case study about social media addiction

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Research trends in social media addiction and problematic social media use: A bibliometric analysis

Alfonso pellegrino.

1 Sasin School of Management, Chulalongkorn University, Bangkok, Thailand

Alessandro Stasi

2 Business Administration Division, Mahidol University International College, Mahidol University, Nakhon Pathom, Thailand

Veera Bhatiasevi

Associated data.

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

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.

Introduction

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 ).

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.

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 ).

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.

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

a Total link strength indicates the number of publications in which an author occurs.

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.

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.

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.

Frequency of occurrence of top 10 keywords.

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.

Implications

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

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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Unable to connect: a case study in social media addiction.

On Tuesday, Sept. 14, The Wall Street Journal published an article detailing three-years-worth of extensive research done by Facebook to better understand how Instagram—which the tech giant purchased in 2012—affects its users. Despite Facebook publicly downplaying and withholding this data, The Wall Street Journal reported that internal investigations have demonstrated that “Instagram is harmful for a sizable percentage of [users] , most notably teenage girls.” However, with or without quantifiable data, most users—chiefly its younger, Gen Z demographic—have been grappling with Instagram’s harmful effects for years.

In response to The Wall Street Journal ’s investigation, The Washington Post published an opinion piece discussing the larger issues elucidated by the research. The Washington Post ’s editorial board noted that in conversations about Instagram, it’s referred to “like it’s a drug” but that “we can’t study the active ingredient.” However, on Mon., Oct. 4, I got to see a real-life case study on Instagram addiction unfold before my very eyes. 

Upon waking up, I tried to begin my day the same way I have since I joined Instagram in 2011: by scrolling through my feed. I joined under the username “tigerlily5” in fifth grade—my biggest flex is I haven’t changed it since—and never looked back. The grip Instagram has had on me (and most users) for ten years is shocking. The longevity and consistent growth of the app is as impressive as it is disturbing. When I was met with a fateful “unable to connect” message and an empty feed, I shrugged it off and continued with my morning routine of perusing the rest of my social media platforms.

Throughout the day, I overheard conversations, read Twitter threads, and received texts about both Facebook and Instagram being down—something I have yet to be convinced was an accident. It was as if the world had stopped, the Gen Z equivalent to a stock market crash. Instagram users like me shuffled through other social media platforms to occupy ourselves. After Facebook and its other apps went dark at 11:40 a.m. (EST), Twitter HQ tweeted “hello literally everyone” only two hours later and received over 3 million likes. Twitter itself then experienced an influx of technical issues over the next two hours, highlighting the sheer volume of users seeking out other platforms to fill the stimulus void Instagram’s crash had generated. 

At 6:33 p.m. (EST) Facebook tweeted to share apologies and good news: 

“To the huge community of people and businesses around the world who depend on us: we’re sorry. We’ve been working hard to restore access to our apps and services and are happy to report they are coming back online now. Thank you for bearing with us.”

Within five hours, Facebook and its subsidiary apps slowly came back to life and so did the world. Companies could target their ads, photo dumps could be posted, and oversimplified infographics could circulate once more. We could all happily re-enter the Instagram echochamber of instant gratification and posturing. I could unpack the meaning of the latter, but that is a whole other article in and of itself.

The sentiments expressed in The Wall Street Journal investigation, The Washington Post piece, and countless other articles were not new to me. As a young woman, I have been acutely aware of the negative impact Instagram has on my self-image, psyche, and overall mental health. What blew me away, however, was the extent of the worldwide dependence on platforms like Instagram, Facebook, and WhatsApp. Small businesses and content creators lost revenue, family members using WhatsApp were stripped of their means of communication, and a large percentage of our world’s population confronted their inability to simply exist with their own thoughts.

One Twitter user (@TwitterOfGod) summed up the blackout perfectly : “ Instagram and Facebook are currently not working, as are democracy, society and a healthy sense of self.” Following the blackout, I continued to think critically about my relationship with Instagram, but it was the terrifying, empirical proof of social media’s drug-like quality that has stuck with me. Facebook and its subsidiaries have sunk their claws into virtually every aspect of our minds and they’re not letting go anytime soon.

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The Growing Case for Social Media Addiction

​dr. ofir turel, a leading researcher in technology addiction and an associate professor at csu fullerton, says compulsively checking instagram, facebook and twitter isn't just fun — it could be hurting our brains..

​Dr. O fir Turel o f CSU Fullerton, who researches how people become addicted to technology, estimates that five to 10 percent of the U.S. population could be at risk for social media addiction. Photo courtesy of CSU East Bay

​You know that warm feeling you get when you see lots of likes from a Facebook or Instagram post? That's the reward system of your brain lighting up like fireflies on a dark summer night. 

It's the same system activated in the brains of drug addicts.

"All addictions operate on the variable-reward system," says Ofir Turel, Ph.D., associate professor of information systems and decision sciences at the College of Business and Economics at California State University, Fullerton . A variable-reward system is one in which a person sometimes gets a reward — like that warm feeling — when they do something, but not always, and they don't know when that good feeling will come next.

Dr. Turel  rese​arches behavioral and managerial issues in technology-focused environments, including how people become pathologically addicted to technology; he estimates that five to 10 percent of Americans could meet the criteria for being at risk for social media addiction.

"We conducted studies that took concepts from the addiction realm and applied them in the case of social media and video games," exaplains Turel. Facebook has a lot of the features of an addictive activity, including ease of use, variable rewards and feelings of anxiety when we're not engaging with it.

"We have observed that the reward system [in the brain] is more active and more sensitive in people who present symptoms of addiction to social media," says Turel. 

"What it means is that social media provides rewarding experiences that generate dopamine in the brain, the same substance produced when we eat cake or have sex. Over time, it trains your brain to want to check social media more and more often."

It's like wine: it's OK to use a little bit, but when it becomes too much it creates problems.    — DR. OFIR Turel, ASSOCIATE PROFESSOR, CSU Fullerton 

The encouraging news is that the brain's self-control system was intact in most of Turel's subjects with addictive symptoms. A key difference between drug addiction and social media addiction is that with substance abuse, researchers find deficits in the self-control system of the brain as well.

"If people have a strong enough motivation to control their social media use, they can," says Turel. For example, if Facebook began users charging $200 an hour, most people would be able to reduce their use. By comparison, a drug like cocaine impairs self-control and breaking an addictive pattern is harder to do.

Are the Kids All Right?

Overuse of social media is much more problematic in children because their developing brain is more malleable. By the time we reach adolescence, our reward system begins to be more activated and develop faster. Not so for our self-control, though; this system isn't fully developed until the age of 21.

"When children are exposed to social media, they can overstimulate their reward center and increase their reward responsiveness," says Turel. He found that excessive and addictive use was associated with structural changes in the brain. In fact, the brain's reward system was actually smaller. A smaller system can process associations much faster.

"Society and academia push the use of technology to create efficiency, but at the same time we need to understand the potential negative effects," notes Turel. "To some extent it's like wine: it's OK to use a little bit, but when it becomes too much it creates problems. When we use technology we need to create boundaries around its use."

​​​5 Tips to Prevent Social Media Addiction

1.   Talk About It Just as parents talk to their kids about safe sex and avoiding drugs, they should be discussing social media usage, says Ofir Turel, Ph.D., associate professor at the College of Business and Economics at CSU Fullerton. "If you share why this behavior is problematic, a lot of changes can be achieved," he says, explaining that most people can act upon information if they are motivated enough.

2.   Set Boundaries The American Medical Association recommends that parents create goals and rules for media use that are in line with their family's values. HealthyChildren.org offers a  Family Media Plan  tool, including a Media Time Calculator.  

3. Practice  Screen Hygiene If parents check their devices at the dinner table, their children will be inclined to do the same. "You teach your kids what's appropriate and what's not appropriate by modeling the behavior. And it's not just about curtailing excessive use — it's teaching them about specific behaviors like cyberbullying, sexting or sharing personal photos," says Turel.

4. Strike a  Balance There is some merit to social media, says Turel. It can help many people feel more connected, and there is value in some video games, such as math games. "One of the biggest benefits of video games is improved hand-eye coordination, but you only have to play one hour a week. People need to take responsibility and determine what's good for them," he says. For example, 30 hours of video games a week for students during exam time could be detrimental.

5.  Turn Off Notifications Constant pings trigger the reward system in the brain, Turel says. "It's difficult for people to resist that, even when they're in the middle of something important." He also recommends removing social media apps from your phone and only checking social media on a desktop or laptop.

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Addictive potential of social media, explained

The curious title of Stanford psychiatrist Anna Lembke 's book, Dopamine Nation: Finding Balance in the Age of Indulgence , pays tribute to the crucial and often destructive role that dopamine plays in modern society.

Dopamine , the main chemical involved in addiction, is secreted from certain nerve tracts in the brain when we engage in a rewarding experience such as finding food, clothing, shelter or a sexual mate. Nature designed our brains to feel pleasure when these experiences happen because they increase our odds of survival and of procreation.

But the days when our species dwelled in caves and struggled for survival are long gone. Dopamine Nation explains how living in a modern society, affluent beyond comparison by evolutionary standards, has rendered us all vulnerable to dopamine-mediated addiction . Today, the addictive substance of choice, whether we realize it or not, is often the internet and social media channels, according to Lembke, MD.

"If you're not addicted yet, it's coming soon to a website near you," Lembke joked when I talked to her about the message of Dopamine Nation , which was published in August. This Q&A is abridged from that exchange.

Why did you decide to write this book?

I wanted to tell readers what I'd learned from patients and from neuroscience about how to tackle compulsive overconsumption. Feel-good substances and behaviors increase dopamine release in the brain's reward pathways .

The brain responds to this increase by decreasing dopamine transmission -- not just back down to its natural baseline rate, but below that baseline. Repeated exposure to the same or similar stimuli ultimately creates a chronic dopamine-deficit state, wherein we're less able to experience pleasure.

What are the risk factors for addiction?

Easy access and speedy reward are two of them. Just as the hypodermic needle is the delivery mechanism for drugs like heroin, the smartphone is the modern-day hypodermic needle, delivering digital dopamine for a wired generation.

The hypodermic needle delivers a drug right into our vascular system, which in turn delivers it right to the brain, making the drug more potent. The same is true for the smartphone; with its bright colors, flashing lights and engaging alerts, it delivers images to our visual cortex that are tough to resist. And the quantity is endless. TikTok never runs out.

What makes social media particularly addictive?

We're wired to connect. It's kept us alive for millions of years in a world of scarcity and ever-present danger. Moving in tribes safeguards against predators, optimizes scarce resources and facilitates pair bonding. Our brains release dopamine when we make human connections, which incentivizes us to do it again.

But social connection has become druggified by social-media apps, making us vulnerable to compulsive overconsumption. These apps can cause the release of large amounts of dopamine into our brains' reward pathway all at once, just like heroin, or meth, or alcohol. They do that by amplifying the feel-good properties that attract humans to each other in the first place.

Then there's novelty. Dopamine is triggered by our brain's search-and-explore functions, telling us, "Hey, pay attention to this, something new has come along." Add to that the artificial intelligence algorithms that learn what we've liked before and suggest new things that are similar but not exactly the same, and we're off and running.

Further, our brains aren't equipped to process the millions of comparisons the virtual world demands. We can become overwhelmed by our inability to measure up to these "perfect" people who exist only in the Matrix . We give up trying and sink into depression, or what neuroscientists called "learned helplessness."

Upon signing off, the brain is plunged into a dopamine-deficit state as it attempts to adapt to the unnaturally high levels of dopamine social media just released. Which is why social media often feels good while we're doing it but horrible as soon as we stop.

Is there an antidote to our addiction to social media?

Yes, a timeout -- at least for a day. But a whole month is more typically the minimum amount of time we need away from our drug of choice, whether it's heroin or Instagram, to reset our dopamine reward pathways. A monthlong dopamine fast will decrease the anxiety and depression that social media can induce, and enhance our ability to enjoy other, more modest rewards again.

If and when we return to social media, we can consolidate our use to certain times of the day, avoid certain apps that suck us into the vortex and prioritize apps that connect us with real people in our real lives.

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Is Social Media Addictive? Here’s What the Science Says.

A major lawsuit against Meta has placed a spotlight on our fraught relationship with online social information.

By Matt Richtel

A group of 41 states and the District of Columbia filed suit on Tuesday against Meta , the parent company of Facebook, Instagram, WhatsApp and Messenger, contending that the company knowingly used features on its platforms to cause children to use them compulsively, even as the company said that its social media sites were safe for young people.

“Meta has harnessed powerful and unprecedented technologies to entice, engage and ultimately ensnare youth and teens,” the states said in their lawsuit filed in federal court. “Its motive is profit.”

The accusations in the lawsuit raise a deeper question about behavior: Are young people becoming addicted to social media and the internet? Here’s what the research has found.

What Makes Social Media So Compelling?

Experts who study internet use say that the magnetic allure of social media arises from the way the content plays to our neurological impulses and wiring, such that consumers find it hard to turn away from the incoming stream of information.

David Greenfield, a psychologist and founder of the Center for Internet and Technology Addiction in West Hartford, Conn., said the devices lure users with some powerful tactics. One is “intermittent reinforcement,” which creates the idea that a user could get a reward at any time. But when the reward comes is unpredictable. “Just like a slot machine,” he said. As with a slot machine, users are beckoned with lights and sounds but, even more powerful, information and reward tailored to a user’s interests and tastes.

Adults are susceptible, he noted, but young people are particularly at risk, because the brain regions that are involved in resisting temptation and reward are not nearly as developed in children and teenagers as in adults. “They’re all about impulse and not a lot about the control of that impulse,” Dr. Greenfield said of young consumers.

Moreover, he said, the adolescent brain is especially attuned to social connections, and “social media is all a perfect opportunity to connect with other people.”

Meta responded to the lawsuit by saying that it had taken many steps to support families and teenagers. “We’re disappointed that instead of working productively with companies across the industry to create clear, age-appropriate standards for the many apps teens use, the attorneys general have chosen this path,” the company said in a statement.

Does Compulsion Equal Addiction?

For many years, the scientific community typically defined addiction in relation to substances, such as drugs, and not behaviors, such as gambling or internet use. That has gradually changed. In 2013, the Diagnostic and Statistical Manual of Mental Disorders, the official reference for mental health conditions, introduced the idea of internet gaming addiction but said that more study was warranted before the condition could be formally declared.

A subsequent stud y explored broadening the definition to “internet addiction.” The author suggested further exploring diagnostic criteria and the language, noting, for instance, that terms like “problematic use” and even the word “internet” were open to broad interpretation, given the many forms the information and its delivery can take.

Dr. Michael Rich, the director of the Digital Wellness Lab at Boston Children’s Hospital, said he discouraged the use of the word “addiction” because the internet, if used effectively and with limits, was not merely useful but also essential to everyday life. “I prefer the term ‘Problematic Internet Media Use,” he said, a term that has gained currency in recent years.

Dr. Greenfield agreed that there clearly are valuable uses for the internet and that the definition of how much is too much can vary. But he said there also were clearly cases where excessive use interferes with school, sleep and other vital aspects of a healthy life. Too many young consumers “can’t put it down,” he said. “The internet is a giant hypodermic, and the content, including social media like Meta, are the psychoactive drugs.”

Matt Richtel is a health and science reporter for The Times, based in Boulder, Colo. More about Matt Richtel

• Open access
• Published: 15 April 2024

Social media addiction: associations with attachment style, mental distress, and personality

• Christiane Eichenberg 1 ,
• Raphaela Schneider 1 &
• Helena Rumpl 1  

BMC Psychiatry volume  24 , Article number:  278 ( 2024 ) Cite this article

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Social media bring not only benefits but also downsides, such as addictive behavior. While an ambivalent closed insecure attachment style has been prominently linked with internet and smartphone addiction, a similar analysis for social media addiction is still pending. This study aims to explore social media addiction, focusing on variations in attachment style, mental distress, and personality between students with and without problematic social media use. Additionally, it investigates whether a specific attachment style is connected to social media addiction.

Data were collected from 571 college students (mean age = 23.61, SD  = 5.00, 65.5% female; response rate = 20.06%) via an online survey administered to all enrolled students of Sigmund Freud PrivatUniversity Vienna. The Bergen Social Media Addiction Scale (BSMAS) differentiated between students addicted and not addicted to social media. Attachment style was gauged using the Bielefeld Partnership Expectations Questionnaire (BFPE), mental distress by the Brief Symptom Inventory (BSI-18), and personality by the Big Five Inventory (BFI-10).

Of the total sample, 22.7% of students were identified as addicted to social media. For personality, it was demonstrated that socially media addicted (SMA) students reported significantly higher values on the neuroticism dimension compared to not socially media addicted (NSMA) students. SMA also scored higher across all mental health dimensions—depressiveness, anxiety, and somatization. SMA more frequently exhibited an insecure attachment style than NSMA, specifically, an ambivalent closed attachment style. A two-step cluster analysis validated the initial findings, uncovering three clusters: (1) secure attachment, primarily linked with fewer occurrences of social media addiction and a lower incidence of mental health problems; (2) ambivalent closed attachment, generally associated with a higher rate of social media addiction and increased levels of mental health problems; and (3) ambivalent clingy attachment, manifesting a medium prevalence of social media addiction and a relatively equitable mental health profile.

Conclusions

The outcomes are aligned with previous research on internet and smartphone addiction, pointing out the relevance of an ambivalent closed attachment style in all three contexts. Therapeutic interventions for social media addiction should be developed and implemented considering these findings.

Peer Review reports

Introduction

Digital media have become ubiquitous. As of April 2023, 5.18 billion people worldwide use the Internet [ 1 ]. On average, global Internet users spend 6 h and 43 min online daily [ 2 ]. In 2023, social media platforms engage 4.8 billion users worldwide, a significant rise from 2.46 billion in 2017 [ 1 , 2 ]. These users spend an average of 2 h and 25 min on social networks each day and have, on average, 8.9 social media accounts [ 2 ]. Smartphones, now an essential device for many, are especially popular among the youth. Specifically, teenagers aged 14 to 24 access their phones approximately 214 times daily [ 3 ]. While social media networks have grown in importance, they also introduce challenges. Issues such as social media fatigue manifest in negative emotional responses like burnout, exhaustion, and frustration during social network activities [ 4 ]. Another possible negative consequence of social media activity is addictive behavior that is reported prior in the context of internet addiction.

Classification and definition of social media addiction

Digital media addictions, with a particular emphasis on social media addictions, are increasingly prevalent in psychotherapy, especially among younger demographics [ 5 , 6 ]. The concern for social media addiction is heightened among females, who show a higher propensity towards this addiction [ 7 , 8 ]. Despite its growing prevalence, social media addiction is yet to be fully acknowledged in diagnostic classification systems. The term “addiction” is therefore only used in this context for the sake of simplicity, as it is not yet officially recognized. The concept of ‘behavioral addiction,’ which characterizes excessive, rewarding behaviors leading to psychological addiction symptoms [ 9 ], is applicable here, though social media addiction still lacks distinct recognition in diagnostic manuals like the ICD and DSM. This gap highlights the need for more comprehensive research and understanding.

Prior research conforms mainly to differentiate between generalized and specific internet addictions [ 10 , 11 , 12 , 13 ]. The first means a multidimensional misuse of the internet using multiple internet functions, whereas the ladder aims a sole specific internet function (e.g., gaming, gambling, social media etc.) [ 13 , 14 ]. Social Media Addiction, encompassing variants like Facebook addiction and general addictive use of social networking sites (SNSs), is characterized as a maladaptive psychological dependency on SNSs, leading to behavioral addiction symptoms [ 15 , 16 , 17 ]. Currently, Social Media Addiction assessment relies on questionnaires like the Bergen Social Media Addiction Scale (BSMAS [ 18 ]),, which is momentarily the most widely used tool and applies criteria such as salience, mood modification, tolerance, withdrawal, conflict, and relapse [ 19 ] to evaluate addictive behaviors [ 10 ].

Prevalence rates and mental stress correlations of social media addiction

Data regarding the prevalence of social media addiction indicate a range between 1% and 18.7% [ 20 ]. However, the accuracy of these rates is debated. Cheng et al. [ 21 ] suggest that estimates of social media addiction are often either under- or overestimated. Their recent meta-analysis revealed prevalence rates ranging from 0 to 82%, a wide disparity stemming from differing theoretical frameworks and measurement instruments. Depending on the strictness of the classification system used, the researchers identified three mean prevalence benchmarks: 5%, 13%, and 25%. Frequently, individuals with problematic social media use also grapple with other mental health issues. Depression [ 20 , 22 ] and social anxiety [ 23 ] are commonly co-occurring disorders, as are challenges related to self-esteem (ibid.). Particularly, young women often feel dissatisfied with their bodies due to social media engagement. The frequent exposure to manipulated and idealized images of models or influencers fuels a comparison culture. As a result, many young women develop a desire to alter their appearance [ 24 ]. The number of “likes” they receive on platforms becomes a proxy for their self-worth, heavily influencing their self-esteem [ 25 ]. Several studies highlight that young adults spending over two hours daily on social media tend to exhibit higher rates of anxiety, depression, and sleep disturbances.

Personality traits and social media addiction

The personality trait neuroticism, and the “fear of missing out” or FOMO [ 26 ], have been identified as predictors of Social Media Addiction [ 27 ]. Conversely, extraversion’s link to social media use is debated. While some evidence suggests extraversion is not a significant factor [ 28 ], other research indicates extraverted individuals are more prone to social media use and potential addiction. Kuss & Griffiths [ 29 ] offer a more nuanced view in their literature review. According to them, extraverted individuals might use social media to augment their social interactions, i.e. they use social media in a positive manner to expand opportunities to interact with others in more ways. Introverted users, on the other hand, use social media to compensate for a perceived social deficit. For them, using social media is a way to connect with others in a way that they feel is not sufficiently possible in real life.

Attachment styles and social media addiction

Extensive research has been conducted on the association between insecure attachment and substance addictions [ 30 , 31 ]. The attachment system, which comprises secure, insecure, and disorganized categories, is a biologically and evolutionarily rooted motivational and behavioral system that operates through attachment figures [ 32 ]. Schuhler et al. [ 33 ] proposed a model elucidating the link between internet addiction and attachment, suggesting that addictive behaviors may arise as a means to compensate for attachment issues. From this perspective, digital addiction represents a flawed attempt to address early attachment deficiencies [ 33 , 34 ]. In a related vein, Brisch [ 35 ] introduced a model that positions the ‘reference object’ as central to the understanding of addictions. According to this model, the primary function of social media addiction isn’t to escape negative emotions, as is often the case with substance addictions. Instead, it’s seen as an excessive digitally-mediated social behavior aiming to substitute for insecure attachments. Supporting this, Eichenberg et al. [ 34 ] showed that insecure attachment style is correlated with problematic smartphone usage and problematic internet usage [ 36 ]. Notably, an ambivalently attached style was identified as particularly relevant in both contexts. A plethora of studies showed a link between social media addiction and attachment in general [ 37 , 38 , 39 , 40 , 41 , 42 , 43 ]. But the question arises whether the specific attachment style as has shown relevant for internet and smartphone addiction will also be prominent for social media addiction.

Research objectives and questions

The primary objective of this study is to explore whether an insecure attachment style correlates with addictive social media use, and to pinpoint which specific style is most relevant. While research has identified an ambivalent closed insecure attachment style as being significant in the context of internet and smartphone addiction, a detailed examination specific to social media addiction remains lacking.

Moreover, this study seeks to gather further information regarding the still emerging psychopathology, specifically focusing on the personality traits neuroticism and extraversion, as well as mental stress.

Mental health

The research questions will be, whether social media addicted students report higher levels of depression, anxiety, and somatization.

• Personality

Further, it will be explored whether neuroticism and extraversion influence an individual’s susceptibility to social media addiction.

Recruitment

A comprehensive survey ( N  = 2846, response rate = 20.06%) was created with the SoSci Survey online survey tool [ 44 ] and was conducted among students at the Sigmund Freud PrivatUniversität in Vienna, Austria. The data collection took place from January to March 2021, resulting in a final sample of 571 respondents. To distribute the online questionnaire, the Study Service Centers from the faculties of psychology, psychotherapy, law, and medicine were approached. They were requested to email the link to the questionnaire, accompanied by a pre-written invitation text, to all actively enrolled students at the Sigmund Freud PrivatUniversität Vienna. Once the participants provided informed consent and completed the survey, they were redirected to a debriefing page. This page detailed the study’s objectives and offered the contact information of the researchers, in case the participants sought support related to the survey topics or had additional inquiries. The survey received approval from the Ethics Commission of the Faculty of Psychotherapy Science and the Faculty of Psychology of the Sigμund Freud University PrivatVienna. Recognizing the sensitive nature of the topic, paramount emphasis was placed on safeguarding the confidentiality of participants’ responses. Furthermore, participants had the liberty to opt out of the study at any juncture. Should they wish to have their data expunged, they could simply reach out to a researcher via email, referencing an unique anonymized code. This would enable the researcher to identify and delete the participant’s anonymized data.

Survey structure

The survey, created using Sosci-Survey, began with a brief that outlined the research rationale and the survey’s objectives. Participants affirmed their agreement with the study’s privacy policy through a checkbox.

Section 1 asked about socio-demographic factors, including age, gender, and study subject. Subsequently, it touched upon matters related to social media:

Services most used : Participants identified which social media services they frequently use, answered dichotomously (yes/no).

Usage frequency : Choices ranged from “less than 30 minutes” to “more than four hours per day” on a seven-point scale.

Social Media Importance : Participants rated from “very significant” to “not significant” on a four-point scale.

Purposes of Use : Employing a five-point scale, respondents indicated frequency, ranging from 1 (“never”) to 5 (“several times a day”).

Perceived downsides : Participants assessed their sentiments on a five-point scale from 1 (“not true at all”) to 5 (“completely true”).

In light of evidence suggesting a discrepancy between objective and self-reported usage time—where users often overestimate their screen time [ 45 ]—the survey did not deploy open-ended questions concerning usage duration. Instead, participants were presented with predefined categories to streamline their responses.

Section 2 incorporated standardized questionnaires to examine further social media addiction, mental distress, personality traits, and attachment styles.

Bergen social media addiction scale BSMAS [ 18 ]

The Bergen Social Media Addiction Scale (BSMAS) [ 18 ] categorizes users into two groups: those addicted to social media and those not addicted. All six items pertain to one’s experience with social media over the past 12 months. It employs a five-point scale, ranging from 1 (“very rarely”) to 5 (“very often”). The scale asks at the beginning of each item “How often during the last year have you…” and continues with “…spent a lot of time thinking about social media or planned use of social media?” (i.e., salience) or “…become restless or troubled if you have been prohibited from using social media?” (i.e., withdrawal). A higher BSMAS score indicates a heightened risk of social media addiction. As suggested by a substantial Hungarian study involving 6000 adolescents [ 20 ], a cutoff score of 19 out of 30 was adopted. The scale was repeatedly reported with high internal consistency, e.g., α = 0.97 [ 46 ] and α = 0.82 (at baseline) plus α = 0.86 (at follow-up) [ 10 ]. Chen et al. [ 10 ] confirm the single-factor structure of the scale, report only medium correlations with scales close to the construct (SABAS/smartphone addiction, IGDS-SF9/internet gaming disorder, r  =.06 and 0.42), and showed invariance across three months among young adults. They presented a good test–retest reliability after three months ( ICC  = 0.86, p  <.001).

Brief symptom inventory BSI-18 [ 47 ]

The BSI-18 is a brief, reliable instrument for assessing mental stress. It contains the three subscales somatization, depression, and anxiety, comprising 6 items, as well as the Global Severity Index (GSI) including all 18 items. Response format of the 18 items is a five-point scale (0=”not at all” to 4=”very strong”). The scale asks at the beginning of a symptoms list: “How much have you had within the past 7 days…”. Examples for the symptoms on this list are “Nausea or upset stomach” for somatization, “Feelings of worthlessness” for depression”, and “Spells of terror or panic” for anxiety. The BSI-18 is the newest and shortest of the multidimensional versions of the Symptom Checklist 90-R. The BSI-18 assesses validly mental stress in both normal population [ 48 ] and clinical populations [ 49 ]. Confirmatory analyses confirm the three-factor structure [ 48 ]. Franke et al. [ 49 ] report good internal consistencies of the scales fear of rejection (BSI-18 (α (somatization) = 0,79, α (depression) = 0,84, α (anxiety) = 0,84, α (GSI) = 0,91).

Big five inventory BFI-10 [ 50 ]

The questionnaire is based on the Big Five personality traits model, also called OCEAN model that is the most widely used model for describing overall personality [ 51 ]. Theoretical background is the sedimentation hypothesis that assumes that every personality trait must be represented in language and, therefore, factor analyses were used to find universal personality dimensions [ 52 ]. Multiple analyses by various researchers resulted repeatedly in the OCEAN model, which consists of the five dimensions agreeableness, neuroticism, conscientiousness, openness to experience, and extraversion. The BFI-10 [ 50 ] contains 10 items, two for each of the five dimensions. The scale asks, “How well do the following statements describe your personality?” and starts a list of attitudes with “I see myself as someone who…“. Example answers are: “…does a thorough job” (i.e., conscientiousness) or “…is outgoing, sociable” (i.e., extraversion). Respondents answered a five-point rating scale from “does not apply at all” (1) to “applies completely” (5) for each item. Rammstedt und John [ 50 ] report moderate test–retest reliability after 6 weeks in a student sample (agreeableness: rtt  = 0.58, neuroticism: rtt  = 0.74, conscientiousness: rtt  = 0.77, openness to experience: rtt  = 0.72, extraversion: rtt  = 0.84). In a representative sample, however, the retest coefficients are lower overall ranging from ( rtt  =.62) for openness to experience to ( rtt  =.49) for neuroticism [ 51 ]. Rammstedt et al. [ 51 ] report sufficient construct validity correlating the BFI-10 with the NEO-PI-R and factorial validity by conducting principal component analyses on a representative sample.

Bielefeld questionnaire on partnership expectations BFPE [ 53 ]

The BFPE operationalizes attachment styles of adults by recording self-reports on three scales: conscious need for care (8 items), fear of rejection (11 items), and readiness for self-disclosure (11 items) [ 53 ]. Example items are: “Knowing myself as I do, I can hardly imagine that my partner will appreciate me” (i.e., fear of rejection), “I prefer to talk with my partner about facts rather than about feelings” (i.e., readiness for self- disclosure), and “It’s important for me that my partner thinks of me often, even when we are not together” (i.e., conscious need for care). The first of the 31 items serves as an icebreaker item and is not evaluated. The degree of expression of each item is indicated on a 5-point scale (1= “does not apply at all” to 5 = “applies exactly”). From the aggregate scores of these scales, one of five attachment styles can be determined: secure, two variations of ambivalent/anxious (closed and clinging), and two variations of the avoidant style (closed and conditionally secure). For simplification purposes, these styles can be dichotomized into two primary categories: secure (which includes both secure and conditionally secure types) and insecure (encompassing avoidant-closed, ambivalent-clingy, and ambivalent-closed types). These distinct attachment styles emerged originally from cluster analysis research [ 53 ]. Höger and Buschkämper [ 53 ] report good internal consistencies of the scales fear of rejection (Cronbach’s α = 0.88), readiness for self-disclosure (Cronbach’s α = 0.89), and conscious need for care (Cronbach’s α = 0.77). The split-half reliabilities calculated according to Guttman and Spearman-Brown are also similarly good for the three scales (fear of rejection = 0.91, readiness for self-disclosure = 0.89, and conscious need for care = 0.77). A validation is based on a German translation of the “Adult Attachment Scale” (AAS [ 54 ]),.

Statistical analysis

The Statistical Package for the Social Sciences Program (SPSS version 27) was used for data input, processing, and statistical analyses. The participants were divided into social media addicted (SMA) and not addicted (NSMA) using the cut-off score according to Bányai et al. [ 20 ]. Additionally, the percentage of social media dependent students has been calculated. To evaluate differences between SMA and NSMA in social media usage, Mann-Whitney U tests for two independent samples were analyzed for differences in downsides of social media and usage purposes, and chi-square tests for differences in social media services, usage frequency, and social media importance, as the corresponding data were not normally distributed. Based on the data obtained with the BFPE, participants were allocated (see above) to the five attachment styles “secure,” “conditionally secure,” “ambivalent clingy,” “ambivalent closed,” and “avoidant closed.” Subsequently, the five attachment styles were dichotomized into the variables “secure” and “insecure” attachment styles. Subsequently, the five attachment styles were dichotomized into the variables “secure” and “insecure” attachment styles. Finally, using the chi-square tests, attachment styles and social media addiction were tested for significance differences. While chi-square tests provide valuable insights into individual associations, a two-step cluster analysis was conducted to gain a comprehensive understanding of how these variables collectively group participants. Two-step cluster analysis was chosen due to its capacity to handle both continuous and categorical variables. The number of clusters was determined based on the Schwarz Bayesian Criterion (BIC), and the selected model was further validated by examining the silhouette measure of cohesion and separation. Since gender and age are variables that could influence social media addiction, they were included in the cluster analysis to investigate their distribution over the resulting clusters. To maintain robustness of analyses, the non-binary gender category was omitted due to very small case number.

The total sample ( N  = 571) consisted of 65.5% female students ( n  = 374) 33.3% male students ( n  = 190), and 1.2% those who did not wish to be defined by these two genders ( n  = 7). Participants were between 18 and 60 years old ( M  = 23.61 years, SD  = 5.00, median = 23, modus = 22). The distribution of study subject was the following: medicine ( n  = 344, 59.7%), psychology ( n  = 121, 21.0%), psychotherapy ( n  = 79, 13.7%), and law ( n  = 32, 5.6%) (some students studied two subjects).

• Social media addiction

A total of 131 people (22.7% of the total sample) could be classified as addicted to social media. In addition, it was also relevant how genders were distributed between the two groups. Of the total number of participants classified as addicted participants ( N  = 131), 79.39% were female, 19.08% male, and 1.53% non-binary. These values are to be contrasted with the group of not addicted ( N  = 440), in which 61.36% were female, 37.5% male, and 1.14% non-binary.

Social media usage

Among the various social media platforms, “WhatsApp” was the predominant choice with 99.1% usage. It was trailed by “YouTube” at 91.2%, “Instagram” at 82.1%, “Facebook” at 66.9%, “Snapchat” at 63.7%, “Facebook Messenger” at 35.6%, “Pinterest” at 32.9%, and “Twitter” at 10.5%. In addressing frequency of use, a significant 91% indicated they access social media multiple times per day. Delving into the duration of daily usage: 12.8% were on for less than an hour, 25.6% used it for around an hour, 32.7% for two hours, 16.8% for three hours, and 12.1% devoted more than three hours. When participants were asked about the significance of social media, 8.9% viewed it as very important, 55.1% as important, 31.3% as less important, and a mere 4.7% as not important. Participants predominantly engaged with social media for “entertainment” ( M  = 4.17, SD  = 1.05), staying “up to date” ( M  = 4.12, SD  = 1.03), combating “boredom” ( M  = 3.94, SD  = 1.22), maintaining “contact with family” ( M  = 3.86, SD  = 1.2), and for “music” ( M  = 3.55, SD  = 1.4). They also sought “inspiration (e.g., fashion, interior)” with a mean score of ( M  = 3.35, SD  = 1.29). However, not all experiences were positive. Downsides associated with social media usage were led by “comparison with others” ( M  = 3.19, SD  = 1.3), followed by “dissatisfaction with own body” ( M  = 2.55, SD  = 1.38), “negative self-esteem in contact with influencers” ( M  = 2.23, SD  = 1.32), and encountering “insults, intrusive behavior” ( M  = 1.88, SD  = 1.3). Distinguishing between SMA and NSMA users, differences emerged in their consumption patterns (see for details Table  1 ). SMA users predominantly gravitated towards image-centric platforms such as “Instagram” (93.1% SMA vs. 78.9% NSMA) and “Pinterest” (46.6% SMA vs. 28.9% NSMA). Remarkably, SMA users expressed heightened concerns regarding the downsides “comparison with others” ( M  = 4.06, SD  = 1.03 for SMA vs. M  = 2.94, SD  = 1.26 for NSMA), “dissatisfaction with own body (when viewing idealized bodies online)” (M = 3.45, SD = 1.34 for SMA vs. M  = 2.28, SD  = 1.28 for NSMA), and “negative self-esteem in contact with influencers” ( M  = 3.16, SD  = 1.34 for SMA vs. M  = 1.95, SD  = 1.18 for NSMA). It became evident that SMA users faced enhanced negative repercussions, especially in terms of body perception when comparing themselves with images of others. In addition, SMA use social media as tool for more purposes than NSMA. Not addicted report here, to use social media only for contact with family and music equally often.

Attachment style

Since 12 participants did not completely fill in the BFPE, the number of participants regarding attachment is 559. Frequencies and percentages of each attachment style can be seen in Table  2 . A small part of the student population was securely bound ( n  = 88, 15.7%) with the biggest part being insecurely bound ( n  = 471, 84.3%). Secure attachment style (corrected residuals: 3.1) is related to a disproportionately higher number of NSMA and insecure attachment style (corrected residuals: 3.1) is related to a disproportionately higher number of SMA, χ² (1) = 9.28, p = .002, C  = 0.13 (see Fig.  1 , see Table  3 ). The five individual attachment styles differ in the frequency distribution of social media addiction, χ² (4) = 30.75, p < .001, C  = 0.24, with avoidant closed (corrected residuals:3.2) having disproportionately more NSMA, ambivalent closed (corrected residuals: 4.8) having disproportionately more SMA, and conditionally secure (corrected residuals: 2.4) having disproportionately more NSMA (see Fig.  2 ). So, findings show that participants with social media addiction had a significant higher likelihood to have an ambivalent closed attachment style.

Relationship between attachment style and social media addiction. This stacked bar chart depicts the proportion of participants with ‘secure’ and ‘insecure’ attachment styles as determined by the Bielefeld Questionnaire on Partnership Expectations (BFPE). Attachment styles are defined by responses to three scales: conscious need for care, fear of rejection, and readiness for self-disclosure. These styles are subsequently dichotomized into ‘secure’ (including secure and conditionally secure styles) and ‘insecure’ (including avoidant-closed, ambivalent-clingy, and ambivalent-closed styles). Dark gray bars represent participants not addicted to social media, while light gray bars represent those with a self-reported addiction determined by the Bergen Social Media Addiction Scale (BSMAS). The numbers within the bars indicate the count of participants in each category

Distribution of five attachment styles and social media addiction. This bar chart visualizes the proportion of participants classified into five distinct attachment styles according to the Bielefeld Questionnaire on Partnership Expectations (BFPE) alongside their social media addiction status, as measured by the Bergen Social Media Addiction Scale (BSMAS). The attachment styles represented are ‘avoidant closed’, ‘conditionally secure’, ‘secure’, ‘ambivalent clingy’, and ‘ambivalent closed’. Dark gray bars indicate participants not identified as addicted to social media, while light gray bars represent those who meet the criteria for addiction according to the BSMAS. The numbers within the bars denote the count of participants corresponding to each category

Regarding extraversion, the total sample ( M  = 3.58, SD  = 0.92, modus = 5, Md  = 3.5) is slightly but significantly less open-minded than a norm sample having same age and education ( M  = 3.93, SD  = 0.83, Rammstedt et al. 2012) ( t (570)=-9.23, p < .001) and regarding neuroticism, the sample ( M  = 3.09, SD  = 0.87, modus = 2.5, Md  = 3) is significantly more neurotic than a comparable norm sample ( M  = 2.25, SD  = 0.69, Rammstedt et al. 2012) ( t (570) = 23.15, p < .001). Further, it was found that SMA ( M  = 3.40, SD  = 0.85) scored significantly higher than NSMA ( M  = 3.00, SD  = 0.85) on the dimension of neuroticism and thus could be classified as more emotionally unstable ( U  = 20636.50, Z = -5.02, p < .001). However, on the dimension of extraversion, SMA ( M  = 3.56, SD  = 0.85) did not differ from NSMA ( M  = 3.58, SD  = 0.94) ( U  = 28408.5, Z  = − 0.25, p = .801).

• Mental distress

The total sample showed in comparison with a norm sample high levels of each of the three dimensions of depression ( M  = 4.18; SD  = 4.52 vs. M norm =1.27; SD norm =2.5, Franke et al. 2017) ( t (570) = 15.40, p < .001), anxiety ( M  = 3.67; SD  = 4.30, vs. M norm =1.09; SD norm =2.1, ibd.) ( t (570) = 14.35, p < .001), and somatization ( M  = 2.23, SD  = 3.00, vs. M norm =0.70; SD norm =14.8, ibd.) ( t (570) = 12.18, p < .001). Moreover, SMA reported still higher scores on all three scales of the BSI-18: depression (SMA M  = 7.93, SD  = 5.25, NSMA M  = 3.06, SD  = 3.59) ( U  = 11,606, Z = -10.47, p < .001), anxiety (SMA M  = 6.18, SD  = 5.34, NSMA M  = 2.92, SD  = 3.61) ( U  = 16,841, Z = -7.31, p < .001), and somatization (SMA M  = 3.60, SD  = 4.02, NSMA M  = 1.82, SD  = 2.48) ( U  = 19,730, Z = -5.64, p < .001) than NSMA. Spitzer et al. (2011) reported BSI-18 patient scores relatively close to SMA scores for depression (mean scores ranging from 6.17 to 11.61) and anxiety (mean scores ranging from 6.26 to 9.51), but not for somatization (mean scores ranging from 6.47 to 6.90). It can therefore be assumed that students in this sample are generally more mentally stressed, with students who are addicted to social media being particularly mentally stressed. This finding could be explained due to the high distress and burden in the early phase of the COVID19 pandemic.

Two-step cluster analysis

The two-step cluster analysis suggested a three-cluster solution as the most appropriate fit. Evaluation of the centroids of continuous variables (Table  4 ) and frequencies of the categorical cluster composition (Table  5 ) result in the following clusters:

The Cluster ambivalent clingy attachment (ACA) ( N  = 178) is relatively balanced in terms of extraversion, neuroticism, depression, anxiety, and somatization. They are uniquely characterized by the ambivalent clingy attachment style with a balanced representation of social media dependence.

The Cluster secure attachment (SA) ( N  = 140) is characterized by individuals who are slightly extroverted, less neurotic, and show lower levels of depression, anxiety, and somatization. This cluster stands out due to its representation of secure and rather secure attachment styles and has the lowest proportion of individuals who are addicted to social media.

The Cluster ambivalent closed attachment (AVA) ( N  = 231) is slightly introverted, more neurotic, and exhibits higher levels of depression and anxiety. Participants of this cluster are exclusively of the ambivalent closed attachment style, and a significant portion seems more susceptible to social media addiction.

For the validation of the derived clustering solution, the Bayesian Information Criterion (BIC) was employed as a model selection criterion to identify the optimal number of clusters. The BIC is advantageous in balancing the goodness of fit of the model against its complexity, penalizing models with more parameters to avoid overfitting. Various numbers of clusters were considered, ranging from 1 to 15, and the corresponding BIC values were calculated for each cluster solution. Table  6 presents the BIC values obtained for different cluster solutions. The BIC drops substantially from 1 cluster to 2 clusters, indicated by a change of -1180.384. There is a smaller but still notable drop from 2 clusters to 3 clusters, with a change of -605.464. After 3 clusters, the BIC drops more slowly, with smaller changes for each additional cluster. Even if the ratio for the change from 2 to 3 clusters is 0.512, the ratio of distance measures that indicates how distinct the clusters are from each other is for the 3-cluster solution still 1.780, which suggests that the 3-cluster solution is equally well-defined compared to the 2-cluster solution. Given this information, we opt for the 3-cluster solution, since the BIC drops more slowly beyond this point, suggesting diminishing returns in terms of model fit as more clusters are added and the 3-cluster solution offers a sufficient granular segmentation. The distribution of age (Table  4 ) and gender (Table  5 ) was relatively even.

Principal results

This study aimed to examine social media addiction with a focus on differences in attachment style, mental distress, and personality between students with and without social media addiction. For personality, it was shown that SMA had significantly higher values on the neuroticism dimension than NSMA, but they did not differ in the extraversion dimension. Thus, SMA can be classified as more emotionally unstable in comparison with NSMA. Further, SMA scored significantly higher on all three levels—depressiveness, anxiety, and somatization—than the group of NSMA, i.e., social media addicted users are comparatively more mentally stressed. At least for attachment style, the assumption that SMA are more likely to show an insecure attachment was confirmed here. In more detail, most SMA displayed an ambivalent closed attachment style. Two-step cluster analysis yielded a holistic insight into the collective grouping of cases by these variables. It corroborated the findings of the univariate analyses, revealing three predominant clusters, chiefly characterized by three attachment styles and varying levels of social media addiction: (a) secure attachment, predominantly associated with fewer instances of social media addiction and lower prevalence of mental health problems; (b) ambivalent closed attachment, typically marked by a higher frequency of social media addiction and elevated levels of mental health problems; and (c) ambivalent clingy attachment, presenting a moderate incidence of social media addiction and a relatively balanced mental health profile.

Prevalence rate of social media addiction (22.8%) lies within the literature reported prevalence of the used instrument (BSMAS), since Chen et al. [ 10 ] specify < 10–40% for the BSMAS. SMA differ from NSMA in their usage of social media, exhibiting higher values in usage frequency, time spent, and perceived importance. Notably, SMA are more active on image-oriented services such as “Instagram” and “Pinterest”. They also report higher levels of “comparison with others”, “dissatisfaction with their own body (especially when exposed to idealized online images)”, and “negative self-esteem when interacting with influencers”. This suggests that SMA may experience heightened negative body awareness when comparing themselves to online images. Moreover, SMA use social media for a broader range of purposes compared to NSMA.

SMA scored significantly higher on the neuroticism dimension than NSMA, suggesting that they tend to be more emotionally unstable and easily irritable. Conversely, no difference was observed in the extraversion dimension. Previous research supports the idea that internet-related addictions are linked to higher scores on the neuroticism dimension. Blackwell et al. [ 27 ] demonstrated that neuroticism predicts social media use. Moreover, a study by Müller [ 55 ] suggests that Internet addiction correlates with increased neuroticism scores. Interestingly, individuals with elevated neuroticism scores associate Internet topics with significantly stronger positive arousal compared to a healthy control group [ 56 ]. Social media addiction has also been positively linked to neuroticism [ 27 , 28 ], and individuals scoring high on this trait are drawn to social networks as they offer recognition and validation [ 27 ]. Marengo et al. [ 28 ] align with our findings by not observing a relationship between social media addiction and extraversion. The contrasting findings presented by Kuss and Griffiths [ 29 ] relate extraversion more to older individuals and openness more to younger ones. Given our primary focus on younger participants, our results are consistent with these observations.

SMA display significantly higher values for depression, anxiety, and somatization compared to NSMA, even considering the evident distress in the overall sample. This suggests that SMA may be mentally more strained than NSMA. Consequently, further evidence for the connection between mental disorders and internet-related addictions in terms of comorbidity was found in the present study. This augments the extant research on depression, anxiety, and internet addiction. Kırcaburun [ 57 ] also identified a significant positive relationship between depressive symptoms, internet use, and social media addiction. In his study, the level of depression in adolescents was indirectly influenced by social media addiction; addicts spent more time online, amplifying the risk of depressive symptoms. Similarly, Wu et al. [ 58 ] found that internet addiction correlates with depression in adolescents, exerting direct, mediated, and moderating effects on depression levels. For anxiety, there’s also documented evidence of a positive association with problematic social media consumption. Baltaci [ 23 ] highlighted social anxiety as a predictor for social media addiction among university students. Other studies have shown a positive correlation between internet addiction and general anxiety levels in students [ 59 , 60 ]. As for somatization, there’s a documented positive correlation with internet addiction in adolescents [ 61 , 62 , 63 ]. Research on somatization and smartphone addiction is somewhat limited [ 63 ]. Results here confirm the positive correlation adding to this research corpus also heightened somatic symptomatology in social media addicted students.

Users with an insecure attachment style are significantly more likely to exhibit social media addiction than those with a secure attachment style. These findings align with a substantial body of research that establishes a connection between insecure attachment styles and internet-related addictions. A systematic review has provided evidence linking insecure attachment styles with both internet addiction in general and social media addiction in particular [ 64 ]. Moreover, certain studies suggest that difficulties in relational behavior or the presence of insecure attachment styles can act as risk factors for smartphone addiction. For instance, Baek et al. [ 65 ] identified a correlation between attachment behavior (specifically internalization problems) and smartphone usage. Other research [ 66 , 67 ] has indicated a mediating effect of attachment style on smartphone addiction. Anxiously attached individuals showed patterns of self-regulation that directly influenced their susceptibility to smartphone addiction. While a secure attachment style offered a protective effect, an anxious attachment style increased vulnerability to addiction. In contrast, an avoidant attachment style didn’t significantly influence addiction development.

For social media addiction, several studies have highlighted its relationship with attachment. For instance, Hart et al. [ 37 ] demonstrated a link between dysfunctional attachment qualities and problematic social media use. A study involving Turkish students revealed that insecure attachment styles might serve as risk factors for social media addiction [ 38 ]. Conversely, secure attachment and high self-esteem can act as protective factors against such addiction [ 38 ]. Numerous studies have established a connection between an anxious attachment style and both heavy social media use [ 39 , 40 , 41 ] and addiction to it [ 42 ]. Specifically, Yaakobi and Goldenberg [ 43 ] identified a positive correlation between an anxious attachment style and the amount of time spent on social media. This same study found that an anxious attachment style negatively predicts the number of online friends. Oldmeadow et al. [ 41 ] also discovered a relationship between anxious attachment and seeking comfort on Facebook, noting an increase in Facebook usage, especially during negative emotional states.

Currently, no studies explore the relationship between an ambivalent closed attachment style and social media addiction. However, the findings in this study indicate that an ambivalent closed attachment style is significantly associated with social media addiction more frequently. These results are consistent with previous data suggesting this style is prevalent for internet-related addictions, as observed in the context of both smartphone [ 34 ] and internet [ 36 ] addictions. According to Höger and Buschkämper [ 53 ], individuals with an ambivalent attachment style exhibit an increased need for attention and concurrently face heightened acceptance issues. This pattern suggests heightened anxiety and a secondary hyperactivating (ambivalent) strategy (ibid.). It’s plausible that the social-compensatory component is particularly influential in this context when it comes to social media [ 34 ]. Individuals with an ambivalent-closed attachment style might turn to online platforms, especially social media, to mitigate their interpersonal relationship deficits (ibid.). The anonymity afforded by the internet allows a new representation of the self to be created, helping this group to compensate for feared problems of acceptance (ibid.). Based on the data, it appears this new representation of the self is often facilitated through image-focused platforms like “Instagram” and “Pinterest”. However, this may inadvertently expose SMA users to the pitfalls of social media, such as body dissatisfaction and reduced self-esteem when interacting with influencers. This dynamic could exacerbate their acceptance issues, perpetuating a detrimental cycle.

The ambivalent clinging and closed attachment styles differ primarily in their perceived willingness to open up. The former demonstrates a moderate willingness, allowing for the expression of strong attachment needs associated with the hyperactivated attachment system, while the latter exhibits a notably low willingness to open [ 53 ]. The findings presented in this study indicate that the degree of openness (for attachment) may play a crucial role in determining the severity of problematic user behavior. Specifically, the more receptive a user is to attachment, the less likely they are to exhibit addictive behaviors. Cluster analysis supports this interpretation. It identified three clusters with varying susceptibilities to social media addiction: those with secure attachment exhibit the lowest likelihood, those with ambivalent clingy attachment have a medium likelihood, and those with ambivalent closed attachment display the highest likelihood. This potential correlation warrants further exploration in subsequent research. Moreover, given that a mediating effect of mentalization between attachment style and both emotion dysregulation [ 68 ] and psychopathology [ 69 ] has been demonstrated, future research should delve deeper into exploring the relationships between mentalization, attachment style, and internet-related addictions.

Limitations

It should be noted that the data are based on self-reporting in an online survey. Response rate is comparable with other online-survey studies [ 70 ]. So, possible self-selection processes could be of importance since online surveys are prone to an inherent selection bias. Social media users may find it appealing to participate for trying to relativize the negative image of social media addiction. Further, the sample is due to the narrow age distribution and educational level not representative. Even if cluster analysis shows no noteworthy age distribution for the clusters, future research should collect sufficient case number for each age group or limit age to a homogenous group. Female students contributed disproportionately here. Which in turn can affect the prevalence of social media addiction since there is evidence that women are more prone to social media addiction [ 8 ]. Though, this gender bias has been frequently observed in online surveys [ 71 ]. Cluster analysis did not reveal any conspicuous distribution for gender either. Altogether, future studies with a broader recruitment strategy may provide more representative data and confirm discussed results. Further, it could be discussed that the design of the study is cross-sectional. Since there is evidence for differences in age, at least for personality dimensions, comparison of two points in time or more can corroborate data or reduce it to differences in generation cohort. Furthermore, since mental health is a key variable, future studies should check psychiatric history of participants.

This study enhances our understanding of how specific attachment problems could contribute to the development of social media addiction, reaffirming findings related to internet and smartphone addiction. It reveals that an avoidant closed attachment style, characterized by a pronounced need for attention, acceptance issues, and notably low openness for attachment, is frequently associated with this addiction. Such a deficit in openness may prompt compensatory behavior to satiate the intensive need for attention in the manageable environment of the digital world, where any conversation can be terminated with a click. This intense attention-seeking behavior seems to find satisfaction through image-centric services on social media, instigating negative comparative processes with others and potentially reinforcing acceptance issues in a self-perpetuating cycle, with mental stress being a substantial correlate.

To break this cycle, therapeutic interventions should consider these interrelations and specifically target critical areas. This could include conducting a thorough media anamnesis, educating about the effects of image-focused services and comparative processes, and establishing a robust and consistent therapeutic alliance—a cornerstone of successful addiction treatment [ 34 ]. The incorporation of attachment-oriented strategies is vital, as attachment-related aspects have yet to be integrated into existing internet addiction treatment protocols [ 34 , 36 ]. In addition, since research showed a good impact of whole school attachment-based interventions [ 72 ], prevention programs to combat digital addictions in schools and universities should also include content that promotes secure attachment behavior, especially to young people with a high need for attention, acceptance issues, and notably low openness for attachment. Beyond individual treatment, the implementation of these strategies has the potential to foster a healthier approach to digital media usage across society, thereby contributing to a more informed and mindful engagement with social media platforms, which can finally lead to a reduction in the prevalence and impact of social media addiction on a broader scale.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Abbreviations

Big Five Inventory

Bielefelder Fragebogen zu Partnerschaftserwartungen

Brief Symptom Inventory

Bergen Social Media Addiction Scale

Not Social Media Addicted

Social Media Addicted

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Eichenberg, C., Schneider, R. & Rumpl, H. Social media addiction: associations with attachment style, mental distress, and personality. BMC Psychiatry 24 , 278 (2024). https://doi.org/10.1186/s12888-024-05709-z

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Scientists Can’t Decide if Social Media Is Addictive

S ocial media can be harmful. That's something all behavioral researchers can agree on. There is much less consensus on how exactly its harmful use is defined, and whether or not there’s a corresponding beneficial way to use social media. And at the very center of this academic debate is the question: Can a person become addicted to social media?

Settling on an answer to this question has a surprising number of implications: for the internet, for policy (most notably in a recent lawsuit against Meta ), and even for people who suffer from or treat more well-defined forms of addiction. Attempts to do so have resulted in fairly conflicting findings, explains Niklas Ihssen, an associate psychology professor at Durham University in the U.K. In particular, some studies suggest abstaining from social media can improve mood and well-being, while others seem to argue that stepping away from the screens can cause serious withdrawal effects that mirror those present in chemical addictions. “There’s tension between those two strands of research,” Ihssen says.

Studying 'digital detox'

A new study, led by Ihssen’s postgraduate student Michael Wadsley and published Nov. 8 in the journal PLOS ONE , attempts to reconcile this conflict. 

Using activity-tracking apps and surveys, Wadsley and Ihssen followed 51 students for 15 days, including a week during which they were instructed to avoid social networking sites including Facebook, Instagram, and TikTok. The participants were then brought in for final surveys and exercises afterward. Around a third of the participants had existing social-media behaviors that qualified as problematic, or harmful to their functioning, on the most widely-accepted scale of social media behavior.

Read More: The ‘Dopamine Detox’ Is Having a Moment

Wadsley and Ihssen searched in the participants’ responses for symptoms of withdrawal in line with those found in substance-use disorders, such as relapses and increased consumption following abstinence. Though 87% of the participants weren’t able to stay off of social media entirely, their use time decreased to an average of 30 minutes, down from between three and four hours per day, and remained lower than before even after the week of abstinence had passed. “If there’s something like withdrawal, we would expect those cravings to go up after a while,” says Ihssen. But in both usage time and in the results of a test given to participants at the end of the week that recorded their reactions to seeing social media app icons, the sharp craving the chemical effects of withdrawal can cause just didn’t manifest as expected.

Ultimately, however, this study can’t conclusively answer on its own whether social media is addictive. In order to reach a consensus on that question, independent study teams working with small sample sizes, like Wadsley and Ihssen, need to use a set of shared metrics, methodologies, and definitions, says David Zendle, a lecturer at the University of York in the U.K. One 2021 study found that across 55 papers on social media addiction, 25 distinct theories and models were used.

When researchers can’t agree on the right place to dig, nobody gets very deep. This current gray zone is “extremely dangerous,” says Zendle. If social media is falsely framed as addictive, “individuals will be treated in a way that is inappropriate to their lives, causing detriment over the long term,” and it delegitimizes the severity of true addictions, he says. If it’s as addictive as illicit drugs, and science misses it, a huge corporate threat to public health could be running unchecked. “This is a nice small-scale study,” says Zendle. “What we need are radical, gigantic studies, to the point where when you see nothing going on, you are extremely confident that nothing really is going on.”

Part of the challenge of determining whether or not problematic social media use is classified as an addiction is that behavioral addictions are newly defined, says Zendle, with gambling addiction the only such disorder recognized by official diagnostic criteria. In gambling, researchers first noticed that a stimulus other than a chemical substance could create near-identical effects in the brain. “That transposition unlocked the world of behavioral addictions,” says Zendle. “But what we are now wondering as a community is where else it might be helpful to transpose this.”

Parallels with video game resarch

To see the long-term consequences of these sorts of competing paradigms in research, just look to the debate surrounding the harms of video-game violence, says Zendle, where there’s “an enormously mixed evidence base.” Because of back-and-forth “bad faith” research, he says, scientists are unable to advise psychologists, lawmakers, and game designers in any meaningful way, so drowned out has any consistent truth become.

Wadsley and Ihssen’s study feels more balanced not only because it marks another strike against the addiction theory, but also because it found none of the equivocally positive effects on mood that other studies have suggested comes from a social media break or “digital detox.” Instead, the results showed a varied mix of effects on mood, which most closely resembles the actual variation on findings across research on the topic, rather than sharply negative or positive effects that many individual studies show. 

This null finding isn’t inconsequential. Instead, it’s as strong an indicator as research has seen that current thinking about social media and addiction just might not line up with what’s actually happening inside the brain. Social media use is far too complicated and varied to tackle as an addictive substance, says Ihssen. “Even though it can cause issues with excessive use … I think we should not over-pathologize those behaviors.”

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Antecedents of social media addiction in high and low relational mobility societies: Motivation to expand social network and fear of reputational damage

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan

Roles Conceptualization, Investigation, Methodology, Project administration, Resources, Supervision, Writing – review & editing

Affiliation Graduate School of Human Sciences, Osaka University, Osaka, Japan

• Shuma Iwatani, 
• Eiichiro Watamura

• Published: April 18, 2024
• https://doi.org/10.1371/journal.pone.0300681
• Reader Comments

Contrary to previous studies on the antecedent factors of social media addiction, we focused on the social environmental factor of relational mobility (i.e., the ease of constructing new interpersonal relationships) and investigated its relationship with social media addiction. People in low relational mobility societies have fewer opportunities to select new relationship partners and consequently feel a stronger need to maintain their reputation. We hypothesized that (1) people in low relational mobility societies are more strongly addicted to social media because they estimate that greater reputational damage will be caused by ignoring messages and (2) people in low relational mobility societies estimate greater reputational damage than actual damage. We conducted two online experiments with 715 and 1,826 participants. Our results demonstrated that (1) there is no relationship between relational mobility and social media addiction and (2) people in both high and low relational mobility societies overestimate reputational damage. Furthermore, we demonstrated that the social media addiction mechanism differs between societies: (3) people in low relational mobility societies estimate greater reputational damage, whereas (4) people in high relational mobility societies are more motivated to expand their social networks; both mechanisms strengthen their social media addiction. Based on these results, we propose interventions for moderating social media addiction in both high and low relational mobility societies.

Citation: Iwatani S, Watamura E (2024) Antecedents of social media addiction in high and low relational mobility societies: Motivation to expand social network and fear of reputational damage. PLoS ONE 19(4): e0300681. https://doi.org/10.1371/journal.pone.0300681

Editor: Giulia Ballarotto, University of Rome La Sapienza: Universita degli Studi di Roma La Sapienza, ITALY

Received: August 9, 2023; Accepted: March 1, 2024; Published: April 18, 2024

Copyright: © 2024 Iwatani, Watamura. 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: Data and R code are publicly available via the Open Science Framework and can be accessed at https://osf.io/ch5py/

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Social media platforms have both positive and negative effects on people [ 1 ]. On the positive side, it allows people to obtain information, send messages from anywhere, and communicate more closely with others. On the negative side, some users are addicted to social media and spend excessive time on it. In this study, we attempted to demonstrate the mechanism through which people become addicted to social media.

The term "addiction" has various meanings, and its definition has expanded over the years. It can be classified into two main categories: substance addiction and non-substance addiction [ 2 ] (non-substance addiction is also referred to as behavioral addiction [ 3 ]). Substance addiction is a neuropsychiatric disorder characterized by a recurring desire to ingest substances, such as drugs or alcohol, despite harmful consequences [ 2 , 4 ]. People who require daily intake of alcohol are defined as being addicted to alcohol. By contrast, non-substance addiction refers to addiction to things other than substances [ 5 – 7 ], such as pathological gambling, the Internet, and mobile phones [ 2 ].

Social media addiction is a type of non-substance addiction. The following are some definitions of social media addiction: “irrational and excessive use of social media to the extent that it interferes with other aspects of daily life” [ 5 ], “excessive use and habitual monitoring of social media, manifested in compulsive usage that comes at the expense of other activities” [8, p.747], and “being overly concerned about SNSs, to be driven by a strong motivation to log on to or use SNSs, and to devote so much time and effort to SNSs that it impairs other social activities, studies/job, interpersonal relationships, and/or psychological health and well-being” ([ 9 ], p.4054; SNS: social network service). The common items in these definitions are (i) devoting excessive time to social media and (ii) the negative consequences of using social media (i.e., interfering with other social activities such as studying, job, interpersonal relationships, psychological health, and well-being).

Social media addiction has various negative effects, including damaging mental health [ 5 ], poor life satisfaction [ 10 ], and chronic physical issues, such as neck pain or headaches [ 11 ]. Some studies that focused on company employees have demonstrated that social media addiction leads to a reduction in sleeping hours [ 12 ], increased distraction at workplace [ 12 ], and impaired productivity [ 8 ].

In this study, we used the term “addiction” or “social media addiction” in a non-clinical sense. This is because social media addiction is not included in the DSM-5-TR classification [ 13 ] and no study has demonstrated that social media addiction can have severe physical consequences [ 14 ].

1.1. Antecedents of social media addiction

Previous studies have investigated various antecedents of social media addiction such as neuroticism [ 15 ], lack of self-control [ 16 ], and extraversion [ 17 ], and have several perspectives on social media addiction [ 18 ]. One perspective focuses on dispositional differences such as attachment styles. D’Arienzo et al. [ 19 ] concluded that avoidant or insecure attachment style is associated with stronger social media addiction. Additionally, an empirical study by Ballarotto et al. [ 20 ] demonstrated that individuals who are less attached to their parents are more strongly addicted to Instagram. Eroglu [ 21 ] showed that people with insecure attachments (i.e., those having negative “internally working models about both themselves and others” [ 21 ] p.151) are more strongly addicted to Facebook. Additionally, Monacis et al. [ 22 ] demonstrated that people with avoidant attachment style (i.e., those who experience discomfort with intimacy) are more strongly addicted to social media.

Furthermore, some studies have focused on the motivation to use social media. For example, those who feel lonely are more strongly addicted to social media [ 23 ] as they are motivated to connect with others [ 24 ]. Moreover, extraverts are more strongly addicted to social media [ 17 ] as they use it to expand their social connections [ 25 ]. Additionally, those with a higher motivation to expand their social network would be more strongly addicted to social media, as it allows them to maintain or expand their social network.

Additionally, demographic variables, such as sex and age, may be related to social media addiction Mari et al. [ 26 ] found that females are more strongly addicted to the Internet, whereas Su et al. [ 27 ] and Alnjadat et al. [ 28 ] found that males are more strongly addicted to the Internet or social media. Moreover, age is related to social media addiction as younger individuals are more strongly addicted to social media [ 25 ].

Also, distressing changes in social situations, such as those during and after the COVID-19 pandemic, may also strengthen social media addiction. Recent studies have noted that the importance of social media as a medium for rapid information dissemination has increased after COVID-19 [ 29 ] and demonstrated that psychological distress owing to COVID-19 has strengthened social media [ 30 ], Internet [ 20 ], and Instagram [ 20 ] addictions, and social media addiction has also increased the likelihood of experiencing depression [ 31 ]. These studies imply that distressing situations and social media addiction have mutually strengthened each other, especially after the COVID-19 pandemic.

Although these studies focused on micro-level factors, such as depression or distress, the effect of macro-level social environmental factors on social media addiction is understudied and must be further investigated [ 18 ]. Based on Sun et al. [ 18 ]’s suggestion, we focused on a social environmental factor (i.e., relational mobility [ 32 ]) and investigated the relationship between the social environment and social media addiction.

We conducted two studies to examine the effect of the social environment (i.e., relational mobility) on social media addiction. Relational mobility of a society refers to how easily people in the society can select new relationship partners when necessary [ 32 ]. Relational mobility is lower in typical rural areas wherein interpersonal relationships are closed to outsiders. As relational mobility affects the sensitivity of an individual to social rejection [ 33 , 34 ], it can affect their interpersonal behavior. As an example of interpersonal behavior on social media, we focused on a message exchange situation and examined whether the estimation of reputational damage incurred by ignoring messages moderates the relationship between relational mobility and social media addiction.

Fig 1 illustrates our conceptual model. In Study 1, we examined the following mediation process: people in lower relational mobility societies estimate that greater reputational damage is incurred by message ignorance, which strengthens their social media addiction. This model was proposed based on previous studies that have indicated that people in lower relational mobility societies are more sensitive to social rejection [ 33 , 34 ], and they make decisions based on their estimations of others’ attitudes [ 35 ].

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https://doi.org/10.1371/journal.pone.0300681.g001

In Study 2, we additionally examined the following dual paths: (1) the mediating effect of estimated reputational damage on the negative relationship between relational mobility and social media addiction and (2) the mediating effect of extroversion, the motivation to expand the social network, and loneliness on the positive relationship between relational mobility and social media addiction. We focused on extroversion, motivation to expand social network, and loneliness because they are related to both relational mobility and social media addiction.

In the following section, we review studies on relational mobility, develop our hypotheses, and outline our contributions.

1.2. Relational mobility and social media addiction

We first focused on the social environmental factor of relational mobility [ 32 ], which is a sociological variable that refers to “the amount of opportunities people have in a given society or social context to select new relationship partners when necessary” [ 32 ]. Relational mobility is lower in typical rural areas, where people exclusively develop intimate relationships with neighbors and seldom construct new relationships with outsiders, whereas it is higher in typical urban areas, where people have weaker social ties and entering or leaving relationships is easier.

Thus, people in low relational mobility societies cannot easily construct alternate relationships, even when they earn a bad reputation and are excluded from their communities. Therefore, the consequences of earning a bad reputation are worse for people in low relational mobility societies [ 36 ], which strengthens their need to avoid reputational damage. Indeed, people in lower relational mobility societies are more sensitive to social rejection [ 33 , 34 ] and refrain from sharing personal information, such as embarrassing experiences or failures [ 37 ].

Based on these studies, we assume that people in lower relational mobility societies are more strongly addicted to social media. Additionally, as they are more sensitive to social rejection, they have more difficulty ignoring messages on social media and thus spend more time on social media, resulting in higher addiction.

• Hypothesis 1 : People in low relational mobility societies are more strongly addicted to social media.

1.3. Mediating effect of estimated reputational damage

People in lower relational mobility societies estimate greater reputational damage incurred by ignoring messages on social media because, as described in the Section 1.2., they are more sensitive to social rejection [ 33 , 34 ]. In some cases, this sensitivity might result in an overestimation of reputational damage, leading them to unnecessarily respond to messages on social media. However, in other cases, this sensitivity could reduce the possibility that they underestimate the damage in situations where ignoring them could lower their reputation, and mistakenly ignore messages and damage their reputation. Therefore, estimating greater reputational damage and refraining from ignoring messages are adaptive in that this estimation ( overestimation in some cases) can lower the possibility of damaging their reputation. However, this estimation can strengthen their addiction to social media. Because forming and maintaining strong and stable interpersonal relationships is important to humans [ 38 ], people make decisions based on their estimations of others’ attitudes [ 35 ]. For example, people are more likely to follow norms when they estimate that deviating from them will tarnish their reputation [ 39 ]. Based on these studies, we assumed that people in lower relational mobility societies estimate greater reputational damage incurred by ignoring messages, which strengthens their social media addiction.

• Hypothesis 2 : The estimation of greater reputational damage incurred by ignoring messages mediates the negative relationship between relational mobility and social media addiction.

1.4. Accuracy of reputational damage estimation

Hypothesis 2 focuses on the mediating effect of estimated reputational damage. In this section, we examine two questions: do people in both high and low relational mobility societies accurately estimate reputational damage?

Based on [ 36 ], we hypothesized that people in low relational mobility societies overestimate the possibility of earning a bad reputation. Overestimation of reputational damage can help them avoid situations wherein they mistakenly estimate that performing detrimental actions would not damage their reputation when it would. An example of this situation on social media is that people mistakenly estimate that ignoring messages will not tarnish their reputation, even if it does. If they ignore messages based on this underestimation, they will gain a bad reputation, the cost of which is higher in lower relational mobility societies. Therefore, people in lower relational mobility societies are more likely to overestimate reputational damage, especially because interpersonal relationships in these societies are closed and the cost of earning a bad reputation is higher. Indeed, Iwatani and Muramoto [ 39 ] focused on community activities, such as cleanup drives, and demonstrated that people in low relational mobility societies overestimate the possibility of gaining a bad reputation, whereas those in high relational mobility societies estimate it accurately. In this study, we extend their findings to the context of social media and investigate the following hypothesis:

• Hypothesis 3 : People in low relational mobility societies overestimate the possibility of receiving a bad evaluation by ignoring messages, whereas people in high relational mobility societies do not.

1.5. Contributions of this study

We believe our study has at least three original contributions. First, it highlights the effects of the social environment on social media addiction. The human mind, including cognition, emotion, and motivation, is affected by both cultural [ 40 ] and social environments [ 41 ]; therefore, social environmental factors can impact social media addiction. However, few studies have investigated the effect of social environments on social media addiction [ 42 ] (however, see [ 43 ], wherein the effect of relational mobility on problematic Internet use was investigated). The novelty of this study lies in its investigation of social media addiction from the perspective of socio-ecological psychology.

Second, we focus on interpersonal interactions between social media users as an antecedent of social media addiction, whereas previous studies have primarily focused on individual psychological factors [ 15 – 17 ]. The originality of our study lies in the fact that we focus on miscommunications between social media users, that is, inaccurately (over)estimated reputational damage as an antecedent factor of social media addiction.

Third, our study also features originality for studies on socio-ecological psychology in that we investigate the effect of relational mobility on online behavior. Previous studies have demonstrated the effect of relationality on general trust, self-esteem, and intimacy with close friends [ 44 ]. However, few studies have demonstrated the effect of offline relational mobility on the online psychological tendencies of humans, except for Dong et al. [ 43 ] and Thomson et al. [ 45 ], who examined the effect of relational mobility on problematic Internet use or online privacy concerns of people.

We conducted two studies to examine the following hypotheses: (1) the direct effect of the social environment (relational mobility) on social media addiction, (2) the mediating effect of reputational damage estimation on the relationship between the social environment and social media addiction, and (3) the accuracy of reputational damage estimation.

2. Materials and methods

2.1. study 1.

We tested the proposed hypotheses using the LINE message exchange service, which is the most popular social media platform in Japan, wherein it is used by approximately 80% of the Internet users [ 46 ]. LINE was considered suitable for this study because it provides a "read notification function," through which users can determine whether their messages have been read and ignored. Additionally, they are aware that their messaging partner can determine if their messages are ignored.

The experiment included two conditions: (1) wherein participants ignored messages (ignorer condition) and (2) wherein participants’ messages were ignored (ignored condition). In the ignorer condition, participants imagined a scenario wherein they read the messages received on LINE and ignored them. They estimated how message senders would evaluate the participants when participants themselves ignored messages (estimated reputational damage). In the ignored condition, participants imagined a scenario wherein they sent messages and the receiver read and ignored them, and evaluated the receiver who ignored the messages (actual reputational damage). We compared the estimated and actual reputational damage and investigated whether people from lower relational mobility societies estimated more reputational damage than the actual damage. We also investigated whether people from lower relational mobility societies estimated higher reputational damage and were more strongly addicted to social media.

2.1.1. Participants.

This study was approved by the Ethics Review Committee of the University of Tokyo. Written informed consent was obtained from all participants. They were recruited through a crowdsourcing service (Yahoo! Crowdsourcing; https://crowdsourcing.yahoo.co.jp/ ) between February 19 and 20, 2022. They were informed of the purpose of this study, and only those who agreed to participate (i.e., those who clicked “agree”) proceeded to answer the questions. Study 1 included 715 participants.

Study 1 was conducted using the between-participant design. We excluded 54 participants who did not pass the instructional manipulation check [ 47 ], 126 who did not use LINE, and 27 who had no friends whom they could contact privately through LINE. We also excluded data with missing values and one participant who answered that their age was 3. Finally, we analyzed the data of 453 participants (males: 308, females: 138, and others: 7). Their average age was 46.46 years ( SD = 11.17).

Half of the participants were randomly assigned to the ignorer condition, and the other half were randomly assigned to the ignored condition, resulting in 222 and 231 participants assigned to the ignorer and ignored conditions, respectively.

We examined whether the sample size was sufficiently large using G*Power version 3.1.9.7 [ 48 ] to conduct a post-hoc power analysis, assuming f = 0.05 (small to medium effect size), α = 0.05, N = 453, and three predictors (condition, relational mobility, and the interaction between them). The calculated power of the test was 0.99, which indicated that the sample size was adequate.

2.1.2. Reputational damage estimation (ignorer condition).

The participants were first asked to write the first-name initials of one of their friends they had privately contacted. The friend’s name is denoted as Mr. A in this study (It was denoted as “A-san” in our actual question). Participants assigned to the ignorer condition were asked to read and imagine a scenario wherein they received a message from Mr. A that stated that they had to discuss something, read it, but did not reply for two or three days.

After participants read the scenario, they estimated Mr. A’s evaluation of them by answering the following six items, extracted from a previous study [ 49 ], on a six-point Likert scale, ranging from 1 (“strongly disagree”) to 6 (“strongly agree”): “Mr. A would think you are a bad person,” “Mr. A would think you are an untrustworthy person,” “Mr. A would think you are an honest person,” “Mr. A would think they do not want to be your friend anymore,” “Mr. A would think they cannot feel secure with you,” and “Mr. A would think you are a cunning person.” We calculated the reputational damage estimation score by averaging the sum of the scores (α = 0.89, M = 2.89, SD = 0.99).

2.1.3. Participants’ evaluation (ignored condition).

Participants assigned to the ignored condition were asked to read and imagine a scenario wherein they sent a message to Mr. A stating that they had to discuss something, Mr. A received and read it but did not reply for two or three days.

After reading the scenario, participants answered questions regarding their evaluation of Mr. A. The items were almost the same as those in the previous scenario, and only the subjects were changed. For example, we changed the item “Mr. A would think you are a bad person” to “I think Mr. A is a bad person.” We again calculated the evaluation score by averaging the sum of the scores (α = 0.89, M = 2.26, SD = 0.88).

2.1.4. Social media addiction.

We used the social media addiction questionnaire (SMAQ; 7-point scale), which is composed of eight items and was proposed by Hawi and Samaha [ 10 ]. We changed the term “social media” in SMAQ to “LINE” for this study. For example, the question “I often think about social media when I am not using it” was modified to “I often think about LINE when I am not using it.” As in [ 10 ], we calculated the social media addiction score by averaging the sum of the scores (α = 0.86, M = 2.73, SD = 1.02). As there was no threshold to distinguish between those addicted to social media and those who were not [ 10 ], we did not perform threshold-based distinguishing between those who were addicted to LINE and those who were not. Participants were considered to be more strongly addicted to LINE if they scored higher on this scale.

2.1.5. Relational mobility.

Relational mobility was measured using the relational mobility scale [ 32 ]. Participants were presented with 12 statements and asked how much they agreed with them based on a six-point Likert scale, from 1 (“strongly disagree”) to 6 (“strongly agree”). The statements included the following: “they (people in the immediate society (your school, workplace, town, neighborhood, etc.) in which you live) have many chances to get to know other people.” The relational mobility score was calculated by averaging the sums of the scores (α = 0.75, M = 3.60, SD = 0.51). The relational mobility of the participant’s society was considered to be higher if they scored higher on this scale.

2.2. Study 2

Although Study 1 only investigated the factors that mediate the negative relationship between relational mobility and social media addiction, Study 2 investigated the factors that mediate the positive relationship between the two. We focused on the following three factors: loneliness, extroversion, and the motivation to expand social network. We examined whether these three factors mediated the positive relationship between relational mobility and social media addiction, which would cancel out the negative relationship examined in Study 1.

First, we focused on loneliness. We assumed that the relationship between relational mobility and loneliness was positive based on the study by Oishi et al. [ 50 ], which demonstrated that people in mobile conditions (wherein they imagined that they would move to a different location every other year) experienced more loneliness than those in stable conditions (wherein they imagined that they would stay in the same city for at least ten years). Additionally, there is a positive relationship between loneliness and social media addiction [ 23 ], which suggests that loneliness mediates a positive relationship between relational mobility and social media addiction.

Next, we focused on extroversion. There is a positive relationship between the within-state migration level and extroversion [ 51 ], which implies that there is a positive relationship between relational mobility and extroversion. Additionally, there is a positive relationship between extroversion and social media addiction [ 17 ]. These findings suggest that extroversion mediates the positive relationship between relational mobility and social media addiction.

Finally, we focus on the motivation to expand social network. An experimental study demonstrated that people in the mobile condition are more motivated to expand their social networks than those in the stable condition [ 50 ]. In addition, extraverts have larger social networks, which can promote their use of social media [ 4 ]. These findings suggest that the motivation to expand the social network mediates the positive relationship between relational mobility and social media addiction. In summary, we developed the following additional hypotheses and examined the model presented in Fig 1 .

• Hypothesis 4a : Loneliness mediates the positive relationship between relational mobility and social media addiction.
• Hypothesis 4b : Extroversion mediates the positive relationship between relational mobility and social media addiction.
• Hypothesis 4c : Motivation to expand social network mediates the positive relationship between relational mobility and social media addiction.

2.2.1. Participants.

This study was approved by the Ethics Review Committee of the University of Tokyo. Written informed consent was obtained from all the participants. Study 2 employed the within-participants design and included 1826 participants, recruited through the same crowdsourcing service (Yahoo! Crowdsourcing; https://crowdsourcing.yahoo.co.jp/ ) between August 26 and 27, 2022. They were informed of the purpose of this study, and only those who agreed to participate proceeded to answer the questions. We excluded 143 participants who did not pass the instructional manipulation check [ 47 ], 309 who did not use LINE, and 209 who had no friends whom they could contact privately through LINE. We also excluded data with missing values and eventually analyzed the data of 1065 participants (males: 670, females: 374, and others: 21). Their average age was 48.11 years ( SD = 12.09).

We examined whether the sample size was sufficiently large by conducting a post-hoc power analysis, assuming a root mean square error of approximation (RMSEA) in the null hypothesis = 0.05, RMSEA in the alternative hypothesis = 0.01, degrees of freedom = 7, N = 1065, and α = 0.05. The calculated power was 0.85, which indicated that the sample size was adequate.

2.2.2. Measurements.

As in Study 1, participants were asked to write the first-name initials of their friends they had privately contacted, who were denoted as Mr. A. Thereafter, they were asked to imagine the following scenarios: (1) wherein they ignored messages and (2) wherein their messages were ignored.

2.2.3. Reputation damage estimation.

The participants read the same scenario as in Study 1 (ignorer condition), wherein they ignored Mr. A’s message, and answered the following five items on a six-point Likert scale based on a previous study [ 49 ], ranging from 1 (“strongly disagree”) to 6 (“strongly agree”): “Mr. A would think you are a bad person,” “Mr. A would think you are an untrustworthy person,” “Mr. A would think they cannot feel secure with you,” “Mr. A would think you are an unreliable person,” and “Mr. A would not want to deepen their friendship with you.” We calculated the reputational damage estimation score by averaging the sums of the scores (α = 0.96, M = 3.16, SD = 1.19).

2.2.4. Participants’ evaluation.

Next, the participants read the same scenario as in Study 1 (ignored condition), wherein Mr. A ignored their messages. Thereafter, they responded with their evaluations of Mr. A. These items were almost the same as those mentioned above, and only their subjects were changed. For example, we changed the item “Mr. A would think you are a bad person” to “I think Mr. A is a bad person.” We calculated the evaluation score by averaging the sum of the scores (α = 0.96, M = 2.68, SD = 1.14).

2.2.5. Social media addiction.

We used the same questionnaires as in Study 1 to calculate the social media addiction scores. The sum of the scores were averaged (α = 0.86, M = 2.69, SD = 1.03).

2.2.6. Extroversion.

We measured extroversion using the Ten-Item Personality Inventory assessment [ 52 ]. The participants were asked to answer the following two items on a seven-point Likert scale, ranging from 1 (“strongly disagree”) to 7 (“strongly agree”): “I see myself as extraverted, enthusiastic” and “I see myself as reserved, quiet” (reverse-scored item). We calculated the extroversion score by averaging the sums of the scores ( r = 0.47, p < 0.01, M = 3.55, SD = 1.31). A participant was considered more extraverted if they scored higher.

2.2.7. Motivation to expand social network.

We measured the motivation to expand the social network using a seven-point Likert scale [ 50 ]. The questionnaire was composed of four items (e.g., “eager to make friends,” “want to meet new people”). We calculated the motivation to expand the social network by averaging the sum of the scores (α = 0.92, M = 3.52, SD = 1.37). Participants were considered to have higher motivation to expand their social networks if they scored higher on this scale.

2.2.8. Loneliness.

We measured loneliness using a five-point Likert scale [ 53 ]. The scale was composed of six statements (e.g., “I usually sense an experience of emptiness,” “I often feel missing close people around me”). We calculated the loneliness score by averaging the sum of the scores (α = 0.85, M = 2.82, SD = 0.76). Participants were considered to be lonelier if they scored higher on this scale.

2.2.9. Relational mobility.

As stated in Section 2.1.5, relational mobility score was measured using the relational mobility scale [ 32 ]. It was calculated by averaging the sum of the scores (α = 0.78, M = 3.66, SD = 0.53).

2.3. Statistical analysis

We used R version 4.3.2 for statistical analyses. For mediation analyses, multiple regression analysis, and generalized linear mixed model analysis, the statistical significance standard was set as p = .05, whereas for structural equation modeling (SEM), the statistical significance standard for the model fit was set as RMSEA = .05.

Study 1 was conducted using a between-participants design ( ignorer and ignored conditions). To test Hypotheses 1 and 2, we analyzed participants in the ignorer condition, (i.e., those who answered reputational damage estimation) and conducted a mediation analysis using the bootstrap method (5000 samples) to examine whether the negative effect of relational mobility on social media addiction was mediated by reputational damage estimation. This analysis was conducted after centering all variables in the model.

For testing Hypothesis 3, we conducted a multiple regression analysis. The evaluation was predicted using a dummy evaluator variable ( ignored condition (i.e., participants’ actual reputational damage) = 0, ignorer condition (i.e., estimated reputational damage from others) = 1), relational mobility, and the interaction between them. This analysis was also conducted after centering all variables in this model.

Study 2 employed a within-participant design. Participants read both the ignorer and ignored condition scenarios. For testing Hypothesis 2 and Hypotheses 4a–c, we employed SEM techniques and examined the following hypotheses: estimation of greater reputational damage mediates the negative relationship between relational mobility and social media addiction, whereas loneliness, extroversion, and motivation to expand social networks mediates the positive relationship between them ( Fig 1 ).

For testing Hypothesis 3, we used a generalized linear mixed model with random intercepts for the participants to examine our hypothetical model. The evaluation toward the ignorer was predicted using the dummy evaluator variable ( ignored condition = 0, ignorer condition = 1), relational mobility, and the interaction between them. This analysis was conducted after centering all variables in this model.

3. Results and discussion

3.1. study 1, 3.1.1. are people in lower relational mobility societies more addicted to social media.

First, we examined Hypotheses 1 and 2: (1) people in low relational mobility societies are more strongly addicted to social media (Hypothesis 1) and (2) the estimation of greater reputational damage incurred by ignoring messages would mediate the negative relationship between relational mobility and social media addiction (Hypothesis 2).

We only analyzed the answers of participants in the ignorer condition because we did not measure the estimated reputational damage in the ignored condition. After centering all variables in the model, we conducted a mediation analysis using the bootstrap method (5000 samples) to examine whether the effect of relational mobility on social media addiction was mediated by reputational damage estimation. Relational mobility had a significant effect on reputational damage estimation, indicating that people in low relational mobility societies estimated a higher reputational damage caused by ignoring messages (β = -0.15, p = 0.04). The effect of reputational damage estimation on social media addiction was not statistically significant (β = 0.14, p = 0.06). Additionally, the direct effect of relational mobility on social media addiction was not significant (β = -0.10, p = 0.18). These results did not support Hypotheses 1 and 2. However, consistent with Hypothesis 2, there was a statistically significant negative correlation between relational mobility and reputational damage estimation ( r = -0.15, p = 0.03) as well as a statistically significant positive correlation between reputational damage estimation and social media addiction ( r = 0.16, p = 0.02), although there was no statistically significant correlation between relational mobility and social media addiction ( r = -0.12, p = 0.07).

Thereafter, we conducted an additional analysis using age and sex (male = 0, female = 1) as control variables. To examine the effect of sex, seven participants who did not answer “male” or “female” were excluded. The effect of relational mobility on reputational damage estimation was statistically significant (β = -0.14, p = 0.05). In contrast to the aforementioned analysis, the effect of reputational damage estimation on social media addiction was also statistically significant (β = 0.15, p = 0.04). The direct effect of relational mobility on social media addiction was not significant (β = -0.09, p = 0.28) as in the above analysis. Additionally, the main effect of sex (β = 0.14, p = 0.03) was statistically significant, whereas that of age (β = -0.09, p = 0.23) was not.

3.1.2. Do people in low relational mobility societies overestimate reputational damage?

Next, we examined Hypothesis 3: people in low relational mobility societies overestimate the possibility of receiving a bad evaluation incurred by ignoring messages, whereas people in high relational mobility societies do not.

Prior to the analysis, we constructed a dummy variable for the evaluator (participants’ actual reputational damage = 0, estimated reputational damage from others = 1). After centering all variables in this model, we conducted a multiple regression analysis. The evaluation was predicted using the dummy evaluator variable, relational mobility, and the interaction between the two.

The main effect of evaluator was significant (β = 0.31, p < 0.01), but the interaction effect between the evaluator and relational mobility was not (β = -0.02, p = 0.60). These results imply that people in low relational mobility societies estimate greater reputational damage incurred by ignoring messages than the actual damage (consistent with Hypothesis 3), and the same holds true for people in high relational mobility societies (inconsistent with Hypothesis 3).

The main effect of relational mobility was also significant (β = -0.13, p < 0.01), which implies that (1) people who ignored messages were evaluated more negatively in low relational mobility societies than in high relational mobility societies and (2) people in low relational mobility societies estimated that ignoring messages would incur higher reputational damage than people in high relational mobility societies.

We conducted an additional analysis using age and sex (male = 0, female = 1) as control variables. To examine the effect of sex, seven participants who did not answer “male” or “female” were excluded. The results were the same as those obtained in the aforementioned analysis. The main effects of the evaluator (β = 0.31, p < 0.01) and relational mobility (β = -0.12, p = 0.01) were statistically significant, whereas the interaction effect between the evaluator and relational mobility was not (β = -0.03, p = 0.56). Additionally, the main effects of age (β = -0.08, p = 0.07) and sex (β = -0.02, p = 0.68) were not significant.

3.1.3. Moderating effect of age.

We exploratively examined the moderating effect of age; whether the effect of reputational damage estimation on social media addiction differed depending on age. A multiple regression analysis was conducted after entering all variables in the model. Social media addiction was used as the dependent variable, whereas relational mobility, reputational damage estimation, sex, age, and the interaction between reputational damage estimation and age were used as independent variables. The main effects of reputational damage estimation (β = 0.15, p = 0.02) and sex (β = 0.14, p = 0.04) were statistically significant, whereas those of relational mobility (β = -0.08, p = 0.22) and age (β = -0.09, p = 0.20) were not. Additionally, the interaction effect was not significant (β = 0.01, p = 0.84).

3.1.4. Discussion.

In Study 1, we examined (1) the effect of relational mobility on social media addiction (Hypothesis 1), (2) mediating effect of reputational damage estimation on the relationship between relational mobility and addiction (Hypothesis 2), and (3) accuracy of reputational damage estimation (Hypothesis 3).

First, we found that both relational mobility and reputational damage estimation had no effect on social media addiction; these results do not support Hypothesis 1. Second, we found that people in lower relational mobility societies estimated higher reputational damage. We also found a positive correlation between reputational damage estimation and social media addiction. These results were consistent with Hypothesis 2 (the mediating effect of reputational damage estimation), but this hypothesis was not supported because no direct relationship between relational mobility and social media addiction was observed. These results imply that other factors mediate the positive relationship between relational mobility and social media addiction, which negates the negative relationship between them. We further examined this possibility in Study 2. Third, we found that people overestimate the reputational damage caused by ignoring messages. This result partially supported Hypothesis 3, in that people in low relational mobility societies overestimate reputational damage incurred by ignoring messages, but contradicted Hypothesis 3, in that people in high relational mobility societies also overestimate it.

3.2. Study 2

3.2.1. relationship between relational mobility and social media addiction..

We investigated the relationship between relational mobility and social media addiction using SEM techniques and examined the following possibilities: estimation of greater reputational damage mediates a negative relationship between relational mobility and social media addiction (Hypothesis 2), whereas (2) loneliness, extroversion, and motivation to expand social networks mediate a positive relationship between relational mobility and social media addiction (Hypotheses 4a, 4b, and 4c; Fig 1 ). However, the model did not fit the data (RMSEA = 0.24).

In this model, we focused on three factors that would mediate the positive relationship between relational mobility and social media addiction (Hypotheses 4a, 4b, and 4c): loneliness, extroversion, and the motivation to expand the social network. Indeed, extroversion and the motivation to expand the social network were significantly and positively correlated with social media addiction ( r = 0.12, p < 0.01; r = 0.28, p < 0.01), but loneliness was not ( r = 0.04, p = 0.23).

Therefore, we focused only on the motivation to expand the social network, as it had the strongest correlation with social media addiction. We used SEM techniques and examined the following possibilities: (1) estimation of greater reputational damage incurred by ignoring messages mediates the negative relationship between relational mobility and social media addiction (Hypothesis 2) and (2) motivation to expand social network mediates the positive relationship between them (Hypothesis 4c). This model fit the data (RMSEA = 0.05; Fig 2 ). We conducted an additional analysis using age and sex (male = 0, female = 1) as control variables. To examine the effect of sex, we excluded 21 participants who did not answer “male” or “female.” The result was the same as that of the aforementioned analysis (RMSEA = 0.05; Fig 2 ). The effect of sex on social media addiction was statistically significant (β = 0.08, p = 0.01), whereas that of age was not (β = 0.01, p = 0.85).

Note**: p < 0.01; the values in parentheses indicate the results of the additional analyses with covariates (i.e., age and gender).

https://doi.org/10.1371/journal.pone.0300681.g002

Based on these results, we conducted a dual mediation analysis using 1000 bootstrap samples. The results indicated that reputational damage estimation mediated the negative relationship between relational mobility and social media addiction (indirect effect = -0.01, p = 0.03), whereas the motivation to expand social network mediated the positive relationship (indirect effect = 0.04, p < 0.01; Fig 3 ). We also conducted an additional analysis using age and sex (male = 0, female = 1) as control variables, and obtained same result as that in the aforementioned analysis; reputational damage estimation mediated the negative relationship between relational mobility and social media addiction (indirect effect = -0.01, p = 0.03), whereas the motivation to expand social network mediated the positive relationship (indirect effect = 0.04, p < 0.01; Fig 3 ). These results support Hypotheses 2 and 4c.

https://doi.org/10.1371/journal.pone.0300681.g003

When we used extroversion or loneliness instead of motivation to expand the social network, the models did not fit the data (RMSEA = 0.12 and 0.20, respectively). The models did not fit when entering the control variables (age and gender), either (RMSEA = 0.09 and 0.14, respectively).

3.2.2. Do people in low relational mobility societies overestimate their reputational damage?

Next, we examine Hypothesis 3. We conducted a generalized linear mixed model analysis in Study 2, although we conducted a multiple regression analysis in Study 1. This is because Study 2 employed the within-participants design, whereas Study 1 employed the between-participants design.

Prior to the analysis, we constructed a dummy variable for the evaluator (participants’ actual evaluations = 0, evaluation from others = 1). After centering all variables in the model, we used a generalized linear mixed model with random intercepts for participants to examine our hypothetical model. The evaluation was predicted using the dummy evaluator variable, a relational mobility variable, and the interaction between the two.

The main effect of the evaluator was significant (β = 0.20, p < 0.01), but the interaction effect between the evaluator and relational mobility was not (β = 0.01, p = 0.49). These results imply that people in low relational mobility societies estimate that greater reputational damage will be incurred by ignoring messages than the actual damage (consistent with Hypothesis 3), and the same hold true for people in high relational mobility societies (inconsistent with Hypothesis 3).

The main effect of relational mobility was also significant (β = -0.10, p < 0.01), which implies that (1) people in low relational mobility societies evaluated those who ignored messages more negatively than those in high relational mobility societies, and (2) people in low relational mobility societies also estimated that ignoring messages would incur higher reputational damage than those in high relational mobility societies.

We conducted an additional analysis using age and sex (male = 0, female = 1) as control variables and obtained the same results as those in the aforementioned analysis. The main effects of the evaluator (β = 0.20, p < 0.01) and relational mobility (β = -0.10, p < 0.01) were statistically significant, whereas the interaction effect between them was not (β = 0.01, p = 0.50). Additionally, the main effects of age (β = -0.04, p = 0.14) and sex (β = -0.02, p = 0.39) were not significant.

3.2.3. Moderating effect of age.

We exploratively examined the moderating effect of age; whether the effect of reputational damage estimation on social media addiction and that of the motivation to expand the social network differs depending on age. We conducted a multiple regression analysis after centering all variables in the model. Social media addiction was used as the dependent variable, whereas relational mobility, reputational damage estimation, the motivation to expand the social network, sex, age, the interaction between reputational damage estimation and age, and the interaction between the motivation to expand the social network and age as independent variables. The main effects of reputational damage estimation (β = 0.15, p < 0.01) and the motivation to expand the social network (β = 0.30, p < 0.01) were statistically significant, whereas those of relational mobility (β = -0.02, p = 0.42), age (β = 0.00, p = 0.90), and sex (β = 0.05, p = 0.07) were not. Additionally, the interaction effect between reputational damage estimation and age was not statistically significant (β = -0.01, p = 0.70), whereas that between the motivation to expand the social network and age was statistically significant (β = -0.06, p = 0.03). The effect of the motivation to expand the social network was greater among younger participants ( M - 1 SD ; β = 0.36, p < 0.01) than among older ( M + 1 SD ; β = 0.24, p < 0.01).

3.2.4. Discussion.

Study 2 hypothesized that (1) reputational damage estimation mediates the negative relationship between relational mobility and social media addiction, whereas (2) loneliness, extroversion, and the motivation to expand the social network mediate the positive relationship. We hypothesized that these two mediations would cancel each other out; therefore, there will be no relationship between relational mobility and social media addiction.

We tested these hypotheses using SEM; however, they were not supported. We additionally tested another model that focused only on the motivation to expand the social network: (1) reputational damage estimation mediates the negative relationship between relational mobility and social media addiction and (2) motivation to expand the social network mediates the positive relationship. This model was supported, which implies that the factors promoting social media addiction differ between high and low relational mobility societies. Reputational damage estimation strengthens social media addiction in low relational mobility societies, whereas the motivation to expand social networks strengthens it in high relational mobility societies.

3.3. General discussion

3.3.1. summary of results..

We focused on message exchanges on social media and investigated the effect of social environment (relational mobility) on social media addiction. In Study 1, we examined the following hypotheses: (1) people in low relational mobility societies are more strongly addicted to social media (Hypothesis 1), (2) the estimation of greater reputational damage incurred by ignoring messages mediates the negative relationship between relational mobility and social media addiction (Hypothesis 2), and (3) people in low relational mobility societies overestimate the possibility of receiving a bad evaluation, whereas people in high relational mobility societies do not. In Study 2, we additionally examined (4) loneliness, extroversion, and the motivation to expand the social network mediate the positive relationship between relational mobility and social media addiction (Hypotheses 4a, 4b, and 4c).

Hypotheses 1 and 2 were not supported; we conducted a mediation analysis but observed no relationship between relational mobility and social media addiction or between reputational damage estimation and social media addiction. In contrast, when we conducted the correlational analyses, although we found no statistically significant correlation between relational mobility and social media addiction, we found a statistically significant negative correlation between relational mobility and reputational damage estimation, as well as a statistically significant positive correlation between reputational damage estimation and social media addiction. These results are partially consistent with Hypothesis 2 and imply that other factors mediate the positive relationship between relational mobility and social media addiction, which might negate the negative relationship hypothesized in Hypothesis 1.

Therefore, we additionally examined this possibility in Study 2 (Hypotheses 4a–c), which was partially supported: reputational damage estimation mediated the negative relationship between relational mobility and social media addiction, whereas the motivation to expand the social network mediated the positive relationship. This result supports Hypotheses 2 and 4c.

Additionally, we found a statistically significant main effect of sex in both Studies 1 and 2 in that females were more strongly addicted to social media than males were. Chen et al. [ 54 ] demonstrated a difference between sexes in the factors associated with smartphone addiction. They found that females were more likely to be addicted to smartphones as they used social networking services, whereas this relationship was not found for males. Although it is only a speculation, our study demonstrated that females were more strongly addicted to social media, partially because we focused on LINE, a social media especially for connecting with others.

The explorative analysis in Study 2 demonstrated an interesting interaction effect between age and the motivation to expand the social network. Those with a higher motivation to expand the social network were more strongly addicted to social media, and this effect was smaller among older people ( M + 1 SD ) than younger ones ( M - 1 SD ). This may be partially because social media usage does not expand the social networks among older people as much as among younger people. According to Kojima (2022) [ 55 ], the rate of those who use LINE every day was lower among older people (50s male: 56.3%; 50s female: 69.9%) than among young people (20s male: 76.2%; 20s female: 86.8%). Even when older people try to send messages to their friends through social media, their friends may not use social media. Future research should focus on the differences in the social media environments between various age groups.

In contrast to Hypothesis 4a, loneliness did not mediate a positive relationship between relational mobility and social media addiction. We found no relationship between loneliness and social media addiction ( r = 0.04, p = 0.23). This result is inconsistent with previous studies that have demonstrated a positive relationship between loneliness and social media addiction [ 23 ]. This non-significant relationship was surprising in that the COVID-19 pandemic would have strengthened the relationship between loneliness and social media use. Kayis et al. [ 56 ] demonstrated that the fear of COVID-19 strengthened loneliness, which in turn strengthened smartphone addiction. Although speculative, the capacity to be alone might have weakened the relationship between loneliness and addiction. As the capacity to be alone is negatively related to social media addiction [ 57 ], even when individuals feel lonely, if their capacity to be alone is significant, they will not be strongly addicted to social media. We also found that loneliness was significantly negatively correlated with relational mobility ( r = -0.26, p < 0.01), which is inconsistent with the results obtained by Oishi et al. [ 50 ], who found that participants felt lonelier when they were asked to imagine a situation wherein they frequently moved to a different location. Although relational mobility is high in societies in which people move frequently [ 58 ], this is not always the case. Even in such societies, some people have fewer opportunities to construct new relationships. This might be the reason that our results, which focused on relational mobility, were inconsistent with those obtained by Oishi et al. [ 50 ].

Moreover, in contrast to Hypothesis 4b, when we used SEM techniques and examined the following hypotheses, the model did not fit the data (RMSEA = 0.12). Although the model did not fit the data, the direction of each path was statistically significant and consistent with our hypotheses: (1) people in a lower relational mobility society estimated greater reputational damage (β = -0.21, p < 0.01), which strengthened their social media addiction (β = 0.14, p < 0.01), whereas (2) people in a higher relational mobility society were more extraverted (β = 0.40, p < 0.01), which strengthened their social media addiction (β = 0.12, p < 0.01). A reason why our model did not fit the data was the weak relationship between extroversion and social media addiction. Although some studies have demonstrated a positive relationship between extroversion and social media addiction [ 17 ], others have indicated no relationship between them [ 15 ]. Future studies should examine the factors that moderate the relationship between extroversion and social media addiction.

We also found no relationship between age and addiction in this study. This may be because, compared with studies that have focused on university students [ 28 , 31 , 54 ], the percentage of younger participants in our studies was low. Studies 1 and 2 included 6.84 and 6.20% of individuals in their 20s, respectively, and 18.10 and 17% in their 30s, respectively. Additionally, we did not recruit minors (aged < 18 years). This may be a reason for us not finding a relationship between age and social media addiction.

We also examined the accuracy of reputational damage estimation incurred by ignoring messages, as hypothesized in Hypothesis 3, which was partially supported: people in low relational mobility societies overestimate the reputational damage incurred by ignoring messages. This was consistent with Hypothesis 3. Meanwhile, people in high relational mobility societies also overestimated the reputational damage incurred by ignoring messages, which was inconsistent with Hypothesis 3.

3.3.2. Practical implications.

Our results suggest that the antecedent factors of social media addiction differ between high and low relational mobility societies, which implies that interventions for moderating social media addiction differ between high and low relational mobility societies. We demonstrated that people in higher relational mobility societies had a higher motivation to expand social networks, which strengthened their social media addiction. Therefore, moderating this motivation could be effective in preventing social media addiction.

In contrast, we also demonstrated that people in lower relational mobility societies estimated greater reputational damage incurred by ignoring messages, which strengthened their social media addiction. This reputational damage was overestimated. Other relevant studies have found that people who are highly sensitive to rejection are more likely to perceive others’ ambiguous behaviors as intentional rejections [ 59 ] and are more strongly addicted to social media [ 60 ]. These studies, as well as our results, imply that people overestimate the possibility of being rejected or reputational damage incurred by ignoring messages, which can strengthen their social media addiction. Therefore, correcting this estimation can be effective for lowering social media addiction, especially among those in lower relational mobility societies or those more sensitive to rejection.

One specific intervention can be to provide them with feedback that ignoring messages does not lower their reputation as much as they estimate. For example, by asking students in a class to evaluate those who ignore messages on social media and by showing them the distribution or average of the evaluation score, they would notice that they overestimate the reputational damage. This type of intervention has previously succeeded in changing behavior, such as reducing college students’ alcohol consumption [ 61 ]. Students used to excessively consume alcohol based on the incorrect estimation that other students prefer alcohol [ 62 ], but by correcting their inaccurate estimation (i.e., by informing them that other students do not prefer alcohol as much as they estimated), their alcohol consumption was decreased [ 61 ]. Although these studies were conducted 30 years ago and did not involve social media, we believe that modifying or correcting the estimation of reputational damage can be a novel and important intervention to lower addiction as it focuses on interpersonal miscommunications between social media users, which differs from other interventions that focus on individual aspects (e.g., asking users to reflect on “what social media they used, how long and how they used the social media, their thoughts and emotions related to their social media use” [ 5 ]).

3.3.3. Limitations and future work.

This study had several limitations. First, it only included participants from Japan. We assumed that even in Japan, different cities have different degrees of relational mobility. Indeed, some studies have surveyed people in Japan and demonstrated the effect of relational mobility on their attitudes [ 63 , 64 ]. However, Japanese people do not necessarily live in high relational mobility societies because relational mobility in Japan is low [ 44 ]. This might be the reason that, inconsistent with the prediction of Hypothesis 3, people from both high and low relational mobility societies overestimated the possibility of earning a bad reputation by ignoring messages. Additional studies must be conducted in higher relational mobility societies, such as the United States, to investigate our hypotheses.

Second, we used a crowdsourcing service to recruit participants from both high and low relational mobility societies. However, it has been demonstrated that some participants recruited via crowdsourcing services answer questions carelessly [ 65 ], which might have affected our results. Although we performed an instructional manipulation check and excluded those who did not pass it, additional studies are required to ensure the robustness of our results.

Finally, our study did not sufficiently investigate the effects of COVID-19 on distress or social media addiction. Some studies have focused on the psychological distress caused by the COVID-19 pandemic and demonstrated that it strengthened social media addiction [ 20 , 30 ]. Therefore, a possible intervention for moderating social media addiction is to lower psychological distress. Tambelli et al . [ 66 ] surveyed late adolescents (aged between 18 and 25 years) and demonstrated that those who felt a greater sense of security from their parents or peers exhibited lower COVID-19-related distress. Lowering distress by constructing good relationships with parents or peers could weaken social media addiction, at least among late adolescents.

4. Conclusion

This study demonstrated that the antecedents of social media addiction differ between high and low relational mobility societies. In Study 1, we demonstrated that people in low relational mobility societies estimate greater reputational damage, but there was no direct relationship between relational mobility and social media addiction. Therefore, in Study 2, we additionally explored the factors that mediate the positive relationship between relational mobility and social media addiction. The results indicated that (1) people in lower relational mobility societies expect higher reputational damage, which strengthens their social media addiction; and (2) people in high relational mobility societies are more motivated to expand their social networks, which strengthens their social media addiction. In addition, both studies demonstrated that people expect greater reputational damage than the actual damage. These results imply that the mechanism of social media addiction differs depending on the social environment: the estimation of reputational damage strengthens social media addiction in low relational mobility societies, whereas the motivation to expand social networks increases social media addiction in high relational mobility societies. Therefore, correcting this damage overestimation would be an effective strategy to moderate social media addiction, especially in low relational mobility societies, whereas reducing the motivation to expand social networks would be effective especially in high relational mobility societies.

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Social Media Addiction

• First Online: 18 September 2022

Cite this chapter

• Tayana Panova 4 &
• Xavier Carbonell 4  

Part of the book series: Studies in Neuroscience, Psychology and Behavioral Economics ((SNPBE))

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The immense popularity of social networks such as Facebook has led to concerns about their potentially addictive nature and the ways in which they may be negatively affecting users, especially adolescents. However, despite the fact that “Facebook addiction” and “social media addiction” have become common terms in the media and social dialogue, the empirical evidence at this time does not support the existence of such a psychological affliction for several reasons: (1) The majority of studies on social media addiction are correlational and use self-report questionnaires which are not suitable for diagnosis; (2) Most studies employ non-standardized measures, cut-off scores, and criteria, and (3) There is an absence of case studies, experimental studies, longitudinal studies, and clinical studies in the field. Social interaction is a fundamental human need which social networks facilitate. Therefore, their widespread appeal is understandable. However, although an  addiction  to social media might not exist, there are still various problems that have been associated with social media use, including lower self-esteem, Fear of Missing Out (FOMO), bullying, anxiety, and depression, among others. In this chapter, we review the research on social media addiction, analyze how it fulfills the psychological criteria that define a true addiction, discuss the various problems associated with social media use outside of the addiction framework, and explore how these problems develop as well as look at potential treatments and prevention strategies for them.

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SYSTEMATIC REVIEW article

Research trends in social media addiction and problematic social media use: a bibliometric analysis.

• 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.

Introduction

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.

Implications

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

Disclaimer: 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.

Social Media Addiction and Mental Health: The Growing Concern for Youth Well-Being

• May 20, 2024
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Kenta Minamitani, Stanford LLM 2024

The Growing Mental Health Crisis and Social Media

Mental health problems have become a major public health issue in the United States, affecting a significant portion of the population. According to the National Institute of Mental Health (NIMH), nearly one in five U.S. adults is living with a mental illness, and the prevalence of mental health problems among youth is even more alarming (NIMH, 2023). The widespread use of social networking sites has been identified as a contributing factor to the growing mental health crisis, especially among younger generations.

The Link Between Social Media and Mental Health Issues

The link between social media and mental health issues has been well documented in numerous studies and research papers. A systematic review found that the use of social networking sites is associated with an increased risk of depression, anxiety, and psychological distress (Keles, et al., 2020). The associations, though not by itself proof of causation, at least some reason for concern. Additionally, this association is particularly strong in adolescents compared to younger children (Twenge & Campbell, 2018). Moreover, in the United States, the 12-month prevalence of major depressive episodes among adolescents increased from 8.7% in 2005 to 11.3% in 2014 (Mojtabai, et al., 2016). The new media screen activities have been suggested as one of the causes of the increase in adolescent depression and suicide (Twenge, et al., 2017).

Although research has not necessarily shown that the use of social media has a causal relationship with poorer mental health in young people, health professionals and policy makers are becoming increasingly wary of the use. The U.S. Department of Health and Human Services is calling for increased transparency and for companies to prioritize user wellbeing over revenue, as various studies have shown negative effects on social media use, especially on the mental health of youth. (Surgeon General, 2021). In addition, the American Academy of Pediatrics warns that “media use and screen time are associated with increased risks for children and adolescents, such as attention deficits, increased aggression, low self-esteem, and depression” (American College of Pediatricians, 2020). The American Psychological Association (APA) also highlights the correlation between high social media use and poor mental health among adolescents (APA, 2024).

New York City’s Unprecedented Action

Recognizing the severity of the problem, New York City has taken the unprecedented step of classifying social networking sites as a public health threat (Ables, 2024). The City of New York, the New York Department of Education, and the New York City Health and Hospitals Corporation have filed a lawsuit against TikTok, Meta, Snap, and YouTube to hold the companies responsible for “fueling the nationwide youth mental health crisis” (Gold, 2024).

The lawsuit filed by New York City is a significant development in the ongoing debate about the responsibility of social media companies to address the negative impact of their platforms on mental health. The U.S. Surgeon General has called on these companies to improve the safety, health, and well-being of their users (Surgeon General, 2021). This includes implementing stricter moderation policies, providing resources for mental health support, and collaborating with researchers and health professionals to better understand the impact of social media on mental health.

A Multi-Faceted Approach to Addressing the Issue

However, addressing the complex relationship between social media and mental health requires a multifaceted approach that goes beyond the actions of social media companies. From a legal perspective, this could include government regulation and individual legal action. Policymakers could consider implementing stricter rules and guidelines for social media companies to follow, such as requiring them to prioritize user well-being and mental health over engagement and profits. This could include mandating regular mental health impact assessments, providing resources for mental health support, and implementing stricter content moderation policies to reduce the spread of harmful and toxic content. However, since strong opposition is expected from users and companies on human rights grounds, including violations of freedom of expression, it is crucial to organize the evidence to date and explain convincingly that the restriction is urgently needed for public health reasons and that there are no other measures that could be taken.

Mental health professionals must adapt to the changing landscape of technology and incorporate social media literacy into their treatment plans. The NIMH emphasizes the importance of teaching individuals how to maintain a healthy relationship with social media, including setting limits on use, engaging in offline activities, and seeking support when needed (NIMH, 2023).

Educational institutions also have a critical role to play in promoting digital literacy and responsible social media use among students. Schools should incorporate digital literacy education into their curricula and teach students how to navigate social media in a healthy and productive way. Parents and caregivers must also be involved in this process by setting appropriate boundaries and modeling responsible social media use, as parental media monitoring has protective effects on a variety of academic, social, and physical outcomes for children (Gentile, et al., 2014).

As individuals, we must take responsibility for our own mental health and well-being in the digital age. This means being mindful of the time we spend on social networking sites, curating our feeds to include positive and uplifting content, and prioritizing offline activities and relationships. In this case, we can use the guidelines or recommendations published by the professionals; for example, the APA has published “Social Media Recommendations” to advocate the appropriate use of social media based on scientific evidence (APA, 2023).

Looking Ahead

As we look to the future, it is clear that the issue of social networking and mental health will continue to be a pressing concern. As technology advances and new platforms emerge, it is critical that we remain vigilant and proactive in addressing the potential risks associated with these services. Increased research and collaboration among policymakers, legal experts, social media companies, mental health professionals, and educators is needed to address this growing issue and develop effective strategies to promote healthy social media use and mitigate its potential harms.

• Ables, K. (2024, January 25). New York City designates social media a public health hazard. The Washington Post. https://www.washingtonpost.com/technology/2024/01/25/nyc-social-media-health-hazard-toxin/
• American College of Pediatricians. (2020). Media Use and Screen Time – Its Impact on Children, Adolescents, and Families. https://acpeds.org/position-statements/media-use-and-screen-time-its-impact-on-children-adolescents-and-families
• American Psychological Association. (2024). Teens are spending nearly 5 hours daily on social media. Here are the mental health outcomes. https://www.apa.org/monitor/2024/04/teen-social-use-mental-health
• American Psychological Association. (2023). Social media brings benefits and risks to teens. Here’s how psychology can help identify a path forward. https://www.apa.org/monitor/2023/09/protecting-teens-on-social-media
• Gentile DA, et al. (2014) Protective Effects of Parental Monitoring of Children’s Media Use: A Prospective Study. JAMA Pediatr. 168(5):479–484. https://doi.org/10.1001/jamapediatrics.2014.146
• Gold, A. (2024, February 14). New York City sues social media companies for negligence, public nuisance. Axios. https://www.axios.com/2024/02/14/new-york-city-sues-social-media-companies-for-negligence-public-nuisance
• Guernsey L (2014). Garbled in translation: Getting media research to the press and public. Journal of Children and Media, 8(1), 87–94. https://doi.org/10.1080/17482798.2014.863486
• Keles, B., et al. (2020). A systematic review: The influence of social media on depression, anxiety and psychological distress in adolescents. International Journal of Adolescence and Youth, 25(1), 79-93. https://doi.org/10.1080/02673843.2019.1590851
• Mojtabai R, et al. (2016). National trends in the prevalence and treatment of depression in adolescents and young adults. Pediatrics, 138(6), e20161878. https://doi.org/10.1542/peds.2016-1878
• National Institute of Mental Health. (2023). Mental illness. https://www.nimh.nih.gov/health/statistics/mental-illness
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• Twenge JM, et al. (2017). Increases in depressive symptoms, suicide-related outcomes, and suicide rates among US adolescents after 2010 and links to increased new media screen time. Clinical Psychological Science, 6(1), 3–17. https://doi.org/10.1177/2167702617723376
• Twenge, J. M., & Campbell, W. K. (2018). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 12, 271–283. https://doi.org/10.1016/j.pmedr.2018.10.003

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• http://orcid.org/0000-0002-2881-8299 Silja Kosola 1 , 2 ,
• Sara Mörö 1 ,
• Elina Holopainen 3
• 1 Pediatric Research Center , Helsinki University Hospital and University of Helsinki , Helsinki , Finland
• 2 Research, Development and Innovations , Western Uusimaa Wellbeing Services County , Espoo , Finland
• 3 Department of Obstetrics and Gynecology , Helsinki University Hospital , Helsinki , Finland
• Correspondence to Dr Silja Kosola, University of Helsinki, Helsinki, Finland; silja.kosola{at}helsinki.fi

Background and objectives Recent studies have reported an increasing incidence of anxiety among adolescent girls, and associated this with self-reported social media use. This study aimed to measure smartphone and social media use objectively and to evaluate its associations with measures of mental health and well-being.

Methods In autumn 2022, we recruited a cohort of 1164 first-year female students from 21 socioeconomically diverse high schools. Students responded to an online survey comprising validated questionnaires (Bergen Social Media Addiction Scale (BSMAS), Generalised Anxiety Disorder-7, and Body Appreciation Scale 2) and visual analogue scales of current health, mood, tiredness, and loneliness. We also requested that they attach screenshots depicting their smartphone use.

Results Among participants (mean age 16.3 years), 16% (n=183) had possible social media addiction and 37% (n=371) exceeded the cut-off for possible anxiety disorders. The BSMAS scores were associated with higher anxiety (r=0.380) and poorer body image (r=−0.268), poorer health (r=−0.252), lower mood (r=−0.261), greater tiredness (r=0.347), and greater loneliness (r=0.226) (p<0.001 for all). Among the 564 adolescents (48%) who sent screenshots of their smartphone use, average daily use was 5.8 hours (SD 2.2), including 3.9 hours (SD 2.0) of social media. Participants who sent screenshots had a higher grade point average than participants without screenshot data, but similar BSMAS and well-being measures.

Conclusions Consistent with other studies, we found social media addiction was common among adolescent girls and was associated with poorer mental health and well-being. Measures should be taken to protect adolescents from the potential harmful effects of social media use.

• Adolescent Health
• Mental health
• Epidemiology

Data availability statement

Data are available upon reasonable request. Due to data protection requirements of our institution, pseudonymous data may be shared within the EU.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/archdischild-2023-326521

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Recent studies have indicated increasing anxiety among adolescent girls and associated this with social media use. We found no previous studies combining objectively collected data on smartphone or social media use and validated measures of social media addiction and well-being.

WHAT THIS STUDY ADDS

In a population-based cohort, smartphone use approached 6 hours daily and one in six adolescent girls had possible social media addiction. Social media addiction scores were associated with poorer well-being.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Objectively measured smartphone and social media use should be assessed in both research and practice settings, while policymakers should limit the addictive elements of social media.

Introduction

Anxiety and other mental disorders are significant contributors to adolescent morbidity in high-income countries. 1 2 Since 2013, reports from high-income countries have indicated a significant rising trend in the prevalence of anxiety, especially among girls. 1 2 In some countries, mental health problems are already the leading cause of absence from work among young adults. 3 During the COVID pandemic, anxiety rates among adolescent girls continued to increase. 4

In a decade, the rapid evolution of technology and applications have led to an unprecedented increase in both the frequency of use and cumulative time spent on social media. A longitudinal study from the UK from 2013 to 2015 found that very frequent social media use, more than three times daily, predicted later psychological distress. 5 In time-use diaries from 2015, 73% of participants used social media for less than 30 min daily, and highest social media use was defined as 120 min daily or more. 6 A longitudinal study from the USA conducted between 2014 and 2016 found that more than 3 hours of social media use, compared with no use, was associated with an increased risk of internalising problems 1 year later (relative risk 1.60). 7 In 2021, American adolescents daily spent on average 3.5 hours on social media and, in 2023, the US Surgeon General’s advisory increased awareness of the connection between social media and youth mental health. 8 9

Anxiety related to social media use may be related to several factors, one of which is addiction. 10 Social media addiction conforms to the same criteria as other behavioural addictions: time spent, craving, attempted control, withdrawal symptoms, and social problems. 11 International prevalence estimates of social media addiction range between 5% and 31%. 10 We found no studies combining objectively collected data on social media use with mental health outcomes. The research community has called for more detailed, objective measures of smartphone and social media use and for utilising validated assessment tools whenever possible. 12 13

Because both anxiety and social media use are more prevalent among girls, we aimed (1) to measure objectively the time adolescent girls spend using their smartphones and especially social media,(2) move beyond simple measures of duration by measuring possible social media addiction using a validated scale, and (3) estimate the associations of social media use and social media addiction with well-being. We hypothesised that social media use and addiction would be associated with increased anxiety, tiredness and loneliness, and worse body image, health and mood among adolescent girls.

Setting and design

The School, Sport, and Social media study (3S) is a population-based, prospective cohort study. The study documents were developed in collaboration with the nine young members of the Youth Research Advisory Board of the Helsinki University Hospital, Helsinki, Finland. After the authors drafted the questionnaire and information and consent forms, the board reviewed them and all documents were revised based on the feedback from the board. Here, we report the findings from the first wave of data collection.

After ethics approval and the approval of the respective municipal educational administrations, we contacted all 49 high schools of three large cities in the capital region of Finland (Helsinki, Espoo, and Vantaa; background population 1.2 million). The principal of each school decided whether the school would participate.

Students are aged 15–16 years at the start of high school. At the end of 2021, the population of 15-year-old girls in these cities totalled 6030. 14 After ninth grade, academic high school positions are provided for about 66% of the birth cohort, while the rest continue to vocational education. Education is publicly funded, although some schools are operated by independent organisations. In Finland, school grades range from 4 to 10 (4 means failing a subject and 10 means high achievement) and, in the study area, a minimum grade point average (GPA) of 7.0 at the end of ninth grade is required for entry into high school (school years 10–12).

In 2021, 99% of the population aged 16–24 years owned a smartphone in Finland. 14

Study population

We visited the participating high schools at the start of the autumn term 2022 and, after providing information on the study to first year female students, collected consent forms from voluntary participants. Participants completed a survey using RedCap, a secure online tool for surveys and databases. Surveys were available in both official languages, Finnish and Swedish. Participants received a movie ticket (value 9€ (£7.70)) after survey completion. Based on power calculations, we aimed to recruit 1000 participants. Assuming a 10% prevalence of social media addiction, 10 this would allow detection of a 3-point difference between groups in outcome measures at 0.05 level.

Twenty-one geographically and socioeconomically diverse schools chose to participate. The 1164 participating adolescents comprised 59.1% of female high school students in the participating high schools and 29.3% of all female high school students in the study area.

Demographic data included date of birth, self-reported gender (non-binary), school name and GPA at the end of the previous spring term.

Smart phone and social media use

Participants estimated their daily smartphone use and were then asked to attach screenshots of the tools (iPhone Screen Time, Huawei Digital Balance, Android Digital Wellbeing) measuring their smartphone use to the survey which allowed participation regardless of phone brand. From the screenshots, we recorded the number of days with screen time data available, daily smartphone pickups, number of most frequently used applications, and time spent using each of them. We divided the total screen time by the number of days for a variable of average daily screen time. We summed the time used on similar types of applications (eg, social media, shopping) and divided this sum by the number of days with data available to find the average daily time spent on different activities. Please see online supplemental table 1 for the classification of applications. We also calculated the proportion of total screen time explained by the data that were available from the screenshots.

Supplemental material

Social media addiction.

The Bergen Social Media Addiction Scale (BSMAS) was forward and backward translated into Finnish and Swedish and used to measure possible addiction. 15 BSMAS is a generalised modification of the previously validated Bergen Facebook Addiction Scale. 16 BSMAS is a 6-item tool with a 5-point Likert scale (‘very rarely’ to ‘very often’). Total scores range from 6 to 30, with higher points indicating higher risk of social media addiction. The developers of BSMAS suggest that scoring ‘often’ or ‘very often’ (ie, 4 or 5 points) for at least four of the six items indicates addiction.

Anxiety was measured using the 7-item generalised anxiety disorder scale (GAD-7), which has been broadly used internationally and in both Finnish and Swedish. 17 Items are scored on a 4-point Likert scale (‘not at all’ to ‘nearly every day’). Total scores range from 0 to 21, with higher points indicating higher levels of anxiety. A cut-off of 10 has a sensitivity of 89% and a specificity of 82% for diagnosis of generalised anxiety disorder (GAD), and 68% sensitivity and 88% specificity for any anxiety disorder. 18 Scores 10–14 may indicate moderate anxiety and scores ≥15 severe anxiety. 17

Body appreciation

The Body Appreciation Scale-2 (BAS-2) was available in Finnish and Swedish and was used to measure positive body image. 19 20 The BAS-2 consists of 10 items, each scored on a 5-point Likert scale (‘never’ to ‘always’). Total scores range from 10 to 50, and higher scores indicate more positive body image.

General well-being

Participants evaluated their current health, mood, tiredness, and loneliness on visual analogue scales from 0 to 100 mm. 21 22 Tiredness and loneliness were reverse scored. In the results, higher scores indicate better well-being.

Statistical analysis

Descriptive statistics included frequencies for self-reported gender and adolescents who scored above the predefined cut-offs for possible addiction or anxiety. Means with SD were used for continuous variables with normal distribution and medians with IQR in case of uneven distribution. Pearson correlation coefficients between continuous variables were calculated according to the hypotheses. Welch’s t-test was used to compare groups with possible social media addiction and no addiction. Adolescents who sent screenshots and those who did not were compared in a ‘sensitivity analysis’. IBM SPSS Statistics version 25 was used for analyses.

The flow chart of data collection is shown in figure 1 and participant characteristics are presented in table 1 .

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Flow chart of data collection. In Finland, all education is publicly funded until a person turns 18 or completes their upper secondary education (ie, academic high school or vocational education). Private schools offer the same education as public schools based on the national education plans, and they cannot charge fees for tuition. GPA, grade point average; SES, socioeconomic status.

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Characteristics of 1164 study participants

Adolescents estimated their daily time on social media to be 312 (SD 138) min, or 5.2 hours ( table 2 ).

Estimated (n=1164) and objective (n=564) smartphone use

Data on average daily smartphone use based on at least 3 days of usage were available for 656 adolescents (56.4%) and 7 days of data for 298 (25.6%). Average daily smartphone use was 350 min, or 5.8 hours, and average time spent using social media was 231 min, or 3.9 hours. Within subject time estimates and objective data showed a medium correlation (r=0.418, p<0.001). No significant difference was found between weekdays or weekends or between data based on 3 to 6 or 7 days of usage ( online supplemental table 2 ).

Detailed data on the most used applications were available for 564 adolescents (48.5%). In all, 205 adolescents (36.3% of those with data available) used social media for less than 3 hours daily, while 77 (13.6%) used social media for 6 hours or more. Data on the frequency of smart phone pick-ups was only available for 74 participants (13.1%); these ranged from 58 to 356 times daily (median 145). For 115 adolescents (20.4%) the most frequently used applications included games which they played for a median of 24 min (range 1–211) per day.

Based on the BSMAS, 183 adolescents (16.6%) had possible social media addiction ( tables 3 and 4 ).

Social media addiction, anxiety, and body appreciation

Group comparisons between adolescents with no social media addiction (n=920) and adolescents with possible addiction (n=183) as means (SD)

On the GAD-7, 371 adolescents (37.2%) scored above the cut-off for potential anxiety disorder.

In unadjusted analyses, daily time on social media was associated with lower GPA (r=−0.280, p<0.001), higher social media addiction scores (r=0.200, p<0.001), higher anxiety (r=0.123, p=0.008), and poorer body image (r=−0.108, p=0.017). Social media addiction scores were associated with higher anxiety, poorer body image, poorer health, lower mood, greater tiredness and greater loneliness ( table 5 ).

Correlations between the Bergen Social Media Addiction Scale Scores and wellbeing measures

The only difference found between adolescents who sent screenshots and those who did not was the higher GPA among adolescents who sent screenshots ( online supplemental table 3 ).

In this study, daily smartphone use among study participants approached 6 hours, and objectively measured and self-reported times used on social media showed a medium correlation with each other. Daily time on social media was associated with lower GPA, increased anxiety, lower body image, and lower well-being.

Smartphone and social media use have increased very rapidly. When a cohort of British adolescents was followed from 2013 to 2015, the proportion of adolescents who used social media regularly more than three times daily increased from 42.6% to 68.5%. 5 In a UK study from 2015, 65% of 15-year-olds used social media for less than 30 min per day. 6 In a small Swedish study conducted in 2019, objectively measured smartphone use among 10- to 15-year-olds averaged 161 min per day, 23 compared with 350 min in our study.

Recently, experts have expressed that total screen time is irrelevant compared with what the screen time comprises. 24 In this cohort, adolescents spent nearly 6 hours daily on their smartphones, and educational and creative purposes accounted for a minority of this time. In Finnish schools, students mostly use laptop computers for their studies and homework. Considering the average length of school days and amount of homework, multitasking on smartphones was very likely to occur. Media multitasking concurrently with studying has been associated with study-related stress. 25 26 Another pathway between social media use and poorer well-being may be the social comparisons that worsen body satisfaction. 27 Although we had no data on the time of-day adolescents used social media, sleep length is another factor connecting social media use and well-being. 5 Among Chinese youth (age 11–25), each minute of objectively measured social media use was associated with 0.3 min less objectively measured sleep the following night. 28

Differences are probable in the use of different types of screens. Smartphones provide a convenient platform for social media but their portable nature also increases the chances of addictive behaviour and harmful multitasking. 26 Internet gaming disorder has been added to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, 29 but the immobile nature of personal computers usually used in gaming could be a protective factor compared with heavy users of social media.

To the best of our knowledge, this is the first study to combine objectively measured smartphone use with validated measures of social media addiction and well-being. Our study’s strengths also include the population-based cohort and high participation rate. We carefully compared participating and non-participating schools as well as adolescents with and without screenshots that provided detailed data on their smartphone use. The greatest limitation of our study is its cross-sectional nature which means potential for both confounders and reverse causation. The results should be interpreted with due caution. We lack knowledge on why many schools chose not to participate. Although the participating schools were from socioeconomically diverse neighbourhoods and included schools with different admission requirements, the study participants only represent adolescents who had chosen the academic high school track and the results may not be generalisable to the whole population. In repeated national surveys, however, girls in high school and in vocational education have reported similar health and well-being. 30 We had no exclusion criteria for participation and some of the study participants may have had pre-existing mental health problems that could confound the results. Adolescents with mental health problems may have been less likely to participate, thus contributing to bias. Also, GPA was self-reported. Our method of assessing smartphone use was challenging for the adolescents and time-consuming for researchers, but European data protection requirements impeded the use of foreign applications for this purpose. Less than half of study participants sent screenshots depicting their smartphone use as requested. Participants who sent screenshots had higher GPA than participants who sent no screenshots or whose screenshots were incomplete, but no difference was found in other measures. Previously, heavy social media use has been associated with lower academic performance and lower socioeconomic status. 31 32

Although we report results from a cross-sectional setting, the implications of nearly 6 hours of daily smartphone use and its associations with adolescent well-being are serious. Self-reported screen time showed a medium correlation with objectively measured use, and future studies should aim to quantify smartphone use objectively. While some advocate for increased mental health services to tackle the rise in adolescent anxiety, 33 no services will suffice unless the root causes are addressed. Consequently, we found the US Surgeon General’s advisory on social media and youth mental health a welcome reminder of the precautionary principle and an important call to action. 9 Professionals should support caregivers in establishing tech-free zones and in fostering in-person relationships. Policymakers should strengthen safety standards and urge technology companies to prioritise safety and health in the development of social media.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the HUS Regional Committee on Medical Research Ethics (HUS/117/2022). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We thank the members of the Youth Research Advisory Board, all study participants, and participating schools. Members of the Youth Research Advisory Board critically reviewed the study questionnaire. SM and medical student Ines Sederholm recruited study participants and acquired data. We acknowledge the help of medical student Ines Sederholm in the recruitment process.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

X @SiljaKosola

Contributors SK, SM and EH conceived and designed the study. SK conducted data analyses. SK, SM and EH interpreted the results. SK is the guarantor of this study.

Funding This study was funded by the Helsinki University Hospital, the Gyllenberg Foundation, the Finnish Society of Pediatric and Adolescent Gynecology, the Foundation for Pediatric Research, the Finnish Medical Foundation, the Olvi Foundation, the Yrjö Jahnsson Foundation, and the Wihuri Foundation.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Is Social Media Fueling Teen Addiction? Uncovering the Hidden Links

In an age where smartphones are as ubiquitous as backpacks in schools, social media has become a pivotal part of teenage life.

While these platforms offer a way for teens to connect and share with peers, they also bring a set of challenges that parents and educators cannot ignore.

One such challenge is the potential role social media plays in substance abuse among teenagers.

Let’s delve into how these digital interactions might be more than just harmless fun, possibly acting as a catalyst for risky behaviors, including drug and alcohol use.

The Social Media Landscape and Teen Engagement

Today, nearly all teenagers in the United States engage with social media on various platforms.

From Snapchat’s quick updates to Instagram’s visual appeal and TikTok’s engaging video content, these platforms capture the attention of young users for hours each day.

Social media isn’t just a tool for communication; it’s a significant part of how teens form their identities and understand the world around them.

They see and share a wide range of content, from the mundane to the extraordinary, influencing their perceptions and behaviors significantly.

The Influence of Social Media on Teen Behavior

The impact of social media on teenagers extends beyond simple communication; it shapes their behaviors and expectations in profound ways.

Teens are exposed to a barrage of images and stories that glorify party culture, including the use of substances like alcohol, vaping, and recreational drugs. These portrayals often lack the context of consequences, presenting a skewed reality that can be enticing at a glance.

As teens scroll through their feeds, the line between online glamorization and real-life choices begins to blur.

Here lies the critical concern about how social media affec t s teen decision-making , especially regarding substance use and abuse.

Peer Pressure in the Digital Realm

While traditional notions of peer pressure involve face-to-face interactions, social media has transformed it into a 24/7 dynamic. Teens are not only influenced by their close friends but also by popular influencers and celebrities who often promote lifestyles laden with risky behaviors.

This digital form of peer pressure can be even more insidious because it comes with a veil of anonymity and lacks the immediate physical presence of peers.

Yet, it’s pervasive and persistent, making it harder for teens to resist because it appears to be the norm.

They face a continuous stream of online cues that can push them toward substance use as a way to fit in or seem cool in a highly curated social media environment.

The Role of Parents and Educators in Mitigating Risks

The involvement of parents and educators is essential to buffer the negative effects of social media on teenagers.

It’s important for adults to become savvy about the digital environments their teens inhabit and to engage in open, ongoing conversations about the realities versus the portrayals of substance use online.

Educating teens about the marketing tactics used on social media, including the promotion of unhealthy behaviors, can empower them to make more informed choices.

Parents can set boundaries around the use of social media, but more importantly, they should strive to foster a relationship where teens feel comfortable discussing what they encounter online.

Legal and Ethical Considerations

As society grapples with the evolving challenges of social media and its impact on youth, legal and ethical questions come to the forefront.

There are growing demands for social media platforms to implement stricter regulations and more robust age verification processes to protect young users from harmful content.

There is a debate about the extent to which these companies should be held accountable for the content that may contribute to risky behaviors such as substance abuse among teens.

These considerations highlight the need for a balanced approach that respects the rights of young users while protecting them from potential harm.

Navigating Addiction Treatment for Teens

Recognizing the signs of substance abuse early can significantly enhance the effectiveness of treatment for teens. Today, there are numerous resources and programs designed to address teen addiction, with approaches ranging from inpatient facilities to outpatient counseling and support groups.

For families seeking assistance, finding a teen treatment center near Carlsbad or in other major cities like Atlanta, Boston, and Chicago can provide the specialized care needed to address these challenges.

These centers often use a combination of therapy, education, and peer support to help teens recover and regain control over their lives.

The focus is on healing the whole person, not just stopping the substance use, ensuring that recovery is sustainable and holistic.

Social media is an integral part of modern teenage life, but its influence on substance abuse cannot be overlooked.

As a catalyst for risky behaviors, it presents a complex challenge that parents, educators, and society must address. Understanding and mitigating the influence of social media on teen behavior is essential for fostering healthier generations.

By promoting open dialogue, setting realistic expectations about social media use, and providing robust support systems, we can help steer our teens away from substance abuse and towards more positive and productive ways to use their digital spaces.

The post Is Social Media Fueling Teen Addiction? Uncovering the Hidden Links appeared first on Kellys Thoughts On Things .

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
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As social workers join Northeast Ohio first responders, studies of mental health outcomes are few

Earlier this month, four Cuyahoga County suburbs announced they would employ social workers to work alongside police and firefighters — following the lead of Shaker Heights, which started a pilot program in 2022.

The concept is meant to improve outcomes for people suffering mental health crises. And while it's only now beginning to spread in Northeast Ohio, the idea of having trained mental health professionals work with first responders isn't new nationally.

A few police departments have used social workers for decades, according to the Ohio Attorney General’s Office . And while the current count of police and fire departments with social workers is unknown , it appears that a growing number of cities have hired mental health workers amid recent demands for police reform.

How effective is the practice in averting mental health crises?

That's unclear.

A 2018 systematic review published to BioMed Central Psychiatry determined, “There remains a lack of evidence to evaluate the effectiveness of street triage and the characteristics, experience, and outcomes of service users."

The report found there's a lot of variation between departments in terms of hours worked, staffing practices and incident response methods — making it difficult to study overall impacts.

However, researchers from Western Carolina University did note that establishing definitive roles between police and social workers appears to result in better outcomes .

When officers and mental health professionals respond to calls together and play distinct roles in dealing with the crisis, "officers benefit by gaining a better understanding of mental health issues, and community members report that these interactions are less stressful and less stigmatizing than a traditional police response,” the researchers wrote.

Success in other cities

Eugene, Oregon has paired crisis workers with its police department for the past 30 years. When calls that contain a mental health component come in, a medic and a crisis worker employed by a local clinic respond. Police only respond if the situation seems to require their help, according to NPR .

In Denver, a mental health response team that paired social workers with police answered nearly 750 calls in six months with no arrests, NPR reported in 2021 . City officials declared that pilot program a success and have allocated funds to continue it.

Closer to Northeast Ohio, the city of Columbus expanded its Alternative Response Pilot Program in 2021 to reduce police involvement in mental health, drug addiction and other calls concerning social matters. That pilot program showed early promise, The Columbus Dispatch reported . All 56 calls received in the first 18 days were handled without any reported use of force, and nearly half required no police or fire presence.

But that program has yet to move from the pilot stage, according to WCMH . Columbus City Council previously said it would set aside money in the city’s operating budget to fund the program, but has failed to do so as of last fall, WCMH reported.

"By intervening early, these teams promote treatment, recovery, and show the community that mental health is taken seriously with the care of the individual in mind."

In Cleveland, police partnered with the Cuyahoga County Alcohol, Drug Addiction, and Mental Health Services (ADAMHS) Board to develop a Crisis Intervention Training — part of a national program designed to train police officers to handle encounters with individuals living with mental illness.

There were nearly 5,000 Crisis Intervention Team incidents in Cleveland in 2022. Of those, mental health issues were present in 89%. Nearly half of those calls required verbal de-escalation techniques while 16% required additional police presence. Only 18 incidents in 2022 required use of force, according to data from the program .

Cleveland has been exploring the concept of sending trained community workers on crisis calls instead of police officers. The city and ADAMHS Board have collaborated on a pilot program expected to launch this summer in two zip codes.

Results in Shaker Heights

The success of Shaker Heights’ mental health response program has led to its expansion to Cleveland Heights, Richmond Heights, South Euclid and University Heights.

Shaker Heights Mayor David Weiss said the city had noticed an increase in 911 calls rooted in mental health issues in the seven years he’s served as mayor, but first responders weren’t properly trained to handle such calls.

As a result, Weiss said the city categorized three types of people served by the mental health response program: someone with known mental health issues, those who weren’t known to have mental health issues and those who were previously in one of the first two categories who may need follow-up care.

Annette Amistadi, the full-time mental health response program clinician in Shaker Heights, works with the city’s first responders and sometimes responds to calls, or provides resources to prevent future incidents. Overall, the skills required of her job differ from other first responders.

“A lot of times, someone in crisis just needs to be heard, and so our mental health professionals and our peers are trained in that active listening and de-escalation to really get what that person needs,” Amistadi said at a press conference earlier this month. “That way, they can refer them to the right service.”

In 2023, Shaker Heights’ program had 645 referrals and completed 730 follow-ups.

Weiss noted that his police and fire chiefs were supportive of the program, contrary to concerns they would feel it infringes on their scope of services.

“In fact, it's just the opposite. They have been huge supporters from day one, and have been terrific partners,” Weiss said.