# data[].attributes.headline
Digital technology can provide opportunities for social connection, access to information, and skill development, which can contribute to positive mental health outcomes for adolescents(Odgers et al).

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Digital technology can provide opportunities for social connection, access to information, and skill development, which can contribute to positive mental health outcomes for adolescents(Odgers et al).

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social media addiction or excessive screen time, is associated with an increased risk of mental health issues, including depression, anxiety, and loneliness(Odgers at al).

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social media addiction or excessive screen time, is associated with an increased risk of mental health issues, including depression, anxiety, and loneliness(Odgers at al).

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Social media has both positive and negative effects on adolescent's mental health.

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Social media has both positive and negative effects on adolescent's mental health.

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Source 8: Adolescent Mental Health in the Digital Age: Facts, Fears and Future Directions by Candice L. Odgers

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Source 8: Adolescent Mental Health in the Digital Age: Facts, Fears and Future Directions by Candice L. Odgers

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Adolescent Mental Health in the Digital Age: Facts, Fears and Future Directions

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Adolescents are spending an increasing amount of their time online and connected to each other via digital technologies. Mobile device ownership and social media usage have reached unprecedented levels, and concerns have been raised that this constant ...

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cyberbullying can also affect the mental health of students.

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cyberbullying can also affect the mental health of students.

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This study contributes valuable insights into the impact of technological advancements on the mental health of young people.

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This study contributes valuable insights into the impact of technological advancements on the mental health of young people.

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Affects depending upon the frequency of use of social media

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Affects depending upon the frequency of use of social media

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Digital technology increased screen time correlating with lower well-being

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Digital technology increased screen time correlating with lower well-being

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Technology is responsible for well being of young adocelents.

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Technology is responsible for well being of young adocelents.

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Technology is responsible for well being of young adocelents.

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Source 7: The association between adolescent well-being and digital technology use by Amy Orben

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Source 7: The association between adolescent well-being and digital technology use by Amy Orben

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Data availability

The data that support the findings of this study are available from the Centre for Disease Control and Prevention (YRBS), Monitoring the Future (MTF) and the UK data service (MCS), but restrictions apply regarding the availability of these data, which were used under licence for the current study and so are not publicly available. Data are, however, available from the relevant third-party repository after agreement to their terms of usage. Information about data collection and questionnaires can be found on the OSF website ( https://osf.io/7xha2/).

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References

1. 6.
Johnston, L. D., Bachman, J. G., O'Malley, P. M., Schulenberg, J. E. & Miech, R. A. Monitoring the future: a continuing study of American Youth (8th- and 10th-Grade Surveys) https://doi.org/10.3886/ICPSR36799.v1 (2016).

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University of London, Institute for Education, Centre for Longitudinal Studies. Millennium Cohort Study: Sixth Survey, 2015 SN: 8156 (2018).

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U.S. Department of Health and Human Services, Health Resources and Services Administration, Maternal and Child Health Bureau. Child Health USA 2014 (U.S. Department of Health and Human Services, 2015).

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Angold, A., Costello, E. J., Messer, S. C. & Pickles, A. Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. Int. J. Methods Psychiatr. Res. 5, 237-249 (1995).

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Acknowledgements

The National Institute on Drug Abuse provided funding for the MTF conducted at the Survey Research Centre in the Institute for Social Research, University of Michigan. The YRBS was collected by the Centres for Disease Control and Prevention. The Centre for Longitudinal Studies, UCL Institute of Education collected the MCS and the UK Data Archive/UK Data Service provided the data. They bear no responsibility for its aggregation, analysis or interpretation. A.O. was supported by a EU Horizon 2020 IBSEN grant. A.K.P. was supported by an Understanding Society Policy Fellowship funded by the Economic and Social Research Council. A.O. and A.K.P.'s funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Thanks are extended to U. Simonsohn, N.K. Reimer and N. Weinstein for their valuable input, and to J.M. Rohrer, U. Simonsohn, J.P. Simmons and L.D. Nelson for code provision. We also acknowledge the use of the University of Oxford Advanced Research Computing facility in carrying out this research: https://doi.org/10.5281/zenodo.22558. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Affiliations

1. Department of Experimental Psychology, University of Oxford, Oxford, UK

Amy Orben

& Andrew K. Przybylski

2. Oxford Internet Institute, University of Oxford, Oxford, UK

Contributions

A.O. conceptualized the study, with regular guidance from A.K.P. A.O. completed the statistical analyses and drafted the manuscript. A.K.P. gave integral feedback in the process.

Competing interests

A.O. has no competing interests. A.K.P. has no competing financial interests; in the last five years A.K.P. has served in an unpaid advisory capacity with the Organization for Economic Co-operation and Development, Facebook Inc., Google Inc. and the ParentZone.

Corresponding author

Correspondence to Amy Orben.

Supplementary information

1. Supplementary Methods, Supplementary Figures 1-12, Supplementary Tables 1, 2, 5, 6, Supplementary Note, and Supplementary References

2. The MTF questionnaire contains different questionnaire types that are completed by different subsets of participants. Different numbers of participants, therefore, completed different combinations of questions, the details of which are displayed in this table. DS, depressive symptoms, SE, self-esteem; LO, loneliness.

3. In both the MTF and YRBS datasets questions were added and changed over the course of the study. This table outlines these alterations, showing both when questions were added and when they were modified.

4. R code and .run scripts to reproduce the analyses presented in the manuscript. A life version of this code can be found on the Open Science Framework: https://osf.io/e84xu/.

To obtain permission to re-use content from this article visit RightsLink.

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The association between adolescent well-being and digital technology use

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  psychological well-being decreases among adolescents when there is rise in screen time associated with smartphone usage( Twenge et al).

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  psychological well-being decreases among adolescents when there is rise in screen time associated with smartphone usage( Twenge et al).

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Source 6 : Decreases in psychological well-being among American adolescents after 2012 and links to screen time during the rise of smartphone technology by Jean M Twenge

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Source 6 : Decreases in psychological well-being among American adolescents after 2012 and links to screen time during the rise of smartphone technology by Jean M Twenge

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Abstract

In nationally representative yearly surveys of United States 8th, 10th, and 12th graders 1991-2016 (N = 1.1 million), psychological well-being (measured by self-esteem, life satisfaction, and happiness) suddenly decreased after 2012. Adolescents who spent more time on electronic communication and screens (e.g., social media, the Internet, texting, gaming) and less time on nonscreen activities (e.g., in-person social interaction, sports/exercise, homework, attending religious services) had lower psychological well-being. Adolescents spending a small amount of time on electronic communication were the happiest. Psychological well-being was lower in years when adolescents spent more time on screens and higher in years when they spent more time on nonscreen activities, with changes in activities generally preceding declines in well-being. Cyclical economic indicators such as unemployment were not significantly correlated with well-being, suggesting that the Great Recession was not the cause of the decrease in psychological well-being, which may instead be at least partially due to the rapid adoption of smartphones and the subsequent shift in adolescents' time use. (PsycINFO Database Record

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# data[].attributes.attachment_link.description
In nationally representative yearly surveys of United States 8th, 10th, and 12th graders 1991-2016 (N = 1.1 million), psychological well-being (measured by self-esteem, life satisfaction, and happiness) suddenly decreased after 2012. Adolescents who spent more time on electronic communication and sc ...

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Social media also has positive effects like increasing social support and self-esteem. 

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source 5: The Relationship Between Social Media Use and Mental Health in Young Adults: A Systematic Review by Smith, Johnson, and Brown.

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Fengxia Lai, Conceptualization, Methodology, Software, Data curation, Writing - original draft, 1, 2,† Lihong Wang, Investigation, Writing - original draft, 1,† Jiyin Zhang, Formal analysis, ² Shengnan Shan, Investigation, ² Jing Chen, Investigation, ² and Li Tian, Conceptualization, Methodology, Investigation, Writing - review & editing, Project administration 1, 2,*

Paul B. Tchounwou, Academic Editor

Abstract

An increasing number of college students are experiencing social anxiety in an era of prevalent social networking. College students' social anxiety may be related to their social media use. However, this relationship has not been confirmed. This study aimed to investigate the relationships between different types of social media use and social anxiety among college students, and the mediation effects of communication capacity in this context. A large sample of 1740 students from seven colleges in China was analyzed. Bivariate correlation and structural equations analysis showed that passive social media use was positively correlated with social anxiety. Active social media use was negatively correlated with social anxiety. Communication capacity partially mediated the relationship between social media use (passive/active) and social anxiety. Active social media use may reduce social anxiety by positively mediating communication capacity, while improved communication capacity may reduce the contribution of passive use to social anxiety. The differences in the effects of different social media use on social anxiety deserve the attention of educators. Developing communication capacity education around college students may help reduce their social anxiety.

Keywords: social media use, social anxiety, communication capacity, college students, mediation effect

1. Introduction

Social anxiety, also known as "social terror", refers to the negative anxiety that individuals experience in real or imaginary social interaction situations due to the fear or apprehension of receiving negative evaluations from others [ 1]. The prevalence of social anxiety in college students is about 7-33% worldwide [ 2, 3, 4], while in China, up to 12-14% of college students suffer from high levels of social anxiety [ 5]. If social anxiety is not corrected or improved, it may develop into a severe social anxiety disorder and continue to affect students' academic achievement, career development, and mental health [ 6]. Given the burden that social anxiety places on people and society, it is imperative to study the mechanisms through which it occurs, and to develop interventions.

Simultaneously, the use of social media has increased dramatically over the past decade, particularly among young people. Social network sites (SNSs) such as Instagram, Facebook, and Twitter have become indispensable parts of people's lives. According to statistics, there are 2.23 billion monthly active Facebook users worldwide, and this figure has an annual growth rate of 11% [ 7]. In China, the number of internet users had reached 1.011 billion by June 2021, with college students accounting for the highest occupational percentage, at over 23.0%.

Since college students frequently use the internet, their psychological status in social interactions may be influenced by the use of social media. According to research, using SNSs may cause personal social anxiety [ 8]. Several theories have shed light on possible mechanisms through which social media use triggers social anxiety. According to the self-presentation theory [ 9], individuals may be more sensitive to negative evaluations of others, and even tend to guess that others have negative evaluations of them in their online self-presentation, which causes social anxiety. Individuals use others as a standard of comparison for self-evaluation in the absence of actual reference material, according to classical social comparison theory [ 10], especially in the absence of communication, and passive use of SNSs by individuals triggers more upward social comparison. According to behaviorist theory [ 6], social anxiety is caused by a conditioned reflex of emotional response, implying that social anxiety may be caused by a lack of social skills and, more precisely, communication capacity.

This evidence calls for a better understanding of the risk factors for social anxiety. These factors also include the way social media is used, interpersonal communication capacity, and previous experiences of social frustration. In this research, we aim to examine the relationship between social media use and social anxiety, taking into consideration the mediating role of communication capacity.

1.1. Social Media Use and Social Anxiety

Social media provides an online medium that allows users to add "friends" to the same network and share their personal feelings, photos, etc., with these "friends" [ 11]. The use of social media makes social comparison easier among young adults, leading to poor mental health and life dissatisfaction [ 12]. Some studies have found that social media use may trigger social anxiety in individuals. A study conducted in Kolkata discovered that social networking sites (SNSs) and dependence on them had significant associations with anxiety and depression among medical students [ 13]. Furthermore, according to a Hong Kong, China study, students who spent more time on SNSs had more severe depression and anxiety problems [ 14]. Users of social media may experience a physiological stress response as a result of receiving negative feedback from others, cyberbullying, becoming more aware of stressful events occurring in the lives of others, and feeling pressure to keep social networks updated [ 15, 16]. Social media use may also lead to general communication overload, as individuals are bombarded with messages from multiple electronic channels at the same time, which is linked to psychological distress [ 17].

Researchers have categorized social media use into active and passive use based on the different ways social networking sites are used [ 18]. Active social media use is actively communicating with others (posting their news, commenting on friends' posts, and other information-generating behaviors); passive social media use mainly refers to browsing social networking sites without interacting with others (viewing friends' news and not participating in comments) [ 19]. To date, the literature distinguishing the different ways of using social media remains limited. However, a recent study suggests that there may be differences in the impact of different social media uses on individual mental health [ 20]. Active and passive Facebook use was also found to show opposing effects on loneliness [ 18]. Based on prior evidence, we came up with the following hypothesis:

Hypothesis 1 (H1):

Higher active social media use and lower passive social media use are positively associated with lower social anxiety.

1.2. The Mediating Role of Communication Capacity

Communication capacity refers to the ability to receive and transmit information, to effectively and clearly express thoughts, feelings, and opinions to others through written, oral, and nonverbal cues, and to quickly and accurately interpret the information transmitted by others to understand their thoughts, feelings, and attitudes [ 21]. Multiple lines of evidence suggest that internet use is associated with poorer cognitive-emotional regulation and communication capacity [ 22, 23, 24, 25]. Furthermore, according to behaviorist theory, social anxiety is caused by a conditioned reflex of emotional response, implying that social anxiety may be caused by a lack of necessary communication capacity [ 6]. Hence, we decided to focus on communication capacity as a mediator of social anxiety.

While social media users may gain a lot of social contact as a result of their internet use, it decreases face-to-face contact, which may impair their social skills in the real world [ 23]. Individuals must constantly practice communication skills and modify their behavior in response to feedback from others, and focusing on internet use may limit people's opportunities to practice communication skills and correct communication capacity deficits [ 23]. Heavy use of online social networks, for example, has been shown to reduce individuals' intimacy and time with parents and family, while increasing conflict with people close to them [ 24]. Adolescents who use social media for extended periods were reported to have more severe social skills deficits [ 25]. Furthermore, a recent study found that active social media use improves subjective wellbeing, while passive social media use decreases subjective wellbeing [ 26]. Thus, rather than social media itself, the consequences of social media use may be related to how social media is used. Based on past evidence, we propose the following hypothesis:

Hypothesis 2 (H2):

Higher active social media use and lower passive social media use are positively associated with better communication capacity.

The capacity to communicate is also critical in social interaction, as college students must manage relationships with different people, for example, classmates, teachers, romantic partners, and even strangers. Difficulties with effective communication during social development can lead to difficulties in establishing and maintaining friendships, which can result in anxiety, low mood, and depression [ 27]. Evidence suggests that social anxiety disorder is significantly associated with greater degrees of communication difficulties [ 25]; in other words, social anxiety is linked to a failure to apply social skills and engage in social interactions [ 28]. Effective communication skills may affect people's capacity to cope with worry in their social interactions [ 29], and social communication deficits may underpin anxiety disorders in individuals suffering from social anxiety. Spending time with others, on the other hand, can improve social skills, but socially anxious people tend to avoid social interactions [ 14]. Moreover, according to an intervention study, improving social skill knowledge has a positive effect on reducing symptoms of depression and anxiety [ 30]. Therefore, for the mediation model of this study, in which social media use is directly related to social anxiety and mediated through communication capacity, we hypothesized that:

Hypothesis 3 (H3):

Better communication capacity is negatively associated with higher social anxiety.

The theoretical moderated mediation model is represented in Figure 1 .

2. Materials and Methods

2.1. Study Design and Participants

A cross-sectional design was implemented. This study was conducted from June to September 2022 with students at seven public colleges in Suzhou, China. A total of 2192 college students were surveyed by online questionnaire, and data from 1740 individuals were eventually included through lie detection questions screening (valid recovery rate = 79.4%). Study procedures involving human participants followed institutional ethical standards. All participants completed the questionnaire anonymously after providing informed consent.

2.2. Measurements

All measures were self-reported, and data were obtained via Sojump.com (a platform providing functions equivalent to those of Amazon Mechanical Turk). The questionnaire link was shared by teachers for students to fill out anonymously and could be submitted only once.

2.2.1. Basic Information

Basic information was collected via a general information questionnaire designed by the researchers according to the content of the study, including students' information such as age, gender, year of study, place of origin, family structure, economic level, and ethnicity. Finally, based on previous studies measuring risk factors related to social anxiety in college students [ 3, 4, 5], participants were asked about class leaders' experiences, frustration experiences in social interactions, their number of friends on SNSs, and childhood left-behind experiences (i.e., those whose parents are migrant workers and those who were children left at home and cared for by relatives).

2.2.2. Active Social Media Use

Active social media use was measured via the Active SNS Use Scale [ 31]. It mainly measures individuals' active use of social media, such as "updating information on their social networking site pages" and "posting photos on their social networking site pages." This scale consists of 5 items. Each item is rated on a 5-point scale (1 = never to 5 = always), with higher total scores indicating higher levels of active social media use. The Cronbach's α value for this questionnaire is 0.77.

2.2.3. Passive Social Media Use

Passive social media use was measured via the Passive SNS use Scale [ 32], using a Chinese version revised by Liu Qingqi [ 33]. It mainly measures individuals' passive use of social media, such as "reading friends' status updates" and "viewing photos uploaded by friends". This scale consists of 4 items. Each item is rated on a 7-point scale (1 = never to 7 = multiple times a day), with higher total scores indicating higher levels of passive social media use. The Cronbach's α coefficient for this questionnaire is 0.70.

2.2.4. Communication Capacity

Communication capacity was measured via the Communication Capacity Scale developed for college students by a Chinese scholar [ 34]. This scale consists of 38 items in 8 dimensions: respect, listening, empathy, emotional sensitivity, comforting others, emotional control, enthusiasm, and verbal expression. Each dimension includes 3-7 items (see Appendix A for all scale items); each item is rated on a 5-point scale (1 = not at all to 5 = fully), with higher total scores indicating higher levels of passive social media use. In this study, the Cronbach's α value of this questionnaire was 0.89.

2.2.5. Social Anxiety

Social anxiety was measured via the Interaction Anxiety Scale [ 35]. It is mainly used to assess the subjective feelings of individuals' social anxiety experience and is widely used in related studies. The scale consists of 15 questions and is scored on a 5-point scale (1 = not at all to 5 = fully), with higher total scores indicating higher levels of social anxiety. In this study, the Cronbach's α value of this questionnaire was 0.81.

2.2.6. Personality Traits

The personality of introversion and extraversion was measured via the Chinese version [ 36] of the Eysenck Personality Questionnaire [ 37]. The scale is suitable for Chinese adults aged 16 years and above, with the advantage of being easy to understand and simple to measure. As social anxiety is mainly influenced by introversion and extroversion personality traits in the Chinese ethnic context [ 38, 39], only the E scale with 12 items was used in this study to analyze the influence of introversion and extroversion personality factors on the results. In this study, the Cronbach's α value of this questionnaire was 0.83.

2.3. Statistical Analysis

Descriptive statistics were used to describe participants' sociodemographic characteristics and the main study variables (age, gender, profession, family structure, the experience of class leaders, etc.). Moreover, we conducted tests of normality and homogeneity of variance. One-way analyses of variance (ANOVAs), t-tests, and Pearson's r correlations were used to test for the unadjusted associations between variables. Because the data obtained are all self-reported by students, this may lead to common method bias (CMBs). Harman's single-factor test was used to test CMBs. If a factor accounts for more than 50% of the total variance, common method bias has an impact on the findings [ 40]. All these analyses were performed using IBM SPSS 26.0. Then, to achieve the main objective of the study, a simple mediation model with 5000 bootstraps was run using IBM SPSS Amos 22.0 As an estimate, a 95% confidence interval (CI) was provided. For the mediation effect, a mediator is significant if the 95% CI of the indicator does not include 0 [ 41]. Confirmatory factor analyses (CFA) were performed and then evaluated by Hu and Bentler's [ 42] guide to various fit metrics. The following indicators and thresholds are included: the chi-square/degrees of freedom (χ ²/ df < 3.00), the root mean square error of approximation (RMSEA ≤ 0.08), the goodness-of-fit index (GFI > 0.90), and the comparative fit index (CFI ≥ 0.95). All statistical tests were two-tailed, and the level of significance was set at 0.05.

2.4. Ethical Considerations

The Institutional review board of Soochow University has approved the ethical considerations in research methods and procedures (SUDA20220620H08).

3. Results

3.1. Descriptive Statistics

The descriptive statistics for all study variables are shown in Table 1 . The mean age of college students was 19 years (standard deviation [SD] = 2), with a range of 15-29 years. 679 (39%) were male students, and 1061 (61%) were female students. The ratios of education levels were 23.0% (undergraduate) and 77.0% (junior college). 57.0% were only children and 43.0% were non-only children; 59.5% had served as student leaders and 40.0% had not. The mean Interaction Anxiety Scale score was (43.46 ± 8.33), indicating a moderate to high level of social anxiety.

Table 1

Characteristics

N (%)

Social Anxiety

M ± SD

t/F

p

Gender

−0.359

p < 0.001

Monthly per capita household income

<3000 yuan

256 (14.7%)

44.56 ± 7.54

5.595

p < 0.001

Teaching assistants experience

−0.762

0.446

Childhood left-behind experience

2.462

0.014

Frustration experience in social interactions

65.589

p < 0.001

Number of friends on SNSs

1.297

0.269

EPQ-Personality traits

59.527

p < 0.001

There were significant differences in social anxiety among college students by gender, family income, the experience of being left behind in childhood, frustration experiences in social interactions, and personality traits ( Table 1 ). According to hoc tests, college students with a per capita household income of less than RMB 3000 had higher levels of social anxiety than those with a per capita household income of more than RMB 5000. The lower the income, the higher the level of social anxiety. Students with more frequent experiences of interpersonal frustration had higher levels of social anxiety than those with occasional or no such experiences. Students with introverted personality traits had higher social anxiety levels than those with intermediate and extroverted personality traits. There were no significant differences in social anxiety between the other sociodemographic variables.

3.2. Correlations between Social Media Use, Communication Capacity, and Social Anxiety

Pearson's correlation analysis ( Table 2 ) showed that active social media use was negatively correlated with social anxiety (r = −0.342, p < 0.001) and positively correlated with communication capacity (r = 0.514, p < 0.01). Passive social media use was positively correlated with social anxiety (r = 0.525, p < 0.01) and negatively correlated with communication capacity (r = −0.253, p < 0.01). Communication capacity was negatively associated with social anxiety (r = −0.371, p < 0.01).

3.3. Common Method Bias Test

Harman's single-factor test showed that a total of 10 factors' eigenvalues were >1, the interpretation rate of the first factor was 33.47% (<50%), and there was no serious common method bias.

3.4. Model Test

We used structural equation modeling with observed variables in SPSS Amos 22.0 to test the relationships between social media use, communication capacity, and social anxiety, while controlling for sociodemographic variables (gender, income, experience of being-left-behind, experience of interpersonal frustration, and personality traits). Figure 2 shows a simplified version of the calculated structural equation model. According to Table 3 , the following model can be accepted: χ ²/ df = 2.121, CFI = 0.975, GFI = 0.975, AGFI = 0.998, and RMSEA = 0.039.

Table 3

Fit Index

CMIN/df

CFI

GFI

AGFI

RMSEA

Test result

2.121

0.975

0.975

0.998

0.089

Fit standard

1 < χ ²/ df < 3

>0.90

>0.90

>0.90

<0.08

The results ( Table 4 ) showed that active and passive social media use had a positive and negative predictive effect on communication capacity (β = 1.697 and −0.700, p < 0.01), respectively, explaining 32.8% of the variance in communication capacity. Active and passive social media use negatively predicted social anxiety (β = −0.477 and 0.646, p < 0.01) and explained 41.3% of the variance in social anxiety. Bootstrap repeat sampling was set to 5000 and with 95% CI. The results showed that the direct effects were −0.477 and 0.646; the 95% CIs were (−0.552 to −0.401) ( p < 0.001) and (0.577 to 0.715) ( p < 0.001). In contrast, the indirect effects were −0.100 and 0.050, and the 95% CIs were (−0.086 to −0.030) ( p < 0.001) and (0.007 to 0.059) ( p < 0.001). The study revealed that the direct and indirect effects of social media use on social anxiety are statistically significant; 95% of the CIs did not include zero, which indicated that there was a significant mediation effect of communication capacity on the relationship between social media use and social anxiety.

Table 4

Path

Effect

Normalized
Path Coefficient (β)

Standard Error (S.E.)

95% CI

p

1. Passive social media use → Communication capacity → Social anxiety

Direct effect (c')

0.646

0.059

0.577~0.715

<0.001

2. Active social media use → Communication capacity → Social anxiety

Direct effect (c')

−0.477

0.039

−0.552~−0.401

<0.001

4. Discussion

This study confirmed that higher active social media use and lower passive social media use were associated with lower social anxiety. Furthermore, this relationship was partially mediated by communication capacity.

4.1. Social Anxiety Was Affected by Gender, Family Income, the Experience of Being Left behind in Childhood, Frustration Experience in Social Interactions, and Personality Traits

Social anxiety problems developed by college students during their development are often the result of a combination of personal, external, and other factors. Research has documented that sociodemographic variables are crucial factors related to social anxiety [ 43, 44]. In this study, female students perceived more social anxiety than male students. According to self-construction theory [ 45], men and women have different understandings of self-awareness. Men tend to construct and maintain an independent sense of self in which others are separate from the self. In contrast, women tend to construct an interdependent sense of self in which others are also considered an essential part of the self-construction. This difference in self-awareness may lead female college students to show nervousness and anxiety during social interactions and sensitivity to the evaluation of social partners. They tend to invest time and energy in repeatedly recalling and evaluating their performance after social interactions, and thus are more likely to experience high levels of social anxiety [ 46]. Moreover, students' family economic level was associated with social anxiety. Social anxiety was higher among college students with lower monthly per capita household income, which may be related to low self-esteem due to low purchasing power [ 47]. Similarly, a study by Jefferies [ 48] on social anxiety among young people in seven countries showed that the unemployed population had higher social anxiety than those employed.

On the other hand, experiences of being left behind in childhood and interpersonal frustration in social interactions were also associated with higher levels of social anxiety. This triggering mechanism may work through the insecure attachment type of the students [ 49]. Experiences of traumatic events and adverse life events suffered in childhood have a profound impact on individuals. They become more fearful of interacting with people, fear being judged, have a negative, skeptical attitude toward themselves, and do not participate in as many social activities [ 50, 51]. The findings also showed that extraversion was negatively related to social anxiety; this is consistent with previous studies [ 50, 52]. Highly extroverted people tend to be sociable, talkative, enthusiastic, and confident [ 53]. These people are more likely to engage in social activities and feel energized by social interactions [ 54]. Hence, they are less likely to report social anxiety.

4.2. Different Manners of Social Media Use Correlated Differently with Social Anxiety and Communication Capacity

Our results showed that the relationship between different use of social media and social anxiety among college students varied. Active social media use was negatively associated with social anxiety, while passive social media use was positively associated with social anxiety. Although the effects were somewhat weak according to the effect size criteria used by Cohen [ 55], the results still support our research hypothesis 1. In previous studies, less research has been conducted on active social media use, with most of them pointing to positive psychological outcomes [ 31, 56, 57]. The reason for this may be related to the fact that active social media use enhances social communication, leading to an increase in daily contact and emotional interaction [ 18]. Users increase their positive emotions by interacting directly with other users and increasing their supportive interactions online [ 58], thereby reducing social anxiety. Passive social media use, on the other hand, points to adverse outcomes in this study. Previous research has shown that passive use of social media positively predicts loneliness, leads to a decrease in individual wellbeing, and affects adolescent body image worries [ 59]. This is because the content presented by individuals on the internet can make the viewers feel that their friends' life is better than their own, which in turn affects subjective wellbeing [ 60].

Moreover, this study revealed that active social media use was positively associated with the communication capacity of college students, while passive use was the opposite. Active online communication has been shown to have a beneficial effect on individuals. For instance, active social media use can indirectly influence friendship quality through positive SNS feedback, and can positively predict friendship quality [ 61]. On the other hand, passive social media use may partially replace the function of real-life interactions and also crowd out the real-life interaction time of college students. It may diminish direct, face-to-face interactions between people, causing college students to alienate themselves from real-world interpersonal interactions to a certain extent, and affecting the improvement of interpersonal communication capacity [ 62].

4.3. Communication Capacity Was Negatively Correlated with Social Anxiety

According to previous studies, maladaptive behavior and irrational cognitive perceptions are two important causes of social anxiety among college students [ 20]. Behaviorism suggests that, as an emotional response, social anxiety stems from conditioned effects and explains the formation of social anxiety through the principle of conditioned effects and social learning theory [ 63]. That is, social anxiety can arise from a lack of social skills. The stronger the individual's communication capacity, the lower the level of social anxiety. A possible explanation for this is that the greater one's communication capacity is, the more clearly one can communicate one's wishes and ideas to others, and the more acutely one can detect the subtle emotional feelings of others through their body language. Hence, one tends to build up a good level of confidence when interacting socially with others, which, as a good emotional experience, helps to reduce the occurrence of social anxiety [ 64]. On the other hand, people with lower communication capacity may have a poorer sense of communication experience in everyday interpersonal interactions due to their lack of essential communication skills, and are therefore more reluctant to engage in frequent interactions with people. The less they communicate with people, the more they fear communicating with people, thus increasing their level of social anxiety [ 65].

4.4. The Mediating Role of Communication Capacity

The other results of this study corroborate the theoretical validity of the mediation model; communication capacity partially mediates the relationship between social media use and social anxiety, which means that communication capacity represents a potential underlying mechanism that could partially explain how social media use is linked with social anxiety. That is, promoting positive social media use and decreasing passive social media use as ways to build up communication capacity might help to relieve social anxiety among college students. Specifically, active use of social media strengthens relational connections between individuals and provides a supportive environment for improving communication capacity [ 66], thus helping to reduce social anxiety. On the other hand, passive social media use significantly increases the risk of developing social anxiety, which can be buffered by enhancing communication capacity. Behaviorism also suggests that social anxiety can be generated by a lack of social skills [ 63]. Therefore, the development of interventions oriented towards enhancing the communication capacity of college students is crucial today, when social networks are prevalent. This may help these individuals to expand their social communication resources and strengthen their interpersonal support, thereby reducing social anxiety.

This study has a few limitations. First, while this study was limited to public colleges, there were some differences in students' use of social media across different types of schools. To improve the generalizability of the results, future studies could replicate this study in other educational institutions (e.g., private or international schools). Second, our mediation model is based on a priori, derived from previous studies. However, it is only one of several reasonable and possible models examining how different variables are related. Future research needs to consider the mediating role of other variables not studied in this research, and verify whether the outcomes are replicated at other educational levels. Finally, while the findings of this study support the hypothesized relationships described in the existing literature, additional prospective studies are required to confirm the results.

5. Conclusions

Our research extends the previous results, showing that the relationship between social media use and social anxiety can be explained when incorporating communication capacity as a mediator. Active social media use was significantly and negatively related to social anxiety, whereas passive social networking site use was significantly and positively related to social anxiety. Reducing the use of passive social media among college students and adopting communication capacity-oriented interventions may yield benefits for improving students' psychological wellbeing; educators should pay sufficient attention to them.

Appendix A. Items of Communication Capacity Scale

Respect

I can respect others in terms of manners.

I can accommodate other people's perspectives.

I speak politely.

Listening

I'm a good listener.

I listen to others carefully when I talk to them.

I can't concentrate on listening to others.

Empathy

I can accurately understand the thoughts of others, whether they are elders or peers.

When I disagree with my family, I will think from a different perspective and work together to solve the problem.

I can put myself in others' shoes.

Emotional sensitivity

I can easily perceive the emotional feelings of others.

I can perceive social situations well and pay attention to what others say and do.

I can interpret other people's attitudes and expressions based on their gestures, expressions, or eyes.

Comforting others

I like to comfort others.

I think it is useless to comfort others when they are in trouble.

I am good at comforting others when they encounter misfortune or difficulties.

When friends feel upset or angry, they are willing to talk to me.

Emotional control

I can find many reasonable ways to deal with my negative emotions without causing harm to myself or others.

It's very difficult for me to control my emotions.

When someone misunderstands me, I can explain to him/her calmly

Enthusiasm

I appear to be cold.

I will take the initiative to say hello when I meet people I know.

I don't initiate communication with new acquaintances.

I am an enthusiastic person.

I always smile with people.

Verbal expression

I can express my thoughts clearly.

I can describe the boring things vividly.

To make my speech more compelling, I incorporate gestures and facial expressions.

People always comprehend what I'm saying easily.

I know how to change the subject and understand the main points of the conversation.

I can control my nerves in front of strangers and converse happily with them.

I don't speak fluently.

Note: Only the items for the eight dimensions are shown here, and the scale's 7 polygraph questions have been omitted.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, F.L. and L.T.; methodology, F.L.; software, F.L.; formal analysis, J.Z. and J.C.; investigation, L.W., L.T. and S.S.; data curation, F.L.; writing-original draft preparation, F.L. and L.W.; writing-review and editing, L.T.; project administration, L.T. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Soochow University, China (SUDA20220620H08).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on reasonable request from the corresponding author. The data are not publicly available due to ethical requirements.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Disclaimer/Publisher's Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

References

55. Cohen J. The SAGE Encyclopedia of Research Design. SAGE Publications; Thousand Oaks, CA, USA: 2022. Statistical Power Analysis for the Behavioral Sciences. [ Google Scholar]

59. Burke M., Marlow C., Lento T. Social Network Activity and Social Well-Being; Proceedings of the 28th International Conference-E on Human Factors in Computing Systems (CHI'10); Atlanta, GA, USA. 10-15 April 2010; New York, NY, USA: ACM Press; 2010. [[ CrossRef] Google Scholar]

Articles from International Journal of Environmental Research and Public Health are provided here courtesy of Multidisciplinary Digital Publishing Institute (MDPI)

# data[].attributes.attachment_link.title
Relationship between Social Media Use and Social Anxiety in College Students: Mediation Effect of Communication Capacity

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An increasing number of college students are experiencing social anxiety in an era of prevalent social networking. College students' social anxiety may be related to their social media use. However, this relationship has not been confirmed. This ...

# data[].attributes.headline
social media usage is linked to personality traits and heightened feelings of social isolation, underscoring the intricate relationship between individual characteristics, online behavior, and social connectedness(Primak at al).

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social media usage is linked to personality traits and heightened feelings of social isolation, underscoring the intricate relationship between individual characteristics, online behavior, and social connectedness(Primak at al).

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Source 4:Social Media Use, Personality Characteristics, and Social Isolation among Young Adults in the United States by Brian A Primak

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Source 4:Social Media Use, Personality Characteristics, and Social Isolation among Young Adults in the United States by Brian A Primak

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Excessive social media use correlates with heightened levels of stress, anxiety, and depression among students, potentially hindering academic performance and disrupting sleep patterns. 

# data[].attributes.subject
Excessive social media use correlates with heightened levels of stress, anxiety, and depression among students, potentially hindering academic performance and disrupting sleep patterns. 

# data[].attributes.headline
Problematic patterns of social media use, such as compulsive behavior and fear of missing out, are linked to adverse psychological outcomes, including fatigue, anxiety, and depression(Dhir et al.)

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Problematic patterns of social media use, such as compulsive behavior and fear of missing out, are linked to adverse psychological outcomes, including fatigue, anxiety, and depression(Dhir et al.)

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Social media indirectly contributes to mental health issues in emerging adults with difficulties in emotion regulation and high perceived stress, acting both as a risk factor and a coping mechanism(Rasmussen et al). 

# data[].attributes.subject
Social media indirectly contributes to mental health issues in emerging adults with difficulties in emotion regulation and high perceived stress, acting both as a risk factor and a coping mechanism(Rasmussen et al). 

# data[].attributes.headline
Research Question: What role does social media usage play in exacerbating stress and anxiety levels among college students, and what factors contribute to this phenomenon?

# data[].attributes.subject
Research Question: What role does social media usage play in exacerbating stress and anxiety levels among college students, and what factors contribute to this phenomenon?

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Promote mindfulness practices to help students become more aware of their emotions and the impact of social media on their mental well-being. Encourage them to engage with social media mindfully, being conscious of how it makes them feel (Buzenski, n.d.).

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subpoint C: strategies for improving usage

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subpoint C: strategies for improving usage

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Higher emotional investment in social media, indicative of spending more time and energy on these platforms, is associated with increased anxiety and depression among university students (Alsunni & Latif, 2021).

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subpoint A: Factors affecting social media use 

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subpoint A: Factors affecting social media use 

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Individuals who struggle with managing their emotions are more likely to turn to social media as a way to cope with their feelings (Dhir et al., 2018).

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Derived Claim: Frequent social media usage, particularly exposure to negative content and social comparison, significantly exacerbates stress and anxiety levels among college students. Factors such as cyberbullying, unrealistic portrayals of life, and the pressure to maintain an ideal online presence contribute to this phenomenon

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Derived Claim: Frequent social media usage, particularly exposure to negative content and social comparison, significantly exacerbates stress and anxiety levels among college students. Factors such as cyberbullying, unrealistic portrayals of life, and the pressure to maintain an ideal online presence contribute to this phenomenon

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Source 3: The Impact of Social Media on Mental Health in Students by Douglus Bozenski

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Source 3: The Impact of Social Media on Mental Health in Students by Douglus Bozenski

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Douglas T. Buzenski, LPCC-S
Psychotherapist, Capital University

Social media has changed the way we interact with our fellow human beings, and this is especially true for those of a traditional college age. Our stage in life and our age at introduction to social media can't help but have some influence on the ways in which we are impacted. In 2004 Facebook became a thing and in 2007 the introduction of smart phones allowed access to the internet at any time and nearly anyplace. This is a long way from the agonizing AOL dial up while being tethered to the home computer. The arrival on the scene of Facebook and smartphones means that traditional college students today have not known life without the existence of social media.

For college students, who are already navigating the challenges of academic pressure, social relationships, and personal development, the pervasive influence of social media can significantly impact their mental health. I think our minds often go straight to the negative impact of social media, but let's begin with some possible positive effects.

Positive Effects of Social Media on College Students' Mental Health

Connection and Support: Social media platforms provide an avenue for college students to connect with family, friends, and peers. This is especially true during times of physical separation, such as going away to college, or having friends leave for their respective universities. Having an online support network can offer comfort, and reduce feelings of loneliness and isolation, which can all help ease the transition into college.

Information and Awareness: Social media can allow college students to stay informed about various current events, mental health issues, self-care techniques, and resources for seeking help. Online communities, at times, can also create safe spaces for individuals to share their struggles and experiences, fostering a sense of belonging.

Expression and Creativity: Social media platforms can serve as creative outlets for college students to express themselves through art, music, writing, or videos. Engaging in creative endeavors can promote positive mental well-being and self-esteem.

Negative Effects of Social Media on College Students' Mental Health

FOMO: The fear of missing out (FOMO) on exciting events or opportunities can lead to a sense of inadequacy and loneliness and can create pressure to feel like the student must attend every event.

Comparison: The prevalence of social media has fed into the ability to compare oneself to others. This can lead to anxiety and a lack of self-confidence. When we compare ourselves to what we see on social media we are generally comparing ourselves to postings of people doing things they enjoy and posting the best shots from those often-ideal activities.

Cyberbullying and Harassment: Social media platforms can expose students to cyberbullying, harassment, or negative comments. Such online abuse can severely impact self-esteem, at times leading to anxiety and depression.

Sleep Disruptions: Excessive use of social media, especially before bedtime, can disrupt sleep patterns among students. Inadequate sleep can lead to increased stress and a decline in overall mental health.

Addiction and Time Management: Constant engagement with social media may lead to a lack of time management or even addiction, thus impacting academic performance and overall well-being.

Filtered Reality: The selective and curated nature of social media posts often creates a filtered and idealized reality. This discrepancy between online and offline lives can contribute to feelings of inadequacy and contribute to anxiety and depression.

Mitigating the Negative Effects

Digital Well-being Education: Students can educate themselves about responsible social media usage, the impact of online behavior, and strategies to maintain a healthy balance between virtual and real-life interactions.

Cultivating Offline Connections: Encouraging students to build meaningful offline relationships and engage in activities outside of social media can strengthen their sense of belonging to their community and reduce the negative effects of online comparison.

Encouraging Mindfulness Practices: Incorporating mindfulness and stress reduction techniques can help students manage the pressures of social media and academic life more effectively. The students will improve their ability to control what they can control and to live in the present reality.

Limiting Screen Time: Setting boundaries and limiting excessive screen time can help students reduce the negative impact of social media on their mental health and leave room for improvements in other areas of their lives.

Social media undoubtedly plays a significant role in the lives of college students, offering both positive connections and detrimental influences on their mental health. While it provides opportunities for support and self-expression, the negative effects of social comparison, cyberbullying, and addiction can be detrimental. By fostering a balanced approach to social media usage and promoting digital well-being, students can empower themselves and learn to navigate the digital landscape while prioritizing their mental health and overall well-being.

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The Impact of Social Media on Mental Health in Students

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Douglas T. Buzenski, LPCC-S Psychotherapist, Capital University Social media has changed the way we interact with our fellow human beings, and this is especially true for those of a traditional college age. Our stage in life and our age at introduction to social media can't help but have some influence on the ways in which we are impacted.

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Source 2: Online Social Media Fatigue and Psychological Wellbeing-A Study of Compulsive Use, Fear of Missing out, Fatigue, Anxiety and Depression by Amandeep Dhir.

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Source 2: Online Social Media Fatigue and Psychological Wellbeing-A Study of Compulsive Use, Fear of Missing out, Fatigue, Anxiety and Depression by Amandeep Dhir.

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Abstract

The constant development of online social media features and related services has constantly attracted and increased the number of social media users. But, at the same time, a myriad of users have deviated themselves, temporarily or permanently, from social media use due to social media fatigue. Scholars have investigated different antecedents and consequences of social media fatigue. However, empirical relationships between psychosocial wellbeing and social media fatigue are currently not known. To bridge this gap, the current study utilises the stressor-strain-outcome framework (SSO) to examine whether psychosocial wellbeing measures, such as compulsive media use and fear of missing out, trigger fatigue and, furthermore, whether social media fatigue results in anxiety and depression. The study utilised repeated cross-sectional methodology whereby two waves of data (N = 1554, 1144) were collected to test the research model with adolescent social media users in India. The study findings suggest that compulsive media use significantly triggered social media fatigue, which later result in elevated anxiety and depression. Fear of missing out indirectly predicted social media fatigue through mediation of compulsive social media use. The theoretical and practical implications, limitations of the present study and agenda for future studies are presented and discussed.

Introduction

An increasing number of social media users are straying from their participation on social media because of encountering social media fatigue (Guest Post, 2017). Prior research has defined social media fatigue as a situation whereby social media users suffer from mental exhaustion after experiencing various technological, informative and communicative overloads through their participation and interactions on the different online social media platforms (Bright, Kleiser, & Grau, 2015; Lee, Son, & Kim, 2016; Ravindran, Kuan, Chua, & Hoe Lian, 2014; Zhang, Zhao, Lu, & Yang, 2016).

This phenomenon has recently motivated scholars from around the world to conduct empirical investigations to determine the antecedents and consequences of social media fatigue (Cramer, Song, & Drent, 2016; Luqman, Cao, Ali, Masood, & Yu, 2017; Sasaki, Kawai, & Kitamura, 2016; Yoa & Cao, 2017). The relative determinants of social media fatigue can be stemmed from psychological and behavioural stress-related conditions, such as information overload and connection overload as well as social interactive activities (Bright et al., 2015; LaRose, Connololy, Lee, Li, & Hales, 2014; Lim, Park, Iijima, & Ahn, 2017; Walton, 2017; Zhang, Zhao, Lu, & Yang 2016). Due to this emotional suffering, social media users are likely to refrain, either temporarily or permanently, from participating in online social media interactions (Oghuma, Libaque-Saenz, Wong, & Chang, 2016; Swar, Hameed, & Reychav, 2017).

Scholars argue that social media fatigue has significant negative implications for both users as well as the businesses and service operators (Oghuma et al., 2016; Shin & Shin, 2016). On a user level, social media fatigue results in deterioration in both mental and physiological strengths whereby users are likely to develop unhealthy behaviours (Choi & Lim, 2016; Shin & Shin, 2016; Sun et al., 2017). Similarly, social media fatigue can be detrimental for businesses and service operators because fatigue results in withdrawal from service use, which translates into lower profits for companies and service operators. Despite these serious implications, research examining social media fatigue is still in its early stage wherein most existing studies have exclusively focused on its relationship with frequency of service use, service satisfaction, privacy, discontinuity, excessive social media use, social media exhaustion and technostress, as well as technology and physical overload (see Table 1). In comparison to this body of literature, the relationship between psychosocial wellbeing and social media fatigue has not yet been well-studied. This gap is addressed by the present study, which utilises a repeated cross-sectional research methodology to investigate this relationship over time. Two waves of cross-sectional data sets were collected in May 2017 (N = 1554) and September 2017 (N = 1144) with adolescent social media users. The current study investigates whether compulsive social media use and fear of missing out among adolescent social media users trigger social media fatigue? Furthermore, whether social media fatigue contributes to increase in anxiety and depression among adolescent social media users.

The current study also addresses three main limitations in the prior literature on social media fatigue, namely limited focus on specific age and cultural groups, and exclusive focus on single shot studies (i.e. cross-sectional surveys at a single point of time). Our review of prior literature revealed that the main focus has been on university-attending young-adults, either from the Western world or East Asian countries. In comparison to this, adolescent social media users from developing countries, such as India, are rarely studied. Similarly, most prior studies are purely cross-sectional in nature wherein data are collected at a single point of time. To address these limitations, the current study utilised repeated cross-sectional studies whereby the same measures were evaluated with similar target user groups over time, i.e., data were collected twice over a period of five months. Furthermore, the study focused on adolescents in a lesser studied cultural and demographic group of social media users. The study concluded with significant theoretical and practical implications for scholars as well as practitioners.

Section snippets

Social media fatigue

A systematic review of prior social media fatigue literature was performed (see Table 1). Prior studies on social media fatigue have looked into two types of online social media, namely online social networking sites (e.g., Facebook) and mobile instant messengers (e.g., KakaoTalk) (Bright et al., 2015; Chen & Lee, 2013; Ravindran et al., 2014; Shin & Shin, 2016). Most of the prior studies were conducted in industrialised Asian countries, for example South Korea, Taiwan, Japan and China (Lee,

Research model

Prior literature has utilised different theoretical frameworks for studying social media fatigue, including the limited capacity model (LCM), the stressor-strain-outcome (SSO) model and the transactional theory of stress and coping (TTSC), in order to determine causal relationships and consequences in relation to social media fatigue (Blabst & Diefenbach, 2017; Bright et al., 2015; Lee, Chou et al., 2014; Lee, Son et al., 2016; Lim et al., 2017; Luqman et al., 2017; Zhang et al., 2016). In the

Measurement model

A confirmatory factor analysis (CFA) using the measurement model was performed to evaluate the model fit by utilising different goodness of model fit indices. A good model fit suggests that the theoretical model fits well with empirical data. Scholars have suggested different threshold values for goodness of model fit indices for demonstrating good model fit, namely Chi-square/degree of freedom (/ df) > 3, Comparative Fit Index (CFI) ≥ 0.95, Tucker-Lewis Index (TLI) ≥ 0.95, and Root Mean

Discussion

Prior literature has examined the different antecedents and consequences or outcomes of social media fatigue. However, the empirical linkages between psychosocial wellbeing and social media fatigue were not known. This gap is addressed by the current study using the stressor-strain-outcome (SSO) framework. This study utilised repeated cross-sectional methodology, which consisted of two large cross-sectional surveys with adolescent social media users, separated over a period of five months. Two

Study implications

The present study findings have several theoretical and practical implications. The theoretical implications are as follows: First, prior literature has not yet examined the psychosocial wellbeing related aspects of social media fatigue. Therefore, the present study is possibly the first empirical study that has examined them, thus significantly contributing to theory development as well as prior mushrooming literature on social media fatigue. Second, the outcomes or consequences of social

Study limitations and future work

The present study findings and related implications should be considered in the light of four important limitations. First, since the data were collected in one specific country and with one age group (i.e., adolescents), it is suspected that current findings may change if other age groups and cultural backgrounds are considered. To address this limitation, we encourage other scholars to validate a similar research model with other age and cultural groups. Second, the present study only focused

Conclusion

Social media is a popular informative and communicative platform among users across the globe. Despite the various positive outcomes which are beneficial to users in various aspects in life, negative consequences due to excessive social media use are also ineviTable Social media fatigue is a prevalent factor which negatively influences users' mental and behavioural conditions. The present study has examined the relationship between social media fatigue and psychosocial wellbeing by utilising

Acknowledgements

This study was financially supported by Academy of Finland mobility grants (Decision No 318452, 311191, 298098). We like to sincerely thank Professor Cathy Weng from National Taiwan University of Science & Technology (NTUST), Taiwan for providing insightful feedback that helped us in preparing this manuscript.

American Psychiatric Association
Diagnostic and statistical manual of mental disorders

Cognitive therapy of panic disorders

Anxiety disorders and phobias: A cognitive perspective

WhatsApp and Wellbeing: A study on WhatsApp usage, communication quality and stress

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Online social media fatigue and psychological wellbeing-A study of compulsive use, fear of missing out, fatigue, anxiety and depression

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The constant development of online social media features and related services has constantly attracted and increased the number of social media users. But, at the same time, a myriad of users have deviated themselves, temporarily or permanently, from social media use due to social media fatigue.

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Source 1:The Serially Mediated Relationship between Emerging Adults’ Social Media Use and Mental Well-Being by Eric E Rasmussen.

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Source 1:The Serially Mediated Relationship between Emerging Adults’ Social Media Use and Mental Well-Being by Eric E Rasmussen.

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