 ). Though limited in number, studies reviewed here suggested that problematic or addictive SM use may be more common in females ( Banyai et al., 2017 ; Kırcaburun et al., 2018 ) and in those starting use at a younger age ( Tsitsika, Janikian, et al., 2014 ). These findings suggest a possible role of screening for addictive SM use, with a particular focus on risk stratification for younger and female adolescents.

With respect to the effects of patterns and types of SM use, studies reviewed here suggest possible differential effects between passive and active, and private versus public SM use. This suggests that screening only for time spent on SM may be insufficient. Moreover, though there are types of SM use that have adverse mental health effects for adolescents (e.g. addictive patterns, nighttime use), other types of SM use, such as for information searching or receiving social support, may have a positive effect ( Coyne et al., 2018 ; Frison & Eggermont, 2016 ; Romer et al., 2013 ). Furthermore, over time, depressed adolescents can successfully shift their use of SM from negative (e.g. cyberbullying) to positive (e.g. searching for humour), possibly through increasing awareness of the effect of SM use on their mood ( Radovic et al., 2017 ). Given the ubiquity of SM use, these results suggest that interventions targeting changes in adolescents’ use of SM may be fruitful in improving their mental health.

Consistent with prior research ( Feinstein et al., 2013 ), studies examining social comparisons found significant associations between social comparisons made via SM and depression. The tendency of individuals to share more positive depictions of themselves on SM ( Subrahmanyam & Greenfield, 2008 ), and the increased opportunities for comparisons ( Steers, Wickham, & Acitelli, 2014 ) may suggest a confluence of risks for depression and an important avenue for interventions. Moreover, the studies reviewed and previous findings ( Buunk & Gibbons, 2007 ) suggest that individuals with low self-esteem may be at higher risk for the negative effects of social comparisons on mental health.

As previously shown ( Cénat et al., 2014 ), most studies found cyberbullying (either perpetration or victimization) was either associated with mental health problems ( Cole et al., 2016 ; Duarte et al., 2018 ) or moderated the relationship between SM use and depression and suicidality ( Sampasa-Kanyinga & Hamilton, 2015 ). Additionally, cyberbullying may be a distinctive form of victimization that requires further investigation in order to understand its impact on adolescent mental health ( Dempsey, Sulkowski, Nichols, & Storch, 2009 ).

Studies examining social support highlight the association of both depressed mood and low in-person social support with social networking and online support-seeking ( Frison & Eggermont, 2015 ). Moreover, while social support online can be beneficial ( Frison & Eggermont, 2015 ), excessive reliance on online communication and support may be problematic ( Twenge et al., 2018 ). Of note, parental involvement both positively and negatively affected SM use and adolescent outcomes. These mixed findings suggest a need to include parental relationships in research (both via online and ‘offline’ communication), to better understand their role in adolescents’ SM use and depression.

Surprisingly, depressed adolescents were not more likely to publish explicit references to depression on SM platforms than their healthy peers ( Ophir et al., 2019 ) which suggests that screening for depression via SM may not be useful when used alone. However, some depressed adolescents posted more negative feelings, anhedonia and suicidal ideation ( Akkın Gürbüz et al., 2017 ), suggesting that SM may be used as a supplemental tool to track the course of depressive mood over time and start discussions about mental health.

Suicide contagion effect is a relatively understudied area, despite concerns raised that increased exposure to SM may amplify this effect ( Bell, 2014 ). Given that adolescents are particularly vulnerable to the group contagion effect of suicide ( Stack, 2003 ) and the potential for increased exposure to suicide stories online ( Dunlop et al., 2011 ), interventions to limit this exposure could decrease suicide contagion.

The studies reviewed identified several potential moderators of the association between SM use and adolescent depression, including age and gender. The differential effects of SM use on mental health depending on the age of the adolescent ( Tsitsika, Tzavela, et al., 2014 ) are not surprising given the developmental differences in social and mood regulation skills between younger and older adolescents. Likewise, potential mediators of the effects of SM on mental health such as social comparisons ( Niu et al., 2018 ), body image concerns ( Marengo et al., 2018 ), perceived support online ( Frison & Eggermont, 2015 ), and parent–child relationship ( Coyne et al., 2014 ) may also be important targets for future interventions.

The studies reviewed present several limitations. Most studies were cross-sectional and could not elucidate the directionality of the association between SM use and depression. Most of the studies included self-report rather than clinician-administered measures of depression, and retrospective reports, asking participants to report on past activities. Newer methods that measure actual (and not just reported) use (e.g. news feed activity, number of likes and comments) and more frequent and timely reports of SM use (e.g. diaries) could more accurately explain these associations. Another limitation is that many of the studies recruited participants in schools, limiting the generalizability to clinical samples. It is possible that those students not in school were spending more time on SM and/or experiencing more depressive symptoms. Most studies included general assessments of SM without specifying whether the use was limited to SNS or other forms of SM or internet use. While we tried to narrow our search to studies that explicitly included questions on SNS use, many also asked about other types of SM use. Separating the different types of SM use may be difficult when asking for adolescents’ self-reports, but more immediate measures of mood symptoms and SNS use could be more specific and informative. Finally, while some studies included contextual factors such as the educational and family environments, other contextual factors such as ethnicity and cultural context are areas of potential for investigation.


In summary, extensive research on the quantity and quality of SM use has shown an association between SM use and depression in adolescents. Given that most studies are cross-sectional, longitudinal research would help assess the direction of this association. At the same time, some aspects of SM use may have a beneficial effect on adolescent well-being, such as the ability to have diversity of friendships and easily accessed supports. Furthermore, the use of SM content to detect symptoms has potential in depression and suicide prevention. Finally, moderators of the association between SM and adolescent depression and suicidality (e.g. gender, age, parental involvement) are areas to explore that would allow more targeted interventions. Since SM will remain an important facet of adolescents’ lives, a better understanding of the mechanisms of its relationship with depression could be beneficial to increase exposure to mental health interventions and promote well-being.


The authors acknowledge the help of Jaime Blanck, MLIS, MPA for her help with the search and retrieval of full-text articles.

Disclosure statement

Dr. Vidal is supported by the Stravos Niarchos Foundation. Ms. Lhaksampa and Dr. Miller are supported by the Once Upon a Time Foundation. Drs. Miller and Dr. Platt are supported by the Patient-Centered Outcomes Research Institute (PCORI). Dr. Platt is supported by the NIMH 1K23MH118431 and the Robert Wood Johnson Foundation.

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Social media addiction: Its impact, mediation, and intervention

Vol.13, no.1 (2019).

Yubo Hou Dan Xiong Tonglin Jiang Lily Song Qi Wang


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This research examined the relations of social media addiction to college students' mental health and academic performance, investigated the role of self-esteem as a mediator for the relations, and further tested the effectiveness of an intervention in reducing social media addiction and its potential adverse outcomes. In Study 1, we used a survey method with a sample of college students (N = 232) and found that social media addiction was negatively associated with the students' mental health and academic performance and that the relation between social media addiction and mental health was mediated by self-esteem. In Study 2, we developed and tested a two-stage self-help intervention program. We recruited a sample of college students (N = 38) who met criteria for social media addiction to receive the intervention. Results showed that the intervention was effective in reducing the students’ social media addiction and improving their mental health and academic efficiency. The current studies yielded original findings that contribute to the empirical database on social media addiction and that have important theoretical and practical implications.

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Systematic review article, research trends in social media addiction and problematic social media use: a bibliometric analysis.

social media addiction introduction research paper

  • 1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand
  • 2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand

Despite their increasing ubiquity in people's lives and incredible advantages in instantly interacting with others, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays in mental health. Much research has discovered how habitual social media use may lead to addiction and negatively affect adolescents' school performance, social behavior, and interpersonal relationships. The present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. Bibliometric analysis was conducted on 501 articles that were extracted from the Scopus database using the keywords social media addiction and problematic social media use. The data were then uploaded to VOSviewer software to analyze citations, co-citations, and keyword co-occurrences. Volume, growth trajectory, geographic distribution of the literature, influential authors, intellectual structure of the literature, and the most prolific publishing sources were analyzed. The bibliometric analysis presented in this paper shows that the US, the UK, and Turkey accounted for 47% of the publications in this field. Most of the studies used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, the findings in this study show that most analysis were cross-sectional. Studies were performed on undergraduate students between the ages of 19–25 on the use of two social media platforms: Facebook and Instagram. Limitations as well as research directions for future studies are also discussed.


Social media generally refers to third-party internet-based platforms that mainly focus on social interactions, community-based inputs, and content sharing among its community of users and only feature content created by their users and not that licensed from third parties ( 1 ). Social networking sites such as Facebook, Instagram, and TikTok are prominent examples of social media that allow people to stay connected in an online world regardless of geographical distance or other obstacles ( 2 , 3 ). Recent evidence suggests that social networking sites have become increasingly popular among adolescents following the strict policies implemented by many countries to counter the COVID-19 pandemic, including social distancing, “lockdowns,” and quarantine measures ( 4 ). In this new context, social media have become an essential part of everyday life, especially for children and adolescents ( 5 ). For them such media are a means of socialization that connect people together. Interestingly, social media are not only used for social communication and entertainment purposes but also for sharing opinions, learning new things, building business networks, and initiate collaborative projects ( 6 ).

Among the 7.91 billion people in the world as of 2022, 4.62 billion active social media users, and the average time individuals spent using the internet was 6 h 58 min per day with an average use of social media platforms of 2 h and 27 min ( 7 ). Despite their increasing ubiquity in people's lives and the incredible advantages they offer to instantly interact with people, an increasing number of studies have linked social media use to negative mental health consequences, such as suicidality, loneliness, and anxiety ( 8 ). Numerous sources have expressed widespread concern about the effects of social media on mental health. A 2011 report by the American Academy of Pediatrics (AAP) identifies a phenomenon known as Facebook depression which may be triggered “when preteens and teens spend a great deal of time on social media sites, such as Facebook, and then begin to exhibit classic symptoms of depression” ( 9 ). Similarly, the UK's Royal Society for Public Health (RSPH) claims that there is a clear evidence of the relationship between social media use and mental health issues based on a survey of nearly 1,500 people between the ages of 14–24 ( 10 ). According to some authors, the increase in usage frequency of social media significantly increases the risks of clinical disorders described (and diagnosed) as “Facebook depression,” “fear of missing out” (FOMO), and “social comparison orientation” (SCO) ( 11 ). Other risks include sexting ( 12 ), social media stalking ( 13 ), cyber-bullying ( 14 ), privacy breaches ( 15 ), and improper use of technology. Therefore, social media's impact on subjective well-being is a source of concern worldwide and calls for up-to-date investigations of the role social media plays with regard to mental health ( 8 ). Many studies have found that habitual social media use may lead to addiction and thus negatively affect adolescents' school performance, social behavior, and interpersonal relationships ( 16 – 18 ). As a result of addiction, the user becomes highly engaged with online activities motivated by an uncontrollable desire to browse through social media pages and “devoting so much time and effort to it that it impairs other important life areas” ( 19 ).

Given these considerations, the present study was conducted to review the extant literature in the domain of social media and analyze global research productivity during 2013–2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” This is valuable as it allows for a comprehensive overview of the current state of this field of research, as well as identifies any patterns or trends that may be present. Additionally, it provides information on the geographical distribution and prolific authors in this area, which may help to inform future research endeavors.

In terms of bibliometric analysis of social media addiction research, few studies have attempted to review the existing literature in the domain extensively. Most previous bibliometric studies on social media addiction and problematic use have focused mainly on one type of screen time activity such as digital gaming or texting ( 20 ) and have been conducted with a focus on a single platform such as Facebook, Instagram, or Snapchat ( 21 , 22 ). The present study adopts a more comprehensive approach by including all social media platforms and all types of screen time activities in its analysis.

Additionally, this review aims to highlight the major themes around which the research has evolved to date and draws some guidance for future research directions. In order to meet these objectives, this work is oriented toward answering the following research questions:

(1) What is the current status of research focusing on social media addiction?

(2) What are the key thematic areas in social media addiction and problematic use research?

(3) What is the intellectual structure of social media addiction as represented in the academic literature?

(4) What are the key findings of social media addiction and problematic social media research?

(5) What possible future research gaps can be identified in the field of social media addiction?

These research questions will be answered using bibliometric analysis of the literature on social media addiction and problematic use. This will allow for an overview of the research that has been conducted in this area, including information on the most influential authors, journals, countries of publication, and subject areas of study. Part 2 of the study will provide an examination of the intellectual structure of the extant literature in social media addiction while Part 3 will discuss the research methodology of the paper. Part 4 will discuss the findings of the study followed by a discussion under Part 5 of the paper. Finally, in Part 7, gaps in current knowledge about this field of research will be identified.

Literature review

Social media addiction research context.

Previous studies on behavioral addictions have looked at a lot of different factors that affect social media addiction focusing on personality traits. Although there is some inconsistency in the literature, numerous studies have focused on three main personality traits that may be associated with social media addiction, namely anxiety, depression, and extraversion ( 23 , 24 ).

It has been found that extraversion scores are strongly associated with increased use of social media and addiction to it ( 25 , 26 ). People with social anxiety as well as people who have psychiatric disorders often find online interactions extremely appealing ( 27 ). The available literature also reveals that the use of social media is positively associated with being female, single, and having attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), or anxiety ( 28 ).

In a study by Seidman ( 29 ), the Big Five personality traits were assessed using Saucier's ( 30 ) Mini-Markers Scale. Results indicated that neurotic individuals use social media as a safe place for expressing their personality and meet belongingness needs. People affected by neurosis tend to use online social media to stay in touch with other people and feel better about their social lives ( 31 ). Narcissism is another factor that has been examined extensively when it comes to social media, and it has been found that people who are narcissistic are more likely to become addicted to social media ( 32 ). In this case users want to be seen and get “likes” from lots of other users. Longstreet and Brooks ( 33 ) did a study on how life satisfaction depends on how much money people make. Life satisfaction was found to be negatively linked to social media addiction, according to the results. When social media addiction decreases, the level of life satisfaction rises. But results show that in lieu of true-life satisfaction people use social media as a substitute (for temporary pleasure vs. longer term happiness).

Researchers have discovered similar patterns in students who tend to rank high in shyness: they find it easier to express themselves online rather than in person ( 34 , 35 ). With the use of social media, shy individuals have the opportunity to foster better quality relationships since many of their anxiety-related concerns (e.g., social avoidance and fear of social devaluation) are significantly reduced ( 36 , 37 ).

Problematic use of social media

The amount of research on problematic use of social media has dramatically increased since the last decade. But using social media in an unhealthy manner may not be considered an addiction or a disorder as this behavior has not yet been formally categorized as such ( 38 ). Although research has shown that people who use social media in a negative way often report negative health-related conditions, most of the data that have led to such results and conclusions comprise self-reported data ( 39 ). The dimensions of excessive social media usage are not exactly known because there are not enough diagnostic criteria and not enough high-quality long-term studies available yet. This is what Zendle and Bowden-Jones ( 40 ) noted in their own research. And this is why terms like “problematic social media use” have been used to describe people who use social media in a negative way. Furthermore, if a lot of time is spent on social media, it can be hard to figure out just when it is being used in a harmful way. For instance, people easily compare their appearance to what they see on social media, and this might lead to low self-esteem if they feel they do not look as good as the people they are following. According to research in this domain, the extent to which an individual engages in photo-related activities (e.g., taking selfies, editing photos, checking other people's photos) on social media is associated with negative body image concerns. Through curated online images of peers, adolescents face challenges to their self-esteem and sense of self-worth and are increasingly isolated from face-to-face interaction.

To address this problem the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) has been used by some scholars ( 41 , 42 ). These scholars have used criteria from the DSM-V to describe one problematic social media use, internet gaming disorder, but such criteria could also be used to describe other types of social media disorders. Franchina et al. ( 43 ) and Scott and Woods ( 44 ), for example, focus their attention on individual-level factors (like fear of missing out) and family-level factors (like childhood abuse) that have been used to explain why people use social media in a harmful way. Friends-level factors have also been explored as a social well-being measurement to explain why people use social media in a malevolent way and demonstrated significant positive correlations with lower levels of friend support ( 45 ). Macro-level factors have also been suggested, such as the normalization of surveillance ( 46 ) and the ability to see what people are doing online ( 47 ). Gender and age seem to be highly associated to the ways people use social media negatively. Particularly among girls, social media use is consistently associated with mental health issues ( 41 , 48 , 49 ), an association more common among older girls than younger girls ( 46 , 48 ).

Most studies have looked at the connection between social media use and its effects (such as social media addiction) and a number of different psychosomatic disorders. In a recent study conducted by Vannucci and Ohannessian ( 50 ), the use of social media appears to have a variety of effects “on psychosocial adjustment during early adolescence, with high social media use being the most problematic.” It has been found that people who use social media in a harmful way are more likely to be depressed, anxious, have low self-esteem, be more socially isolated, have poorer sleep quality, and have more body image dissatisfaction. Furthermore, harmful social media use has been associated with unhealthy lifestyle patterns (for example, not getting enough exercise or having trouble managing daily obligations) as well as life threatening behaviors such as illicit drug use, excessive alcohol consumption and unsafe sexual practices ( 51 , 52 ).

A growing body of research investigating social media use has revealed that the extensive use of social media platforms is correlated with a reduced performance on cognitive tasks and in mental effort ( 53 ). Overall, it appears that individuals who have a problematic relationship with social media or those who use social media more frequently are more likely to develop negative health conditions.

Social media addiction and problematic use systematic reviews

Previous studies have revealed the detrimental impacts of social media addiction on users' health. A systematic review by Khan and Khan ( 20 ) has pointed out that social media addiction has a negative impact on users' mental health. For example, social media addiction can lead to stress levels rise, loneliness, and sadness ( 54 ). Anxiety is another common mental health problem associated with social media addiction. Studies have found that young adolescents who are addicted to social media are more likely to suffer from anxiety than people who are not addicted to social media ( 55 ). In addition, social media addiction can also lead to physical health problems, such as obesity and carpal tunnel syndrome a result of spending too much time on the computer ( 22 ).

Apart from the negative impacts of social media addiction on users' mental and physical health, social media addiction can also lead to other problems. For example, social media addiction can lead to financial problems. A study by Sharif and Yeoh ( 56 ) has found that people who are addicted to social media tend to spend more money than those who are not addicted to social media. In addition, social media addiction can also lead to a decline in academic performance. Students who are addicted to social media are more likely to have lower grades than those who are not addicted to social media ( 57 ).

Research methodology

Bibliometric analysis.

Merigo et al. ( 58 ) use bibliometric analysis to examine, organize, and analyze a large body of literature from a quantitative, objective perspective in order to assess patterns of research and emerging trends in a certain field. A bibliometric methodology is used to identify the current state of the academic literature, advance research. and find objective information ( 59 ). This technique allows the researchers to examine previous scientific work, comprehend advancements in prior knowledge, and identify future study opportunities.

To achieve this objective and identify the research trends in social media addiction and problematic social media use, this study employs two bibliometric methodologies: performance analysis and science mapping. Performance analysis uses a series of bibliometric indicators (e.g., number of annual publications, document type, source type, journal impact factor, languages, subject area, h-index, and countries) and aims at evaluating groups of scientific actors on a particular topic of research. VOSviewer software ( 60 ) was used to carry out the science mapping. The software is used to visualize a particular body of literature and map the bibliographic material using the co-occurrence analysis of author, index keywords, nations, and fields of publication ( 61 , 62 ).

Data collection

After picking keywords, designing the search strings, and building up a database, the authors conducted a bibliometric literature search. Scopus was utilized to gather exploration data since it is a widely used database that contains the most comprehensive view of the world's research output and provides one of the most effective search engines. If the research was to be performed using other database such as Web Of Science or Google Scholar the authors may have obtained larger number of articles however they may not have been all particularly relevant as Scopus is known to have the most widest and most relevant scholar search engine in marketing and social science. A keyword search for “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. The information was gathered in March 2022, and because the Scopus database is updated on a regular basis, the results may change in the future. Next, the authors examined the titles and abstracts to see whether they were relevant to the topics treated. There were two common grounds for document exclusion. First, while several documents emphasized the negative effects of addiction in relation to the internet and digital media, they did not focus on social networking sites specifically. Similarly, addiction and problematic consumption habits were discussed in relation to social media in several studies, although only in broad terms. This left a total of 511 documents. Articles were then limited only to journal articles, conference papers, reviews, books, and only those published in English. This process excluded 10 additional documents. Then, the relevance of the remaining articles was finally checked by reading the titles, abstracts, and keywords. Documents were excluded if social networking sites were only mentioned as a background topic or very generally. This resulted in a final selection of 501 research papers, which were then subjected to bibliometric analysis (see Figure 1 ).


Figure 1 . Preferred reporting items for systematic reviews and meta-analysis (PRISMA) flowchart showing the search procedures used in the review.

After identifying 501 Scopus files, bibliographic data related to these documents were imported into an Excel sheet where the authors' names, their affiliations, document titles, keywords, abstracts, and citation figures were analyzed. These were subsequently uploaded into VOSViewer software version 1.6.8 to begin the bibliometric review. Descriptive statistics were created to define the whole body of knowledge about social media addiction and problematic social media use. VOSViewer was used to analyze citation, co-citation, and keyword co-occurrences. According to Zupic and Cater ( 63 ), co-citation analysis measures the influence of documents, authors, and journals heavily cited and thus considered influential. Co-citation analysis has the objective of building similarities between authors, journals, and documents and is generally defined as the frequency with which two units are cited together within the reference list of a third article.

The implementation of social media addiction performance analysis was conducted according to the models recently introduced by Karjalainen et al. ( 64 ) and Pattnaik ( 65 ). Throughout the manuscript there are operational definitions of relevant terms and indicators following a standardized bibliometric approach. The cumulative academic impact (CAI) of the documents was measured by the number of times they have been cited in other scholarly works while the fine-grained academic impact (FIA) was computed according to the authors citation analysis and authors co-citation analysis within the reference lists of documents that have been specifically focused on social media addiction and problematic social media use.

Results of the study presented here include the findings on social media addiction and social media problematic use. The results are presented by the foci outlined in the study questions.

Volume, growth trajectory, and geographic distribution of the literature

After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use of social media, the authors obtained a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books and 1 conference review. The included literature was very recent. As shown in Figure 2 , publication rates started very slowly in 2013 but really took off in 2018, after which publications dramatically increased each year until a peak was reached in 2021 with 195 publications. Analyzing the literature published during the past decade reveals an exponential increase in scholarly production on social addiction and its problematic use. This might be due to the increasingly widespread introduction of social media sites in everyday life and the ubiquitous diffusion of mobile devices that have fundamentally impacted human behavior. The dip in the number of publications in 2022 is explained by the fact that by the time the review was carried out the year was not finished yet and therefore there are many articles still in press.


Figure 2 . Annual volume of social media addiction or social media problematic use ( n = 501).

The geographical distribution trends of scholarly publications on social media addiction or problematic use of social media are highlighted in Figure 3 . The articles were assigned to a certain country according to the nationality of the university with whom the first author was affiliated with. The figure shows that the most productive countries are the USA (92), the U.K. (79), and Turkey ( 63 ), which combined produced 236 articles, equal to 47% of the entire scholarly production examined in this bibliometric analysis. Turkey has slowly evolved in various ways with the growth of the internet and social media. Anglo-American scholarly publications on problematic social media consumer behavior represent the largest research output. Yet it is interesting to observe that social networking sites studies are attracting many researchers in Asian countries, particularly China. For many Chinese people, social networking sites are a valuable opportunity to involve people in political activism in addition to simply making purchases ( 66 ).


Figure 3 . Global dispersion of social networking sites in relation to social media addiction or social media problematic use.

Analysis of influential authors

This section analyses the high-impact authors in the Scopus-indexed knowledge base on social networking sites in relation to social media addiction or problematic use of social media. It provides valuable insights for establishing patterns of knowledge generation and dissemination of literature about social networking sites relating to addiction and problematic use.

Table 1 acknowledges the top 10 most highly cited authors with the highest total citations in the database.


Table 1 . Highly cited authors on social media addiction and problematic use ( n = 501).

Table 1 shows that MD Griffiths (sixty-five articles), CY Lin (twenty articles), and AH Pakpour (eighteen articles) are the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use . If the criteria are changed and authors ranked according to the overall number of citations received in order to determine high-impact authors, the same three authors turn out to be the most highly cited authors. It should be noted that these highly cited authors tend to enlist several disciplines in examining social media addiction and problematic use. Griffiths, for example, focuses on behavioral addiction stemming from not only digital media usage but also from gambling and video games. Lin, on the other hand, focuses on the negative effects that the internet and digital media can have on users' mental health, and Pakpour approaches the issue from a behavioral medicine perspective.

Intellectual structure of the literature

In this part of the paper, the authors illustrate the “intellectual structure” of the social media addiction and the problematic use of social media's literature. An author co-citation analysis (ACA) was performed which is displayed as a figure that depicts the relations between highly co-cited authors. The study of co-citation assumes that strongly co-cited authors carry some form of intellectual similarity ( 67 ). Figure 4 shows the author co-citation map. Nodes represent units of analysis (in this case scholars) and network ties represent similarity connections. Nodes are sized according to the number of co-citations received—the bigger the node, the more co-citations it has. Adjacent nodes are considered intellectually similar.


Figure 4 . Two clusters, representing the intellectual structure of the social media and its problematic use literature.

Scholars belonging to the green cluster (Mental Health and Digital Media Addiction) have extensively published on medical analysis tools and how these can be used to heal users suffering from addiction to digital media, which can range from gambling, to internet, to videogame addictions. Scholars in this school of thought focus on the negative effects on users' mental health, such as depression, anxiety, and personality disturbances. Such studies focus also on the role of screen use in the development of mental health problems and the increasing use of medical treatments to address addiction to digital media. They argue that addiction to digital media should be considered a mental health disorder and treatment options should be made available to users.

In contrast, scholars within the red cluster (Social Media Effects on Well Being and Cyberpsychology) have focused their attention on the effects of social media toward users' well-being and how social media change users' behavior, focusing particular attention on the human-machine interaction and how methods and models can help protect users' well-being. Two hundred and two authors belong to this group, the top co-cited being Andreassen (667 co-citations), Pallasen (555 co-citations), and Valkenburg (215 co-citations). These authors have extensively studied the development of addiction to social media, problem gambling, and internet addiction. They have also focused on the measurement of addiction to social media, cyberbullying, and the dark side of social media.

Most influential source title in the field of social media addiction and its problematic use

To find the preferred periodicals in the field of social media addiction and its problematic use, the authors have selected 501 articles published in 263 journals. Table 2 gives a ranked list of the top 10 journals that constitute the core publishing sources in the field of social media addiction research. In doing so, the authors analyzed the journal's impact factor, Scopus Cite Score, h-index, quartile ranking, and number of publications per year.


Table 2 . Top 10 most cited and more frequently mentioned documents in the field of social media addiction.

The journal Addictive Behaviors topped the list, with 700 citations and 22 publications (4.3%), followed by Computers in Human Behaviors , with 577 citations and 13 publications (2.5%), Journal of Behavioral Addictions , with 562 citations and 17 publications (3.3%), and International Journal of Mental Health and Addiction , with 502 citations and 26 publications (5.1%). Five of the 10 most productive journals in the field of social media addiction research are published by Elsevier (all Q1 rankings) while Springer and Frontiers Media published one journal each.

Documents citation analysis identified the most influential and most frequently mentioned documents in a certain scientific field. Andreassen has received the most citations among the 10 most significant papers on social media addiction, with 405 ( Table 2 ). The main objective of this type of studies was to identify the associations and the roles of different variables as predictors of social media addiction (e.g., ( 19 , 68 , 69 )). According to general addiction models, the excessive and problematic use of digital technologies is described as “being overly concerned about social media, driven by an uncontrollable motivation to log on to or use social media, and devoting so much time and effort to social media that it impairs other important life areas” ( 27 , 70 ). Furthermore, the purpose of several highly cited studies ( 31 , 71 ) was to analyse the connections between young adults' sleep quality and psychological discomfort, depression, self-esteem, and life satisfaction and the severity of internet and problematic social media use, since the health of younger generations and teenagers is of great interest this may help explain the popularity of such papers. Despite being the most recent publication Lin et al.'s work garnered more citations annually. The desire to quantify social media addiction in individuals can also help explain the popularity of studies which try to develop measurement scales ( 42 , 72 ). Some of the highest-ranked publications are devoted to either the presentation of case studies or testing relationships among psychological constructs ( 73 ).

Keyword co-occurrence analysis

The research question, “What are the key thematic areas in social media addiction literature?” was answered using keyword co-occurrence analysis. Keyword co-occurrence analysis is conducted to identify research themes and discover keywords. It mainly examines the relationships between co-occurrence keywords in a wide variety of literature ( 74 ). In this approach, the idea is to explore the frequency of specific keywords being mentioned together.

Utilizing VOSviewer, the authors conducted a keyword co-occurrence analysis to characterize and review the developing trends in the field of social media addiction. The top 10 most frequent keywords are presented in Table 3 . The results indicate that “social media addiction” is the most frequent keyword (178 occurrences), followed by “problematic social media use” (74 occurrences), “internet addiction” (51 occurrences), and “depression” (46 occurrences). As shown in the co-occurrence network ( Figure 5 ), the keywords can be grouped into two major clusters. “Problematic social media use” can be identified as the core theme of the green cluster. In the red cluster, keywords mainly identify a specific aspect of problematic social media use: social media addiction.


Table 3 . Frequency of occurrence of top 10 keywords.


Figure 5 . Keywords co-occurrence map. Threshold: 5 co-occurrences.

The results of the keyword co-occurrence analysis for journal articles provide valuable perspectives and tools for understanding concepts discussed in past studies of social media usage ( 75 ). More precisely, it can be noted that there has been a large body of research on social media addiction together with other types of technological addictions, such as compulsive web surfing, internet gaming disorder, video game addiction and compulsive online shopping ( 76 – 78 ). This field of research has mainly been directed toward teenagers, middle school students, and college students and university students in order to understand the relationship between social media addiction and mental health issues such as depression, disruptions in self-perceptions, impairment of social and emotional activity, anxiety, neuroticism, and stress ( 79 – 81 ).

The findings presented in this paper show that there has been an exponential increase in scholarly publications—from two publications in 2013 to 195 publications in 2021. There were 45 publications in 2022 at the time this study was conducted. It was interesting to observe that the US, the UK, and Turkey accounted for 47% of the publications in this field even though none of these countries are in the top 15 countries in terms of active social media penetration ( 82 ) although the US has the third highest number of social media users ( 83 ). Even though China and India have the highest number of social media users ( 83 ), first and second respectively, they rank fifth and tenth in terms of publications on social media addiction or problematic use of social media. In fact, the US has almost double the number of publications in this field compared to China and almost five times compared to India. Even though East Asia, Southeast Asia, and South Asia make up the top three regions in terms of worldwide social media users ( 84 ), except for China and India there have been only a limited number of publications on social media addiction or problematic use. An explanation for that could be that there is still a lack of awareness on the negative consequences of the use of social media and the impact it has on the mental well-being of users. More research in these regions should perhaps be conducted in order to understand the problematic use and addiction of social media so preventive measures can be undertaken.

From the bibliometric analysis, it was found that most of the studies examined used quantitative methods in analyzing data and therefore aimed at testing relationships between variables. In addition, many studies were empirical, aimed at testing relationships based on direct or indirect observations of social media use. Very few studies used theories and for the most part if they did they used the technology acceptance model and social comparison theories. The findings presented in this paper show that none of the studies attempted to create or test new theories in this field, perhaps due to the lack of maturity of the literature. Moreover, neither have very many qualitative studies been conducted in this field. More qualitative research in this field should perhaps be conducted as it could explore the motivations and rationales from which certain users' behavior may arise.

The authors found that almost all the publications on social media addiction or problematic use relied on samples of undergraduate students between the ages of 19–25. The average daily time spent by users worldwide on social media applications was highest for users between the ages of 40–44, at 59.85 min per day, followed by those between the ages of 35–39, at 59.28 min per day, and those between the ages of 45–49, at 59.23 per day ( 85 ). Therefore, more studies should be conducted exploring different age groups, as users between the ages of 19–25 do not represent the entire population of social media users. Conducting studies on different age groups may yield interesting and valuable insights to the field of social media addiction. For example, it would be interesting to measure the impacts of social media use among older users aged 50 years or older who spend almost the same amount of time on social media as other groups of users (56.43 min per day) ( 85 ).

A majority of the studies tested social media addiction or problematic use based on only two social media platforms: Facebook and Instagram. Although Facebook and Instagram are ranked first and fourth in terms of most popular social networks by number of monthly users, it would be interesting to study other platforms such as YouTube, which is ranked second, and WhatsApp, which is ranked third ( 86 ). Furthermore, TikTok would also be an interesting platform to study as it has grown in popularity in recent years, evident from it being the most downloaded application in 2021, with 656 million downloads ( 87 ), and is ranked second in Q1 of 2022 ( 88 ). Moreover, most of the studies focused only on one social media platform. Comparing different social media platforms would yield interesting results because each platform is different in terms of features, algorithms, as well as recommendation engines. The purpose as well as the user behavior for using each platform is also different, therefore why users are addicted to these platforms could provide a meaningful insight into social media addiction and problematic social media use.

Lastly, most studies were cross-sectional, and not longitudinal, aiming at describing results over a certain point in time and not over a long period of time. A longitudinal study could better describe the long-term effects of social media use.

This study was conducted to review the extant literature in the field of social media and analyze the global research productivity during the period ranging from 2013 to 2022. The study presents a bibliometric overview of the leading trends with particular regard to “social media addiction” and “problematic social media use.” The authors applied science mapping to lay out a knowledge base on social media addiction and its problematic use. This represents the first large-scale analysis in this area of study.

A keyword search of “social media addiction” OR “problematic social media use” yielded 553 papers, which were downloaded from Scopus. After performing the Scopus-based investigation of the current literature regarding social media addiction and problematic use, the authors ended up with a knowledge base consisting of 501 documents comprising 455 journal articles, 27 conference papers, 15 articles reviews, 3 books, and 1 conference review.

The geographical distribution trends of scholarly publications on social media addiction or problematic use indicate that the most productive countries were the USA (92), the U.K. (79), and Turkey ( 63 ), which together produced 236 articles. Griffiths (sixty-five articles), Lin (twenty articles), and Pakpour (eighteen articles) were the most productive scholars according to the number of Scopus documents examined in the area of social media addiction and its problematic use. An author co-citation analysis (ACA) was conducted which generated a layout of social media effects on well-being and cyber psychology as well as mental health and digital media addiction in the form of two research literature clusters representing the intellectual structure of social media and its problematic use.

The preferred periodicals in the field of social media addiction and its problematic use were Addictive Behaviors , with 700 citations and 22 publications, followed by Computers in Human Behavior , with 577 citations and 13 publications, and Journal of Behavioral Addictions , with 562 citations and 17 publications. Keyword co-occurrence analysis was used to investigate the key thematic areas in the social media literature, as represented by the top three keyword phrases in terms of their frequency of occurrence, namely, “social media addiction,” “problematic social media use,” and “social media addiction.”

This research has a few limitations. The authors used science mapping to improve the comprehension of the literature base in this review. First and foremost, the authors want to emphasize that science mapping should not be utilized in place of established review procedures, but rather as a supplement. As a result, this review can be considered the initial stage, followed by substantive research syntheses that examine findings from recent research. Another constraint stems from how 'social media addiction' is defined. The authors overcame this limitation by inserting the phrase “social media addiction” OR “problematic social media use” in the search string. The exclusive focus on SCOPUS-indexed papers creates a third constraint. The SCOPUS database has a larger number of papers than does Web of Science although it does not contain all the publications in a given field.

Although the total body of literature on social media addiction is larger than what is covered in this review, the use of co-citation analyses helped to mitigate this limitation. This form of bibliometric study looks at all the publications listed in the reference list of the extracted SCOPUS database documents. As a result, a far larger dataset than the one extracted from SCOPUS initially has been analyzed.

The interpretation of co-citation maps should be mentioned as a last constraint. The reason is that the procedure is not always clear, so scholars must have a thorough comprehension of the knowledge base in order to make sense of the result of the analysis ( 63 ). This issue was addressed by the authors' expertise, but it remains somewhat subjective.


The findings of this study have implications mainly for government entities and parents. The need for regulation of social media addiction is evident when considering the various risks associated with habitual social media use. Social media addiction may lead to negative consequences for adolescents' school performance, social behavior, and interpersonal relationships. In addition, social media addiction may also lead to other risks such as sexting, social media stalking, cyber-bullying, privacy breaches, and improper use of technology. Given the seriousness of these risks, it is important to have regulations in place to protect adolescents from the harms of social media addiction.

Regulation of social media platforms

One way that regulation could help protect adolescents from the harms of social media addiction is by limiting their access to certain websites or platforms. For example, governments could restrict adolescents' access to certain websites or platforms during specific hours of the day. This would help ensure that they are not spending too much time on social media and are instead focusing on their schoolwork or other important activities.

Another way that regulation could help protect adolescents from the harms of social media addiction is by requiring companies to put warning labels on their websites or apps. These labels would warn adolescents about the potential risks associated with excessive use of social media.

Finally, regulation could also require companies to provide information about how much time each day is recommended for using their website or app. This would help adolescents make informed decisions about how much time they want to spend on social media each day. These proposed regulations would help to protect children from the dangers of social media, while also ensuring that social media companies are more transparent and accountable to their users.

Parental involvement in adolescents' social media use

Parents should be involved in their children's social media use to ensure that they are using these platforms safely and responsibly. Parents can monitor their children's online activity, set time limits for social media use, and talk to their children about the risks associated with social media addiction.

Education on responsible social media use

Adolescents need to be educated about responsible social media use so that they can enjoy the benefits of these platforms while avoiding the risks associated with addiction. Education on responsible social media use could include topics such as cyber-bullying, sexting, and privacy breaches.

Research directions for future studies

A content analysis was conducted to answer the fifth research questions “What are the potential research directions for addressing social media addiction in the future?” The study reveals that there is a lack of screening instruments and diagnostic criteria to assess social media addiction. Validated DSM-V-based instruments could shed light on the factors behind social media use disorder. Diagnostic research may be useful in order to understand social media behavioral addiction and gain deeper insights into the factors responsible for psychological stress and psychiatric disorders. In addition to cross-sectional studies, researchers should also conduct longitudinal studies and experiments to assess changes in users' behavior over time ( 20 ).

Another important area to examine is the role of engagement-based ranking and recommendation algorithms in online habit formation. More research is required to ascertain how algorithms determine which content type generates higher user engagement. A clear understanding of the way social media platforms gather content from users and amplify their preferences would lead to the development of a standardized conceptualization of social media usage patterns ( 89 ). This may provide a clearer picture of the factors that lead to problematic social media use and addiction. It has been noted that “misinformation, toxicity, and violent content are inordinately prevalent” in material reshared by users and promoted by social media algorithms ( 90 ).

Additionally, an understanding of engagement-based ranking models and recommendation algorithms is essential in order to implement appropriate public policy measures. To address the specific behavioral concerns created by social media, legislatures must craft appropriate statutes. Thus, future qualitative research to assess engagement based ranking frameworks is extremely necessary in order to provide a broader perspective on social media use and tackle key regulatory gaps. Particular emphasis must be placed on consumer awareness, algorithm bias, privacy issues, ethical platform design, and extraction and monetization of personal data ( 91 ).

From a geographical perspective, the authors have identified some main gaps in the existing knowledge base that uncover the need for further research in certain regions of the world. Accordingly, the authors suggest encouraging more studies on internet and social media addiction in underrepresented regions with high social media penetration rates such as Southeast Asia and South America. In order to draw more contributions from these countries, journals with high impact factors could also make specific calls. This would contribute to educating social media users about platform usage and implement policy changes that support the development of healthy social media practices.

The authors hope that the findings gathered here will serve to fuel interest in this topic and encourage other scholars to investigate social media addiction in other contexts on newer platforms and among wide ranges of sample populations. In light of the rising numbers of people experiencing mental health problems (e.g., depression, anxiety, food disorders, and substance addiction) in recent years, it is likely that the number of papers related to social media addiction and the range of countries covered will rise even further.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

AP took care of bibliometric analysis and drafting the paper. VB took care of proofreading and adding value to the paper. AS took care of the interpretation of the findings. All authors contributed to the article and approved the submitted version.

Conflict of interest

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.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: bibliometric analysis, social media, social media addiction, problematic social media use, research trends

Citation: Pellegrino A, Stasi A and Bhatiasevi V (2022) Research trends in social media addiction and problematic social media use: A bibliometric analysis. Front. Psychiatry 13:1017506. doi: 10.3389/fpsyt.2022.1017506

Received: 12 August 2022; Accepted: 24 October 2022; Published: 10 November 2022.

Reviewed by:

Copyright © 2022 Pellegrino, Stasi and Bhatiasevi. 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: Alfonso Pellegrino, alfonso.pellegrino@sasin.edu ; Veera Bhatiasevi, veera.bhatiasevi@mahidol.ac.th


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