hypothesis on effects of social media

ORIGINAL RESEARCH article

Effects of social media use on psychological well-being: a mediated model.

• 1 School of Finance and Economics, Jiangsu University, Zhenjiang, China
• 2 Research Unit of Governance, Competitiveness, and Public Policies (GOVCOPP), Center for Economics and Finance (cef.up), School of Economics and Management, University of Porto, Porto, Portugal
• 3 Department of Business Administration, Sukkur Institute of Business Administration (IBA) University, Sukkur, Pakistan
• 4 CETYS Universidad, Tijuana, Mexico
• 5 Department of Business Administration, Al-Quds University, Jerusalem, Israel
• 6 Business School, Shandong University, Weihai, China

The growth in social media use has given rise to concerns about the impacts it may have on users' psychological well-being. This paper's main objective is to shed light on the effect of social media use on psychological well-being. Building on contributions from various fields in the literature, it provides a more comprehensive study of the phenomenon by considering a set of mediators, including social capital types (i.e., bonding social capital and bridging social capital), social isolation, and smartphone addiction. The paper includes a quantitative study of 940 social media users from Mexico, using structural equation modeling (SEM) to test the proposed hypotheses. The findings point to an overall positive indirect impact of social media usage on psychological well-being, mainly due to the positive effect of bonding and bridging social capital. The empirical model's explanatory power is 45.1%. This paper provides empirical evidence and robust statistical analysis that demonstrates both positive and negative effects coexist, helping to reconcile the inconsistencies found so far in the literature.

Introduction

The use of social media has grown substantially in recent years ( Leong et al., 2019 ; Kemp, 2020 ). Social media refers to “the websites and online tools that facilitate interactions between users by providing them opportunities to share information, opinions, and interest” ( Swar and Hameed, 2017 , p. 141). Individuals use social media for many reasons, including entertainment, communication, and searching for information. Notably, adolescents and young adults are spending an increasing amount of time on online networking sites, e-games, texting, and other social media ( Twenge and Campbell, 2019 ). In fact, some authors (e.g., Dhir et al., 2018 ; Tateno et al., 2019 ) have suggested that social media has altered the forms of group interaction and its users' individual and collective behavior around the world.

Consequently, there are increased concerns regarding the possible negative impacts associated with social media usage addiction ( Swar and Hameed, 2017 ; Kircaburun et al., 2020 ), particularly on psychological well-being ( Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ). Smartphones sometimes distract their users from relationships and social interaction ( Chotpitayasunondh and Douglas, 2016 ; Li et al., 2020a ), and several authors have stressed that the excessive use of social media may lead to smartphone addiction ( Swar and Hameed, 2017 ; Leong et al., 2019 ), primarily because of the fear of missing out ( Reer et al., 2019 ; Roberts and David, 2020 ). Social media usage has been associated with anxiety, loneliness, and depression ( Dhir et al., 2018 ; Reer et al., 2019 ), social isolation ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ), and “phubbing,” which refers to the extent to which an individual uses, or is distracted by, their smartphone during face-to-face communication with others ( Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ).

However, social media use also contributes to building a sense of connectedness with relevant others ( Twenge and Campbell, 2019 ), which may reduce social isolation. Indeed, social media provides several ways to interact both with close ties, such as family, friends, and relatives, and weak ties, including coworkers, acquaintances, and strangers ( Chen and Li, 2017 ), and plays a key role among people of all ages as they exploit their sense of belonging in different communities ( Roberts and David, 2020 ). Consequently, despite the fears regarding the possible negative impacts of social media usage on well-being, there is also an increasing number of studies highlighting social media as a new communication channel ( Twenge and Campbell, 2019 ; Barbosa et al., 2020 ), stressing that it can play a crucial role in developing one's presence, identity, and reputation, thus facilitating social interaction, forming and maintaining relationships, and sharing ideas ( Carlson et al., 2016 ), which consequently may be significantly correlated to social support ( Chen and Li, 2017 ; Holliman et al., 2021 ). Interestingly, recent studies (e.g., David et al., 2018 ; Bano et al., 2019 ; Barbosa et al., 2020 ) have suggested that the impact of smartphone usage on psychological well-being depends on the time spent on each type of application and the activities that users engage in.

Hence, the literature provides contradictory cues regarding the impacts of social media on users' well-being, highlighting both the possible negative impacts and the social enhancement it can potentially provide. In line with views on the need to further investigate social media usage ( Karikari et al., 2017 ), particularly regarding its societal implications ( Jiao et al., 2017 ), this paper argues that there is an urgent need to further understand the impact of the time spent on social media on users' psychological well-being, namely by considering other variables that mediate and further explain this effect.

One of the relevant perspectives worth considering is that provided by social capital theory, which is adopted in this paper. Social capital theory has previously been used to study how social media usage affects psychological well-being (e.g., Bano et al., 2019 ). However, extant literature has so far presented only partial models of associations that, although statistically acceptable and contributing to the understanding of the scope of social networks, do not provide as comprehensive a vision of the phenomenon as that proposed within this paper. Furthermore, the contradictory views, suggesting both negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Van Den Eijnden et al., 2016 ; Jiao et al., 2017 ; Whaite et al., 2018 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) and positive impacts ( Carlson et al., 2016 ; Chen and Li, 2017 ; Twenge and Campbell, 2019 ) of social media on psychological well-being, have not been adequately explored.

Given this research gap, this paper's main objective is to shed light on the effect of social media use on psychological well-being. As explained in detail in the next section, this paper explores the mediating effect of bonding and bridging social capital. To provide a broad view of the phenomenon, it also considers several variables highlighted in the literature as affecting the relationship between social media usage and psychological well-being, namely smartphone addiction, social isolation, and phubbing. The paper utilizes a quantitative study conducted in Mexico, comprising 940 social media users, and uses structural equation modeling (SEM) to test a set of research hypotheses.

This article provides several contributions. First, it adds to existing literature regarding the effect of social media use on psychological well-being and explores the contradictory indications provided by different approaches. Second, it proposes a conceptual model that integrates complementary perspectives on the direct and indirect effects of social media use. Third, it offers empirical evidence and robust statistical analysis that demonstrates that both positive and negative effects coexist, helping resolve the inconsistencies found so far in the literature. Finally, this paper provides insights on how to help reduce the potential negative effects of social media use, as it demonstrates that, through bridging and bonding social capital, social media usage positively impacts psychological well-being. Overall, the article offers valuable insights for academics, practitioners, and society in general.

The remainder of this paper is organized as follows. Section Literature Review presents a literature review focusing on the factors that explain the impact of social media usage on psychological well-being. Based on the literature review, a set of hypotheses are defined, resulting in the proposed conceptual model, which includes both the direct and indirect effects of social media usage on psychological well-being. Section Research Methodology explains the methodological procedures of the research, followed by the presentation and discussion of the study's results in section Results. Section Discussion is dedicated to the conclusions and includes implications, limitations, and suggestions for future research.

Literature Review

Putnam (1995 , p. 664–665) defined social capital as “features of social life – networks, norms, and trust – that enable participants to act together more effectively to pursue shared objectives.” Li and Chen (2014 , p. 117) further explained that social capital encompasses “resources embedded in one's social network, which can be assessed and used for instrumental or expressive returns such as mutual support, reciprocity, and cooperation.”

Putnam (1995 , 2000) conceptualized social capital as comprising two dimensions, bridging and bonding, considering the different norms and networks in which they occur. Bridging social capital refers to the inclusive nature of social interaction and occurs when individuals from different origins establish connections through social networks. Hence, bridging social capital is typically provided by heterogeneous weak ties ( Li and Chen, 2014 ). This dimension widens individual social horizons and perspectives and provides extended access to resources and information. Bonding social capital refers to the social and emotional support each individual receives from his or her social networks, particularly from close ties (e.g., family and friends).

Overall, social capital is expected to be positively associated with psychological well-being ( Bano et al., 2019 ). Indeed, Williams (2006) stressed that interaction generates affective connections, resulting in positive impacts, such as emotional support. The following sub-sections use the lens of social capital theory to explore further the relationship between the use of social media and psychological well-being.

Social Media Use, Social Capital, and Psychological Well-Being

The effects of social media usage on social capital have gained increasing scholarly attention, and recent studies have highlighted a positive relationship between social media use and social capital ( Brown and Michinov, 2019 ; Tefertiller et al., 2020 ). Li and Chen (2014) hypothesized that the intensity of Facebook use by Chinese international students in the United States was positively related to social capital forms. A longitudinal survey based on the quota sampling approach illustrated the positive effects of social media use on the two social capital dimensions ( Chen and Li, 2017 ). Abbas and Mesch (2018) argued that, as Facebook usage increases, it will also increase users' social capital. Karikari et al. (2017) also found positive effects of social media use on social capital. Similarly, Pang (2018) studied Chinese students residing in Germany and found positive effects of social networking sites' use on social capital, which, in turn, was positively associated with psychological well-being. Bano et al. (2019) analyzed the 266 students' data and found positive effects of WhatsApp use on social capital forms and the positive effect of social capital on psychological well-being, emphasizing the role of social integration in mediating this positive effect.

Kim and Kim (2017) stressed the importance of having a heterogeneous network of contacts, which ultimately enhances the potential social capital. Overall, the manifest and social relations between people from close social circles (bonding social capital) and from distant social circles (bridging social capital) are strengthened when they promote communication, social support, and the sharing of interests, knowledge, and skills, which are shared with other members. This is linked to positive effects on interactions, such as acceptance, trust, and reciprocity, which are related to the individuals' health and psychological well-being ( Bekalu et al., 2019 ), including when social media helps to maintain social capital between social circles that exist outside of virtual communities ( Ellison et al., 2007 ).

Grounded on the above literature, this study proposes the following hypotheses:

H1a: Social media use is positively associated with bonding social capital.

H1b: Bonding social capital is positively associated with psychological well-being.

H2a: Social media use is positively associated with bridging social capital.

H2b: Bridging social capital is positively associated with psychological well-being.

Social Media Use, Social Isolation, and Psychological Well-Being

Social isolation is defined as “a deficit of personal relationships or being excluded from social networks” ( Choi and Noh, 2019 , p. 4). The state that occurs when an individual lacks true engagement with others, a sense of social belonging, and a satisfying relationship is related to increased mortality and morbidity ( Primack et al., 2017 ). Those who experience social isolation are deprived of social relationships and lack contact with others or involvement in social activities ( Schinka et al., 2012 ). Social media usage has been associated with anxiety, loneliness, and depression ( Dhir et al., 2018 ; Reer et al., 2019 ), and social isolation ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ). However, some recent studies have argued that social media use decreases social isolation ( Primack et al., 2017 ; Meshi et al., 2020 ). Indeed, the increased use of social media platforms such as Facebook, WhatsApp, Instagram, and Twitter, among others, may provide opportunities for decreasing social isolation. For instance, the improved interpersonal connectivity achieved via videos and images on social media helps users evidence intimacy, attenuating social isolation ( Whaite et al., 2018 ).

Chappell and Badger (1989) stated that social isolation leads to decreased psychological well-being, while Choi and Noh (2019) concluded that greater social isolation is linked to increased suicide risk. Schinka et al. (2012) further argued that, when individuals experience social isolation from siblings, friends, family, or society, their psychological well-being tends to decrease. Thus, based on the literature cited above, this study proposes the following hypotheses:

H3a: Social media use is significantly associated with social isolation.

H3b: Social isolation is negatively associated with psychological well-being.

Social Media Use, Smartphone Addiction, Phubbing, and Psychological Well-Being

Smartphone addiction refers to “an individuals' excessive use of a smartphone and its negative effects on his/her life as a result of his/her inability to control his behavior” ( Gökçearslan et al., 2018 , p. 48). Regardless of its form, smartphone addiction results in social, medical, and psychological harm to people by limiting their ability to make their own choices ( Chotpitayasunondh and Douglas, 2016 ). The rapid advancement of information and communication technologies has led to the concept of social media, e-games, and also to smartphone addiction ( Chatterjee, 2020 ). The excessive use of smartphones for social media use, entertainment (watching videos, listening to music), and playing e-games is more common amongst people addicted to smartphones ( Jeong et al., 2016 ). In fact, previous studies have evidenced the relationship between social use and smartphone addiction ( Salehan and Negahban, 2013 ; Jeong et al., 2016 ; Swar and Hameed, 2017 ). In line with this, the following hypotheses are proposed:

H4a: Social media use is positively associated with smartphone addiction.

H4b: Smartphone addiction is negatively associated with psychological well-being.

While smartphones are bringing individuals closer, they are also, to some extent, pulling people apart ( Tonacci et al., 2019 ). For instance, they can lead to individuals ignoring others with whom they have close ties or physical interactions; this situation normally occurs due to extreme smartphone use (i.e., at the dinner table, in meetings, at get-togethers and parties, and in other daily activities). This act of ignoring others is called phubbing and is considered a common phenomenon in communication activities ( Guazzini et al., 2019 ; Chatterjee, 2020 ). Phubbing is also referred to as an act of snubbing others ( Chatterjee, 2020 ). This term was initially used in May 2012 by an Australian advertising agency to describe the “growing phenomenon of individuals ignoring their families and friends who were called phubbee (a person who is a recipients of phubbing behavior) victim of phubber (a person who start phubbing her or his companion)” ( Chotpitayasunondh and Douglas, 2018 ). Smartphone addiction has been found to be a determinant of phubbing ( Kim et al., 2018 ). Other recent studies have also evidenced the association between smartphones and phubbing ( Chotpitayasunondh and Douglas, 2016 ; Guazzini et al., 2019 ; Tonacci et al., 2019 ; Chatterjee, 2020 ). Vallespín et al. (2017 ) argued that phubbing behavior has a negative influence on psychological well-being and satisfaction. Furthermore, smartphone addiction is considered responsible for the development of new technologies. It may also negatively influence individual's psychological proximity ( Chatterjee, 2020 ). Therefore, based on the above discussion and calls for the association between phubbing and psychological well-being to be further explored, this study proposes the following hypotheses:

H5: Smartphone addiction is positively associated with phubbing.

H6: Phubbing is negatively associated with psychological well-being.

Indirect Relationship Between Social Media Use and Psychological Well-Being

Beyond the direct hypotheses proposed above, this study investigates the indirect effects of social media use on psychological well-being mediated by social capital forms, social isolation, and phubbing. As described above, most prior studies have focused on the direct influence of social media use on social capital forms, social isolation, smartphone addiction, and phubbing, as well as the direct impact of social capital forms, social isolation, smartphone addiction, and phubbing on psychological well-being. Very few studies, however, have focused on and evidenced the mediating role of social capital forms, social isolation, smartphone addiction, and phubbing derived from social media use in improving psychological well-being ( Chen and Li, 2017 ; Pang, 2018 ; Bano et al., 2019 ; Choi and Noh, 2019 ). Moreover, little is known about smartphone addiction's mediating role between social media use and psychological well-being. Therefore, this study aims to fill this gap in the existing literature by investigating the mediation of social capital forms, social isolation, and smartphone addiction. Further, examining the mediating influence will contribute to a more comprehensive understanding of social media use on psychological well-being via the mediating associations of smartphone addiction and psychological factors. Therefore, based on the above, we propose the following hypotheses (the conceptual model is presented in Figure 1 ):

H7: (a) Bonding social capital; (b) bridging social capital; (c) social isolation; and (d) smartphone addiction mediate the relationship between social media use and psychological well-being.

Figure 1 . Conceptual model.

Research Methodology

Sample procedure and online survey.

This study randomly selected students from universities in Mexico. We chose University students for the following reasons. First, students are considered the most appropriate sample for e-commerce studies, particularly in the social media context ( Oghazi et al., 2018 ; Shi et al., 2018 ). Second, University students are considered to be frequent users and addicted to smartphones ( Mou et al., 2017 ; Stouthuysen et al., 2018 ). Third, this study ensured that respondents were experienced, well-educated, and possessed sufficient knowledge of the drawbacks of social media and the extreme use of smartphones. A total sample size of 940 University students was ultimately achieved from the 1,500 students contacted, using a convenience random sampling approach, due both to the COVID-19 pandemic and budget and time constraints. Additionally, in order to test the model, a quantitative empirical study was conducted, using an online survey method to collect data. This study used a web-based survey distributed via social media platforms for two reasons: the COVID-19 pandemic; and to reach a large number of respondents ( Qalati et al., 2021 ). Furthermore, online surveys are considered a powerful and authenticated tool for new research ( Fan et al., 2021 ), while also representing a fast, simple, and less costly approach to collecting data ( Dutot and Bergeron, 2016 ).

Data Collection Procedures and Respondent's Information

Data were collected by disseminating a link to the survey by e-mail and social network sites. Before presenting the closed-ended questionnaire, respondents were assured that their participation would remain voluntary, confidential, and anonymous. Data collection occurred from July 2020 to December 2020 (during the pandemic). It should be noted that, because data were collected during the pandemic, this may have had an influence on the results of the study. The reason for choosing a six-month lag time was to mitigate common method bias (CMB) ( Li et al., 2020b ). In the present study, 1,500 students were contacted via University e-mail and social applications (Facebook, WhatsApp, and Instagram). We sent a reminder every month for 6 months (a total of six reminders), resulting in 940 valid responses. Thus, 940 (62.6% response rate) responses were used for hypotheses testing.

Table 1 reveals that, of the 940 participants, three-quarters were female (76.4%, n = 719) and nearly one-quarter (23.6%, n = 221) were male. Nearly half of the participants (48.8%, n = 459) were aged between 26 and 35 years, followed by 36 to 35 years (21.9%, n = 206), <26 (20.3%, n = 191), and over 45 (8.9%, n = 84). Approximately two-thirds (65%, n = 611) had a bachelor's degree or above, while one-third had up to 12 years of education. Regarding the daily frequency of using the Internet, nearly half (48.6%, n = 457) of the respondents reported between 5 and 8 h a day, and over one-quarter (27.2%) 9–12 h a day. Regarding the social media platforms used, over 38.5 and 39.6% reported Facebook and WhatsApp, respectively. Of the 940 respondents, only 22.1% reported Instagram (12.8%) and Twitter (9.2%). It should be noted, however, that the sample is predominantly female and well-educated.

Table 1 . Respondents' characteristics.

Measurement Items

The study used five-point Likert scales (1 = “strongly disagree;” 5 = “strongly agree”) to record responses.

Social Media Use

Social media use was assessed using four items adapted from Karikari et al. (2017) . Sample items include “Social media is part of my everyday activity,” “Social media has become part of my daily life,” “I would be sorry if social media shut down,” and “I feel out of touch, when I have not logged onto social media for a while.” The adapted items had robust reliability and validity (CA = 783, CR = 0.857, AVE = 0.600).

Social Capital

Social capital was measured using a total of eight items, representing bonding social capital (four items) and bridging social capital (four items) adapted from Chan (2015) . Sample construct items include: bonging social capital (“I am willing to spend time to support general community activities,” “I interact with people who are quite different from me”) and bridging social capital (“My social media community is a good place to be,” “Interacting with people on social media makes me want to try new things”). The adapted items had robust reliability and validity [bonding social capital (CA = 0.785, CR = 0.861, AVE = 0.608) and bridging social capital (CA = 0.834, CR = 0.883, AVE = 0.601)].

Social Isolation

Social isolation was assessed using three items from Choi and Noh (2019) . Sample items include “I do not have anyone to play with,” “I feel alone from people,” and “I have no one I can trust.” This adapted scale had substantial reliability and validity (CA = 0.890, CR = 0.928, AVE = 0.811).

Smartphone Addiction

Smartphone addiction was assessed using five items taken from Salehan and Negahban (2013) . Sample items include “I am always preoccupied with my mobile,” “Using my mobile phone keeps me relaxed,” and “I am not able to control myself from frequent use of mobile phones.” Again, these adapted items showed substantial reliability and validity (CA = 903, CR = 0.928, AVE = 0.809).

Phubbing was assessed using four items from Chotpitayasunondh and Douglas (2018) . Sample items include: “I have conflicts with others because I am using my phone” and “I would rather pay attention to my phone than talk to others.” This construct also demonstrated significant reliability and validity (CA = 770, CR = 0.894, AVE = 0.809).

Psychological Well-Being

Psychological well-being was assessed using five items from Jiao et al. (2017) . Sample items include “I lead a purposeful and meaningful life with the help of others,” “My social relationships are supportive and rewarding in social media,” and “I am engaged and interested in my daily on social media.” This study evidenced that this adapted scale had substantial reliability and validity (CA = 0.886, CR = 0.917, AVE = 0.688).

Data Analysis

Based on the complexity of the association between the proposed construct and the widespread use and acceptance of SmartPLS 3.0 in several fields ( Hair et al., 2019 ), we utilized SEM, using SmartPLS 3.0, to examine the relationships between constructs. Structural equation modeling is a multivariate statistical analysis technique that is used to investigate relationships. Further, it is a combination of factor and multivariate regression analysis, and is employed to explore the relationship between observed and latent constructs.

SmartPLS 3.0 “is a more comprehensive software program with an intuitive graphical user interface to run partial least square SEM analysis, certainly has had a massive impact” ( Sarstedt and Cheah, 2019 ). According to Ringle et al. (2015) , this commercial software offers a wide range of algorithmic and modeling options, improved usability, and user-friendly and professional support. Furthermore, Sarstedt and Cheah (2019) suggested that structural equation models enable the specification of complex interrelationships between observed and latent constructs. Hair et al. (2019) argued that, in recent years, the number of articles published using partial least squares SEM has increased significantly in contrast to covariance-based SEM. In addition, partial least squares SEM using SmartPLS is more appealing for several scholars as it enables them to predict more complex models with several variables, indicator constructs, and structural paths, instead of imposing distributional assumptions on the data ( Hair et al., 2019 ). Therefore, this study utilized the partial least squares SEM approach using SmartPLS 3.0.

Common Method Bias (CMB) Test

This study used the Kaiser–Meyer–Olkin (KMO) test to measure the sampling adequacy and ensure data suitability. The KMO test result was 0.874, which is greater than an acceptable threshold of 0.50 ( Ali Qalati et al., 2021 ; Shrestha, 2021 ), and hence considered suitable for explanatory factor analysis. Moreover, Bartlett's test results demonstrated a significance level of 0.001, which is considered good as it is below the accepted threshold of 0.05.

The term CMB is associated with Campbell and Fiske (1959) , who highlighted the importance of CMB and identified that a portion of variance in the research may be due to the methods employed. It occurs when all scales of the study are measured at the same time using a single questionnaire survey ( Podsakoff and Organ, 1986 ); subsequently, estimates of the relationship among the variables might be distorted by the impacts of CMB. It is considered a serious issue that has a potential to “jeopardize” the validity of the study findings ( Tehseen et al., 2017 ). There are several reasons for CMB: (1) it mainly occurs due to response “tendencies that raters can apply uniformity across the measures;” and (2) it also occurs due to similarities in the wording and structure of the survey items that produce similar results ( Jordan and Troth, 2019 ). Harman's single factor test and a full collinearity approach were employed to ensure that the data was free from CMB ( Tehseen et al., 2017 ; Jordan and Troth, 2019 ; Ali Qalati et al., 2021 ). Harman's single factor test showed a single factor explained only 22.8% of the total variance, which is far below the 50.0% acceptable threshold ( Podsakoff et al., 2003 ).

Additionally, the variance inflation factor (VIF) was used, which is a measure of the amount of multicollinearity in a set of multiple regression constructs and also considered a way of detecting CMB ( Hair et al., 2019 ). Hair et al. (2019) suggested that the acceptable threshold for the VIF is 3.0; as the computed VIFs for the present study ranged from 1.189 to 1.626, CMB is not a key concern (see Table 2 ). Bagozzi et al. (1991) suggested a correlation-matrix procedure to detect CMB. Common method bias is evident if correlation among the principle constructs is >0.9 ( Tehseen et al., 2020 ); however, no values >0.9 were found in this study (see section Assessment of Measurement Model). This study used a two-step approach to evaluate the measurement model and the structural model.

Table 2 . Common method bias (full collinearity VIF).

Assessment of Measurement Model

Before conducting the SEM analysis, the measurement model was assessed to examine individual item reliability, internal consistency, and convergent and discriminant validity. Table 3 exhibits the values of outer loading used to measure an individual item's reliability ( Hair et al., 2012 ). Hair et al. (2017) proposed that the value for each outer loading should be ≥0.7; following this principle, two items of phubbing (PHUB3—I get irritated if others ask me to get off my phone and talk to them; PHUB4—I use my phone even though I know it irritated others) were removed from the analysis Hair et al. (2019) . According to Nunnally (1978) , Cronbach's alpha values should exceed 0.7. The threshold values of constructs in this study ranged from 0.77 to 0.903. Regarding internal consistency, Bagozzi and Yi (1988) suggested that composite reliability (CR) should be ≥0.7. The coefficient value for CR in this study was between 0.857 and 0.928. Regarding convergent validity, Fornell and Larcker (1981) suggested that the average variance extracted (AVE) should be ≥0.5. Average variance extracted values in this study were between 0.60 and 0.811. Finally, regarding discriminant validity, according to Fornell and Larcker (1981) , the square root of the AVE for each construct should exceed the inter-correlations of the construct with other model constructs. That was the case in this study, as shown in Table 4 .

Table 3 . Study measures, factor loading, and the constructs' reliability and convergent validity.

Table 4 . Discriminant validity and correlation.

Hence, by analyzing the results of the measurement model, it can be concluded that the data are adequate for structural equation estimation.

Assessment of the Structural Model

This study used the PLS algorithm and a bootstrapping technique with 5,000 bootstraps as proposed by Hair et al. (2019) to generate the path coefficient values and their level of significance. The coefficient of determination ( R 2 ) is an important measure to assess the structural model and its explanatory power ( Henseler et al., 2009 ; Hair et al., 2019 ). Table 5 and Figure 2 reveal that the R 2 value in the present study was 0.451 for psychological well-being, which means that 45.1% of changes in psychological well-being occurred due to social media use, social capital forms (i.e., bonding and bridging), social isolation, smartphone addiction, and phubbing. Cohen (1998) proposed that R 2 values of 0.60, 0.33, and 0.19 are considered substantial, moderate, and weak. Following Cohen's (1998) threshold values, this research demonstrates a moderate predicting power for psychological well-being among Mexican respondents ( Table 6 ).

Table 5 . Summary of path coefficients and hypothesis testing.

Figure 2 . Structural model.

Table 6 . Strength of the model (Predictive relevance, coefficient of determination, and model fit indices).

Apart from the R 2 measure, the present study also used cross-validated redundancy measures, or effect sizes ( q 2 ), to assess the proposed model and validate the results ( Ringle et al., 2012 ). Hair et al. (2019) suggested that a model exhibiting an effect size q 2 > 0 has predictive relevance ( Table 6 ). This study's results evidenced that it has a 0.15 <0.29 <0.35 (medium) predictive relevance, as 0.02, 0.15, and 0.35 are considered small, medium, and large, respectively ( Cohen, 1998 ). Regarding the goodness-of-fit indices, Hair et al. (2019) suggested the standardized root mean square residual (SRMR) to evaluate the goodness of fit. Standardized root mean square is an absolute measure of fit: a value of zero indicates perfect fit and a value <0.08 is considered good fit ( Hair et al., 2019 ). This study exhibits an adequate model fitness level with an SRMR value of 0.063 ( Table 6 ).

Table 5 reveals that all hypotheses of the study were accepted base on the criterion ( p -value < 0.05). H1a (β = 0.332, t = 10.283, p = 0.001) was confirmed, with the second most robust positive and significant relationship (between social media use and bonding social capital). In addition, this study evidenced a positive and significant relationship between bonding social capital and psychological well-being (β = 0.127, t = 4.077, p = 0.001); therefore, H1b was accepted. Regarding social media use and bridging social capital, the present study found the most robust positive and significant impact (β = 0.439, t = 15.543, p = 0.001); therefore, H2a was accepted. The study also evidenced a positive and significant association between bridging social capital and psychological well-being (β = 0.561, t = 20.953, p = 0.001); thus, H2b was accepted. The present study evidenced a significant effect of social media use on social isolation (β = 0.145, t = 4.985, p = 0.001); thus, H3a was accepted. In addition, this study accepted H3b (β = −0.051, t = 2.01, p = 0.044). Furthermore, this study evidenced a positive and significant effect of social media use on smartphone addiction (β = 0.223, t = 6.241, p = 0.001); therefore, H4a was accepted. Furthermore, the present study found that smartphone addiction has a negative significant influence on psychological well-being (β = −0.068, t = 2.387, p = 0.017); therefore, H4b was accepted. Regarding the relationship between smartphone addiction and phubbing, this study found a positive and significant effect of smartphone addiction on phubbing (β = 0.244, t = 7.555, p = 0.001); therefore, H5 was accepted. Furthermore, the present research evidenced a positive and significant influence of phubbing on psychological well-being (β = 0.137, t = 4.938, p = 0.001); therefore, H6 was accepted. Finally, the study provides interesting findings on the indirect effect of social media use on psychological well-being ( t -value > 1.96 and p -value < 0.05); therefore, H7a–d were accepted.

Furthermore, to test the mediating analysis, Preacher and Hayes's (2008) approach was used. The key characteristic of an indirect relationship is that it involves a third construct, which plays a mediating role in the relationship between the independent and dependent constructs. Logically, the effect of A (independent construct) on C (the dependent construct) is mediated by B (a third variable). Preacher and Hayes (2008) suggested the following: B is a construct acting as a mediator if A significantly influences B, A significantly accounts for variability in C, B significantly influences C when controlling for A, and the influence of A on C decreases significantly when B is added simultaneously with A as a predictor of C. According to Matthews et al. (2018) , if the indirect effect is significant while the direct insignificant, full mediation has occurred, while if both direct and indirect effects are substantial, partial mediation has occurred. This study evidenced that there is partial mediation in the proposed construct ( Table 5 ). Following Preacher and Hayes (2008) this study evidenced that there is partial mediation in the proposed construct, because the relationship between independent variable (social media use) and dependent variable (psychological well-being) is significant ( p -value < 0.05) and indirect effect among them after introducing mediator (bonding social capital, bridging social capital, social isolation, and smartphone addiction) is also significant ( p -value < 0.05), therefore it is evidenced that when there is a significant effect both direct and indirect it's called partial mediation.

The present study reveals that the social and psychological impacts of social media use among University students is becoming more complex as there is continuing advancement in technology, offering a range of affordable interaction opportunities. Based on the 940 valid responses collected, all the hypotheses were accepted ( p < 0.05).

H1a finding suggests that social media use is a significant influencing factor of bonding social capital. This implies that, during a pandemic, social media use enables students to continue their close relationships with family members, friends, and those with whom they have close ties. This finding is in line with prior work of Chan (2015) and Ellison et al. (2007) , who evidenced that social bonding capital is predicted by Facebook use and having a mobile phone. H1b findings suggest that, when individuals believe that social communication can help overcome obstacles to interaction and encourage more virtual self-disclosure, social media use can improve trust and promote the establishment of social associations, thereby enhancing well-being. These findings are in line with those of Gong et al. (2021) , who also witnessed the significant effect of bonding social capital on immigrants' psychological well-being, subsequently calling for the further evidence to confirm the proposed relationship.

The findings of the present study related to H2a suggest that students are more likely to use social media platforms to receive more emotional support, increase their ability to mobilize others, and to build social networks, which leads to social belongingness. Furthermore, the findings suggest that social media platforms enable students to accumulate and maintain bridging social capital; further, online classes can benefit students who feel shy when participating in offline classes. This study supports the previous findings of Chan (2015) and Karikari et al. (2017) . Notably, the present study is not limited to a single social networking platform, taking instead a holistic view of social media. The H2b findings are consistent with those of Bano et al. (2019) , who also confirmed the link between bonding social capital and psychological well-being among University students using WhatsApp as social media platform, as well as those of Chen and Li (2017) .

The H3a findings suggest that, during the COVID-19 pandemic when most people around the world have had limited offline or face-to-face interaction and have used social media to connect with families, friends, and social communities, they have often been unable to connect with them. This is due to many individuals avoiding using social media because of fake news, financial constraints, and a lack of trust in social media; thus, the lack both of offline and online interaction, coupled with negative experiences on social media use, enhances the level of social isolation ( Hajek and König, 2021 ). These findings are consistent with those of Adnan and Anwar (2020) . The H3b suggests that higher levels of social isolation have a negative impact on psychological well-being. These result indicating that, consistent with Choi and Noh (2019) , social isolation is negatively and significantly related to psychological well-being.

The H4a results suggests that substantial use of social media use leads to an increase in smartphone addiction. These findings are in line with those of Jeong et al. (2016) , who stated that the excessive use of smartphones for social media, entertainment (watching videos, listening to music), and playing e-games was more likely to lead to smartphone addiction. These findings also confirm the previous work of Jeong et al. (2016) , Salehan and Negahban (2013) , and Swar and Hameed (2017) . The H4b results revealed that a single unit increase in smartphone addiction results in a 6.8% decrease in psychological well-being. These findings are in line with those of Tangmunkongvorakul et al. (2019) , who showed that students with higher levels of smartphone addiction had lower psychological well-being scores. These findings also support those of Shoukat (2019) , who showed that smartphone addiction inversely influences individuals' mental health.

This suggests that the greater the smartphone addiction, the greater the phubbing. The H5 findings are in line with those of Chatterjee (2020) , Chotpitayasunondh and Douglas (2016) , Guazzini et al. (2019) , and Tonacci et al. (2019) , who also evidenced a significant impact of smartphone addiction and phubbing. Similarly, Chotpitayasunondh and Douglas (2018) corroborated that smartphone addiction is the main predictor of phubbing behavior. However, these findings are inconsistent with those of Vallespín et al. (2017 ), who found a negative influence of phubbing.

The H6 results suggests that phubbing is one of the significant predictors of psychological well-being. Furthermore, these findings suggest that, when phubbers use a cellphone during interaction with someone, especially during the current pandemic, and they are connected with many family members, friends, and relatives; therefore, this kind of action gives them more satisfaction, which simultaneously results in increased relaxation and decreased depression ( Chotpitayasunondh and Douglas, 2018 ). These findings support those of Davey et al. (2018) , who evidenced that phubbing has a significant influence on adolescents and social health students in India.

The findings showed a significant and positive effect of social media use on psychological well-being both through bridging and bonding social capital. However, a significant and negative effect of social media use on psychological well-being through smartphone addiction and through social isolation was also found. Hence, this study provides evidence that could shed light on the contradictory contributions in the literature suggesting both positive (e.g., Chen and Li, 2017 ; Twenge and Campbell, 2019 ; Roberts and David, 2020 ) and negative (e.g., Chotpitayasunondh and Douglas, 2016 ; Jiao et al., 2017 ; Choi and Noh, 2019 ; Chatterjee, 2020 ) effects of social media use on psychological well-being. This study concludes that the overall impact is positive, despite some degree of negative indirect impact.

Theoretical Contributions

This study's findings contribute to the current literature, both by providing empirical evidence for the relationships suggested by extant literature and by demonstrating the relevance of adopting a more complex approach that considers, in particular, the indirect effect of social media on psychological well-being. As such, this study constitutes a basis for future research ( Van Den Eijnden et al., 2016 ; Whaite et al., 2018 ) aiming to understand the impacts of social media use and to find ways to reduce its possible negative impacts.

In line with Kim and Kim (2017) , who stressed the importance of heterogeneous social networks in improving social capital, this paper suggests that, to positively impact psychological well-being, social media usage should be associated both with strong and weak ties, as both are important in building social capital, and hence associated with its bonding and bridging facets. Interestingly, though, bridging capital was shown as having the greatest impact on psychological well-being. Thus, the importance of wider social horizons, the inclusion in different groups, and establishing new connections ( Putnam, 1995 , 2000 ) with heterogeneous weak ties ( Li and Chen, 2014 ) are highlighted in this paper.

Practical Contributions

These findings are significant for practitioners, particularly those interested in dealing with the possible negative impacts of social media use on psychological well-being. Although social media use is associated with factors that negatively impact psychological well-being, particularly smartphone addiction and social isolation, these negative impacts can be lessened if the connections with both strong and weak ties are facilitated and featured by social media. Indeed, social media platforms offer several features, from facilitating communication with family, friends, and acquaintances, to identifying and offering access to other people with shared interests. However, it is important to access heterogeneous weak ties ( Li and Chen, 2014 ) so that social media offers access to wider sources of information and new resources, hence enhancing bridging social capital.

Limitations and Directions for Future Studies

This study is not without limitations. For example, this study used a convenience sampling approach to reach to a large number of respondents. Further, this study was conducted in Mexico only, limiting the generalizability of the results; future research should therefore use a cross-cultural approach to investigate the impacts of social media use on psychological well-being and the mediating role of proposed constructs (e.g., bonding and bridging social capital, social isolation, and smartphone addiction). The sample distribution may also be regarded as a limitation of the study because respondents were mainly well-educated and female. Moreover, although Internet channels represent a particularly suitable way to approach social media users, the fact that this study adopted an online survey does not guarantee a representative sample of the population. Hence, extrapolating the results requires caution, and study replication is recommended, particularly with social media users from other countries and cultures. The present study was conducted in the context of mainly University students, primarily well-educated females, via an online survey on in Mexico; therefore, the findings represent a snapshot at a particular time. Notably, however, the effect of social media use is increasing due to COVID-19 around the globe and is volatile over time.

Two of the proposed hypotheses of this study, namely the expected negative impacts of social media use on social isolation and of phubbing on psychological well-being, should be further explored. One possible approach is to consider the type of connections (i.e., weak and strong ties) to explain further the impact of social media usage on social isolation. Apparently, the prevalence of weak ties, although facilitating bridging social capital, may have an adverse impact in terms of social isolation. Regarding phubbing, the fact that the findings point to a possible positive impact on psychological well-being should be carefully addressed, specifically by psychology theorists and scholars, in order to identify factors that may help further understand this phenomenon. Other suggestions for future research include using mixed-method approaches, as qualitative studies could help further validate the results and provide complementary perspectives on the relationships between the considered variables.

Data Availability Statement

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

Ethics Statement

The studies involving human participants were reviewed and approved by Jiangsu University. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

This study is supported by the National Statistics Research Project of China (2016LY96).

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.

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Keywords: smartphone addiction, social isolation, bonding social capital, bridging social capital, phubbing, social media use

Citation: Ostic D, Qalati SA, Barbosa B, Shah SMM, Galvan Vela E, Herzallah AM and Liu F (2021) Effects of Social Media Use on Psychological Well-Being: A Mediated Model. Front. Psychol. 12:678766. doi: 10.3389/fpsyg.2021.678766

Received: 10 March 2021; Accepted: 25 May 2021; Published: 21 June 2021.

Reviewed by:

Copyright © 2021 Ostic, Qalati, Barbosa, Shah, Galvan Vela, Herzallah and Liu. 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: Sikandar Ali Qalati, sidqalati@gmail.com ; 5103180243@stmail.ujs.edu.cn ; Esthela Galvan Vela, esthela.galvan@cetys.mx

† ORCID: Dragana Ostic orcid.org/0000-0002-0469-1342 Sikandar Ali Qalati orcid.org/0000-0001-7235-6098 Belem Barbosa orcid.org/0000-0002-4057-360X Esthela Galvan Vela orcid.org/0000-0002-8778-3989 Feng Liu orcid.org/0000-0001-9367-049X

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• Published: 01 July 2020

The effect of social media on well-being differs from adolescent to adolescent

• Ine Beyens   ORCID: orcid.org/0000-0001-7023-867X 1 ,
• J. Loes Pouwels   ORCID: orcid.org/0000-0002-9586-392X 1 ,
• Irene I. van Driel   ORCID: orcid.org/0000-0002-7810-9677 1 ,
• Loes Keijsers   ORCID: orcid.org/0000-0001-8580-6000 2 &
• Patti M. Valkenburg   ORCID: orcid.org/0000-0003-0477-8429 1  

Scientific Reports volume  10 , Article number:  10763 ( 2020 ) Cite this article

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The question whether social media use benefits or undermines adolescents’ well-being is an important societal concern. Previous empirical studies have mostly established across-the-board effects among (sub)populations of adolescents. As a result, it is still an open question whether the effects are unique for each individual adolescent. We sampled adolescents’ experiences six times per day for one week to quantify differences in their susceptibility to the effects of social media on their momentary affective well-being. Rigorous analyses of 2,155 real-time assessments showed that the association between social media use and affective well-being differs strongly across adolescents: While 44% did not feel better or worse after passive social media use, 46% felt better, and 10% felt worse. Our results imply that person-specific effects can no longer be ignored in research, as well as in prevention and intervention programs.

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Introduction.

Ever since the introduction of social media, such as Facebook and Instagram, researchers have been studying whether the use of such media may affect adolescents’ well-being. These studies have typically reported mixed findings, yielding either small negative, small positive, or no effects of the time spent using social media on different indicators of well-being, such as life satisfaction and depressive symptoms (for recent reviews, see for example 1 , 2 , 3 , 4 , 5 ). Most of these studies have focused on between-person associations, examining whether adolescents who use social media more (or less) often than their peers experience lower (or higher) levels of well-being than these peers. While such between-person studies are valuable in their own right, several scholars 6 , 7 have recently called for studies that investigate within-person associations to understand whether an increase in an adolescent’s social media use is associated with an increase or decrease in that adolescent’s well-being. The current study aims to respond to this call by investigating associations between social media use and well-being within single adolescents across multiple points in time 8 , 9 , 10 .

Person-specific effects

To our knowledge, four recent studies have investigated within-person associations of social media use with different indicators of adolescent well-being (i.e., life satisfaction, depression), again with mixed results 6 , 11 , 12 , 13 . Orben and colleagues 6 found a small negative reciprocal within-person association between the time spent using social media and life satisfaction. Likewise, Boers and colleagues 12 found a small within-person association between social media use and increased depressive symptoms. Finally, Coyne and colleagues 11 and Jensen and colleagues 13 did not find any evidence for within-person associations between social media use and depression.

Earlier studies that investigated within-person associations of social media use with indicators of well-being have all only reported average effect sizes. However, it is possible, or even plausible, that these average within-person effects may have been small and nonsignificant because they result from sizeable heterogeneity in adolescents’ susceptibility to the effects of social media use on well-being (see 14 , 15 ). After all, an average within-person effect size can be considered an aggregate of numerous individual within-person effect sizes that range from highly positive to highly negative.

Some within-person studies have sought to understand adolescents’ differential susceptibility to the effects of social media by investigating differences between subgroups. For instance, they have investigated the moderating role of sex to compare the effects of social media on boys versus girls 6 , 11 . However, such a group-differential approach, in which potential differences in susceptibility are conceptualized by group-level moderators (e.g., gender, age) does not provide insights into more fine-grained differences at the level of the single individual 16 . After all, while girls and boys each represent a homogenous group in terms of sex, they may each differ on a wide array of other factors.

As such, although worthwhile, the average within-person effects of social media on well-being obtained in previous studies may have been small or non-significant because they are diluted across a highly heterogeneous population (or sub-population) of adolescents 14 , 15 . In line with the proposition of media effects theories that each adolescent may have a unique susceptibility to the effects of social media 17 , a viable explanation for the small and inconsistent findings in earlier studies may be that the effect of social media differs from adolescent to adolescent. The aim of the current study is to investigate this hypothesis and to obtain a better understanding of adolescents’ unique susceptibility to the effects of social media on their affective well-being.

Social media and affective well-being

Within-person studies have provided important insights into the associations of social media use with cognitive well-being (e.g., life satisfaction 6 ), which refers to adolescents’ cognitive judgment of how satisfied they are with their life 18 . However, the associations of social media use with adolescents’ affective well-being (i.e., adolescents’ affective evaluations of their moods and emotions 18 ) are still unknown. In addition, while earlier within-person studies have focused on associations with trait-like conceptualizations of well-being 11 , 12 , 13 , that is, adolescents’ average well-being across specific time periods 18 , there is a lack of studies that focus on well-being as a momentary affective state. Therefore, we extend previous research by examining the association between adolescents’ social media use and their momentary affective well-being. Like earlier experience sampling (ESM) studies among adults 19 , 20 , we measured adolescents’ momentary affective well-being with a single item. Adolescents’ momentary affective well-being was defined as their current feelings of happiness, a commonly used question to measure well-being 21 , 22 , which has high convergent validity, as evidenced by the strong correlations with the presence of positive affect and absence of negative affect.

To assess adolescents’ momentary affective well-being (henceforth referred to as well-being), we conducted a week-long ESM study among 63 middle adolescents ages 14 and 15. Six times a day, adolescents were asked to complete a survey using their own mobile phone, covering 42 assessments per adolescent, assessing their affective well-being and social media use. In total, adolescents completed 2,155 assessments (83.2% average compliance).

We focused on middle adolescence, since this is the period in life characterized by most significant fluctuations in well-being 23 , 24 . Also, in comparison to early and late adolescents, middle adolescents are more sensitive to reactions from peers and have a strong tendency to compare themselves with others on social media and beyond. Because middle adolescents typically use different social media platforms, in a complementary way 25 , 26 , 27 , each adolescent reported on his/her use of the three social media platforms that s/he used most frequently out of the five most popular social media platforms among adolescents: WhatsApp, followed by Instagram, Snapchat, YouTube, and, finally, the chat function of games 28 . In addition to investigating the association between overall social media use and well-being (i.e., the summed use of adolescents’ three most frequently used platforms), we examined the unique associations of the two most popular platforms, WhatsApp and Instagram 28 .

Like previous studies on social media use and well-being, we distinguished between active social media use (i.e., “activities that facilitate direct exchanges with others” 29 ) and passive social media use (i.e., “consuming information without direct exchanges” 29 ). Within-person studies among young adults have shown that passive but not active social media use predicts decreases in well-being 29 . Therefore, we examined the unique associations of adolescents’ overall active and passive social media use with their well-being, as well as active and passive use of Instagram and WhatsApp, specifically. We investigated categorical associations, that is, whether adolescents would feel better or worse if they had actively or passively used social media. And we investigated dose–response associations to understand whether adolescents’ well-being would change as a function of the time they had spent actively or passively using social media.

The hypotheses and the design, sampling and analysis plan were preregistered prior to data collection and are available on the Open Science Framework, along with the code used in the analyses ( https://osf.io/nhks2 ). For details about the design of the study and analysis approach, see Methods.

In more than half of all assessments (68.17%), adolescents had used social media (i.e., one or more of their three favorite social media platforms), either in an active or passive way. Instagram (50.90%) and WhatsApp (53.52%) were used in half of all assessments. Passive use of social media (66.21% of all assessments) was more common than active use (50.86%), both on Instagram (48.48% vs. 20.79%) and WhatsApp (51.25% vs. 40.07%).

Strong positive between-person correlations were found between the duration of active and passive social media use (overall: r  = 0.69, p  < 0.001; Instagram: r  = 0.38, p  < 0.01; WhatsApp: r  = 0.85, p  < 0.001): Adolescents who had spent more time actively using social media than their peers, had also spent more time passively using social media than their peers. Likewise, strong positive within-person correlations were found between the duration of active and passive social media use (overall: r  = 0.63, p  < 0.001; Instagram: r  = 0.37, p  < 0.001; WhatsApp: r  = 0.57, p  < 0.001): The more time an adolescent had spent actively using social media at a certain moment, the more time s/he had also spent passively using social media at that moment.

Table 1 displays the average number of minutes that adolescents had spent using social media in the past hour at each assessment, and the zero-order between- and within-person correlations between the duration of social media use and well-being. At the between-person level, the duration of active and passive social media use was not associated with well-being: Adolescents who had spent more time actively or passively using social media than their peers did not report significantly higher or lower levels of well-being than their peers. At the within-person level, significant but weak positive correlations were found between the duration of active and passive overall social media use and well-being. This indicates that adolescents felt somewhat better at moments when they had spent more time actively or passively using social media (overall), compared to moments when they had spent less time actively or passively using social media. When looking at specific platforms, a positive correlation was only found for passive WhatsApp use, but not for active WhatsApp use, and not for active and passive Instagram use.

Average and person-specific effects

The within-person associations of social media use with well-being and differences in these associations were tested in a series of multilevel models. We ran separate models for overall social media use (i.e., active use and passive use of adolescents’ three favorite social media platforms, see Table 2 ), Instagram use (see Table 3 ), and WhatsApp use (see Table 4 ). In a first step we examined the average categorical associations for each of these three social media uses using fixed effects models (Models 1A, 3A, and 5A) to investigate whether, on average, adolescents would feel better or worse at moments when they had used social media compared to moments when they had not (i.e., categorical predictors: active use versus no active use, and passive use versus no passive use). In a second step, we examined heterogeneity in the within-person categorical associations by adding random slopes to the fixed effects models (Models 1B, 3B, and 5B). Next, we examined the average dose–response associations using fixed effects models (Models 2A, 4A, and 6A), to investigate whether, on average, adolescents would feel better or worse when they had spent more time using social media (i.e., continuous predictors: duration of active use and duration of passive use). Finally, we examined heterogeneity in the within-person dose–response associations by adding random slopes to the fixed effects models (Models 2B, 4B, and 6B).

Overall social media use.

The model with the categorical predictors (see Table 2 ; Model 1A) showed that, on average, there was no association between overall use and well-being: Adolescents’ well-being did not increase or decrease at moments when they had used social media, either in a passive or active way. However, evidence was found that the association of passive (but not active) social media use with well-being differed from adolescent to adolescent (Model 1B), with effect sizes ranging from − 0.24 to 0.68. For 44.26% of the adolescents the association was non-existent to small (− 0.10 <  r  < 0.10). However, for 45.90% of the adolescents there was a weak (0.10 <  r  < 0.20; 8.20%), moderate (0.20 <  r  < 0.30; 22.95%) or even strong positive ( r  ≥ 0.30; 14.75%) association between overall passive social media use and well-being, and for almost one in ten (9.84%) adolescents there was a weak (− 0.20 <  r  < − 0.10; 6.56%) or moderate negative (− 0.30 <  r  < − 0.20; 3.28%) association.

The model with continuous predictors (Model 2A) showed that, on average, there was a significant dose–response association for active use. At moments when adolescents had used social media, the time they spent actively (but not passively) using social media was positively associated with well-being: Adolescents felt better at moments when they had spent more time sending messages, posting, or sharing something on social media. The associations of the time spent actively and passively using social media with well-being did not differ across adolescents (Model 2B).

Instagram use

As shown in Model 3A in Table 3 , on average, there was a significant categorical association between passive (but not active) Instagram use and well-being: Adolescents experienced an increase in well-being at moments when they had passively used Instagram (i.e., viewing posts/stories of others). Adolescents did not experience an increase or decrease in well-being when they had actively used Instagram. The associations of passive and active Instagram use with well-being did not differ across adolescents (Model 3B).

On average, no significant dose–response association was found for Instagram use (Model 4A): At moments when adolescents had used Instagram, the time adolescents spent using Instagram (either actively or passively) was not associated with their well-being. However, evidence was found that the association of the time spent passively using Instagram differed from adolescent to adolescent (Model 4B), with effect sizes ranging from − 0.48 to 0.27. For most adolescents (73.91%) the association was non-existent to small (− 0.10 <  r  < 0.10), but for almost one in five adolescents (17.39%) there was a weak (0.10 <  r  < 0.20; 10.87%) or moderate (0.20 <  r  < 0.30; 6.52%) positive association, and for almost one in ten adolescents (8.70%) there was a weak (− 0.20 <  r  < − 0.10; 2.17%), moderate (− 0.30 <  r  < − 0.20; 4.35%), or strong ( r  ≤ − 0.30; 2.17%) negative association. Figure  1 illustrates these differences in the dose–response associations.

The dose–response association between passive Instagram use (in minutes per hour) and affective well-being for each individual adolescent (n = 46). Red lines represent significant negative within-person associations, green lines represent significant positive within-person associations, and gray lines represent non-significant within-person associations. A graph was created for each participant who had completed at least 10 assessments. A total of 13 participants were excluded because they had completed less than 10 assessments of passive Instagram use. In addition, one participant was excluded because no graph could be computed, since this participant's passive Instagram use was constant across assessments.

WhatsApp use

As shown in Model 5A in Table 4 , just as for Instagram, we found that, on average, there was a significant categorical association between passive (but not active) WhatsApp use and well-being: Adolescents reported that they felt better at moments when they had passively used WhatsApp (i.e., read WhatsApp messages). For active WhatsApp use, no significant association was found. Also, in line with the results for Instagram use, no differences were found regarding the associations of active and passive WhatsApp use (Model 5B).

In addition, a significant dose–response association was found for passive (but not active) use (Model 6A). At moments when adolescents had used WhatsApp, we found that, on average, the time adolescents spent passively using WhatsApp was positively associated with well-being: Adolescents felt better at moments when they had spent more time reading WhatsApp messages. The time spent actively using WhatsApp was not associated with well-being. No differences were found in the dose–response associations of active and passive WhatsApp use (Model 6B).

This preregistered study investigated adolescents’ unique susceptibility to the effects of social media. We found that the associations of passive (but not active) social media use with well-being differed substantially from adolescent to adolescent, with effect sizes ranging from moderately negative (− 0.24) to strongly positive (0.68). While 44.26% of adolescents did not feel better or worse if they had passively used social media, 45.90% felt better, and a small group felt worse (9.84%). In addition, for Instagram the majority of adolescents (73.91%) did not feel better or worse when they had spent more time viewing post or stories of others, whereas some felt better (17.39%), and others (8.70%) felt worse.

These findings have important implications for social media effects research, and media effects research more generally. For decades, researchers have argued that people differ in their susceptibility to the effects of media 17 , leading to numerous investigations of such differential susceptibility. These investigations have typically focused on moderators, based on variables such as sex, age, or personality. Yet, over the years, studies have shown that such moderators appear to have little power to explain how individuals differ in their susceptibility to media effects, probably because a group-differential approach does not account for the possibility that media users may differ across a range of factors, that are not captured by only one (or a few) investigated moderator variables.

By providing insights into each individual’s unique susceptibility, the findings of this study provide an explanation as to why, up until now, most media effects research has only found small effects. We found that the majority of adolescents do not experience any short-term changes in well-being related to their social media use. And if they do experience any changes, these are more often positive than negative. Because only small subsets of adolescents experience small to moderate changes in well-being, the true effects of social media reported in previous studies have probably been diluted across heterogeneous samples of individuals that differ in their susceptibility to media effects (also see 30 ). Several scholars have noted that overall effect sizes may mask more subtle individual differences 14 , 15 , which may explain why previous studies have typically reported small or no effects of social media on well-being or indicators of well-being 6 , 11 , 12 , 13 . The current study seems to confirm this assumption, by showing that while the overall effect sizes are small at best, the person-specific effect sizes vary considerably, from tiny and small to moderate and strong.

As called upon by other scholars 5 , 31 , we disentangled the associations of active and passive use of social media. Research among young adults found that passive (but not active) social media use is associated with lower levels of affective well-being 29 . In line with these findings, the current study shows that active and passive use yielded different associations with adolescents’ affective well-being. Interestingly though, in contrast to previous findings among adults, our study showed that, on average, passive use of Instagram and WhatsApp seemed to enhance rather than decrease adolescents’ well-being. This discrepancy in findings may be attributed to the fact that different mechanisms might be involved. Verduyn and colleagues 29 found that passive use of Facebook undermines adults’ well-being by enhancing envy, which may also explain the decreases in well-being found in our study among a small group of adolescents. Yet, adolescents who felt better by passively using Instagram and WhatsApp, might have felt so because they experienced enjoyment. After all, adolescents often seek positive content on social media, such as humorous posts or memes 32 . Also, research has shown that adolescents mainly receive positive feedback on social media 33 . Hence, their passive Instagram and WhatsApp use may involve the reading of positive feedback, which may explain the increases in well-being.

Overall, the time spent passively using WhatsApp improved adolescents’ well-being. This did not differ from adolescent to adolescent. However, the associations of the time spent passively using Instagram with well-being did differ from adolescent to adolescent. This discrepancy suggests that not all social media uses yield person-specific effects on well-being. A possible explanation may be that adolescents’ responses to WhatsApp are more homogenous than those to Instagram. WhatsApp is a more private platform, which is mostly used for one-to-one communication with friends and acquaintances 26 . Instagram, in contrast, is a more public platform, which allows its users to follow a diverse set of people, ranging from best friends to singers, actors, and influencers 28 , and to engage in intimate communication as well as self-presentation and social comparison. Such diverse uses could lead to more varied, or even opposing responses, such as envy versus inspiration.

Limitations and directions for future research

The current study extends our understanding of differential susceptibility to media effects, by revealing that the effect of social media use on well-being differs from adolescent to adolescent. The findings confirm our assumption that among the great majority of adolescents, social media use is unrelated to well-being, but that among a small subset, social media use is either related to decreases or increases in well-being. It must be noted, however, that participants in this study felt relatively happy, overall. Studies with more vulnerable samples, consisting of clinical samples or youth with lower social-emotional well-being may elicit different patterns of effects 27 . Also, the current study focused on affective well-being, operationalized as happiness. It is plausible that social media use relates differently with other types of well-being, such as cognitive well-being. An important next step is to identify which adolescents are particularly susceptible to experience declines in well-being. It is conceivable, for instance, that the few adolescents who feel worse when they use social media are the ones who receive negative feedback on social media 33 .

In addition, future ESM studies into the effects of social media should attempt to include one or more follow-up measures to improve our knowledge of the longer-term influence of social media use on affective well-being. While a week-long ESM is very common and applied in most earlier ESM studies 34 , a week is only a snapshot of adolescent development. Research is needed that investigates whether the associations of social media use with adolescents’ momentary affective well-being may cumulate into long-lasting consequences. Such investigations could help clarify whether adolescents who feel bad in the short term would experience more negative consequences in the long term, and whether adolescents who feel better would be more resistant to developing long-term negative consequences. And while most adolescents do not seem to experience any short-term increases or decreases in well-being, more research is needed to investigate whether these adolescents may experience a longer-term impact of social media.

While the use of different platforms may be differently associated with well-being, different types of use may also yield different effects. Although the current study distinguished between active and passive use of social media, future research should further differentiate between different activities. For instance, because passive use entails many different activities, from reading private messages (e.g., WhatsApp messages, direct messages on Instagram) to browsing a public feed (e.g., scrolling through posts on Instagram), research is needed that explores the unique effects of passive public use and passive private use. Research that seeks to explore the nuances in adolescents’ susceptibility as well as the nuances in their social media use may truly improve our understanding of the effects of social media use.

Participants

Participants were recruited via a secondary school in the south of the Netherlands. Our preregistered sampling plan set a target sample size of 100 adolescents. We invited adolescents from six classrooms to participate in the study. The final sample consisted of 63 adolescents (i.e., 42% consent rate, which is comparable to other ESM studies among adolescents; see, for instance 35 , 36 ). Informed consent was obtained from all participants and their parents. On average, participants were 15 years old ( M  = 15.12 years, SD  = 0.51) and 54% were girls. All participants self-identified as Dutch, and 41.3% were enrolled in the prevocational secondary education track, 25.4% in the intermediate general secondary education track, and 33.3% in the academic preparatory education track.

The study was approved by the Ethics Review Board of the Faculty of Social and Behavioral Sciences at the University of Amsterdam and was performed in accordance with the guidelines formulated by the Ethics Review Board. The study consisted of two phases: A baseline survey and a personalized week-long experience sampling (ESM) study. In phase 1, researchers visited the school during school hours. Researchers informed the participants of the objective and procedure of the study and assured them that their responses would be treated confidentially. Participants were asked to sign the consent form. Next, participants completed a 15-min baseline survey. The baseline survey included questions about demographics and assessed which social media each adolescent used most frequently, allowing to personalize the social media questions presented during the ESM study in phase 2. After completing the baseline survey, participants were provided detailed instructions about phase 2.

In phase 2, which took place two and a half weeks after the baseline survey, a 7-day ESM study was conducted, following the guidelines for ESM studies provided by van Roekel and colleagues 34 . Aiming for at least 30 assessments per participant and based on an average compliance rate of 70 to 80% reported in earlier ESM studies among adolescents 34 , we asked each participant to complete a total of 42 ESM surveys (i.e., six 2-min surveys per day). Participants completed the surveys using their own mobile phone, on which the ESM software application Ethica Data was installed during the instruction session with the researchers (phase 1). Each 2-min survey consisted of 22 questions, which assessed adolescents’ well-being and social media use. Two open-ended questions were added to the final survey of the day, which asked about adolescents’ most pleasant and most unpleasant events of the day.

The ESM sampling scheme was semi-random, to allow for randomization and avoid structural patterns in well-being, while taking into account that adolescents were not allowed to use their phone during school time. The Ethica Data app was programmed to generate six beep notifications per day at random time points within a fixed time interval that was tailored to the school’s schedule: before school time (1 beep), during school breaks (2 beeps), and after school time (3 beeps). During the weekend, the beeps were generated during the morning (1 beep), afternoon (3 beeps), and evening (2 beeps). To maximize compliance, a 30-min time window was provided to complete each survey. This time window was extended to one hour for the first survey (morning) and two hours for the final survey (evening) to account for travel time to school and time spent on evening activities. The average compliance rate was 83.2%. A total of 2,155 ESM assessments were collected: Participants completed an average of 34.83 surveys ( SD  = 4.91) on a total of 42 surveys, which is high compared to previous ESM studies among adolescents 34 .

The questions of the ESM study were personalized based on the responses to the baseline survey. During the ESM study, each participant reported on his/her use of three different social media platforms: WhatsApp and either Instagram, Snapchat, YouTube, and/or the chat function of games (i.e., the most popular social media platforms among adolescents 28 ). Questions about Instagram and WhatsApp use were only included if the participant had indicated in the baseline survey that s/he used these platforms at least once a week. If a participant had indicated that s/he used Instagram or WhatsApp (or both) less than once a week, s/he was asked to report on the use of Snapchat, YouTube, or the chat function of games, depending on what platform s/he used at least once a week. In addition to Instagram and WhatsApp, questions were asked about a third platform, that was selected based on how frequently the participant used Snapchat, YouTube, or the chat function of games (i.e., at least once a week). This resulted in five different combinations of three platforms: Instagram, WhatsApp, and Snapchat (47 participants); Instagram, WhatsApp, and YouTube (11 participants); Instagram, WhatsApp, and chatting via games (2 participants); WhatsApp, Snapchat, and YouTube (1 participant); and WhatsApp, YouTube, and chatting via games (2 participants).

Frequency of social media use

In the baseline survey, participants were asked to indicate how often they used and checked Instagram, WhatsApp, Snapchat, YouTube, and the chat function of games, using response options ranging from 1 ( never ) to 7 ( more than 12 times per day ). These platforms are the five most popular platforms among Dutch 14- and 15-year-olds 28 . Participants’ responses were used to select the three social media platforms that were assessed in the personalized ESM study.

Duration of social media use

In the ESM study, duration of active and passive social media use was measured by asking participants how much time in the past hour they had spent actively and passively using each of the three platforms that were included in the personalized ESM surveys. Response options ranged from 0 to 60 min , with 5-min intervals. To measure active Instagram use, participants indicated how much time in the past hour they had spent (a) “posting on your feed or sharing something in your story on Instagram” and (b) “sending direct messages/chatting on Instagram.” These two items were summed to create the variable duration of active Instagram use. Sum scores exceeding 60 min (only 0.52% of all assessments) were recoded to 60 min. To measure duration of passive Instagram use, participants indicated how much time in the past hour they had spent “viewing posts/stories of others on Instagram.” To measure the use of WhatsApp, Snapchat, YouTube and game-based chatting, we asked participants how much time they had spent “sending WhatsApp messages” (active use) and “reading WhatsApp messages” (passive use); “sending snaps/messages or sharing something in your story on Snapchat” (active use) and “viewing snaps/stories/messages from others on Snapchat” (passive use); “posting YouTube clips” (active use) and “watching YouTube clips” (passive use); “sending messages via the chat function of a game/games” (active use) and “reading messages via the chat function of a game/games” (passive use). Duration of active and passive overall social media use were created by summing the responses across the three social media platforms for active and passive use, respectively. Sum scores exceeding 60 min (2.13% of all assessments for active overall use; 2.90% for passive overall use) were recoded to 60 min. The duration variables were used to investigate whether the time spent actively or passively using social media was associated with well-being (dose–response associations).

Use/no use of social media

Based on the duration variables, we created six dummy variables, one for active and one for passive overall social media use, one for active and one for passive Instagram use, and one for active and one for passive WhatsApp use (0 =  no active use and 1 =  active use , and 0 =  no passive use and 1 =  passive use , respectively). These dummy variables were used to investigate whether the use of social media, irrespective of the duration of use, was associated with well-being (categorical associations).

Consistent with previous ESM studies 19 , 20 , we measured affective well-being using one item, asking “How happy do you feel right now?” at each assessment. Adolescents indicated their response to the question using a 7-point scale ranging from 1 ( not at all ) to 7 ( completely ), with 4 ( a little ) as the midpoint. Convergent validity of this item was established in a separate pilot ESM study among 30 adolescents conducted by the research team of the fourth author: The affective well-being item was strongly correlated with the presence of positive affect and absence of negative affect (assessed by a 10-item positive and negative affect schedule for children; PANAS-C) at both the between-person (positive affect: r  = 0.88, p < 0.001; negative affect: r  = − 0.62, p < 0.001) and within-person level (positive affect: r  = 0.74, p < 0.001; negative affect: r  = − 0.58, p < 0.001).

Statistical analyses

Before conducting the analyses, several validation checks were performed (see 34 ). First, we aimed to only include participants in the analyses who had completed more than 33% of all ESM assessments (i.e., at least 14 assessments). Next, we screened participants’ responses to the open questions for unserious responses (e.g., gross comments, jokes). And finally, we inspected time series plots for patterns in answering tendencies. Since all participants completed more than 33% of all ESM assessments, and no inappropriate responses or low-quality data patterns were detected, all participants were included in the analyses.

Following our preregistered analysis plan, we tested the proposed associations in a series of multilevel models. Before doing so, we tested the homoscedasticity and linearity assumptions for multilevel analyses 37 . Inspection of standardized residual plots indicated that the data met these assumptions (plots are available on OSF at  https://osf.io/nhks2 ). We specified separate models for overall social media use, use of Instagram, and use of WhatsApp. To investigate to what extent adolescents’ well-being would vary depending on whether they had actively or passively used social media/Instagram/WhatsApp or not during the past hour (categorical associations), we tested models including the dummy variables as predictors (active use versus no active use, and passive use versus no passive use; models 1, 3, and 5). To investigate whether, at moments when adolescents had used social media/Instagram/WhatsApp during the past hour, their well-being would vary depending on the duration of social media/Instagram/WhatsApp use (dose–response associations), we tested models including the duration variables as predictors (duration of active use and duration of passive use; models 2, 4, and 6). In order to avoid negative skew in the duration variables, we only included assessments during which adolescents had used social media in the past hour (overall, Instagram, or WhatsApp, respectively), either actively or passively. All models included well-being as outcome variable. Since multilevel analyses allow to include all available data for each individual, no missing data were imputed and no data points were excluded.

We used a model building approach that involved three steps. In the first step, we estimated an intercept-only model to assess the relative amount of between- and within-person variance in affective well-being. We estimated a three-level model in which repeated momentary assessments (level 1) were nested within adolescents (level 2), who, in turn, were nested within classrooms (level 3). However, because the between-classroom variance in affective well-being was small (i.e., 0.4% of the variance was explained by differences between classes), we proceeded with estimating two-level (instead of three-level) models, with repeated momentary assessments (level 1) nested within adolescents (level 2).

In the second step, we assessed the within-person associations of well-being with (a) overall active and passive social media use (i.e., the total of the three platforms), (b) active and passive use of Instagram, and (c) active and passive use of WhatsApp, by adding fixed effects to the model (Models 1A-6A). To facilitate the interpretation of the associations and control for the effects of time, a covariate was added that controlled for the n th assessment of the study week (instead of the n th assessment of the day, as preregistered). This so-called detrending is helpful to interpret within-person associations as correlated fluctuations beyond other changes in social media use and well-being 38 . In order to obtain within-person estimates, we person-mean centered all predictors 38 . Significance of the fixed effects was determined using the Wald test.

In the third and final step, we assessed heterogeneity in the within-person associations by adding random slopes to the models (Models 1B-6B). Significance of the random slopes was determined by comparing the fit of the fixed effects model with the fit of the random effects model, by performing the Satorra-Bentler scaled chi-square test 39 and by comparing the Bayesian information criterion (BIC 40 ) and Akaike information criterion (AIC 41 ) of the models. When the random effects model had a significantly better fit than the fixed effects model (i.e., pointing at significant heterogeneity), variance components were inspected to investigate whether heterogeneity existed in the association of either active or passive use. Next, when evidence was found for significant heterogeneity, we computed person-specific effect sizes, based on the random effect models, to investigate what percentages of adolescents experienced better well-being, worse well-being, and no changes in well-being. In line with Keijsers and colleagues 42 we only included participants who had completed at least 10 assessments. In addition, for the dose–response associations, we constructed graphical representations of the person-specific slopes, based on the person-specific effect sizes, using the xyplot function from the lattice package in R 43 .

Three improvements were made to our original preregistered plan. First, rather than estimating the models with multilevel modelling in R 43 , we ran the preregistered models in Mplus 44 . Mplus provides standardized estimates for the fixed effects models, which offers insight into the effect sizes. This allowed us to compare the relative strength of the associations of passive versus active use with well-being. Second, instead of using the maximum likelihood estimator, we used the maximum likelihood estimator with robust standard errors (MLR), which are robust to non-normality. Sensitivity tests, uploaded on OSF ( https://osf.io/nhks2 ), indicated that the results were almost identical across the two software packages and estimation approaches. Third, to improve the interpretation of the results and make the scales of the duration measures of social media use and well-being more comparable, we transformed the social media duration scores (0 to 60 min) into scales running from 0 to 6, so that an increase of 1 unit reflects 10 min of social media use. The model estimates were unaffected by this transformation.

Reporting summary

Further information on the research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The dataset generated and analysed during the current study is available in Figshare 45 . The preregistration of the design, sampling and analysis plan, and the analysis scripts used to analyse the data for this paper are available online on the Open Science Framework website ( https://osf.io/nhks2 ).

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Acknowledgements

This study was funded by the NWO Spinoza Prize and the Gravitation grant (NWO Grant 024.001.003; Consortium on Individual Development) awarded to P.M.V. by the Dutch Research Council (NWO). Additional funding was received from the VIDI grant (NWO VIDI Grant 452.17.011) awarded to L.K. by the Dutch Research Council (NWO). The authors would like to thank Savannah Boele (Tilburg University) for providing her pilot ESM results.

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I.B., J.L.P., I.I.v.D., L.K., and P.M.V. designed the study; I.B., J.L.P., and I.I.v.D. collected the data; I.B., J.L.P., and L.K. analyzed the data; and I.B., J.L.P., I.I.v.D., L.K., and P.M.V. contributed to writing and reviewing the manuscript.

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• Published: 22 September 2023

How social media usage affects psychological and subjective well-being: testing a moderated mediation model

• Chang’an Zhang 1 ,
• Lingjie Tang 1 &
• Zhifang Liu 2  

BMC Psychology volume  11 , Article number:  286 ( 2023 ) Cite this article

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A growing body of literature demonstrates that social media usage has witnessed a rapid increase in higher education and is almost ubiquitous among young people. The underlying mechanisms as to how social media usage by university students affects their well-being are unclear. Moreover, current research has produced conflicting evidence concerning the potential effects of social media on individuals' overall well-being with some reporting negative outcomes while others revealing beneficial results.

To address the research gap, the present research made an attempt to investigate the crucial role of social media in affecting students’ psychological (PWB) and subjective well-being (SWB) by testing the mediating role of self-esteem and online social support and the moderation effect of cyberbullying. The data in the study were obtained from a sample of 1,004 college students (483 females and 521 males, M age  = 23.78, SD  = 4.06) enrolled at 135 Chinese universities. AMOS 26.0 and SPSS 26.0 as well as the Process macro were utilized for analyzing data and testing the moderated mediation model.

Findings revealed that social media usage by university students was positively associated with their PWB and SWB through self-esteem and online social support, and cyberbullying played a moderating role in the first phase of the mediation process such that the indirect associations were weak with cyberbullying reaching high levels.

These findings highlight the importance of discerning the mechanisms moderating the mediated paths linking social media usage by young adults to their PWB and SWB. The results also underline the importance of implementing measures and interventions to alleviate the detrimental impacts of cyberbullying on young adults’ PWB and SWB.

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Introduction

In this digital world, the utilization of social media has become a massive and meaningful part of our everyday life and has grown substantially in recent years [ 1 , 2 ]. People of all ages, adults and adolescents, utilize a diverse array of social media platforms to engage in meaningful connections, both in intimate settings with loved ones and in expansive networks encompassing friends, acquaintances, and professional peers [ 3 ]. It is worth emphasizing that the younger generation is dedicating an ever-growing portion of their time to engaging in online networking platforms, indulging in e-games, exchanging messages, and immersing themselves in various forms of social media [ 4 ]. As a result, there is growing attention among the scholars of social sciences paid to social media research. Despite a handful of studies that have been conducted to shed light on the reasons behind the excessive usage of social media, still literature exploring the potential consequences of utilizing social media is limited, particularly among college students in the context of China. Taking up this research gap, we intend to examine the effects of social media usage on students’ wellbeing, for example, PWB and SWB, which are two distinct but related dimensions of well-being.

Studies on well-being have been grounded on two different philosophical approaches: the hedonic perspective, which defines well-being as the pursuit of pleasure and avoidance of pain, and the eudaimonic perspective, which conceptualizes well-being as the extent to which an individual achieves their potential and experiences personal growth [ 5 ]. Most studies on the hedonic psychological perspective have focused on using SWB measures [ 6 ], whereas the eudaimonic approach, as proposed by Ryff [ 7 ], includes a multidimensional model of PWB consisting of six different aspects of positive functioning: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance [ 8 ]. Although researchers have different approaches, they generally agree that well-being should be understood as a complex concept that incorporates elements from both the hedonic and eudaimonic perspectives [ 5 , 9 ]. Moreover, many scholars recommended that both concepts of wellbeing be re-examined by conducting in-depth and larger research subjects involving diverse cultures and countries [ 10 ]. This is necessary and meaningful since existing studies are typically conducted with subjects in countries referred to as WEIRD (Western, Educated, Industrialized, Rich, Democratic). As such, in this study, we attempted to investigate the impact of social media usage on both PWB and SWB.

Existing literature has revealed that the use of social media is closely related to individuals’ well-being. Some studies found that social media usage can produce beneficial effects. For instance, social media can increase users’ sense of connectedness with others [ 4 ], thus reducing social isolation. Some other studies have demonstrated that engaging in social interactions through smartphones exquisitely enhances one's overall sense of well-being, as it remarkably diminishes feelings of loneliness and shyness [ 11 ] while providing a sense of intimacy [ 12 ], and mobile voice communication with loved ones is a powerful predictor of enhanced PWB [ 13 ]. Furthermore, numerous studies have revealed that the utilization of entertainment-motivated social media can help improve users’ self-disclosure [ 14 ], and facilitated social connections through social media platforms can decrease the sense of stigmatization [ 15 ] and enhance belongingness and social inclusion [ 16 ], contributing to increased SWB. However, some researchers have stressed that social media usage can occasionally divert users' attention from meaningful relationships and hinder social interactions [ 17 , 18 ] and a number of scholars have cautioned against the potential additive relationship with digital devices like smartphones if used excessively [ 12 , 19 ], possibly due to the fear of missing out [ 20 ]. The utilization of social media has unfortunately been linked to a range of distressing consequences including heightened feelings of anxiety [ 21 ], profound loneliness [ 22 ], and debilitating depression [ 23 ]. Additionally, it has been found to perpetuate a sense of social isolation, as well as engender a phenomenon known as "phubbing," whereby individuals become excessively engrossed in their smartphones, thereby compromising genuine interpersonal connections during in-person interactions [ 24 ].

The inconsistent research findings regarding the impact of social media on individuals’ well-being suggest that some factors may play a role in this mechanism. Actually, in addition to the direct association between social media usage and well-being, a number of studies have further identified mediators to investigate underlying mechanisms of this relationship. Previous studies have identified self-esteem and online social support as two promising mediators of the link between social media usage and PWB and SWB. And empirical studies have revealed that media attention and dependency were proven to improve individuals’ self-efficacy [ 25 ], thus increasing their self-esteem. Most importantly, people would rely more on social media, especially during the COVID-19 pandemic in China [ 26 ], to seek social support via the Internet as in-person social support was seriously reduced [ 27 ]. Moreover, social media usage like for informational uses was found to increase people’s self-esteem [ 28 ] and can provide an important avenue for obtaining online social support from friends, peers and important others [ 29 ], which, in turn, reinforce peoples’ PWB and SWB. Although previous studies on mediation effects of self-esteem and online social support have helped elucidate the complex relationship between social media and well-being, further exploration can be made. To test the concurrent mediating effects of self-esteem and online social support, which have been investigated separately in prior studies, would shed more light on the interplay between social media usage and well-being. Furthermore, researchers have acknowledged the importance of exploring the generalizability of their findings to different cultures, like Asian cultures, particularly Chinese culture where collectivism runs strong [ 30 ]. Because previous research indicated that individuals who recorded high collectivism were apt to experience higher levels of well-being, regardless of social media usage [ 15 ], suggesting that a hierarchical society with a strong collectivist culture can play an important role in the impact of people’s social media use on their well-being.

Another factor that intrigued us is cyberbullying. A review of literature on this topic concluded that cyberbully is prevalent on the Internet and some 11.2% to 56.9% of Chinese adolescents reported experiences of cyberbullying victimization, the second-highest median rate among nine nations surveyed in the study [ 31 ]. Similar to traditional bullying, cyberbullying as a victim via social media is founded to be closely related to a series of behavioral and psychological problems (e.g., depression, anxiety, post-traumatic stress disorder, and suicidal ideation) [ 32 , 33 ]. Cyberbullying victimization has also been found to reduce individuals’ self-esteem [ 34 ] and make them feel less inclined to engage with social media platforms and online communities [ 35 ], thus decreasing online social support from peers, friends, and family members. This analysis inspired us to examine whether cyberbullying acts as a moderator in the association between social media usage and well-being. Given the widespread occurrence and undesirable effects of cyberbullying, it is significant for scholars to explore its underlying mechanisms and underexamined consequences. Meanwhile, previous empirical investigations on cyberbullying have largely focused on children and teens [ 36 ]. There have been comparably fewer studies on the influence of cyberbullying on mental health among young adults, like college students, especially in China. In addition, cyberbullying may have a differential impact on adults vs.children. This is particularly true for cyberbullying on social media, as there are differences in the amount of time spent on social media and the specific platforms used by children and adults [ 37 ].

Against the above background and in line with previous studies [ 16 , 38 , 39 , 40 ] we formulated a moderated mediation model to test the roles of self-esteem and online social support as mediators and cyberbullying as a moderator in the relationship of social media and PWB and SWB. Figure  1 presents our moderated mediation model.

Proposed moderated mediation model

Literature review and hypotheses development

Students’ social media usage and well-being.

University students utilize the Internet for various reasons, including leisure activities like participating in online communities or playing games, educational tasks such as completing assignments or applying for scholarships, and practical activities such as researching companies for job interviews. Previous studies have unveiled the rising popularity of social media among students, while more recent investigations have underscored the profound impact that the usage of social media has on their PWB and SWB [ 41 , 42 ]. Research studies have observed a directly or indirectly positive relationship of social media usage with students’ PWB [ 43 , 44 ] and SWB [ 41 , 42 ]. Specifically, PWB serves as a crucial determinant of the overall quality of life, referring to individuals' emotional states and appraisals of their existence [ 45 ], and can include a multiple of dimensions such as autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance [ 8 ]. The utilization of social media by students offers them a broader platform to voice their opinions and emotions regarding their rights, fostering their self-assurance and confidence, and bolstering their knowledge and understanding [ 46 ]. During times of crisis like during the period of COVID-19, the utilization of social media platforms by students presents a valuable avenue for stress relief as they can openly express their thoughts and receive advice from others on how to navigate and overcome the challenging circumstances they find themselves in [ 47 ]. In addition, researchers have also revealed that students’ frequent social media usage to exchange thoughts and strengthen bonds with family and friends can have a positive impact on their PWB by reducing loneliness [ 11 ] and social isolation [ 48 ], and strengthening life satisfaction [ 49 ]. Based on these findings, we can make this hypothesis;

H1a: Social media usage among university students is positively related to their PWB

SWB refers to an individual's overall contentment and happiness, taking into account their personal perception of the significance they place on various aspects of their life. Put simply, SWB encompasses a comprehensive assessment of one's life, encompassing both cognitive evaluations of life satisfaction (cognition) and emotional assessments of feelings and moods (emotion) [ 50 ]. This concept is a growing area of concern in light of the increase in mental health issues in higher education [ 51 ]. A decline in SWB is frequently observed prior to the onset of more severe mental health problems and behavioral issues, including but not limited to depression, suicidal tendencies, and dropping out of college [ 52 , 53 ]. However, some studies have linked social media usage to better SWB. For instance, prior research has demonstrated that social media platforms like Facebook can contribute to users’ accrual of network social capital, thus bolstering SWB [ 54 ]. Also, positive feedback received from individuals with whom one interacts online can significantly enhance overall well-being and mental health. And more frequent quality-based online communication with relatives, friends, family members, and relevant others was also found to have positive impacts on SWB [ 55 ] through lowered depression over time [ 56 ] and enhanced life satisfaction [ 55 ].

Moreover, according to the flow theory, individuals can experience a state of flow when they direct their attention toward accomplishing a specific task or overcoming a challenge in order to attain certain objectives [ 57 ]. This state of flow is characterized by a sense of fulfillment, enhanced cognitive abilities, heightened motivation, and overall happiness [ 58 ]. That is to say, flow improves people’s SWB. To experience a flow state, three conditions need to be fulfilled: having a clear goal and a perceived challenge, maintaining a balance between the difficulty of the challenge and one's skill level, and receiving immediate feedback on progress. Social media, with its enjoyable and controllable nature, provides these conditions and allows users to have an immersive experience, making it a significant source of flow experiences and contributing to people's SWB. In light of this principle, as students increase their usage of social media, they allocate a greater portion of their focus and energy toward engaging with these platforms. In the process of pursuing their objectives, such as engaging in lively conversations with friends via popular messaging applications like WeChat and QQ, or exhibiting their picturesque travel snapshots on platforms like Weibo, they might unexpectedly receive affirming feedback and positive responses from their virtual connections. This immersive and seamless flow experience not only enables individuals to unwind and experience a heightened sense of contentment but also directly enhances their overall sense of SWB. Along this line, we can propose the following hypothesis;

H1b: Social media usage by university students is positively associated with their SWB.

Self-esteem and online social support as mediators

Self-esteem refers to an individual's enduring attitude, whether positive or negative, towards oneself that remains consistent regardless of various circumstances and the passage of time [ 59 , 60 ]. Self-esteem is crucial, especially for young individuals, as they are going through a period of forming their identity, and feedback about themselves can greatly impact their self-esteem [ 61 ]. Research has demonstrated that individuals who possess high self-esteem often experience lower levels of aggressive negative emotions and depression compared to those with low self-esteem [ 62 , 63 ]. Research also revealed that self-esteem functions as an important and positive predictor of PWB and SWB [ 64 ] and success later in life [ 65 ]. By contrast, people who have low self-esteem are likely to be socially anxious, shy, lonely, and introverted. Individuals who experience a decrease in their self-esteem frequently limit their interactions with others, which can impede the formation of close and supportive relationships that are crucial for their overall well-being [ 66 ]. Additionally, they tend to have less stable and satisfying relationships compared to those with high self-esteem [ 67 ]. Furthermore, individuals with low self-esteem tend to engage in self-victimization and shift blame onto others when faced with social failures, rather than acknowledging their own choices. These tendencies lead to avoidance of social interactions, unfamiliar situations, and a general disconnection from society, which in turn heighten the chances of developing social anxiety and depression [ 68 ].

However, interacting with others on social media can generate favorable impacts on one's self-esteem when individuals experience a feeling of belonging and receive encouragement and assistance from their online connections. In the study by Apaolaza et al. [ 69 ], people socializing on social media sites can experience a rise in self-esteem and improvement in their SWB. Moreover, receiving positive feedback on social media can also help boost self-esteem, as others' responses to an individual's posts are usually positive. Studies have shown that the number of likes on social networking sites like Facebook is linked to higher self-esteem [ 70 ]. In more recent research using objective data, it was revealed that Facebook 'likes' have a positive association with happiness, as they boost self-esteem [ 71 ]. Similarly, engaging in self-reflection on social media can have a positive effect on one's self-esteem. By allowing users to carefully select and present information about themselves, social media enables individuals to highlight their positive attributes and experiences, which can boost their self-esteem when they review their profile or past interactions with others [ 40 , 72 ]. As a result, we hypothesized that;

H2a: There exists a mediating role of self-esteem in the relationship between social media usage by university students and their PWB and SWB.

Social support, being one of the most prominent factors that provide protection, plays a crucial and indispensable role in the prevention of mental illnesses [ 73 , 74 ]. It serves as a vital element in safeguarding individuals from the onset and development of psychological disorders [ 75 ]. When individuals received increased levels of social support, they experienced a decrease in feelings of loneliness and an increase in overall happiness [ 76 ]. Online social support refers to the emotional, informational, and instrumental support received through the Internet, as well as the feeling of connection and acceptance from friends, family, and other individuals within one's social circles. Online social support represents the extension of social support that is traditionally available in the physical world to the virtual realm of cyberspace and can enhance the well-being and overall health of individuals, both physically and mentally. This support is facilitated by online platforms and serves as a source of comfort, guidance, and a sense of belonging in times of need. It encompasses various forms of assistance, ranging from empathetic conversations and advice to tangible resources and assistance [ 77 , 78 ]. Through online social support, individuals are able to seek solace, share their experiences, and build meaningful relationships with others, ultimately enhancing their overall well-being and social connectedness in the digital realm. Past research has indicated that the utilization of mobile social media platforms can effectively fortify individuals' connections with others, thus offering them online social support, which in turn aids in the improvement of their well-being [ 79 , 80 ]. A recent review by Gilmour et al. [ 81 ] discovered that using social networking sites like Facebook for seeking social support can enhance users’ overall well-being, as well as improve both physical and mental health. Additionally, it was found to decrease instances of mental illnesses such as depression, anxiety, and loneliness. Thus, online social support seems to have promising effects on young people’s well-being. Along this line, we made the following hypotheses;

H2b: There exists a mediating role of online social support in the relationship between social media usage by university students and their PWB and SWB.

In addition, it has been revealed that self-esteem is a crucial individual factor affecting social support [ 82 ]. Researchers contend that people having greater self-esteem are more inclined to have positive self-evaluations [ 83 ], gain acceptance from others [ 84 ], and exhibit proactive and optimistic behaviors in online contexts [ 85 ]. As a result, they are more likely to receive social support and assistance from their online communities. In comparison, individuals with lower self-esteem typically have negative opinions about themselves, display more negative behavior online, and may not receive as much social support on the Internet [ 86 ]. Furthermore, empirical studies also found a positive relationship between the two variables [ 87 , 88 ]. Given the literature review, we proposed;

H2c: University students’ self-esteem is positively related to their online social support.

Cyberbullying as a moderator

Cyberbullying, according to Rafferty and Vander Ven [ 88 ], was depicted as ‘repeated unwanted, hurtful, harassing, and threatening interaction through electronic communication media’. In contrast to conventional websites, social media platforms provide users with the unique opportunity to selectively share information and content by adjusting their account settings. This remarkable feature has granted young individuals an unprecedented level of access to personal information, as well as a readily accessible platform to exploit this information to their advantage when interacting with others. Cyberbullying can manifest itself across various platforms such as text messages, electronic mail, online chat rooms, and social networking sites. It has emerged as a substantial public health worry due to its potential to induce mental and behavioral health complications, along with an elevated susceptibility to suicidal tendencies [ 89 ]. In fact, cyberbullying poses a detrimental impact on all groups of people who have access to technology, but its consequences are particularly severe for students due to their vulnerable age and susceptibility to online harassment [ 90 ].

According to existing literature, individuals who fall victim to cyberbullying commonly experience a range of psychological issues, including but not limited to stress, depression, feelings of isolation, loneliness, low self-esteem, low academic success, fear of attending school, heightened levels of social anxiety and suicidal ideations [ 91 ]. Furthermore, numerous research studies have consistently demonstrated that cyberbullying inflicts severe emotional and physiological harm upon vulnerable individuals who find themselves unable to defend against such attacks [ 92 ], decreasing their SWB [ 93 ] and causing psychological challenges, such as behavioral issues, alcohol consumption, smoking, and diminished dedication to their academic pursuits [ 94 ]. Due to the detrimental impact of cyberbullying on individuals' well-being, it hinders students' academic success as they struggle to overcome the emotional distress caused by this form of harassment. It was revealed that cyberbullying victimization is strongly associated with various psychological issues such as anxiety, depression, substance abuse, diminished self-esteem, interpersonal difficulties, strained familial relationships, and subpar academic performance among university students [ 95 ].

Research consistently reveals that individuals who are bullied typically have lower levels of self-esteem compared to those who are not victimized [ 34 , 96 ]. And empirical studies based on student samples also confirmed that experience of cyberbullying as a victim was found to be correlated with significantly lower levels of self-esteem [ 94 , 97 ]. In a more recent study based on Chinese university students, Ding et al. [ 98 ] also observed a negative association between cyberbullying and self-esteem. On the other hand, cyberbullying often comes in many forms, such as being ignored, disrespected, threatened, made fun of, and harassed, causing psychological and emotional distress for the victim. Such undesirable feelings and experiences may dampen their motivation and weaken their enthusiasm to engage with online communities [ 35 ], thus decreasing potential online social support they would receive from peers, friends, family members, educators, and romantic partners. Also, cyberbullying erodes the trust individuals have in their online connections so that they would become more cautious about sharing personal information or expressing their thoughts and feelings online [ 99 ], thus hindering the development of genuine connections and limiting the depth of online social support received. In addition, continuous exposure to cyberbullying can damage a person's self-esteem, self-confidence and self-worth, resulting in a wrong belief that they are undeserving of support or that others will not empathize with their experiences [ 95 , 100 ] which may lead to refraining from seeking or accepting online social support. And those suffering from cyberbullying may also choose not to seek online or offline social support due to fear or anxiety, which would in turn have an adverse impact on their well-being [ 101 ].

Based on these findings, it can be inferred that the occurrence of cyberbullying might impact the connection between students' engagement with social media platforms and the positive outcomes it typically fosters. Thus, we hypothesized that;

H3a: Cyberbullying moderates the relationship between social media usage by university students and their self-esteem, wherein the relationship is weaker when cyberbullying is high.

H3b: Cyberbullying moderates the relationship between social media usage by university students and their online social support, wherein the relationship is weaker when cyberbullying is high.

H3c: Cyberbullying moderates the relationship between social media usage by university students and their PWB, wherein the relationship is weaker when cyberbullying is high.

H3d: Cyberbullying moderates the relationship between social media usage by university students and their SWB, wherein the relationship is weaker when cyberbullying is high.

Methodology

Participants and procedure.

The data for the present study were collected via an online survey carried out from April 2023 to May 2023. The survey was based on Wenjuanxing ( www.wjx.cn ), a widely accepted and professional online survey platform for questionnaire design and data collection in China. Questionnaire links can be sent to participants through various social media platforms, such as WeChat, QQ, Weibo, and email. Once the survey is finished, the statistical charts can be downloaded to a Word document for SPSS analysis online, or the original data can be downloaded to Excel and imported into SPSS software for further analysis. It has advantages due to its high efficiency, high quality and low cost. In the present study, questionnaires were designed in Chinese using Wenjuanxing and were then distributed and collected via WeChat and QQ, two popular social platforms that many Chinese people use on a daily basis.

A total of 1,301 active responses were recorded in a response to 1,500 distributed questionnaires (86.73% response rate). Each individual who took part in the research willingly agreed to participate and were given the assurance that their answers would be kept confidential, anonymous, and solely used for the purpose of conducting the study. Since the current study aimed at investigating the influence of social media usage, those who had no access to electronic devices or reported having not used any social media platforms were excluded ( N  = 9). And following careful data cleansing, the final sample comprised 1,004 students, and their major characteristics are displayed in Table 1 . The research participants consisted of both undergraduate (825) and graduate students (179) enrolled in 135 universities and colleges throughout China. Of the total participants, 48.11% were female students and 68.92% were from single-child families. The age range of the sample ranged from 18 to 31 years ( M  = 23.78, SD  = 4.06).

Scale items used in the present study were drawn from the extant literature; thus, well established and validated scales widely applied in prior studies were employed to measure the various constructs in the model shown in Fig.  1 . Given that the respondents in the study are Chinese, the English-language scales used for measuring social media usage and cyberbullying were translated into Chinese. To guarantee that the language was consistent in its meaning, a technique known as back-translation designed by Brislin [ 102 ] was employed. Specifically, this process involved the translation of items from English to Chinese by a bilingual linguist and the back-translation by another bilingual scholar. The other scales we employed were Chinese versions with valid and reliable psychometric properties.

Social media usage scale

In order to assess individuals' engagement on online social platforms, the researchers chose the 9-item general social media usage subscale from the Media and Technology Usage and Attitude Scale (MTUAS) devised by Rosen et al. [ 103 ]. The original MTUAS scale was designed to assess technology and media usage as well as attitudes toward technology. It consists of 60 questions, each of which measures 1 of 11 usage subscales of the questionnaire, and the subscales can be applied collectively or separately. Participants were requested to provide information regarding how often they engage in various activities on social media platforms (e.g., “Read postings; Comment on postings, status updates, photos, etc.”). Each participant assessed the accuracy of the statements using a frequency scale that ranged from 1 ( never ) to 10 ( all the time ) with higher scores indicating more social media usage. According to Rosen et al. [ 103 ] and Barton et al. [ 104 ], the general social media usage scale demonstrated good reliability and validity with the alpha coefficient calculated at 0.97 and 0.90, respectively. In the current study, the measure showed good reliability (Cronbach’s α = 0. 906).

Cyberbullying scale

An instrument devised by Ybarra et al. [ 105 ] captures the prevalence of an individual experiencing aggressive behavior online across various digital media platforms and electronic devices. The four-item self-report scale assesses the frequency of being subjected to such behaviors within the preceding year on a 5-point Likert scale with response options ranging from 1 ( not sure ) to 5 ( often ). Sample statements include: (a) “Someone made a rude or mean comment to me online”, (b) “Someone sent a text message that said rude or mean things”. Higher scores represent greater levels of cyberbullying as a victim. In the present study, the reliability of the scale calculated based on the current sample was high (Cronbach’s α = 0.818).

Self-esteem scale

The Rosenberg Self-Esteem Scale (RSES; Rosenberg, [ 59 ]) was adopted to assess global self-esteem with 10 statements on a 4-point Likert scale. This measure has already been translated into Chinese, demonstrating reliable and adequate psychometric properties [ 85 , 106 ]. Participants’ response categories were set as 1( strongly disagree ) and 4 ( strongly agree ). Example questions include: (a) “I feel that I have a number of good qualities,” and (b) “I take a positive attitude toward myself.” The five negatively worded items on the scale were reverse scored and the height of the scores taken from the measure suggests that a respondent’s self-esteem is high. For the present study, the measure demonstrated good reliability (Cronbach’s α = 0.945).

Online social support scale

The measure of online social support an individual receives was adapted from the Chinese short version of the Online Social Support Scale (OSSS-CS) developed by Zhou and Cheng [ 107 ] as this 20-item instrument has been translated into Chinese and has been tested in Chinese populations demonstrating good internal consistency and high construct validity for its four subscales: esteem/emotional support (0.92), social companionship (0.80), informational support (0.98), and instrumental support (0.92). These four factors were also validated based on confirmatory factor analysis (CFA). Example items include: (a) “People encourage me when I am online”, (b) “People help me learn new things when I am online”, and (c) “When I am online, people help me with school or work”. Participants were asked to rate the frequency of social support in these dimensions they received from the online world and their responses were recorded on a 5-point Likert scale with anchors of 1 ( never ) and 5 ( a lot ). Higher scores indicate greater online social support. In the present study, the measure demonstrated good reliability (Cronbach’s α = 0.956).

The PWB of the participants was evaluated using a shorter Chinese version for Ryff and Keyes’ [ 8 ] PWB Scale [ 108 ]. The 18-item scale is broken down into six different facets: autonomy, environmental mastery, personal growth, positive relations with others, purpose in life, and self-acceptance. Each aspect was measured by three items and the response to the individual questions was reverse-coded and configured with a 7-point Likert scale, ranging from 1 ( strongly agree ) to 7 ( strongly disagree ). Example items are: (a) “I tend to be influenced by people with strong opinions,” (b) “I have not experienced many warm and trusting relationships with others," and (c) "In many ways I feel disappointed about my achievements in life." Higher scores mean greater PWB. The shortened version scale has been adopted in a series of previous studies on Chinese samples with good internal consistency [ 109 ]. For the current study, the scale was reliable (Cronbach’s α = 0. 959).

The revised version of the College Student SWB Questionnaire (CSSWQ) with 16 self-report items that comprise four subscales was adopted to assess participants’ SWB in terms of academic efficacy, college gratitude, school connectedness, and academic satisfaction [ 53 ]. The four dimensions were measured using four items, respectively, on a 7-point Likert scale with anchors of 1 ( strongly disagree ) and 7 ( strongly agree ). Sample statements are: (a) “I have had a great academic experience at this college,” (b) “I am a diligent student,” and (c) “I feel thankful for the opportunity to learn so many new things." The overall well-being score was calculated by computing the average of all the items on the scale with higher scores reflecting better SWB. This scale has been translated into Chinese and validated on Chinese samples [ 110 ], revealing reliable and valid psychometric properties. In the present study, the measure demonstrated good reliability (Cronbach’s α = 0.953).

Statistical analysis

Before further analyses, we carried out a confirmatory factor analysis (CFA) using AMOS 26.0 to ensure the validity and reliability of the study variables. The potential common method variance (CMV) was checked considering self-report questionnaire was the principal method for obtaining data. After that, data analysis in the study was carried out in three steps using SPSS 26.0. Firstly, descriptive statistics and Pearson’s correlations were summarized and calculated. Then, to test the proposed hypotheses in the study, we employed Haye’s PROCESS macro Model 6 (version 3.4.1 software) [ 111 ] to test the mediating role of self-esteem and online social support in the relationship between social media usage and PWB and SWB. Finally, Haye’s PROCESS macro Model 85 [ 111 ] was conducted to test whether the first stage of indirect relationships and the direct association between social media usage and PWB and SWB was moderated by cyberbullying. In the process, all variables were standardized and the interaction terms were computed from the standardized variables. The bias-corrected percentile bootstrap method and 95% confidence intervals (CI) were applied. If the effect does not include 0 in the 95% CI, it is considered to be statistically significant. Moreover, the simple slope analysis was employed to evaluate the moderating effects [ 112 ]. We plotted the relationship between the independent variable (social media usage) and the dependent variables (self-esteem and online social support) when the levels of the moderator variable (cyberbullying) were one standard deviation below and one standard deviation above mean value of the moderator variable. In addition, demographic variables (i.e., gender, age, family origin) were controlled during the analyses. A p -value of < 0.05 was considered to be statistically significant.

Validity, construct reliability, and common method variance

The content validity and reliability of the study variables analyzed through CFA are displayed in Table 2 . As shown in the table, the item loadings of all factors in the study exceed the threshold value of 0.60 as recommended by Hair et al. [ 113 ]. To ensure the convergent validity of our model, we conducted an analysis of the composite reliability (CR), average variance extracted (AVE), and Cronbach alpha (CA) of all the constructs. The findings from this analysis revealed that the CR and CA values for all the constructs exceeded the recommended threshold of 0.70, indicating a high level of internal consistency. Additionally, construct validity is also confirmed because the AVE values for all the constructs were also above the suggested threshold of 0.50, as advised by previous research studies [ 114 , 115 ]. To assess the discriminant validity of our study, we employed the methodology suggested by Fornell and Larcker [ 114 ]. Our approach involved examining the square root values of AVE for each construct and comparing them with their respective inter-correlations. Considering that the square root of AVE for each factor is greater than its correlations with other factors, it can be concluded that discriminant validity is also established (see Tables 2 and 3 for comparison).

In order to minimize the risk of CMV in our data, we implemented multiple strategies to ensure the accuracy and reliability of the self-reported answers provided by the participants. For instance, as a procedural measure, we took into consideration the suggestions put forward by Podsakoff et al. [ 116 ] to address any potential concerns regarding the anonymity and confidentiality of our participants. We took great care in ensuring our participants that their identities would be kept strictly confidential, and that any information they shared would be treated with the highest level of confidentiality. Additionally, we employed the Herman single-factor test, as recommended by Podsakoff et al. [ 116 ], to evaluate the potential threat of CMV in our study. The results of this test indicated that the first factor accounted for 33.97% of the variance, suggesting that there is no significant problem of CMV present in our study.

Preliminary analyses

Descriptive statistics and correlation matrix between the variables are reported in Table 3 . As expected, all proposed path variables were revealed to be intercorrelated significantly (see Table 3 ). Significant positive correlations were obtained between social media usage and PWB ( r  = 0.40, p  < 0.01) and SWB ( r  = 0.46, p  < 0.01), respectively with large effect sizes. Self-esteem and online social support were found to be positively associated with social media usage ( r  = 0.45, p  < 0.01; r  = 0.43, p  < 0.01), PWB ( r  = 0.54, p  < 0.01; r  = 0.55, p  < 0.01), and SWB ( r  = 0.50, p  < 0.01; r  = 0.53, p  < 0.01), respectively. In addition, cyberbullying was negatively related to self-esteem ( r  = -0.18, p  < 0.01), online social support ( r  = -0.20, p  < 0.01), PWB and SWB ( r  = -0.27, p  < 0.01; r  = -0.16, p  < 0.01), respectively whereas a positive association was observed between this variable and social media usage ( r  = 0.18, p  < 0.01). In general, no significant relationships were identified between the demographic variables and the other variables under investigation. We, therefore, included them as control variables in the follow-up analyses.

Testing for the mediating effect

To test the hypothesized relationship between social media usage and outcomes as well as the mediation of self-esteem and online social support, we utilized SPSS PROCESS macros [ 111 ]. The results presented in Table 4 revealed that social media usage was positively related to self-esteem ( B  = 0.20, t  = 15.75, p  < 0.001), online social support ( B  = 0.09, t  = 7.00, p  < 0.001), PWB ( B  = 0.11, t  = 4.78, p  < 0.001), and SWB ( B  = 0.19, t  = 8.36, p  < 0.001), confirming our hypotheses H1a and H1b. Moreover, the results further showed that self-esteem and online social support mediate the relationship between students’ usage of social media and their PWB and SWB. Specifically, social media usage was significantly and positively associated with PWB via self-esteem (indirect effect = 0.100, SE  = 0.01, 95% CI  = [0.075, 0.126]), via online social support (indirect effect = 0.046, SE  = 0.01, 95% CI  = [0.030, 0.063]), and via self-esteem and online social support (indirect effect = 0.058, SE  = 0.01, 95% CI  = [0.043, 0.074]). Similarly, the utilization of social media by students was also significantly and positively related to their SWB via self-esteem (indirect effect = 0.072, SE  = 0.02, 95% CI  = [0.049, 0.097]), online social support (indirect effect = 0.043, SE  = 0.01, 95% CI  = [0.027, 0.061]), and the two mediators (indirect effect = 0.054, SE  = 0.01, 95% CI  = [0.039, 0.070]). Thus, self-esteem and online social support acted as effective mediators in the association between social media usage and PWB and SWB, supporting H2a, H2b. Moreover, self-esteem had a significant and positive effect on online social support ( B  = 0.57, t  = 19.76, p  < 0.001), thus confirming H2c.

Testing for moderated mediation

In Hypothesis 3, cyberbullying was projected to moderate the first phase of the indirect associations as well as the direct relations between social media usage and PWB and SWB. To test these hypotheses, we performed a moderated mediation analysis by using Haye’s PROCESS macro [ 111 ] in SPSS and investigated Cyberbullying across the levels. Concerning the relationships among study variables, as shown in Table 5 , cyberbullying was negatively correlated with self-esteem ( B  = -0.24, t  = -10.24, p  < 0.001), online social support ( B  = -0.16, t  = -7.16, p  < 0.001), PWB ( B  = -0.30, t  = -7.67, p  < 0.001), and SWB ( B  = -0.19, t  = -4.67, p  < 0.001). The effect of social media usage on self-esteem ( B  = 0.22, t  = 17.69, p  < 0.001) and online social support ( B  = 0.12, t  = 9.12, p  < 0.001) was significant, and more importantly, this effect was moderated by cyberbullying ( B  = -0.11, t  = -7.30, p  < 0.001; B  = -0.10, t  = -6.66, p  < 0.001), respectively. Contrary to our H3c and H3d, the direct relationships between social media usage and PWB ( B  = 0.00, t  = 0.10, p  > 0.05) and SWB ( B  = 0.00, t  = 0.11, p  > 0.05) were not significantly moderated by cyberbullying. Furthermore, the bias-corrected percentile bootstrapping results revealed that the indirect effect of social media usage on PWB via self-esteem (Index of moderated mediation = -0.05, SE  = 0.01, 95% CI  = [-0.07, -0.03]) and online social support (Index = -0.04, SE  = 0.01, 95% CI  = [.-0.06, -0.03]) was moderated by cyberbullying. Likewise, the relationship between social media usage and SWB was indirect and moderated by cyberbullying via self-esteem (Index = -0.04, SE  = 0.01, 95% CI  = [-0.05, -0.02]) and online social support (Index = -0.04, SE  = 0.01, 95% CI  = [-0.06, -0.03]). In addition, results showed that the indirect effects of social media usage by students via self-esteem on their PWB (effect = 0.056, SE  = 0.01, 95% CI  = [0.036, 0.078]) and SWB (effect = 0.041, SE  = 0.01, 95% CI  = [0.024, 0.061]) were weaker at + 1SD than at -1SD (effect = 0.128, SE  = 0.02, 95% CI  = [0.093, 0.165]; effect = 0.094, SE  = 0.02, 95% CI  = [0.061, 0.130]), respectively. Also, a similar pattern was observed for the indirect effects of social media usage via online social support on PWB (effect = 0.019, SE  = 0.01, 95% CI  = [0.003, 0.036]) and SWB (effect = 0.019, SE  = 0.01, 95% CI  = [0.003, 0.037]) at higher level of cyberbullying than at lower level (effect = 0.082, SE  = 0.01, 95% CI  = [0.058, 0.107]; effect = 0.081, SE  = 0.01, 95% CI  = [0.055, 0.107]), respectively. These results have given support to our H3a and H3b.

For clarity, we also plotted graphical diagrams to better examine the role of cyberbullying as a moderator in the relations between social media usage and self-esteem (Fig.  2 ) and online social support (Fig.  3 ), separately for students experiencing low and high cyberbullying (at 1 SD below the mean and 1 SD above the mean, respectively). Simple slope tests suggested that the relationships between social media usage and self-esteem and online social support were statistically weaker respectively when at the higher level of cyberbullying.

Cyberbullying moderates the relationship between social media usage and self-esteem

Cyberbullying moderates the relationship between social media usage and online social support

In this study, a moderated mediation model was formulated to explore whether students’ utilization of social media would be indirectly associated with their PWB and SWB via self-esteem and online social support and whether the first phase of this indirect relationship and the direct correlation would be moderated by cyberbullying they have experienced. Although numerous studies have examined the impacts of social media usage among various groups of people, especially children, this study is one of the few that considers both PWB and SWB as outcome variables among Chinese university students, a sample that has been insufficiently examined. Moreover, this study provides a probable explanation as to why university students' frequent use of social media results in higher levels of PWB and SWB. Moreover, it is the first empirical study confirming the mediating roles of self-esteem and online social support underlying this linkage. The research findings further our understanding of how social media usage impacts users’ well-being and what role cyberbullying plays in the process.

Consistent with our expectations, social media usage by university students positively predicted their PWB and SWB; and self-esteem and online social support mediated the relationships, which extends previous theoretical and empirical studies. Specifically, it helps advance our understanding of the intricate relationship between social media usage and people’s well-being, especially PWB and SWB. Previous research on this association has generated varied results. Some studies have observed a negative relationship while others have acknowledged that a positive association exists as social media can facilitate online social connections [ 117 ] and reduce the levels of negative emotions and feelings, such as stress, loneliness, depression, and the sense of social isolation [ 48 ], thus beneficial to users’ PWB. The research findings suggest that incorporating social media into the daily lives of college students and actively engaging with shared content can have a profound impact on their self-esteem and access to diverse forms of online social support, which, in turn, has the potential to enhance their overall PWB and SWB. In previous empirical studies [ 118 , 119 ], self-esteem was mainly found to be positively correlated with several indicators of SWB including affect, meaning in life, and subjective vitality. The present study contributes to the existing body of research by specifically identifying the positive associations between self-esteem and both PWB and SWB in relation to the usage of social media platforms. In this competitive world, healthy self-esteem is required for university students to effectively deal with potential psychological distress that may arise in their academic and career pursuits. And in accordance with self-affirmation theory, greater self-esteem can work as a buffer against unpleasant and stressful experiences and failures [ 120 ]. Furthermore, Sociometer Theory [ 121 ] suggests that an individual's self-esteem is influenced by their sense of social acceptance and the importance placed on their relationships. This theory provides further insight into the strong correlation between self-esteem and PWB. In collectivistic cultures like China, where social bonds are highly valued, young adults place a great emphasis on their connections with others, particularly within their families and interpersonal relationships. As a result, individuals with higher levels of self-esteem are more likely to experience greater PWB, as their self-esteem serves as a potential indicator of their value within their social circles. In addition to self-esteem, our study also identified positive effects of online social support on students’ well-being consistent with prior research [ 122 ]. The reason behind this phenomenon can be attributed to the fact that students who have a vast network of connections on social media and dedicate a considerable amount of time to actively engaging in various interactions on these platforms are more likely to garner a substantial amount of support from their online acquaintances [ 123 ]. As the number of friends a user possesses increases, the probability of receiving positive and supportive comments on their status updates, appreciation for their uploaded photos, and congratulations for their personal accomplishments also increases. This correlation implies that a larger social circle enhances the likelihood of receiving encouragement and validation from friends. This particular positive experience, which is frequently absent in face-to-face interactions, can strengthen the feeling of being a part of a social network and instill a sense of being valued, respected, and esteemed among students. As a result, it can lead to the development of a positive psychological and emotional state, ultimately contributing to an elevated level of SWB [ 124 ].

Apart from the general mediation effect, it is important to highlight the significance of each individual stage within the mediation process. First, our research finding is in line with prior reports that social media usage increases users' self-esteem [ 69 , 70 ]. Previous research on self-esteem theories has identified a close relationship between the use of various social media sites such as Facebook, Twitter, and Instagram and users’ self-esteem [ 125 , 126 ], revealing that peer interaction and feedback on the self represents critical predictors of young adults’ self-esteem [ 127 ]. In addition to facilitating instant messaging and enabling activities like posting and commenting on photos, social media platforms offer a valuable channel for young people to receive feedback, interact with their peers, enhance their social skills, and gain insights by observing others [ 79 ]. College students in China use similar sites like WeChat and Weibo to portray a different version of themselves online by sharing their photos, videos, and other posts within their friend circles or beyond. The likes they receive on social media sites are regarded as verification for acceptance and approval within their groups of peers, which may, in turn, boost their self-esteem. Since the main objective of social media platforms is to encourage communication and connections between individuals, students who frequently use these sites will have a higher likelihood of actively engaging with their fellow peers and more opportunities to receive positive feedback on social network profiles compared to those who use social media less frequently, thus enhancing their self-esteem. And as predicted, students’ higher self-esteem predicted greater online social support, corresponding to research findings by Jin et al. [ 87 ] and Zheng et al. [ 82 ]. These findings align with the principles of Sociometer Theory [ 84 ], which suggests that there is a strong relationship between self-esteem and how individuals perceive acceptance from society and others. People with high self-esteem often feel valued, which in turn encourages them to engage in positive online communication, receive more affirmation and praise from others, and ultimately be accepted within online communities. On the contrary, individuals who possess low self-esteem often harbor a pessimistic outlook towards their own self-image, leading to more negative online interactions and making it harder for them to receive acceptance from online communities, thus hindering their ability to develop a robust online social support system [ 128 ].

Furthermore, in line with previous research [ 79 , 80 ], our findings indicate that there is a positive correlation between the amount of time students spend on social media and the level of online social support they receive or perceive online. Social support in an online setting has attracted the attention of scholars who have studied its prevalence within social networks. One example of this is when individuals show support for their peers by sharing or forwarding online news articles that would be beneficial to their friends in the digital realm. Moreover, public officials have also recognized the significance of social media in providing updates to citizens during critical events such as natural disasters, criminal incidents, or accidents. In such cases, these officials utilize their social media accounts to keep the public informed and engaged. Additionally, people are able to obtain interpersonal support by connecting and interacting with like-minded individuals on various social media platforms. This form of support, commonly referred to as peer support, serves as a valuable resource for college students seeking understanding, guidance, and empathy from others who share similar interests or experiences [ 129 ]. Moreover, a previous research study conducted on college students found that when seeking social support, students were more inclined to rely on social media platforms rather than seeking help from their parents or mental health professionals. Many of them believed that social media use provided them with positive experiences, offering a support network and helping them feel more connected with their friends. Additionally, the study indicated that students tended to gravitate towards communities composed of their peers who shared similar interests, such as fandom communities [ 130 ]. Building upon a series of similar findings, our study provides new empirical support for the positive effect of social media usage on online social support.

Meanwhile, we identified cyberbullying as a boundary condition variable in our research model. Specifically, the results indicated that the links between social media usage and their PWB and SWB via the two mediators: self-esteem and online social support were weaker for those students suffering greater levels of cyberbullying. In today's technologically advanced society, the issue of online bullying has become a prominent worry in numerous settings. The research we conducted has provided evidence that cyberbullying has the potential to diminish the positive effects that students typically derive from their use of social media. For individuals experiencing a low level of cyberbullying, self-esteem, and online social support can have significant beneficial effects on their PWB and SWB. Increased cyberbullying, however, leads to more psychological distress, reduced life satisfaction, increased depressive symptoms and anxiety [ 131 ], or even suicidal thoughts and attempts [ 132 ]. However, contrary to part of our hypotheses, cyberbullying did not moderate the direct relationship between social media usage and PWB and SWB. A probable explanation for this is that the relationship between social media usage, cyberbullying, and well-being is multifaceted and influenced by various factors. It is possible that other variables not considered in this study could be influencing these relationships. For instance, as evidenced by previous research [ 25 ], cultural and contextual factors like collectivism in Chinese culture can play an important role in the effects of media use on well-being. Meanwhile, as suggested by the Differential Susceptibility to Media Effects Model [ 133 ] and Cultivation Theory [ 134 ], sociocultural and psycho-demographic factors can also moderate social media effects by strengthening, diminishing, and/or moderating individuals’ cognitive, emotional, and behavioral responses to media. Another possible reason is that individuals affected by cyberbullying might have developed coping strategies or mechanisms (e.g., emotion-focused coping and avoidance-coping) to deal with cyberbullying to lessen its impact on their PWB and SWB [ 135 ]. These coping mechanisms might mitigate the expected moderating effect.

Limitations and future directions

The present investigation provides a more comprehensive insight into the intricate relationship between social media usage by Chinese university students and their PWB and SWB and how such relationship is mediated by self-esteem and online social support, and moderated by cyberbullying. However, several limitations should be taken into consideration when analyzing and interpreting the research findings.

First, in our study, we employed a cross-sectional research design, which is not without its limitations, particularly the potential for common method variance (CMV). To address this concern, we implemented various measures, such as guaranteeing the confidentiality and anonymity of participants and conducting statistical analyses to confirm the absence of CMV. Nonetheless, we recognize that our model's credibility and validity could be further strengthened by employing a longitudinal research design or carrying out an experimental laboratory study. Second, it is important to approach the generalizability of the present findings with caution. It remains uncertain whether the findings in our study based on samples collected from Chinese universities can be applied to samples obtained in different contexts, populations (e.g., children, older adults), and countries. Therefore, more studies are warranted to examine these relationships in more diverse samples and contexts since it is noteworthy that social network sites may have different effects on individuals of different ages or nationalities. Third, given our failure to confirm hypotheses regarding cyberbullying moderating the impact of social media usage on PWB and SWB due to possible deficiencies in our research design, it is important to note that future studies should formulate a more comprehensive research design by taking into account a broader context and more factors (e.g., coping strategies, social contexts, cultural norms, and psycho-demographic factors) that may moderate social media impact on health outcomes. Meanwhile, given that some studies have found negative effects of excessive and problematic use of social media on users’ well-being, it is necessary for future studies to examine specific factors resulting in such detrimental outcomes, such as time spent on social media, active or passive social media use [ 136 ], and users’ motives [ 137 ]. Third, the current study found support for the important roles of self-esteem and online social support in explaining why social media usage can be beneficial to users’ PWB and SWB, yet some other factors may also take effect. A more extensive investigation is required in order to gain a comprehensive understanding of the specific circumstances under which predictor variables become significant and the ways in which they interact with online processes and individuals' overall well-being, such as positive and negative emotions while using various social networking sites, bridging and bonding social capital, social connectedness, social comparison, and interpersonal competence. In addition, more studies are needed to determine the circumstances in which social media usage can have positive effects, such as investigating whether social networking platforms that encourage more direct social interaction can improve well-being. Furthermore, future studies can also compare the different roles of direct contact and online contact via different social media platforms in affecting people’s overall well-being. Additionally, it could be further explored how previous experiences with specific social media platforms, potentially influenced by the age of the site and the user, impact the association between usage and PWB and SWB.

Theoretical and practical implications

Despite the limitations, this research has a series of important theoretical and practical implications. First, the current study is one of the few attempts to examine the impact of social media on well-being from both the hedonic and eudaimonic perspectives among university students in the context of China, contributing to the existing literature by empirically confirming the positive implications of social media usage on PWB and SWB. Second, this study extends the extant literature on social media by identifying a mediation pathway that includes self-esteem and online social support, underlying their positive effects. This finding helps shed light on how self-esteem within the theoretical context of Identity Theory and Sociometer Theory can be applied in the digital domain, opening up a new research trajectory to further exploring the effect of various dimensions of self-esteem on health outcomes within the framework of social media research. Also, the examination of online social support as a mediator aligns with communication and media theories that emphasize the importance of technology-mediated communication in shaping relationships and well-being. Moreover, it provides firm support for the Social Compensation hypothesis, which is concerned with how online interaction can generate a host of benefits for individuals struggling with face-to-face interaction due to lack of social skills or low well-being [ 133 ], especially during the pandemic. This can enrich our understanding of how these theories apply within a non-WEIRD cultural context, particularly considering the moderating role of cyberbullying. Lastly, another important contribution of our research is the investigation of the moderating role of cyberbullying, which was found to harm the positive utility of social media on students’ PWB and SWB via diminishing the beneficial effects of self-esteem and online social support. This serves as the core theoretical contribution of this study, adding to the previous body of literature on cyberbullying research, especially its moderating role.

In terms of practical contributions, our results highlight the importance and the beneficial outcomes of social media among college students on their overall well-being. This suggests that educational institutions, teachers, administrators, and parents should recognize the positive application of various social media platforms in academia and encourage rational social media use inside and outside schools. Then the positive effects of self-esteem and online social support indicate that students should communicate and interact more frequently with peers, friends, families and important others as a way to increase their self-esteem and seek more emotional and informational support as well as social companionship. However, the finding that cyberbullying victimization as a moderator can reduce the positive effects of social media usage on health outcomes through mediators of self-esteem and online social support indicates that it is important to empower students at-risk for cyberbullying victimization through prevention efforts. Self-esteem as a social construct is especially influenced by interactions with peers. Hence, it is crucial to offer opportunities for cyberbullying victims to connect with their peers, establish strong relationships, and develop meaningful friendships that contribute to their self-worth and foster a positive self-perception. In addition, as for those enduring cyberbullying-related psychological or behavioral problems (e.g., depression, anxiety, social isolation, and suicidal attempts), most Chinese university counselling centers could open online platforms for psychoeducation like training sessions and courses easily accessible through popular apps, such as WeChat and Tencent [ 138 ], and offer timely and target psychological interventions and counseling. Most importantly, given the prevalence of cyberbullying in China, it is imperative that universities initiate training programs and provide relevant curricula to empower students with basic skills and knowledge to recognize, prevent, and cope with cyberbullying. Bullying tracking software and similar practices can be utilized to prevent cyberbullying while using social media for academic purposes. The authorities may also implement more stringent laws and regulations against cyberbullying and online harassment to create a safe online environment.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Zhang, C., Tang, L. & Liu, Z. How social media usage affects psychological and subjective well-being: testing a moderated mediation model. BMC Psychol 11 , 286 (2023). https://doi.org/10.1186/s40359-023-01311-2

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Science News

Social media harms teens’ mental health, mounting evidence shows. what now.

Understanding what is going on in teens’ minds is necessary for targeted policy suggestions

Most teens use social media, often for hours on end. Some social scientists are confident that such use is harming their mental health. Now they want to pinpoint what explains the link.

Carol Yepes/Getty Images

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By Sujata Gupta

February 20, 2024 at 7:30 am

In January, Mark Zuckerberg, CEO of Facebook’s parent company Meta, appeared at a congressional hearing to answer questions about how social media potentially harms children. Zuckerberg opened by saying: “The existing body of scientific work has not shown a causal link between using social media and young people having worse mental health.”

But many social scientists would disagree with that statement. In recent years, studies have started to show a causal link between teen social media use and reduced well-being or mood disorders, chiefly depression and anxiety.

Ironically, one of the most cited studies into this link focused on Facebook.

Researchers delved into whether the platform’s introduction across college campuses in the mid 2000s increased symptoms associated with depression and anxiety. The answer was a clear yes , says MIT economist Alexey Makarin, a coauthor of the study, which appeared in the November 2022 American Economic Review . “There is still a lot to be explored,” Makarin says, but “[to say] there is no causal evidence that social media causes mental health issues, to that I definitely object.”

The concern, and the studies, come from statistics showing that social media use in teens ages 13 to 17 is now almost ubiquitous. Two-thirds of teens report using TikTok, and some 60 percent of teens report using Instagram or Snapchat, a 2022 survey found. (Only 30 percent said they used Facebook.) Another survey showed that girls, on average, allot roughly 3.4 hours per day to TikTok, Instagram and Facebook, compared with roughly 2.1 hours among boys. At the same time, more teens are showing signs of depression than ever, especially girls ( SN: 6/30/23 ).

As more studies show a strong link between these phenomena, some researchers are starting to shift their attention to possible mechanisms. Why does social media use seem to trigger mental health problems? Why are those effects unevenly distributed among different groups, such as girls or young adults? And can the positives of social media be teased out from the negatives to provide more targeted guidance to teens, their caregivers and policymakers?

“You can’t design good public policy if you don’t know why things are happening,” says Scott Cunningham, an economist at Baylor University in Waco, Texas.

Increasing rigor

Concerns over the effects of social media use in children have been circulating for years, resulting in a massive body of scientific literature. But those mostly correlational studies could not show if teen social media use was harming mental health or if teens with mental health problems were using more social media.

Moreover, the findings from such studies were often inconclusive, or the effects on mental health so small as to be inconsequential. In one study that received considerable media attention, psychologists Amy Orben and Andrew Przybylski combined data from three surveys to see if they could find a link between technology use, including social media, and reduced well-being. The duo gauged the well-being of over 355,000 teenagers by focusing on questions around depression, suicidal thinking and self-esteem.

Digital technology use was associated with a slight decrease in adolescent well-being , Orben, now of the University of Cambridge, and Przybylski, of the University of Oxford, reported in 2019 in Nature Human Behaviour . But the duo downplayed that finding, noting that researchers have observed similar drops in adolescent well-being associated with drinking milk, going to the movies or eating potatoes.

Holes have begun to appear in that narrative thanks to newer, more rigorous studies.

In one longitudinal study, researchers — including Orben and Przybylski — used survey data on social media use and well-being from over 17,400 teens and young adults to look at how individuals’ responses to a question gauging life satisfaction changed between 2011 and 2018. And they dug into how the responses varied by gender, age and time spent on social media.

Social media use was associated with a drop in well-being among teens during certain developmental periods, chiefly puberty and young adulthood, the team reported in 2022 in Nature Communications . That translated to lower well-being scores around ages 11 to 13 for girls and ages 14 to 15 for boys. Both groups also reported a drop in well-being around age 19. Moreover, among the older teens, the team found evidence for the Goldilocks Hypothesis: the idea that both too much and too little time spent on social media can harm mental health.

“There’s hardly any effect if you look over everybody. But if you look at specific age groups, at particularly what [Orben] calls ‘windows of sensitivity’ … you see these clear effects,” says L.J. Shrum, a consumer psychologist at HEC Paris who was not involved with this research. His review of studies related to teen social media use and mental health is forthcoming in the Journal of the Association for Consumer Research.

Cause and effect

That longitudinal study hints at causation, researchers say. But one of the clearest ways to pin down cause and effect is through natural or quasi-experiments. For these in-the-wild experiments, researchers must identify situations where the rollout of a societal “treatment” is staggered across space and time. They can then compare outcomes among members of the group who received the treatment to those still in the queue — the control group.

That was the approach Makarin and his team used in their study of Facebook. The researchers homed in on the staggered rollout of Facebook across 775 college campuses from 2004 to 2006. They combined that rollout data with student responses to the National College Health Assessment, a widely used survey of college students’ mental and physical health.

The team then sought to understand if those survey questions captured diagnosable mental health problems. Specifically, they had roughly 500 undergraduate students respond to questions both in the National College Health Assessment and in validated screening tools for depression and anxiety. They found that mental health scores on the assessment predicted scores on the screenings. That suggested that a drop in well-being on the college survey was a good proxy for a corresponding increase in diagnosable mental health disorders. 

Compared with campuses that had not yet gained access to Facebook, college campuses with Facebook experienced a 2 percentage point increase in the number of students who met the diagnostic criteria for anxiety or depression, the team found.

When it comes to showing a causal link between social media use in teens and worse mental health, “that study really is the crown jewel right now,” says Cunningham, who was not involved in that research.

A need for nuance

The social media landscape today is vastly different than the landscape of 20 years ago. Facebook is now optimized for maximum addiction, Shrum says, and other newer platforms, such as Snapchat, Instagram and TikTok, have since copied and built on those features. Paired with the ubiquity of social media in general, the negative effects on mental health may well be larger now.

Moreover, social media research tends to focus on young adults — an easier cohort to study than minors. That needs to change, Cunningham says. “Most of us are worried about our high school kids and younger.” 

And so, researchers must pivot accordingly. Crucially, simple comparisons of social media users and nonusers no longer make sense. As Orben and Przybylski’s 2022 work suggested, a teen not on social media might well feel worse than one who briefly logs on. 

Researchers must also dig into why, and under what circumstances, social media use can harm mental health, Cunningham says. Explanations for this link abound. For instance, social media is thought to crowd out other activities or increase people’s likelihood of comparing themselves unfavorably with others. But big data studies, with their reliance on existing surveys and statistical analyses, cannot address those deeper questions. “These kinds of papers, there’s nothing you can really ask … to find these plausible mechanisms,” Cunningham says.

One ongoing effort to understand social media use from this more nuanced vantage point is the SMART Schools project out of the University of Birmingham in England. Pedagogical expert Victoria Goodyear and her team are comparing mental and physical health outcomes among children who attend schools that have restricted cell phone use to those attending schools without such a policy. The researchers described the protocol of that study of 30 schools and over 1,000 students in the July BMJ Open.

Goodyear and colleagues are also combining that natural experiment with qualitative research. They met with 36 five-person focus groups each consisting of all students, all parents or all educators at six of those schools. The team hopes to learn how students use their phones during the day, how usage practices make students feel, and what the various parties think of restrictions on cell phone use during the school day.

Talking to teens and those in their orbit is the best way to get at the mechanisms by which social media influences well-being — for better or worse, Goodyear says. Moving beyond big data to this more personal approach, however, takes considerable time and effort. “Social media has increased in pace and momentum very, very quickly,” she says. “And research takes a long time to catch up with that process.”

Until that catch-up occurs, though, researchers cannot dole out much advice. “What guidance could we provide to young people, parents and schools to help maintain the positives of social media use?” Goodyear asks. “There’s not concrete evidence yet.”

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Sangwon Lee, Trevor Diehl, Sebastián Valenzuela, Rethinking the Virtuous Circle Hypothesis on Social Media: Subjective versus Objective Knowledge and Political Participation, Human Communication Research , Volume 48, Issue 1, January 2022, Pages 57–87, https://doi.org/10.1093/hcr/hqab014

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Despite early promise, scholarship has shown little empirical evidence of learning from the news on social media. At the same time, scholars have documented the problem of information ‘snacking’ and information quality on these platforms. These parallel trends in the literature challenge long-held assumptions about the pro-social effects of news consumption and political participation. We argue that reliance on social media for news does not contribute to people’s real level of political knowledge (objective knowledge), but instead only influences people’s impression of being informed (subjective knowledge). Subjective knowledge is just as important for driving political participation, a potentially troubling trend given the nature of news consumption on social media. We test this expectation with panel survey data from the 2018 U.S. midterm elections. Two path model specifications (fixed effects and autoregressive) support our theoretical model. Implications for the study of the ‘dark side’ of social media and democracy are discussed.

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Adolescence

More research questions the “social media hypothesis” of mental health, a new study shows that social media does not lead to anxiety or depression..

Posted August 10, 2023 | Reviewed by Gary Drevitch

• What Changes During Adolescence?
• Find a therapist to support kids and teens
• Many believe that social media causes teens to experience depression and anxiety, despite lacking evidence.
• A new study found that when teenagers used social media more, their mental health did not change over time.
• Mainstream media should devote more coverage to studies like this one.

As I’ve discussed previously , conventional wisdom suggests that using social media promotes poor mental health, especially in teenagers . But there is good reason to question this idea. As more high-quality research becomes available, we can see room for nuance and see that social media is not consistently detrimental to everyone’s well-being.

A critical limitation in many existing studies on this topic is that they are cross-sectional. This means all variables are assessed only once, and at the same time. This isn’t necessarily a bad thing; it just means we don’t know how behavioral changes over time might be associated with changes in emotional variables. Longitudinal research helps us to better understand how change happens by measuring these variables repeatedly over a period of months or even years.

Longitudinal research is especially valuable in this case because some young people may use social media to alleviate distress , so we might observe that increases in depression or anxiety will predict increases in social media use , rather than the reverse. On the other hand, if the social media hypothesis is correct, then as teenagers spend more and more time online, this should be followed by decreased mental health (i.e., greater anxiety/depression). But that’s not what the data reveal.

What Researchers Found

A research team in Norway recently published a study in which they tracked young people aged 10-16, and assessed them every 2 years. Each time, the researchers interviewed participants about their behaviors online (e.g., posting photos, “liking,” or commenting on others' posts), and they conducted clinical assessments of depression and anxiety with standardized psychiatric measures. The researchers found no evidence that increased social media use was followed by elevated anxiety or depression. This means that as these teenagers used more social media, their mental health did not change. These findings directly contradict the idea that social media use leads to poor psychological well-being.

The authors are careful to note that even though social media did not make teenagers feel worse, on average, it also did not make them feel better. So, social media use may not have an overall negative or positive effect for the average teenager. This idea is consistent with what I have argued previously , which is that social media use may have differential effects depending on the user’s initial motivations. When people are motivated to use social media because they find it interesting or rewarding, then it’s likelier to make them happy, whereas when they feel compelled or obligated to use it, then it’s likelier to make them feel worse. Motivations matter more than the technology itself.

The researchers also suggest that perhaps subgroups of teenagers may experience different outcomes following social media use, such as those who are bullied or have low self-esteem . The specific content that people view on social media may also play a role. It is also true that digital technologies change rapidly and we cannot assume that all future forms of social media will operate the same way psychologically. New applications have the potential to be better or worse than what people currently use.

Time Trend Data Are Inconclusive

Those who hold with the “social media hypothesis” of mental health will often point to time trend data as evidence. They argue that because social media use has risen in teenagers over the past 15 years, and that teen depression and anxiety has also risen over the same period of time, then those two trends are likely connected.

But if that were true, we ought to be able to observe this trend happening during teenagers’ lives. The fact is, we do not observe this pattern, and these null findings should make us skeptical about such claims. When researchers track teenagers’ mental health over a span of years, there is no link between their social media use and their experiences of depression or anxiety. In the words of the authors , “ the frequency with which adolescents engage in behaviors like posting, liking, and commenting on others’ posts does not influence their risk for symptoms of depression and anxiety .”

It would be great to see more mainstream media coverage of studies like this, especially considering the widespread belief that if young people are permitted to use social media, their mental health will deteriorate. Perhaps parents of teenagers can take some comfort in the fact that for the average user, there is little risk of this.

Cauberghe, V., Van Wesenbeeck, I., De Jans, S., Hudders, L., & Ponnet, K. (2021). How Adolescents Use Social Media to Cope with Feelings of Loneliness and Anxiety During COVID-19 Lockdown. Cyberpsychology, behavior and social networking , 24 (4), 250–257. https://doi.org/10.1089/cyber.2020.0478

Puukko, K., Hietajärvi, L., Maksniemi, E., Alho, K., & Salmela-Aro, K. (2020). Social Media Use and Depressive Symptoms—A Longitudinal Study from Early to Late Adolescence. International Journal of Environmental Research and Public Health , 17 (16), 5921. MDPI AG. Retrieved from http://dx.doi.org/10.3390/ijerph17165921

Steinsbekk, S., Nesi, J., & Wichstrøm, L. (2023). Social media behaviors and symptoms of anxiety and depression. A four-wave cohort study from age 10–16 years. Computers in Human Behavior , 147 , 107859.

Dylan Selterman, Ph.D., is an Associate Teaching Professor at Johns Hopkins University in the Department of Psychological and Brain Sciences. He teaches courses and conducts research on personality traits, happiness, relationships, morality/ethics, game theory, political psychology, and more.

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Social Impact Theory In Psychology

Olivia Guy-Evans, MSc

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Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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Bibb Latané created social impact theory in 1981, and he is also credited as one of the psychologists who brought the bystander effect to light.

Latané’s theory suggests that we are greatly influenced by the actions of others. We can be persuaded, inhibited, threatened, and supported by others.

Latané’s theory proposes that individuals can be the sources or targets of social influence . Social impact theory is a model that conceives of other people’s influence as the result of social forces acting on the individual.

The likelihood that someone will respond to social influence is thought to increase with the source’s strength, the event’s immediacy, and the number of sources exerting the impact.

What is a division of impact?

A division of impact means that the social impact gets spread out between all the people it is directed at. If all the influence is targeted at a single individual, this puts a huge pressure on them to conform or obey.

However, if the influence is directed at two people, the influence is halved.

The more targets there are, the more pressure is shared. This idea is known as diffusion of responsibility. This can explain how the bystander effect can occur in a situation where one person needs help, and a group of people can watch and not feel responsible for helping, compared to if they were the only other person present.

Social Impact Theory’s Three Variables

This is how important influencing an individual or group of people is to the person. There are thought to be two categories of strength that determine a source’s impact:

Trans-situational strength – this exists no matter what the situation is, including the source’s age, physical appearance, authority, and perceived intelligence.

Situation-specific – this looks closer at the situation at hand and the behavior that the target is being asked to perform.

For instance, you may be more likely to listen to a doctor when seeking medical advice but may be less likely to take on their interior design advice.

Someone is more likely to influence another if they are close to each other at the time of the influence attempt. There are three types of immediacy:

Physical immediacy – how physically close the source is to a target.

Temporal immediacy  – a target is more likely to be influenced immediately after a source has asked them to do so.

Social immediacy – if the source is close friends or family members with the target, they may be more likely to influence them.

Moreover, if someone is of the same gender, sexual orientation, or religion, they can likely influence each other as they relate to each other.

Simply, this involves the number of people there is in a group. There is a rule called psychosocial law which states that at some point, the number of influencers has less of an effect on the target.

Influence tends to significantly increase up until about 5 or 6 sources are attempting to influence.

Once past 5 or 6 people, the difference in impact increases but at a decreasing rate, meaning it is not as strong.

Numerous studies support the social impact theory. Below are some examples of famous studies:

Sedikides & Jackson (1990)

This was a field experiment that took place at the birdhouse at a zoo. A confederate told groups of visitors not to lean on the railings near the cages that held the birds to see whether the visitors would obey.

It was found that if the confederate was dressed in a zookeeper uniform, obedience was high. If they were dressed casually, obedience was lower.

This demonstrates social impact, especially the strength aspect, because of the perceived authority of the confederate.

As time went on, more visitors started ignoring the instruction not to lean on the railings.

This demonstrates immediacy because as the instruction gets less immediate, it has less of an impact. It was also found that the larger the group of visitors, the more disobedience was observed, which supports the idea of a division of impact.

Darley & Latané (1968)

This experiment involved participants sitting in booths with the purpose of discussing health issues over an intercom.

One of the speakers was a confederate who would pretend to suffer a heart attack during their talk. It was then observed whether the participants would help the confederate.

It was found that if there was one other participant present, they went for help 85% of the time. This dropped to 62% if there were two other participants and dropped further to 31% if there were 4+ participants.

This study supports Latané’s idea of numbers affecting social impact and the diffusion of responsibility.

You are more likely to help someone if you are the only person present, but there is less responsibility when there are more people present.

Milgram (1965)

Milgram completed many variations on his original famous experiment wherein ‘teacher’ participants were instructed to administer electric shocks to a ‘learner’ confederate who did not actually receive any shocks.

One variation experiment had two peer confederates in the room with the teacher, who refused to continue the experiment.

The results showed that obedience dropped from 65% to 10% with the presence of two rebelling confederates. This supports that social impact can be influenced by the number of individuals present.

What is dynamic social impact theory?

Social impact theory predicts how sources can influence a target, but a criticism is that it neglects how the target may influence the source.

Social impact theory is now often called dynamic social impact theory as it considers the target’s ability to influence the source. It views influence as a two-way exchange rather than a one-way street.

How does social impact theory relate to social media?

Social impact theory was obviously developed long before social media platforms existed. Nevertheless, social impact theory can be observed and utilized by people and brands to influence others.

If we have friends, family, and co-workers who post on social media, we are more likely to be influenced by their opinions if they are trusted people who are close to us (strength and social immediacy).

Likewise, the number of people who share the same opinion on social media is likely to influence others.

Brands can utilize social impact theory to sell their products on social media platforms. Brands and companies can get people of high status to help promote their products and get people to buy them.

For instance, if we see a celebrity that we like promoting a product on social media, saying how good it is, we may be more influenced to buy the product because of the strength of their influence.

This influence often works best if the influencer is of high status, the influencing statement is more immediate, and there are multiple influencers sharing the same message (strength, immediacy, and number).

Latane, B., & Darley, J. M. (1968). Group inhibition of bystander intervention in emergencies.   Journal of personality and social psychology ,  10 (3), 215.

Latané, B. (1981). The psychology of social impact.  American Psychologist, 36 (4), 343.

Latané, B., & Wolf, S. (1981). The social impact of majorities and minorities.  Psychological Review ,  88 (5), 438.

Milgram, S. (1965). Some conditions of obedience and disobedience to authority .  Human relations ,  18 (1), 57-76.

Sedikides, C., & Jackson, J. M. (1990). Social impact theory: A field test of source strength, source immediacy and number of targets.  Basic and applied social psychology ,  11 (3), 273-281.

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Why are social media users blocking celebrities and influencers on TikTok? A look at the #Blockout movement

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Each year the Met Gala marks the intersection of Hollywood and the fashion industry, with stars like Zendaya, Jennifer Lopez and Kim Kardashian taking their typical red carpet looks to new heights. But not everyone was thrilled about the so-called “Hollywood’s Prom” this year , with dozens of pro-Palestinian protesters outside the event hoping to get those inside to acknowledge Israel’s war in Gaza.

Now, more people are taking their protests to social media — and those behind the movement say the results could impact the money stars and influencers make from these platforms.

Why are people angry with the Met Gala attendees?

While many people applauded the looks , social media users called out the Met Gala this year for its bold display of wealth and opulence while the Israeli war in Gaza still raged.

Social media users have since been cutting off celebrities from their bread and butter (aka, online capital) in the wake of the Met Gala, with the help of widely spreading digital campaigns.

"The Met Gala was a bit of a hyperbolic moment that got a lot of people's attention," Marcus Collins, an assistant professor of marketing at the University of Michigan, told NPR of the digital campaigns. "The celebrity boycotts had existed, but they weren't really at the top of the social zeitgeist. But then you have a moment like the Met Gala that wasn't really related to the conflict, but the pieces were all at play. When the attacks [in Gaza] were happening the same day, the juxtaposition just got people talking and moving."

What #Blockout2024 means

After the Met Gala, TikToker @BlockOut2024 posted a video encouraging users to block celebrities on social media , preventing them from making money from ad revenue, as a way to offer pushback to their silence on the crisis in Gaza. He noted that he had blocked Kim Kardashian (a Met Gala staple) back in December 2023.

Social media users quickly picked up on the trend, posting videos of who they were specifically targeting to block alongside the hashtags #blockout, #digitine and #celebrityblock.

And @BlockOut2024 wasn’t the only user who created a digital campaign to cut off celebrities online.

What does Marie Antoinette have to do with this?

At a hotel prior to the Met Gala, for which she was hired as a host, TikToker Haley Kalil — who boasts 9.9 million followers on the app — posted a TikTok using audio of the phrase “Let them eat cake” from the 2006 movie Marie Antoinette. The real French queen Marie Antoinette (to whom the phrase is often attributed but who probably never actually said it, per historians) was ultimately beheaded by guillotine during the French Revolution primarily due to her association with the monarchy, which was seen as out of touch with the needs of the people.

Kalil’s video sparked the creation of the “digitine,” or digital guillotine, coined by TikToker @LadyFromTheOutside . “It’s time to block all the celebrities, influencers and wealthy socialites who are not using their resources to help those in dire need,” she said in her video, which received more than 500,000 likes on the platform, as well as hundreds of encouraging comments.

Who is being blocked?

Based on social media posts, users are blocking a wide range of stars like Harry Styles, Jojo Siwa, Ellen DeGeneres, Kevin Hart, Shakira, Kylie Jenner and Taylor Swift. However, people share thoughts on the different stars they are blocking daily.

What impact has this unfollowing had on celebrities?

Thus far, any real impact has yet to be seen. However, #Blockout2024 claims celebrities have been losing a significant amount of followers.

In theory, celebrities (as well as influencers, who are also on these lists) will be impacted by a lack of users engaging with their content, as well as the drop in followers if people who blocked them previously followed their content online.

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The Disparate Impact of Social Media on Global Politics

S ocial media has woven itself into the fabric of political discourse, acting as a double-edged sword that both empowers and undermines democratic processes worldwide. A deep dive into this phenomenon reveals a complex landscape where social media’s influence varies significantly based on political systems, regional stability, and the actors involved.

At the heart of social media’s impact on politics are three distinct user cohorts: the domestic opposition, which includes dissidents and populist candidates; external forces such as other nation-states and multinational entities; and the governing regimes themselves. Each exploits social media’s vast reach for varying agendas—from mobilizing support to disseminating propaganda.

In weak authoritarian states, social media has occasionally played a destabilizing role, offering a powerful platform for coordination and mobilization against oppressive governments. The Arab Spring provides a prime example, where platforms like Twitter and Facebook helped galvanize public sentiment and organize protests that led to significant political changes.

In stark contrast, weak democratic states face radicalization through social media. Populist movements, utilizing platforms like WhatsApp and Facebook, have bypassed traditional media to spread divisive and often misleading information, sometimes with the assistance of foreign interference. This has led to a troubling shift toward illiberalism and autocracy in places like Brazil, where President Jair Bolsonaro’s rise to power was significantly buoyed by a social media campaign rife with misinformation.

Strong authoritarian regimes have leveraged social media as a tool of intensification, enhancing their surveillance and control measures to fortify their hold on power. Russia’s efforts to control the online narrative within its borders and its alleged meddling in the democratic processes of other nations via social media mark a dangerous new front in information warfare.

Meanwhile, strong democratic regimes experience a weakening effect, where the proliferation of fake news and polarizing content challenges the integrity of their political processes and institutions. The 2016 U.S. presidential election and the Brexit referendum in the UK are cases in point, where the role of external forces and domestic populism, facilitated by social media, stoked division and mistrust among the populace.

Relevant articles:

– Analysis of millions of posts shows that users seek out echo chambers on social media , Phys.org

– The echo chamber effect on social media , National Institutes of Health (NIH) (.gov)

– The Echo Chamber Effect: Social Media’s Role in Political Bias , Institute for Youth in Policy

– The Political Effects of Social Media Platforms on Different Regime Types , Texas National Security Review

Man or bear? Hypothetical question sparks conversation about women's safety

Women explain why they would feel safer encountering a bear in the forest than a man they didn't know. the hypothetical has sparked a broader discussion about why women fear men..

If you were alone in the woods, would you rather encounter a bear or a man? Answers to that hypothetical question have sparked a debate about why the vast majority say they would feel more comfortable choosing a bear.

The topic has been hotly discussed for weeks as men and women chimed in with their thoughts all over social media.

Screenshot HQ , a TikTok account, started the conversation, asking a group of women whether they would rather run into a man they didn't know or a bear in the forest. Out of the seven women interviewed for the piece, only one picked a man.

"Bear. Man is scary," one of the women responds.

A number of women echoed the responses given in the original video, writing in the comments that they, too, would pick a bear over a man. The hypothetical has people split, with some expressing their sadness over the state of the world and others cracking jokes. Some men were flabbergasted.

Here's what we know.

A bear is the safer choice, no doubt about it, many say

There were a lot of responses, more than 65,000, under the original post. Many wrote that they understood why the women would choose a bear.

"No one’s gonna ask me if I led the bear on or give me a pamphlet on bear attack prevention tips," @celestiallystunning wrote.

@Brennduhh wrote: "When I die leave my body in the woods, the wolves will be gentler than any man."

"I know a bear's intentions," another woman wrote. "I don't know a man's intentions. no matter how nice they are."

Other TikTok users took it one step further, posing the hypothetical question to loved ones. Meredith Steele, who goes by @babiesofsteele , asked her husband last week whether he would rather have their daughter encounter a bear or a man in the woods. Her husband said he "didn't like either option" but said he was leaning toward the bear.

"Maybe it's a friendly bear," he says.

Diana, another TikTok user , asked her sister-in-law what she would choose and was left speechless.

"I asked her the question, you know, just for giggles. She was like, 'You know, I would rather it be a bear because if the bear attacks me, and I make it out of the woods, everybody’s gonna believe me and have sympathy for me," she said. "But if a man attacks me and I make it out, I’m gonna spend my whole life trying to get people to believe me and have sympathy for me.'"

Bear vs. man debate stirs the pot, woman and some men at odds

The hypothetical has caused some tension, with some women arguing that men will never truly understand what it's like to be a woman or the inherent dangers at play.

Social media users answered this question for themselves, producing memes, spoken word poetry and skits in the days and weeks since.

So, what would you choose?

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Pop Culture

The met gala has fueled backlash against stars who are silent about the gaza conflict.

Chloe Veltman

Zendaya at the 2024 Met Gala in New York City. The actress is one of many celebrities whose name has appeared this week on social media "block" lists for not speaking out publicly about the conflict in Gaza. Jamie McCarthy/Getty Images hide caption

Zendaya at the 2024 Met Gala in New York City. The actress is one of many celebrities whose name has appeared this week on social media "block" lists for not speaking out publicly about the conflict in Gaza.

A collective effort on TikTok and other social media platforms to push celebrities to speak publicly about the conflict in Gaza went into overdrive this week after The Met Gala.

Creators on TikTok have earned millions of views for videos they've made linked to hashtags like #celebrityblocklist , #letthemeatcake and #blockout .

Many of these posts list the names of actors, musicians and other high-profile figures whom the video creators say had not yet spoken out against Israel's attacks on the region — or hadn't spoken out sufficiently — and therefore should be blocked.

And there's been a special push in recent days to name those who attended the opulent, star-studded annual Met Gala on Monday.

@silentcelebs8 Hoping to finish list soon!Appreciate any help! #metgala #blockout2024 #fyp #blockout #letthemeatcake #celebrityblocklist ♬ original sound-SilentCelebs🍉

"I made a Google Doc of every celebrity that attended the Met Gala, and now I'm going through and writing if they've been silent, or if they've been using their platform to speak up about the genocide in Gaza," said one TikTok user in a video displaying a long list of celebrity names against a black background with the word "SILENT" in red next to to some, including Zendaya, Nicki Minaj, Keith Urban and Andrew Scott. "Some of these celebrities have not been completely silent," the Tiktoker continued. "Zendaya did make a post back in October on her story supporting Palestine, but has been silent since. So I went ahead and put 'silent.'"

The Met Gala fans the flames

Calls on social media to boycott celebrity silences have been on a slow burn for months.

@latmpod prolly one of my last rambles on celebrity #fyp #standwith🍉 #ceasefirenow #celebrityculture #beyonce #taylorswift #rhianna ♬ original sound-look at the material podcast

But the fact the New York event, with its unchecked display of privilege and wealth, took place at around the same time as thousands of Palestinians were being forced to flee Rafah at less than 24 hours notice as Israeli troops took control of the Gaza territory's border crossing with Egypt, fanned the glowing embers into full-on flames.

"The Met Gala was a bit of a hyperbolic moment that got a lot of people's attention," said Marcus Collins, an assistant professor of marketing at the University of Michigan. "The celebrity boycotts had existed, but they weren't really at the top of the social zeitgeist. But then you have a moment like the Met Gala that wasn't really related to the conflict, but the pieces were all at play. When the attacks [in Gaza] were happening the same day, the juxtaposition just got people talking and moving."

The Picture Show

2024 met gala red carpet: looks we love.

Even relatively minor celebrities like social media influencer Hayley Baylee — who wasn't even a guest at the event, but had been hired as a pre-gala host to interview those invited as they headed to the party — were caught up in the backlash on TikTok.

Many creators posted negative reactions to a video Baylee posted of herself that night (which has since been taken down), saying, "Let them eat cake!" It was a nod, as she later admitted in a video apologizing for her actions, to a current trend on social media for looks inspired by Marie Antoinette, and a line from the 2006 film starring Kirsten Dunst, about the ill-fated French queen.

@haleyybaylee ❤️ ♬ original sound-haleyybaylee

"The world is just not peaceful or stable enough for the average person to accept and enjoy celebrities flaunting their wealth on social media," said one user on TikTok in response both to Baylee's faux-pas and the overall flaunting of wealth in New York that night. "Flexing on the peasants only works when the peasants aren't watching other peasants be wiped off the face of the planet."

The impact of blocking celebrities on the people of Gaza

The rationale behind the calls on social media to block celebrities, thereby negatively impacting their advertising revenue, is to put pressure on them to use their massive influence to try to stop the violence in Gaza.

"The hope is that it will either bring more visibility to the cause and shift the balance in getting political forces like the U.S. government to do something to mitigate the violence that's happening in the Middle East," said Collins. "But as rational as that logic may seem, I don't think there are very many examples where this has actually worked."

@christopherclaflin Should celebs bother with addressing social issues?Or should they stay in their lane?# #metgala # #metgala2024 # #letthemeatcake ♬ Let Them Eat Cake-vibeyvidz

Collins cited the example of George Clooney's efforts, albeit in an era before the rise of social media, to end the war in Sudan. A 2014 article in The Guardian by the Sudan-based journalist Maeve Shearlaw assessed the impact of the celebrity's dedicated efforts over the years to bring about change: "I don't see that it has halted, or even reduced, the genocide. The killing, displacement, sexual assaults and rape never stopped."

On the other hand, pressure on social media has occasionally impacted the ways celebrities speak out about world events. For example, the backlash against Oprah Winfrey and Dwayne "The Rock" Johnson for asking the public to donate to a Maui wildfire recovery fund last fall caused the pair to put more of their own significant resources into the effort. However, the amount they contributed was not disclosed.

The impact on everyone else

It remains to be seen whether the latest celebrity-blocking social media campaign will bring about positive change for the people of Gaza.

But some experts say the fact that it doesn't directly target the issue, but rather focuses on which celebrities are remaining silent, obscures the desired goal.

Middle East crisis — explained

Israeli forces seize the gaza side of rafah, as hamas truce talks resume in egypt.

"That's not what we're debating on and trending about and talking about and arguing about," said Chris Morse, a communications professor at Bryant University. "It's the fact that Celebrity A won't tell us their stance. Isn't that weird that they won't do that? Let's boycott them until they do do that."

Indeed — while the number of blocks to an account is not visible — some stars have seen a fall-off in followers over the past week. For example, Taylor Swift, who's at the top of many of the block lists, lost around 300,000 followers on TikTok over the past week, according to a comparison between her TikTok follower number at the time of writing and the number obtained from last week via Wayback Machine , and around 50,000 on Instagram . But that's nothing for a star of Swift's magnitude.

"A large celebrity has their touring, has multiple large social channels, is featured on television, is featured in the press," said Eric Dahan, CEO of the social media marketing company Mighty Joy. "If you have north of 100 million followers and you lose three or five million, it sucks. But is that the end of the world for you? No."

Dahan added that blocking celebrities doesn't prevent them from appearing in targeted social media ad campaigns.

When celebrities show up to protest, the media follows — but so does the backlash

"Blocking an account doesn't prevent you from receiving an ad, because the ad is not run through the celebrity's account per se," said Dahan. "And so, for example, you can block Kim Kardashian, but Hulu could run an ad targeting the Kardashians at you."

Meanwhile, controversies involving celebrities very often bring attention to social media platforms.

"TikTok definitely benefits, right? Because the trend is happening on their format," said Bryant University's Morse. "We are constantly mentioning TikTok in all of the stories, and that makes people curious in order to see the trend and see what people are doing. So you got to go to TikTok, and you really got to become a member because you can't really see too many things without actually engaging with the platform."

TikTok did not immediately respond to NPR's request for comment.

And even if the many, much-viewed videos aimed at canceling celebrities don't help to bring about a change for the people of Gaza, there's at least an emotional reward for those doing the canceling.

"It does provide some sense of agency," said the University of Michigan's Collins. "A sense that I've done something to influence other people to do something that perhaps maybe might make a difference. Because in the minds of those folks, it's better than doing nothing."

• haley baylee
• Dwayne 'The Rock' Johnson
• Taylor Swift
• george clooney
• social media
• #celebrityblocklist