research articles on social media addiction

• 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.

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

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Social media use has become part of daily life for many people. Earlier research showed that problematic social media use is associated with psychological distress and relationship satisfaction. The aim of the present study was to examine the mediating role of psychological distress in the relationship between social media addiction (SMA) and romantic relationship satisfaction (RS). Participants comprised 334 undergraduates from four mid-sized universities in Turkey who completed an offline survey. The survey included the Relationship Assessment Scale, the Social Media Disorder Scale, and the Depression Anxiety and Stress Scale. According to the results, there were significant correlations between all variables. The results also indicated that depression, anxiety, and stress partially mediated the impact of SMA on RS. Moreover, utilizing the bootstrapping procedure the study found significant associations between SMA and RS via psychological distress. Consequently, reducing social media use may help couples deal with romantic relationship dissatisfaction, thereby mitigating their depression, anxiety, and stress.

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Establishing social relationships is one of the basic needs of human beings (Heaney & Israel, 2008 ). How this basic need is met can vary greatly. In particular, technological developments, such as computers, the Internet, and smartphones have created new ways for people to communicate with each other. One of the most successful new means of communication is through social media. Social media involves many different communication (i.e., social networking) platforms. Among the most popular are platforms in Western countries are Facebook, Twitter, Instagram, and YouTube. These sites, which are accessed via the Internet, provide many opportunities for communication, such as voice and video messaging, photograph and video sharing, and creating profiles, through which individuals can introduce themselves and make connections with others.

The communication opportunities brought about by social networking sites (SNSs) allow for the development of social relationships (Fuchs, 2017 ; Hazar, 2011 ; Valentini, 2015 ). In addition, social media is used for a wider variety of purposes, including obtaining information, communicating, entertainment, playing games, and sharing photos, videos, and music (Griffiths, 2012 ). However, excessive use of social media including SNSs can cause negative effects (Griffiths, 2013 ; van den Eijnden et al., 2016 ). This phenomenon, which is sometimes referred as “social media addiction,” is defined as the irrational and excessive use of social media at a level that negatively affects the daily life of the user (Griffiths, 2012 ). When social media use reaches the level of addiction, it can prevent the establishment of real, face-to-face social relationships (Glaser et al., 2018 ; Kuss & Griffiths, 2017 ; Young, 2019 ). When general characteristics of social media addiction have been examined, it has been found that individuals tend to have restless thoughts concerning the urges and craving to be on social media, lose their self-control over their use of social media, spend excessive amounts of time staying on (or thinking about) social media which in turn lead to negative impacts on their relationships with their families and friends, and compromise their occupation and/or education (Andreassen et al., 2012 ; Griffiths et al., 2014 ). Therefore, examining social media addiction in terms of its effect on human relationships and mental health is an important pursuit.

Theoretical Framework

Social media addiction and relationship satisfaction.

Research into the effects of social media addiction on romantic relationships has increased (Abbasi, 2019a ; Demircioğlu & Köse, 2018 ). The literature suggests that social media addiction negatively affects romantic relationships due to its tendency to create jealousy and suspicion and facilitate deception between married couples and committed partners (Abbasi, 2019b ). Additionally, problematic social media use can hinder the development of face-to-face relationships (Glaser et al., 2018 ; Kuss & Griffiths, 2017 ; Pollet et al., 2011 ; Young, 2019 ). Therefore, it is possible that some couples’ relationships may become disrupted and that dissatisfaction may be experienced. In some cases, not only has social media use decreased the amount of relationships that individuals have in person, but it has also markedly impaired the quality of the time spent together. Therefore, it can be concluded that some couples may experience relationship dissatisfaction.

Similarly, social media addiction can result in low relationship satisfaction due to the existence of online alternative centers of attraction and investments of time and emotion outside the bilateral relationship in individuals aged between 18 and 73 years (Abbasi, 2019a ). In addition, social media addiction has also been associated with physical and emotional infidelity, romantic separation, decline in the quality of romantic relationships, and relationship dissatisfaction (e.g., Abbasi, 2019a , b ; Demircioğlu & Köse, 2018 ; Valenzuela et al., 2014 ). Therefore, these aforementioned findings indicate that social media addiction negatively affects relationship satisfaction.

Social Media Addiction and Psychological Distress

One of the most important consequences of social media addiction is the mental health of individuals. When social media use reaches the level of addiction, it can create stress and negatively affect mental health rather than being a method of healthy coping. This occurs because social media addiction triggers social media fatigue and, as a result, individuals may experience anxiety and depression (Dhir et al., 2018 ). Social media users may use social media as a means of diversion in order to cope with stress (van den Eijnden et al., 2016 ). However, social media addicts give a lower priority to hobbies, daily routines, and close relationships (Tutgun-Ünal & Deniz, 2015 ) which in turn lead to problems with daily functioning, completion of tasks, and relationship maintenance. This puts such individuals at risk for experiencing negative physical and psychological health.

In fact, some research has claimed that social media addiction triggers psychological distress factors, such as depression, anxiety (Woods & Scott, 2016 ), and stress (Larcombe et al., 2016 ). In addition, a meta-analysis synthesizing the findings of 13 studies found that social media addiction may increase depression, anxiety, and stress levels (Keles et al., 2020 ). In both meta-analyses and cross-sectional studies, it has been found that social media addiction can increase psychological distress (e.g., Hou et al., 2019 ; Keles et al., 2020 ; Marino et al., 2018 ; Meena et al., 2015 ). In sum, these findings consistently associate social media addiction with psychological distress.

Psychological Distress and Relationship Satisfaction

Individuals experiencing psychological discomfort often have non-functional communication styles characterized by highly negative behaviors, such as criticism, complaining, hostility, defensiveness, and tendency to end relationships. They also experience problems actively listening to others (Fincham et al., 2018 ). In this respect, psychological distress prevents healthy communication in relationships, and a lack of healthy communication may cause conflicts that can embitter psychological distress between couples. Such a situation can continue in a cyclical manner that prevents relationship satisfaction. In romantic relationships, couples are supposed to fulfill their partners’ emotional needs (Willard, 2011 ). When individuals have psychological problems due to social media addiction, they will ignore their partner’s emotional needs because they would be trying to deal with their own problems, which, in turn, may lead to lower relationship satisfaction.

When psychological distress and romantic relationship satisfaction are examined, it can be seen that much psychological distress, such as major depression, panic disorder, social phobia, general anxiety disorder, post-traumatic stress disorder, and mood disorder, positively predict relationship dissatisfaction (Whisman, 1999 ). On the other hand, it can also be seen that individuals who are sensitive to negative affect in romantic relationships and who can successfully stop these emotions early on and cope with their feelings are satisfied with their relationships (Fincham et al., 2018 ).

Couples who have high levels of stress are reported to experience less satisfaction in their relationships (Bodenmann et al., 2007 ). In addition, it is known that depression negatively predicts relationship satisfaction (Cramer, 2004a , b ; Tolpin et al., 2006 ). Therefore, it appears that psychological distress negatively affects relationship satisfaction.

The Present Study

The prevalence of the use of the internet and Internet-related tools has consistently increased year on year (Roser et al., 2020 ). Even though the social media use is widespread and facilitates communication when it is used normally, it can negatively affect daily life when it is used excessively by some individuals. Literature reviews have shown that social media addiction has been mostly studied in East Asian countries like China, Japan, and South Korea (e.g., Bian & Leung, 2015 ; Kwon et al., 2013 ; Tateno et al., 2019 ). In this respect, when the prevalence of social media use among Turkish people and the different cultural context of the present study are considered, the findings would arguably make important contributions to the current literature. Furthermore, the present study appears to be the first to examine the mediating role of psychological distress in the relationship between social media addiction and romantic relationship satisfaction.

Older aged adolescents and emerging adults are inextricably connected with technology in terms of their social media use and stand out as an important risk group in relation to problematic social media use (Griffiths et al., 2014 ). Many young adults closely follow technological developments and often adopt every innovation that arises into their lives without wasting time (Kuyucu, 2017 ). When such use becomes problematic, some individuals experience serious difficulty in maintaining their mental health. For example, cross-sectional studies among adolescents (Woods & Scott, 2016 ) and young adults (Larcombe et al., 2016 ) have found that social media addiction can lead to stress, anxiety, and depression. Moreover, the establishment of close relationships as a young adult is an important stage of emotional and social development (Cashen & Grotevant, 2019 ; Orenstein, & Lewis, 2020 ). Romantic relationship satisfaction may be seen as an important indicator of young people’s ability to engage in intimacy in a healthy manner (Orenstein & Lewis, 2020 ). Therefore, the findings obtained as a result of examining the relationships between social media addiction, psychological distress, and romantic relationship satisfaction among young people will contribute to an understanding of the associations between the psychological and social variables regarding maintenance of their mental health and their success in establishing close relationships.

In previous studies of the variables examined in the present study, even though studies examining the three variables dichotomously have been conducted (e.g., Abbasi, 2019a , b ; Bodenmann et al., 2007 ; Keles et al., 2020 ; Larcombe et al., 2016 ; Whisman, 1999 ), no research examining social media addiction, psychological distress (depression, anxiety and stress), and romantic relationship satisfaction together has been published. In particular, there is no study examining the role of psychological distress mediating between social media addiction and relationship satisfaction. In this respect, the results of the present study may also allow the findings of previous studies (which have been conducted with the aim of identifying the relationship between these variables) to be evaluated from a wider perspective.

Consequently, given the aforementioned theoretical explanations and the research findings, it has been demonstrated that social media addiction appears to induce both psychological distress and a low level of romantic relationship satisfaction (e.g., Demircioğlu & Köse, 2018 ; Woods & Scott, 2016 ). This is due to the deterioration of individuals’ mental health that can arise as a result of social media addiction (Baker & Algorta, 2016 ; Dhir et al., 2018 ), and in contrast to the advantages of developing relationships, it can lead to romantic relationship dissatisfaction (Abbasi, 2019b ; Muise et al., 2009 ). Therefore, when the relationships between social media addiction, psychological distress, and romantic relationship satisfaction are evaluated simultaneously, psychological distress may represent a mediating variable between social media addiction and romantic relationship satisfaction. Consequently, it was hypothesized that psychological distress would mediate the association between social media addiction and relationship satisfaction.

Participants and Procedure

The present cross-sectional study was carried out on a convenience sample of university students from three universities that are located in the west, middle, and east part of Turkey. A total of 350 surveys were originally distributed. Of these, 16 participants were removed because of incomplete data, yielding a final sample of 334 participants aged between 18 and 29 years ( M  = 20.71 years, SD  = 2.18). The participants comprised 214 females (64%) and 120 males (36%), of which 90 were freshmen, 87 were sophomores, 84 were junior students, and 73 were senior students. Participants reported that they were currently in a romantic relationship and reported having an average of 3.21 romantic relationships to date ( SD  = 2.21). Table 1 shows the detailed demographic characteristics of the participants. Written informed consent was obtained from the volunteer participants prior to participation in the study. Research participants were assured of the confidentiality of the collected data. Data collection was carried out through a “paper-and-pencil” survey in the classroom environment. The surveys took less than 15 min to complete.

Relationship Assessment Scale (RAS)

The RAS was designed to assess general relationship satisfaction (Hendrick, 1988 ). Items (e.g., “In general, how satisfied are you with your relationship?”) utilize a seven-point Likert scale ranging from 1 ( low ) to 7 ( high ). The total score ranges from 7 to 49. The higher the score, the higher the relationship satisfaction. Hendrick ( 1988 ) reported very good reliability. The RAS was adapted into Turkish by Curun ( 2001 ) with very good internal consistency. In the present study, the internal consistency of this scale was also good ( α  = 0.80).

Social Media Disorder Scale (SMD)

The SMD was designed to assess overall social media addiction, and the items were developed by adapting the DSM-5 criteria for Internet gaming disorder (van den Eijnden et al., 2016 ). This scale includes nine items (e.g., “… regularly found that you can't think of anything else but the moment that you will be able to use social media again?”) to which participants indicate their level of agreement on a five-point Likert scale ranging from 0 ( never ) to 4 ( always ). The total score ranges from 0 to 36. The higher the score, the higher the risk of social media addiction. The SMD was adapted to Turkish by Savci et al. ( 2018 ) and has very good internal consistency. In the present study, the internal consistency of this scale was also very good ( α  = 0.88).

Depression Anxiety and Stress Scale (DASS-21)

The DASS was designed to assess the level of psychological distress (Henry & Crawford, 2005 ). The scale consists of 21 items that are rated on a four-point Likert scale from 0 ( did not apply to me at all ) to 3 ( applied to me very much or most of the time ) and comprises three sub-scales: depression (seven items; e.g., “I found it difficult to work up the initiative to do things”), anxiety (seven items; e.g., “I felt I was close to panic”), and stress (seven items; “I found myself getting agitated”). The scores range from 0 to 21 for each sub-scale. The DASS-21 subscales’ scores were multiplied by two based on Lovibund and Lovibond’s ( 1995 ) suggestion to the cut-offs (see Appendix 1 ). The DASS-21 was adapted to Turkish by Yilmaz et al. ( 2017 ) with good to very good internal consistencies. In the present study, the internal consistency of the sub-scales were all very good ( α  = 0.89, 0.82, 0.85, respectively).

Statistical Analyses

Pearson correlations, means, and standard deviations were examined as preliminary analyses for all study variables. To examine whether the association between social media addiction and relationship satisfaction was mediated by psychological distress, the mediation model was calculated using the PROCESS macro (model 4), developed by Hayes ( 2018 ). As recommended by Hayes ( 2018 ), all regression/path coefficients are in unstandardized form. A total of 10,000 bootstrap samples were generated and bias corrected 95% confidence intervals calculated.

Written informed consent was obtained from the volunteer participants prior to participation in the study. This research was approved by Artvin Coruh University Scientific Research and Ethical Review Board (REF: E.5375).

Descriptive Statistics

Bivariate Pearson correlations among study variables were investigated (see Table 2 ). As expected, social media addiction was significantly and positively correlated with depression, anxiety, and stress. There was a significant negative correlation between social media addiction and relationship satisfaction.

Results indicated that 156 participants had no depressive symptoms (46.7%), 54 participants had mild depressive symptoms (16.2%), and the remainder had depressive symptoms (16.5% moderate, 9.9% severe, and 10.8% extremely severe). Moreover, 101 participants had no anxiety symptoms (30.2%), 30 participants had mild anxiety symptoms (9.0%), and the remainder had anxiety symptoms (20.4% moderate, 15.6% severe, and 24.9% extremely severe). Finally, 163 participants had no stress symptoms (48.8%), 47 participants had mild depressive symptoms (14.1%), and the remainder had stress symptoms (17.7% moderate, 12.6% severe, and 6.9% extremely severe) (see Appendix 1 ).

Statistical Assumption Tests

Prior to mediation analysis, statistical assumptions were evaluated. Skewness and kurtosis values (> ± 2; George & Mallery, 2003 ) were checked for normality, and there were no violations (see Table 3 ). All reliability coefficients were above Nunnally and Bernstein’s ( 1994 ) 0.70 criterion. Multicollinearity was checked with variance inflated factor (VIF), tolerance, and Durbin-Watson (DW) value. The results showed that VIF ranged from 1.47 to 2.09 and tolerance ranged from 0.48 to 0.87. These findings also showed that there was no multiple linearity problem according to Field’s ( 2013 ) recommendation. Also, the DW value was 1.82 indicating no significant correlations between the residuals.

Mediation Analyses

Applying PROCESS model 4, the analysis assessed whether psychological distress mediated the relationship between social media addiction and relationship satisfaction (see Table 4 ; Fig.  1 ). The results showed a significant total direct effect ( path c ; without mediator) of social media addiction on relationship satisfaction (B =  − 0.36, t (334)  =  − 4.74, p  = 0.001, 95% CI =  − 0.51, − 0.21), significant direct effect ( path c ; with mediator) (B =  − 0.16, t (334)  =  − 2.11, p  = 0.03, 95% CI =  − 0.04, − 0.01), and a significant indirect effect via psychological distress (total B =  − 0.20, 95% CI =  − 0.29, − 0.12).

The mediation model. * p  < .05. ** p  < .001

The results also showed that the social media addiction was associated with higher depression scores (path a 1 ; B = 0.23, p  = 0.001), anxiety scores (path a 2 ; B = 0.23, p  = 0.001), and stress scores (path a 3 ; B = 0.27, p  = 0.001), and these, in turn, were negatively associated with relationship satisfaction (path b 1, b 2, b 3 ; B =  − 0.28, B =  − 0.28, B =  − 0.26, all p values < 0.05, respectively).

In contemporary society, rapidly developing technology has entered human life, but some individuals may have difficulty in adapting to the innovations brought by such technology. Consequently, some individuals may experience psychological and social problems. Social media use, which has markedly increased in the past decade, can cause psychological distress (e.g., Keles et al., 2020 ; Marino et al., 2018 ) and the deterioration of interpersonal relationships (e.g., Glaser et al., 2018 ; Kuss & Griffiths, 2017 ; Young, 2019 ) among a minority of individuals. In this context, the main purpose of the present study was to evaluate the mediating role of psychological distress in the relationship between social media addiction and romantic relationship satisfaction.

According to the findings, a high level of social media addiction leads to a decrease in relationship satisfaction. Consequently, the first hypothesis was confirmed. A recent study conducted by Abbasi ( 2019b ) found that social media addiction was negatively associated with romantic relationship commitment. In another recent study, it was emphasized that social media addiction results in deception between couples through social media and may lead to the deterioration of relationships as a consequence (Abbasi, 2019a ). In addition, social media addiction not only leads to physical and emotional deception but also appears to negatively impact on the quality of romantic relationships (Demircioğlu & Köse 2018 ; Valenzuela et al., 2014 ). Therefore, the findings obtained in the present study are in line with the findings of previous research.

In the study here, the findings showed that a high level of social media addiction appears to result in psychological distress. Dhir et al. ( 2018 ) argued that social media addiction triggers social media fatigue, leading to anxiety and depression. Similarly, social media addiction has been found to be associated with depression, anxiety (Woods & Scott, 2016 ) and stress (Larcombe et al., 2016 ). In addition, a recent meta-analysis also concluded that social media addiction is closely and positively associated depression, anxiety and stress (Marino et al., 2018 ). Therefore, the findings of the present study are consistent with previous research.

Thirdly, the findings indicate that individuals who experience psychological distress have a low level of satisfaction in their romantic relationships. Whisman ( 1999 ) found that psychological distress positively predicted relationship dissatisfaction. It has also been suggested that couples with high levels of stress experience dissatisfaction in their romantic relationships (Bodenmann et al., 2007 ). In addition, there have also been a number of studies which indicate that the relationship satisfaction of individuals with high levels of depression is low (Cramer, 2004a , b ; Tolpin et al., 2006 ). In this respect, the findings obtained from the present study are similar to the findings of the previous studies.

Within the scope of this study, it was hypothesized that psychological distress would mediate between social media addiction and relationship satisfaction. In this sense, the study showed that social media addiction predicted romantic relationship satisfaction, partially mediated by psychological distress. Consequently, the fourth hypothesis of the research was also confirmed. No previous studies have examined the effect of psychological distress in the relationship between social media addiction and relationship satisfaction. However, there are research findings which provide evidence that social media addiction predicts both psychological distress (e.g., Larcombe et al., 2016 ; Woods & Scott, 2016 ) and relationship dissatisfaction (e.g., Demircioğlu & Köse, 2018 ; Valenzuela et al., 2014 ) and that psychological distress predicts relationship dissatisfaction (e.g., Bodenmann et al., 2007 ; Whisman, 1999 ). Due to the consideration of a variable’s mediating conditions (Barron & Kenny, 1986 ), it may be asserted that the findings of the previous studies in the literature and the findings of this research are consistent. Furthermore, it has been demonstrated that technological addiction, such as Internet addiction and smartphone addiction, is associated with psychological distress (McNicol & Thorsteinsson, 2017 ; Samaha & Hawi, 2016 ; Young & Rogers, 1998 ). Psychological distress may also predict variables such as closeness in relationships (Manne et al., 2010 ), dating violence (Cascardi, 2016 ), and social support (Robitaille et al., 2012 ) which are based on interpersonal relationships. It is therefore suggested that there is similarity between these findings and the findings of the present study. Consequently, it may be that the results of the studies conducted previously support the findings of this the present research indirectly, if not directly.

In the study here, the mediating role of psychological distress in the relationship between social media addiction and romantic relationship satisfaction was investigated. However, there could be some other variables that can mediate the relationship between social media addiction and romantic relationship satisfaction. For instance, romantic relationships are considered interpersonal (Knap et al., 2002 ); therefore, it can be assumed that interpersonal relationships and communication skills can be seen as potential mediators of the relationship between social media addiction and romantic relationship satisfaction. Additionally, given that psychological problems are the indicators of poor mental health (American Psychiatric Association, 2013 ), it can be assumed that variables (i.e., other indicators of poor mental health such as burnout, somatization, and hostility) would mediate the relationship between social media addiction and romantic relationship satisfaction. Therefore, future studies should investigate such relationships more closely.

When the role of social media addiction in the development of psychological distress is considered, it is necessary for social media addiction to be included in the process of forming the content of the intervention programs that aim to treat psychological distress. As such, it is interesting that an intervention program aimed at decreasing the level of social media addiction was also found to have a beneficial impact on individuals’ mental health (Hou et al., 2019 ). Likewise, the treatment of couples’ social media usage habits in family and couple therapies may be effective in terms of the efficacy of the therapy, since social media addiction decreases satisfaction in romantic relationships. Moreover, given the mediation relationships in the present research, the results may provide a more holistic viewpoint for mental health professionals which consider all of the three variables (social media addiction, psychological distress, and romantic relationship satisfaction) rather than a focus on only one. In this context, the following suggestions are made: to prevent social media addiction, effective Internet use skills can be taught to couples. In addition, awareness-raising skills such as yoga and meditation could be provided to individuals to protect them from social media addiction and psychological distress.

In terms of the study’s participatory group, it is significant that social media addiction (Kittinger et al., 2012 ; Koc & Gulyagci, 2013 ), psychological distress (Canby et al., 2015 ; Larcombe et al., 2016 ), and relationship satisfaction problems (Bruner et al., 2015 ; Roberts & David, 2016 ) are frequently experienced by university students. Consequently, the findings of the present study may be of particular help to specialists who work in the psychological counseling centers of universities. Within this framework, meetings, conferences, and psycho-educational group activities could be carried out to improve relationship building skills, as well as activities preventing social media addiction and psychological distress.

The present study has some limitations. Firstly, the data comprised self-report scales, which may decrease internal reliability, a limitation which may be prevented through the use of different methods of data collection. Secondly, the generalizability of the findings is limited since the sample was based on convenience sampling. Thirdly, the research design was cross-sectional. This may make it difficult to explain the cause-effect relationship of variables in the study, and therefore, experimental and longitudinal studies are recommended in future research which should examine the relationship between these variables. Finally, only the mediating role of psychological distress was examined in the research. Other possible mediating variables were not examined.

In the present research, the mediation of psychological distress in the relationship between social media addiction and romantic relationship satisfaction was empirically tested. Results showed that social media addiction predicted the partial mediation of depression, anxiety, and stress on romantic relationship satisfaction. In other words, social media addiction apparently increased individuals’ depression, anxiety, and stress levels, and this situation decreased the level of satisfaction in individual’s romantic relationships. In the present study, psychological and social variables were examined simultaneously. Overall, this study suggests that social media addiction may have a meaningful but negative impact on romantic relationship satisfaction via depression, anxiety, and stress.

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Problematic social media use mediates the effect of cyberbullying victimisation on psychosomatic complaints in adolescents

• Prince Peprah 1 , 2 ,
• Michael Safo Oduro 3 ,
• Godfred Atta-Osei 4 ,
• Isaac Yeboah Addo 5 , 6 ,
• Anthony Kwame Morgan 7 &
• Razak M. Gyasi 8 , 9  

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Adolescent psychosomatic complaints remain a public health issue globally. Studies suggest that cyberbullying victimisation, particularly on social media, could heighten the risk of psychosomatic complaints. However, the mechanisms underlying the associations between cyberbullying victimisation and psychosomatic complaints remain unclear. This cross-cultural study examines the mediating effect of problematic social media use (PSMU) on the association between cyberbullying victimisation and psychosomatic complaints among adolescents in high income countries. We analysed data on adolescents aged 11–16.5 years (weighted N = 142,298) in 35 countries participating in the 2018 Health Behaviour in School-aged Children (HBSC) study. Path analysis using bootstrapping technique tested the hypothesised mediating role of PSMU. Results from the sequential binary mixed effects logit models showed that adolescents who were victims of cyberbullying were 2.39 times significantly more likely to report psychosomatic complaints than those who never experienced cyberbullying (AOR = 2.39; 95%CI = 2.29, 2.49). PSMU partially mediated the association between cyberbullying victimisation and psychosomatic complaints accounting for 12% ( \(\beta\)  = 0.01162, 95%CI = 0.0110, 0.0120) of the total effect. Additional analysis revealed a moderation effect of PSMU on the association between cyberbullying victimisation and psychosomatic complaints. Our findings suggest that while cyberbullying victimisation substantially influences psychosomatic complaints, the association is partially explained by PSMU. Policy and public health interventions for cyberbullying-related psychosomatic complaints in adolescents should target safe social media use.

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Adolescence is noted to be a critical developmental stage, with many problems, including loneliness 1 , poor friendships, an adverse class climate, school pressure 2 , suicidal ideation and attempts, and psychosomatic complaints 3 . Psychosomatic complaint is a combination of physical ailments (i.e., headaches, stomach aches, fatigue, and muscle pain) caused or exacerbated by psychological factors such as stress, irritability, anxiety, or emotional distress 4 , 5 . Psychosomatic complaints are common among adolescents, and recent estimates indicate that the global prevalence of psychosomatic complaints ranges between 10 and 50% 6 . Also, an increase in self-reported psychosomatic complaints and related mental health complaints have been reported in adolescents from high-income countries 7 , 8 . The high prevalence of psychosomatic complaints is of concern as psychosomatic complaints have severe implications for multiple detrimental health outcomes, healthcare expenditure, and quality of life of young people 9 . Thus, it is of utmost importance to identify the proximate risk factors for psychosomatic complaints among young people to aid in developing targeted interventions to reduce the incidence of psychosomatic complaints, mainly in high-income countries.

While extant research has identified risk factors for psychosomatic complaints, including malnutrition, low physical activity, and poor parental guidance 10 , 11 , 12 , one understudied but potentially important risk factor is cyberbullying victimisation. Cyberbullying victimisation is an internet-based aggressive and intentional act of continually threatening, harassing, or embarrassing individuals who cannot defend themselves using electronic contact forms such as emails, text messages, images, and videos 13 , 14 . Indeed, being typical of interpersonal interactions, cyberbullying victimisation has shown a rising trend, particularly during adolescence 15 . International literature has shown the prevalence of cyberbullying victimisation to be between 12 and 72% among young people 14 , 16 . It may be hypothesised that cyberbullying victimisation potentially increases the risk of psychosomatic complaints through factors such as problematic social media use (PSMU) 17 , 18 . However, studies are needed to identify whether and the extent to which such factors mediate the potential association of cyberbullying victimisation with psychosomatic complaints among young people.

Given this background, the present study aimed to investigate the association between cyberbullying victmisation and psychosomatic complaints in 142,298 young people aged 11–16.5 years from 35 high-income countries. A further aim was to quantify how PSMU mediates the association between cyberbullying victimisation and psychosomatic complaints.

Cyberbullying victimisation and adolescents’ psychosomatic complaints

Research has consistently shown that cyberbullying victimisation significantly impacts adolescents’ mental health 19 . For example, Kowalski and Limber 20 found that cyberbullying victimisation is associated with increased levels of depression, anxiety, and social anxiety, as well as psychosomatic complaints, such as fatigue and muscle tension. Further, studies have shown that cyberbullying victimisation and perpetration can lead to a variety of physical, social, and mental health issues, including substance abuse and suicidal thoughts and attempts 21 , 22 , 23 , 24 . Furthermore, cyberbullying victimisation is strongly associated with suicidal thoughts and attempts, regardless of demographic factors like gender or age 21 , 25 . These findings underscore the urgent need for interventions that address the mental health consequences of cyberbullying, particularly for adolescents, who are most vulnerable to its harmful effects. The findings also suggest that cyberbullying might be a potential underlying predictor of higher psychosomatic disorders among adolescents. This present study, therefore, hypothesises that H1: there is a statistically significant association between cyberbullying victimisation (X) and psychosomatic complaints (Y) (total effect).

The role of adolescents’ PSMU

Problematic Social Media Use (PSMU), a subtype of problematic internet use, refers to the uncontrolled, compulsive or excessive engagement with social media platforms such as Facebook and Twitter, characterised by addictive behaviours like mood alteration, withdrawal symptoms, and interpersonal conflicts. This pattern of social media usage can result in functional impairments and adverse outcomes 26 . Scholars and professionals have shown great concern about the length of time adolescents spend on social media. Studies have observed that (early) adolescence could be a crucial and sensitive developmental stage in which adolescent users might be unable to avoid the harmful impacts of social media use 27 . According to current research, PSMU may increase adolescents’ exposure to cyberbullying victimisation, which can have severe consequences for their mental health 28 , 29 , 30 . Similarly, an association between PSMU and physical/somatic problems, as well as somatic disorders, has been established in many studies 31 , 32 . Hanprathet et al. 33 demonstrated the negative impact of problematic Facebook use on general health, including somatic symptoms, anxiety, insomnia, depression, and social dysfunction. According to Cerutti et al. 34 , adolescents with problematic social media usage have more somatic symptoms, such as stomach pain, headaches, sore muscles, and poor energy, than their counterparts. Hence, inadequate sleep may be associated with PSMU, harming both perceived physical and mental health 35 , 36 . Again, supporting the above evidence, the relationship between PSMU, well-being, and psychological issues have been highlighted in meta-analytic research and systematic reviews 27 , 31 , 37 , 38 . Thus, this study proposes the following hypothesis: H2: there is a specific indirect effect of cyberbullying victimisation (X) on psychosomatic complaints (Y) through PSMU (M1) (indirect effect a 1 b 1 ).

Study, sample, and procedures

This study used data from the 2018 Health Behaviour in School-aged Children (HBSC) survey conducted in 35 countries and regions across Europe and Canada during the 2017–2018 academic year 39 . The HBSC research team/network is an international alliance of researchers collaborating on a cross-national survey of school students. The HBSC collects data every four years on 11-, 13- and 15- year-old adolescent boys’ and girls’ health and well-being, social environments, and health behaviours. The sampling procedure for the 2018 survey followed international guidelines 40 , 41 . A systematic sampling method was used to identify schools in each region from the complete list of both public and private schools. Participants were recruited through a cluster sampling approach, using the school class as the primary sampling unit 42 . Some countries oversampled subpopulations (e.g., by geography and ethnicity), and standardised weights were created to ensure representativeness of the population of 11, 13, and 15 years 43 . Questionnaires were translated based on a standard procedure to allow comparability between the participating countries. Our analysis used data from 35 countries and regions with complete data on cyberbullying victimisation, PSMU, and psychosomatic complaints. The study complies with ethical standards in each country and follows ethical guidelines for research and data protection from the World Health Organisation and the Organisation for Economic Co-operation and Development. Depending on the country, active or passive consent was sought from parents or legal guardians and students which was checked by teachers to participate in the study. The survey was conducted anonymously and participation in the study was voluntary for schools and students. Schools, children and adolescents could refuse to participate or withdraw their consent until the day of the survey. Moreover, all participating students were free to cease filling out the questionnaire at any moment, or to answer only selected questions. More detailed information on the methodology of the HBSC study including ethics and data protection can be found elsewhere 44 , 45 .

Outcome variable: psychosomatic complaints

Psychosomatic complaints was assessed by one collective item asking students how often they had experienced the following complaints over the past six months: headache, stomach aches, feeling low, irritability or bad mood, feeling nervous, dizziness, abdominal pain, sleep difficulty, and backache. Response options included: about every day, more than once a week, about every week, about every month, and rarely or never. This scale has sufficient test–retest reliability and validity 46 , good internal consistency (Cronbach’s a = 0.82) 47 , and has been applied in several multiple country analyses 48 , 49 . The scale is predictive of emotional problems and suicidal ideation in adolescents 50 , 51 . For our analysis, the scale was dichotomised with two or more complaints several times a week or daily coded as having psychosomatic complaints 47 , 49 .

Exposure variable: Cyberbullying victimisation

Cyberbullying victimisation is the exposure variable in this study. Thus, the exposure variable pertains to only being a victim of cyberbullying and does not include perpetration of cyberbullying. Students were first asked to read and understand a short definition of cyberbullying victimisation. They were then asked how often they were bullied over the past two months (e.g., someone sending mean instant messages, emails, or text messages about you; wall postings; creating a website making fun of you; posting unflattering or inappropriate pictures of you online without your permission or sharing them with others). Responses included: “ I have not   been  cyberbullied”, “once or twice”, “two or three times a month”, “about once a week”, and “several times a week”. These were dichotomised into “never" or “once or more". This measure of bullying victimisation has been validated across multiple cultural settings 43 , 52 , 53 , 54 .

Mediating variable

Problematic social media use (PSMU) was assessed with the Social Media Disorder Scale (Cronbach’s a = 0.89) 55 . The scale contains nine dichotomous (yes/no) items describing addiction-like symptoms, including preoccupation with social media, dissatisfaction about lack of time for social media, feeling bad when not using social media, trying but failing to spend less time using social media, neglecting other duties to use social media, frequent arguments over social media, lying to parents or friends about social media use, using social media to escape from negative feelings, and having a severe conflict with family over social media use. In this study, the endorsement of six or more items indicated PSMU as evidence suggests that a threshold of six or more is an indicative of PSMU 54 , 56 . This scale has been used across cultural contexts 43 , 52 , 54 .

Informed by previous studies 43 , 54 , 57 , the analysis controlled for theoretically relevant confounders, including sex (male/female) and age. Family affluence/socio-economic class was assessed using the Relative Family Affluence Scale, a validated six-item measure of material assets in the home, such as the number of vehicles, bedroom sharing, computer ownership, bathrooms at home, dishwashers at home, and family vacations) 56 , 58 . Finally, parental and peer support were measured using an eight item-measure 59 . Responses were recorded on a 7-point Likert scale (ranging from 0 indicating very strongly disagree to 6 indicating very strongly agree).

Statistical analysis

Region-specific descriptive statistics were calculated to describe the sample. Next, Pearson’s Chi-squared association test with Yates’ continuity correction was performed to examine plausible associations between psychosomatic complaints and other categorical study variables. Also, to account for the regional clustering or unobserved heterogeneity observed in the analytic sample, sequential mixed effect binary logit models with the inclusion of a random intercept were fitted to further examine the associations between psychosomatic complaints and cyberbullying victimisation as well as other considered covariates. Furthermore, a parallel mediator model was fitted to evaluate the specified hypothesis and understand the potential mechanism linking cyberbullying victimisation and psychosomatic complaints. More specifically, cyberbullying victimisation (X) was modelled to directly influence psychosomatic complaints (Y) and indirectly via PSMU (M). Since core variables were binary, paths could be estimated with a sequence of three logit equations: 60 , 61

where, \({i}_{1}\) , \({i}_{2}\) , and \({i}_{3}\) represent the intercept in the respective equations. The path coefficient, c, in Eq. ( 1 ) represents the total effect of predictor X on outcome Y . In Eq. ( 2 ), the path coefficient a denotes the effect of predictor X on the mediator M . Also, the c' parameter in Eq. ( 3 ) represents the direct effect of the predictor X on the response Y , adjusting for the mediator M . Lastly, the path coefficient b coefficient in Eq. ( 3 ) represents the indirect effect of the mediator M on the outcome Y , when adjusting for the predictor X . These logit models provide effect estimates on the log-odds scale, and thus can be transformed into odds ratios. Each model was adjusted for the potential confounding variables.

All statistical analyses were performed using R Software (v4.1.2; R Core Team 2021) with \(\alpha\)  =  0.05 as the significance level. More specifically, the package “mediation” in R 62 was used for the mediation analysis to estimate direct, indirect, and total effects. Inference is based on a non-parametric, 95% bias-corrected and accelerated (BCa) bootstrapped confidence interval 63 , 64 . Bootstrapping for indirect effects was set at 1000 samples, and once the 95% bootstrapped CI of the mediation effects did not include zero (0), it was deemed statistically significant. We also conducted further analysis by including an interaction between cyberbullying victimisation and PSMU to obtain insights analogous to the mediation model.

Ethics approval and consent to participate

The research was exclusively based on data sourced from the World Bank, which adheres to rigorous ethical standards in its data collection processes. Therefore, no separate ethical approval was sought or deemed necessary. Ethical approval was not required for this study since the data used for this study are secondary data. Necessary permissions and survey data were obtained from the World Bank. The World Bank data collection process upheld ethical standards and relevant guidelines in the research process including informed consent from all subjects and/or their legal guardian(s).

Preliminary analyses

The final analytic sample comprised complete information on 142,298 adolescents from 35 high-income countries (Table 1 ). The median age of the sample was 13.6 years. Most participants resided in Wales (6.26%) and the Czech Republic (6.16%). Notably, the prevalence of cyberbullying victimisation was 26.2%, and the majority (53%) were females. As observed in Table 2 , 84.6% of the participants self-reported high levels of psychosomatic complaints. Furthermore, among the participants who experienced PSMU, about 81.16% reported high levels of psychosomatic complaints. About 84.47% of the participants indicated receiving parental and peer support (see Table 2 ).

Main analyses

Results from the sequential binary mixed effects logit model are shown in Table 3 . In the first step, we included only cyberbullying victimisation in the model. We found that cyberbullying victims were 2.430 times more likely to report psychosomatic complaints than those who were not cyberbullied (OR = 2.430; 95%CI = 2.330, 2.530). The second step included sex, PSMU, parental and peer support, and family affluence as covariates. We found that cyber bullying victims were 2.390 times significantly more likely to report psychosomatic complaints than those who never experienced cyberbullying (AOR = 2.390; 95%CI = 2.29, 2.49). Additionally, the third model, which is an additional analysis involved the inclusion of an interaction between and cyberbullying victimisation and PSMU. The results showed that PSMU moderates the association between cyberbullying victimisation and psychosomatic complaints. Adolescents who were cyberbullied but did not report PSMU had reduced odds of psychosomatic complaints compared to those with PSMU (AOR = 1.220; 95%CI = 1.110–1.350). Furthermore, a caterpillar plot of empirical Bayes residuals of the models for the random intercept, region/country is obtained and shown in Fig.  1 . This represents individual effects for each country and offers additional insights into the extent of psychosomatic complaints heterogeneity across different countries. The plots visually demonstrates that regional variation for psychosomatic complaints does exist.

A caterpillar plot of empirical Bayes residuals of the models for the random intercept, region/country. This represents individual effects for each region/country. Region or country abbreviations in the figure are as follows: [AL] Albania, [AZ] Azerbaijan, [AT] Austria, [BE-VLG] Vlaamse Gewest (Belgium), [BE-WAL] Wallone, Région (Belgium), [CA] Canada, [CZ] Czech Republic, [DE] Germany, [EE] Estonia, [CA] Canada, [ES] Spain, [FR] France, [GB-ENG] England, [GB-SCT] Scotland, [GB-WLS] Wales, [GE] Georgia, [GR] Greece, [HR] Croatia, [HU] Hungary, [IE] Ireland, [IL] Israel, [IS] Iceland, [IT] Italy, [KZ] Kazakhstan, [LT] Lithuania, [LU] Luxembourg, [MD] Moldova, [MT] Malta, [NL] Netherlands, [PT] Portugal, [RO] Romania, [RS] Serbia, [RU] Russia, [SE] Sweden, [SI] Slovenia, [TR] Turkey, [LU] Luxembourg and [UA] Ukraine.

Figure  2 shows the adjusted parallel mediation results. The effect of cyberbullying victimisation on psychosomatic complaints was significantly mediated by PSMU. The paths from cyberbullying victimisation to PSMU (a: \(\beta\) =0.648, p < 0.001), PSMU to psychosomatic complaints (b: \(\beta\) =0.889, p < 0.001), and that of cyberbullying victimisation to 0.8069 (c′: \(\beta\) =0.051, p < 0.001) were also statistically significant.

A parallel mediation model of the influence of PSMU on the association between Cyberbullying Victimisation and Psychosomatic Complaints. a = path coefficient of the effect of exposure on the mediator. b = path coefficient of the effect of the mediator on the outcome. c’ = path coefficient of the direct effect of the exposure on outcome. CV, cyberbullying victimisation. PC, psychosomatic complaints.

Bootstrapping test of mediating effects

The total, direct, and indirect effects of the mediation model based on nonparametric bootstrap are presented in Table 4 . We observe that the estimated CI did not include zero (0) for any effects. This observation suggests a statistically significant indirect effect of cyberbullying victimisation on psychosomatic complaints via PSMU ( \(\beta\)  = 0.01162, 95%CI = 0.0110, 0.0120), yielding 12% of the total effect.

Key findings

This cross-cultural study examined the direct and indirect associations of cyberbullying victimisation with psychosomatic complaints via PSMU among adolescents. The results showed that cyberbullying victimisation independently influenced the experience of psychosomatic complaints. Specifically, adolescents who were victims of cyberbullying were more than two times more likely to report psychosomatic complaints. Crucially, our mediation analyses indicated that PSMU explain approximately 12% of the association between cyberbullying victimisation and psychosomatic complaints. In a further analysis, PSMU moderated the association between cyberbullying victimisation and psychosomatic complaints. This study is the first to examine the direct and indirect associations between cyberbullying victimisation and psychosomatic complaints through PSMU in adolescents across multiple high-income countries.

Interpretation of the findings

Our results confirmed the first hypothesis that there is a statistically significant direct association between cyberbullying victimisation and psychosomatic complaints. Thus, we found that cyberbullying independently directly affected the adolescents' experience of psychosomatic complaints. Previous studies have mainly focused on the direct effect of traditional face-to-face bullying on psychosomatic complaints 20 , 65 or compared the impact of traditional face-to-face bullying to cyberbullying concerning mental health 19 , 66 , 67 , 68 , 69 . A systematic review of traditional bullying and cyberbullying victimisation offers a comprehensive synthesis of the consequences of cyberbullying on adolescent health 19 . Another review suggested that cyberbullying threatened adolescents’ well-being and underscored many studies that have demonstrated effective relationships between adolescents’ involvement in cyberbullying and adverse health outcomes 70 . Other population-based cross-sectional studies have similarly shown that victims of cyberbullying experience significant psychological distress and feelings of isolation, which can further exacerbate their physical and mental health challenges 22 , 71 , 72 . The present study builds on the previously published literature by highlighting the effect of cyberbullying victimisation on adolescent psychosomatic complaints and the extent to which the association is mediated by PSMU.

Consistent with the second hypothesis, we found that PSMU mediated about 12% of the association between cyberbullying victimisation and psychosomatic complaints in this sample. While studies on the mediational role of PSMU in the relationship between cyberbullying victimisation and psychosomatic complaints are limited, evidence shows significant interplay among PSMU, cyberbullying victimisation, and psychosomatic complaints. For example, a study of over 58,000 young people in Italy found that PSMU was associated with increased levels of multiple somatic and psychological symptoms, such as anxiety and depression. 73 Another study of 1707 adolescents in Sweden found that cyberbullying victimisation was associated with increased depressive symptoms and the lowest level of subjective well-being 74 .

Other possible mediators of the cyberbullying victimisation-psychosomatic complaints association may include low self-esteem, negative body image, emotion regulation difficulties, social support, and personality traits such as neuroticism and impulsivity 20 , 67 , 72 , 75 , 76 . For example, Schneider et al. 75 have shown that emotional distress could increase psychosomatic symptoms such as headaches, stomach aches, and muscle tension. In addition, social isolation can lead to social withdrawal and a decreased sense of belonging 78 , 79 . Therefore, it is essential to explore these variables further and develop effective interventions and prevention strategies to address these interrelated factors and reduce their negative impact on adolescent health and well-being.

In a further analysis, the results show that PSMU does not only mediate but also moderate the association between cyberbullying victimisation and psychosomatic complaints among adolescents. Specifically, cyberbullied adolescents with no report of PSMU had reduced likelihoods of experiencing psychosomatic complaints compared to those with PSMU. This result is interesting and could be due to several factors. First, individuals with PSMU may already be experiencing heightened levels of psychological distress due to their excessive social media use, making them more vulnerable to the negative effects of cyberbullying 80 , 81 , 82 . For instance, excessive time spent on social media, particularly in activities such as comparing oneself to others or seeking validation through likes and comments, has been linked to increased psychological distress 83 , 84 . Conversely, the finding that cyberbullied adolescents without PSMU had reduced likelihoods of experiencing psychosomatic complaints compared to those with PSMU suggests a protective effect of lower social media use. Adolescents who are not excessively engaged with social media may have fewer opportunities for exposure to cyberbullying and may also have healthier coping strategies in place to deal with any instances of online victimisation 43 , 85 , 86 .

The results suggest that professionals in the fields of education, counselling, and healthcare should prioritise addressing the issue of cyberbullying victimisation when assessing the physical and psychological health of adolescents. Evidently, adolescents who experience cyberbullying require support. Thus, proactive measures are essential, and support could be provided by multiple professional communities that serve adolescents and young people in society, such as educational, behavioural health, and medical professionals. Sensitive inquiry regarding cyberbullying experiences is necessary when addressing adolescent health issues such as depression, substance use, suicidal ideation, and somatic concerns 19 . Our findings underscore the need for comprehensive, school-based programs focused on cyberbullying victimisation prevention and intervention.

Strengths and limitations

The study's main strength lies in the use of a large sample size representing multiple countries in high income countries. This large sample size improved the representativeness and veracity of our findings. The complex research approach helps advance our understanding of the interrelationships between cyberbullying victimisation, PSMU, and psychosomatic complaints among adolescents. However, the study has its limitations. First, the cross-sectional design does not allow directionality and causal inferences. Second, retrospective self-reporting for the critical study variables could lead to recall and social desirability biases. Third, the presence of residual and unobserved confounders, despite adjusting for some covariates, can be considered a limitation of this study. Further research is needed to confirm these findings and better understand how PSMU mediates the relationship between cyberbullying victimisation and psychosomatic complaints.

Conclusions

This study has provided essential insights into the interrelationships between cyberbullying victimisation, PSMU, and psychosomatic complaints among adolescents in high income countries. The findings suggest that cyberbullying is directly associated with psychosomatic complaints and that PSMU significantly and partially mediates this association. This study also highlights the importance of addressing cyberbullying victimisation and its negative impact on adolescent health and emphasises the need to address PSMU. Overall, the study underscores the importance of promoting healthy online behaviour and providing appropriate support for adolescents who experience cyberbullying victimisation. Further studies will benefit from longitudinal data to confirm our findings.

Data availability

The data that support the findings of this study are available from the World Bank, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are, however, available from the corresponding author ([email protected]) upon reasonable request and with permission of the World Bank.

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We thank the 2017/2018 HBSC survey team/network, the coordinator and the Data Bank Manager for granting us access to the datasets. We duly acknowledge all school children who participated in the surveys.

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Stop children using smartphones until they are 13, says French report

Children should be banned from most social media until 18 amid attempts to ‘monetise’ them, says Macron-commissioned study

Children should not be allowed to use smartphones until they are 13 and should be banned from accessing conventional social media such as TikTok, Instagram and Snapchat until they are 18, according to a report by experts commissioned by Emmanuel Macron .

The French president had asked scientists and experts to suggest screen use guidelines for children with a view to France taking unprecedented steps on limiting their exposure . It was unclear how the government might now proceed after the report’s publication. Macron said in January: “There might be bans, there might be restrictions.”

The hard-hitting report said children needed to be protected from the tech industry’s profit-driven “strategy of capturing children’s attention, using all forms of cognitive bias to shut children away on their screens, control them, re-engage them and monetise them”.

Children were becoming “merchandise” in this new tech market, the report said, adding: “We want [the industry] to know we’ve seen what they’re doing and we won’t let them get away with it.”

A three-month study by scientists and experts led by a neurologist, Servane Mouton, and Amine Benyamina, the head of the psychiatry and addiction service at Paul-Brousse hospital, said children under three should have no exposure to screens – television included – and no child should have a phone before the age of 11.

Any phone given to a child aged between 11 and 13 should be a handset without access to the internet, it said, setting the minimum age at which they should be allowed a smartphone connected to the internet at 13.

The report said a 15-year-old should be able to access only what it called “ethical” social media, such as Mastodon. Conventional, mass-marketed, profit-driven social media such as TikTok, Instagram or Snapchat should not be available to teenagers until they reached 18, it found. Teenagers should also receive better education on the science behind the need to get enough sleep.

The report made equally stringent recommendations for the very young, saying phones and screens should be limited as much as possible on maternity wards to help parents bond with their babies. Phone use should also be addressed among childminders, it said.

For children up to the age of six, screens of all kinds should be “strongly limited” and only very rarely used for education content when sitting with an adult. Screens should be totally banned from nursery schools for children under six. In primary schools, children should not be given individual tablets or digital devices to work on, unless it was for a specific disability.

The report also suggested banning connected toys, except those used as audio for storytelling.

“Before the age of six, no child needs a screen in order to develop,” Mouton said. “In fact, screens can stop them developing properly at this age.”

The scientists said they did not want to chide parents, who themselves were “victims of a powerful tech industry”. They said parents should instead be helped to avoid what they called “techno-ference” – when parents constantly checking their own phones interfered with their ability concentrate on talking to, eating with or playing with their children.

This was harming young people’s emotional development, the report said. It included adults scrolling on their phones while feeding young children, or homes where a television was constantly on in the background.

Scientists said parents were not to blame and more should be done in society as a whole, such as allowing adults to properly disconnect from work out of hours, limiting screens in public places, introducing screen-free restaurants and cafes, or parents putting their phones in a box when they got home from work.

The scientists said “parental controls” should not be seen as a sufficient means of protecting children. Rather, they were an ineffective distraction, peddled by the tech industry “to get itself off the hook” for creating algorithms, particularly within social media, designed to addict and monetise children.

Benyamina said: “Tech is and will remain a fantastic tool, but it has to act in people’s service, not people being reduced to serving a product.”

He said screens had negative effects on children “in terms of their eyesight, their metabolism … their intelligence, concentration and cognitive processes”.

He said addictions to screens were not to the product itself but to content. He said: “Algorithms that re-engage and stimulate the pleasure system and are built to avoid you losing interest in the content have a type of addictive dynamic.”

He said people should be vigilant on social media if they noticed that content was re-engaging them. “If you decided you wanted to look at one or two videos and you were on it all evening, you need to question it.”

• Emmanuel Macron
• Social media
• Smartphones

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MINI REVIEW article

Recent insights in the correlation between social media use, personality traits and exercise addiction: a literature review.

• 1 National Centre on Addiction and Doping, Italian National Institute of Health, Rome, Italy
• 2 Università degli Studi Internazionali di Roma, Rome, Italy

Introduction and aim: The excessive involvement in physical activity without stopping in between sessions despite injuries, the continuous thinking to exercise feeling insane thoughts and experiencing withdrawal symptoms are all characteristics of the Exercise Addiction (EA), an addictive behavior. While the primary exercise addiction is directly caused by compulsive exercise, many studies highlighted the relationship between Eating Disorders (ED) and EA, defining the secondary EA. The correlation between EA, social media use (SMU) and other individual traits remains a relatively underexplored domain. Therefore, this review aimed to examine the latest evidence on the relationship between EA, SMU, and some personality traits such as perfectionism and body image.

Methods: Electronic databases including PubMed, Medline, PsycARTICLES, Embase, Web of Science were searched from January 2019 to October 2023, following the PRISMA guidelines.

Results: A total of 15 articles were examined and consolidated in this review. EA was found to be related to different individual traits such perfectionism, body dissatisfaction, depression, obsessive-compulsive personality disorders. While controversial results were found regarding the relationship between EA and SMU.

Conclusion: The interaction between mental health, exercise addiction and social media use is complex. Excessive engagement in these latter may result in negative mental health consequences despite their potential benefits. Understanding individual differences and developing effective interventions is crucial to promoting healthy habits and mitigating the EA risks, ultimately enhancing mental well-being. Further research should focus on the identification of risks and protective factors with the eventual aim of developing and implementing effective prevention strategies.

1 Introduction

The constant pursuit of a healthy lifestyle is widely related to the growing attention to physical and mental health to contrast the acceleration of the societal ageing process. Whereas physical exercise and sports engagement were widely valued, excessive involvement in exercise may drive to addictive behavior, referred to as exercise addiction (EA). Although not formally recognized in diagnostic manuals such as the Diagnostic and Statistical Manual of Mental Disorders 5 ( 1 ), EA, also known as “exercise dependence” or “compulsive exercising”, is acknowledged as a behavioral addiction. Indeed, the discrimination between exercise-addicted and regular exercisers is challenging, making the symptom intensity evaluation of particular importance ( 2 ).

The uncontrollable urge to engage in physical activity that surpasses health or fitness requirements is the main characteristic of this addiction. Conversely to regular and healthy physical exercise, excessive engagement may lead to adverse consequences. Adverse effects include tolerance and withdrawal symptoms, mood alteration, impulsivity, lack of control, detrimental social and financial consequences, physical injuries ( 3 , 4 ). Specifically, when the exercise’s positive effects on mood and well-being are transient, it may exert a feeling of deprivation when exercise is inaccessible, a compulsion to resume exercise promptly, negative emotions, increased exercise duration, inability to cease exercise even when injured, and sleeplessness ( 5 , 6 ). Furthermore, secondary EA was recently defined as an aspect of eating disorders (ED), characterized by obsessive exercising in conjunction with anorexia or bulimia nervosa ( 7 ). In this case, a body image disturbance may exist at the base of the EA, besides heightened levels of anxiety and depression ( 8 ). The pursuit of physical perfection and fixation on maintaining a specific body image may contribute to the onset of EA, detrimentally impacting mental well-being ( 9 , 10 ). Problematic Social media use (PSMU) and ED, like EA, are linked to several psychological and physical health problems including difficulties in emotion regulation, psychological distress, excessive daytime sleepiness and body dissatisfaction ( 11 , 12 ). Some studies suggest that individuals with EA may be inclined more towards using social media to showcase their fitness achievements, seeking validation from online peers ( 13 – 15 ). These individuals may be trapped by the carefully curated nature of social media content, depicting unattainable representations of individuals’ lives, affecting their self-esteem ( 13 , 16 ).

Moreover, a relationship between EA, PSMU or social media addiction (SMA), and perceived discomfort regarding images of physical idealization was corroborated by the so-called “fitspiration” ( 17 – 19 ). This term derives from the fusion of “fitness” and “inspiration,” which involves posting online, primarily through social networking channels, images promoting health, wellness, healthy eating, self-care, and especially physical exercise ( 20 ). Moreover, the “fear of missing out” (FOMO) phenomenon on social media could drive individuals to excessively engage in both exercise and social media use, contributing to adverse mental health outcomes ( 17 , 21 ).

Conversely, excessive exposure to fitness-related content on social media might exacerbate exercise addiction by perpetuating unrealistic body standards and nurturing an obsession with exercise ( 22 , 23 ).

The main focus of studies reported in the literature is on defining, diagnosing, characterizing, and elucidating comorbidities ( 16 , 24 ). Moreover, current researches examine the relationship among EA ED and anxiety ( 25 – 27 ) making the specific correlation between EA, SMU and other personality traits (perfectionism, body image) still a domain that has not yet been fully explored. For this reason we performed a literature review to clarify the relationship between EA, SMU, and mental health outcomes by bringing together existing research and examining the underlying mechanisms that drive their interactions.

We performed comprehensive literature research to identify articles investigating the relationship between exercise addiction, social media use, and personality traits. Considering the recent focus on the EA-related issues, Electronic databases including PubMed, Medline, PsycARTICLES, Embase, Web of Science were searched from January 2019 to October 2023. Preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement was the methodology selected for the present review ( 28 ). According to guidelines of the 2020 PRISMA statement ( 29 ) the research team evaluated the following items: definition of the research question, hypothesis and objectives; bibliographic search; data collection, screening of the scientific papers selected and finally, analysis of the main findings and conclusions including the strengths and weakness of these studies ( Figure 1 ). Our eligibility criteria included: articles written in English, cross-sectional, longitudinal, and case control studies investigating the association between exercise addiction, social media use and individual traits (e.g. perfectionism, perceived body image, depression), original research performed in general population, adolescents or professional athletes, studies using reliable research tools. Papers published in non-English languages were excluded. Reviews were also excluded but were used for the snowball search strategy. The researchers and performed the initial selection of original manuscripts by screening titles and abstracts, creating a reference list of papers for the topics evaluated in the present review using Rayyan software ( 30 ). Two investigators conducted each stage of the studies selection, deleted duplicate inputs and reviewed studies as excluded or requiring further assessment. All data were extracted by two investigators and cross-checked by the other investigator. In case of discrepancies in the selected studies, we opted for reconciliation through team discussion. This narrative review protocol was registered in PROSPERO (international prospective register of systematic reviews) on the 7 th of February 2024, with the registration number CRD42024510767.

Figure 1 PRISMA flow diagram of the study selection.

3.1 Literature research

A total of 96 studies were identified from the initial search, of which 41 duplicates were removed. Titles and abstracts of the rest 55 studies were screened according to the predefined inclusion criteria, and 35 studies were excluded. In total, 15 articles were critically reviewed and consolidated for this review ( Table 1 ). The studies were mainly conducted in the last 2 years (2022 and 2023), with prevalence in Australia (n = 5) and Europe (n = 6). The considered population was more often specific, such as gym instructors, competitive athletes, or clinical populations (individuals with ED).

Table 1 Studies investigating the relationship between exercise addiction, social media use, and personality traits.

3.2 Results in domain investigated

The 15 studies included ( Table 1 ) in the literature search considered 4 main domains, such as body image-related dysfunction, eating disorders, difficult individual traits, and/or problematic social media use. As a result, different connections with EA emerged.

Two different studies highlighted the strong association between EA and ED which have in common weight concerns, perfectionism, perception of body image, body dissatisfaction, depression, psychological distress and insomnia ( 32 , 41 ). Furthermore, compulsive exercise plays a role in mediating the clinical perfectionism and EA, especially in vulnerable athletes or underweight adolescents ( 31 , 37 ).

Body dissatisfaction (BD) is a disorder characterized by individual suffering due to the difference between what is the real and the idealistic image of the body. It has been reported that BD is a risk factor for the development of EA and ED especially in fitness instructors or practitioners ( 32 , 39 ). More recently, cognitive constructs were investigated in relation to EA. Indeed, the relationship between Early Maladaptive Schema (EMS) and EA, the only two specific domains which influenced EA were the other-directedness and the impaired limits. To this concern, individuals unable to set appropriate internal limits and have excessive external focus on others’ desires and needs may be more prone to developing EA ( 33 ).

Recently, the EA was investigated in relation to PSMU consequences on mental health, focusing on anxiety, depression, and stress rather than personality traits such as extraversion, perfectionism, and aggression. As a result, EA appeared to play a mediating role since it is strictly connected to body image concerns, psychological distress and compulsive eating, which may cause negative mental health outcomes influencing the PSMU ( 35 ).

SMA was positively correlated with psychological/addicted eating behavior and unhealthy diet-exercise behavior, but negatively with healthy eating/exercise behavior ( 40 ). SMU impacts the physical activity behavior. The passive SMU corresponds to a low rate of daily physical activity practice (minimum 60 minutes), while the actively SMU is linked to a higher probability of exercise activity ( 43 ). On the other hand, another study reported that EA is not associated with the frequency of active or passive social networking sites usage ( 42 )

SMA may be part of a broader spectrum of addictive behaviors. It was found that EA and substance abuse are weakly related to SMA while this latter is significantly associated with shopping addiction ( 44 ).

The relationship between EA, depression, and anxiety has been extensively studied, indeed many studies reported that EA co-occurs with mental health disorders such as major depressive disorder, anxiety, obsessive-compulsive personality disorder ( 34 , 36 , 45 ). Moreover, people with obsessive-compulsive traits and high levels of self-efficacy are at higher risk of becoming exercise addicts ( 45 ).

4 Discussion

Whereas different EA definitions have been formulated, the terminology is still inconsistently used with “exercise addiction” and “compulsive exercise” or “exercise dependence” used as synonyms, although labile characteristics allow to discriminate the different conditions related to excessive exercise. A panel of experts in the field, including physicians, physiotherapists, coaches, trainers, and athletes defined excessive exercise as an “addiction”, identifying perfectionism, obsessive-compulsive drive, and hedonism as components of EA ( 23 ). The co-occurrence of these components and the excessive exercise was described as a behavioral addiction with a similar mechanism to substance addictions ( 23 ).

In recent years, the scientific community raised concerns about the connection between EA, SMU, and mental health, due to the potential outcomes on mental well-being of the recent spreading of both excessive exercise and extensive social media. Among the others, the complex relationship between EA, and SMA, perfectionism, body image disorders, and “fitspiration” construct have been studied, since 2015 ( 46 ). Interestingly, “fitspiration” diversion into a distortion of body perception could emerge ( 20 , 47 , 48 ). Although “fitspiration” generally conveys positive messages, the images associated with that may have negative effects on the body image of individuals who engage in it, as they predominantly portray a lean and toned body figure. Noteworthy, “fitspiration” emerged as a positive alternative to the “thin-spiration” trend, combining “thin” and “inspiration”. Notably, perfectionism is a personality trait in individuals characterized by unrealistic expectations for themselves and others, with feelings of inadequacy, self-criticism, and guilt ( 49 ), with different mechanisms of connection to EA and ED, although there is still limited clarity on EA mediating role between perfectionism and ED. Furthermore, EA is related to other personality traits such as the tendency towards depression, or an inability to manage it. These traits also constitute risk factors for behavioral addictions, such as SMA, which also involves a distortion of body perception. The EA appears to have a similar developmental pattern to other addiction or addictive behaviors, following the biopsychosocial model ( 50 ). Besides, EA has consistent co-occurrence patterns to depression and anxiety revealing that individuals with obsessive-compulsive traits and high self-efficacy present high risk of becoming exercise addicted.

However, a lack of specific and robust tools to study the EA emerged, imposing the adaptation of diagnostic tools validated for the assessment of other behavioral addictions such as gambling or gaming disorders. Hence, certain diagnostic criteria are still not provided to clinicians to precisely identify the EA. Otherwise, people are widely informed through social media communications about the EA associated risks. Furthermore, the lack of specific tools determines that only the relation with other disorders is evaluated, while EA is never considered alone. Indeed, the EA role as a consequence or cause of a broad spectrum of other disorders should be clarified.

On the other hand, study protocols should be harmonized, preferably based on standardized measurement tools that would ensure result consistency. This approach would facilitate the study of EA, clarifying the mediating role of behavioral addictions on mental health.

A general weakness in EA investigation is represented by the size and the quality of the population involved in the studies. Indeed, only four studies considered at least 1,000 individuals ( 31 , 35 , 41 , 45 ), and only one investigated over 10,000 participants ( 43 ). Moreover, the adult population were the most examined while only one-third of the studies included the adolescent population. To this concern, the adolescent population should be further explored, considering the early onset of behavioral addictions, and ED ( 51 – 54 ).

Lastly, another important issue is the lack of validated intervention and prevention programs with evidence-based efficacy in managing EA.

5 Conclusion

The relationship between EA, SMU, and mental health is intricate and knotted. While both exercise and social media have the potential to contribute positively to mental well-being, their excessive and addictive use can lead to adverse outcomes. Improved knowledge on mechanisms and assessment of individual differences are essential to develop effective interventions, promoting healthy exercise habits and mindful social media use. Eventually, improved mental health and well-being in the digital age would be fostered. Finally, it would be necessary to expand the number of these studies to identify risk factors and protective factors, which in turn are fundamental elements for implementing prevention strategies for behavioral addictions.

Author contributions

AM: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing. AT: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing. VA: Validation, Writing – review & editing. GC: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft. PB: Writing – review & editing. NM: Data curation, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

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: exercise addiction, body image, perfectionism, behavior, addictive

Citation: Minutillo A, Di Trana A, Aquilina V, Ciancio GM, Berretta P and La Maida N (2024) Recent insights in the correlation between social media use, personality traits and exercise addiction: a literature review. Front. Psychiatry 15:1392317. doi: 10.3389/fpsyt.2024.1392317

Received: 27 February 2024; Accepted: 29 April 2024; Published: 10 May 2024.

Reviewed by:

Copyright © 2024 Minutillo, Di Trana, Aquilina, Ciancio, Berretta and La Maida. 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: Annagiulia Di Trana, [email protected]

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