thesis for negative 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: 07 May 2024

Mechanisms linking social media use to adolescent mental health vulnerability

• Amy Orben   ORCID: orcid.org/0000-0002-2937-4183 1 ,
• Adrian Meier   ORCID: orcid.org/0000-0002-8191-2962 2 ,
• Tim Dalgleish   ORCID: orcid.org/0000-0002-7304-2231 1 &
• Sarah-Jayne Blakemore 3 , 4  

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Research linking social media use and adolescent mental health has produced mixed and inconsistent findings and little translational evidence, despite pressure to deliver concrete recommendations for families, schools and policymakers. At the same time, it is widely recognized that developmental changes in behaviour, cognition and neurobiology predispose adolescents to developing socio-emotional disorders. In this Review, we argue that such developmental changes would be a fruitful focus for social media research. Specifically, we review mechanisms by which social media could amplify the developmental changes that increase adolescents’ mental health vulnerability. These mechanisms include changes to behaviour, such as sharing risky content and self-presentation, and changes to cognition, such as modifications in self-concept, social comparison, responsiveness to social feedback and experiences of social exclusion. We also consider neurobiological mechanisms that heighten stress sensitivity and modify reward processing. By focusing on mechanisms by which social media might interact with developmental changes to increase mental health risks, our Review equips researchers with a toolkit of key digital affordances that enables theorizing and studying technology effects despite an ever-changing social media landscape.

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Introduction.

Adolescence is a period marked by profound neurobiological, behavioural and environmental changes that facilitate the transition from familial dependence to independent membership in society 1 , 2 . This critical developmental stage is also characterized by diminished well-being and increased vulnerability to the onset of mental health conditions 3 , 4 , 5 , particularly socio-emotional disorders such as depression, and eating disorders 4 , 6 (Fig. 1 ). Notable symptoms of socio-emotional disorders include heightened negative affect, mood dysregulation and an increased focus on distress or challenges concerning interpersonal relationships, including heightened sensitivity to peers or perceptions of others 6 . Although some risk factors for socio-emotional disorders do not necessarily occur in adolescence (including genetic predispositions, adverse childhood experiences and poverty 7 , 8 , 9 ), the unique developmental characteristics of this period of life can interact with pre-existing vulnerabilities, increasing the risk of disorder onset 10 .

Meta-analytic proportion of age of onset of anxiety (red), obsessive-compulsive disorder (purple), eating disorders (orange), personality disorders (green), schizophrenia (grey) and mood disorders (blue). The peak age of onset (dotted lines) is 5.5 and 15.5 years for anxiety, 14.5 years for obsessive-compulsive disorder, 15.5 years for eating disorders and 20.5 years for personality disorders, schizophrenia and mood disorders. Adapted from ref. 258 , CC BY 4.0 ( https://creativecommons.org/licenses/by/4.0/ ).

Over the past decade, declines in adolescent mental health have become a great concern 11 , 12 . The prevalence of socio-emotional disorders has increased in the adolescent age range (10–24 years 2 ) 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , leading to mounting pressures on child and adolescent mental health services 16 , 21 , 22 . This increase has not been as pronounced among other age groups when compared with adolescents 20 , 22 , 23 (measured in ref.  20 , ref.  22 and ref.  23 as age 12–25 years, 12–20 years and 18–25 years, respectively), even if some studies have found increases across the entire lifespan 24 , 25 . Although these trends might not be generalizable across the world 26 or to subclinical indicators of distress 15 , similar trends have been found in a range of countries 27 . Declines in adolescent mental health, especially socio-emotional problems, are consistent across datasets and researchers have argued that they are not solely driven by changes in social attitudes, stigma or reporting of distress 28 , 29 .

Concurrently, adolescents’ lives have become increasingly digital, with most young people using social media platforms throughout the day 30 . Ninety-five per cent of UK adolescents aged 15 years use social media 31 , and 50% of US adolescents aged 13–17 years report being almost constantly online 32 . The social media environment impacts adolescent and adult life across many domains (for example, by enabling social communication or changing the way news is accessed) and influences individuals, dyads and larger social systems 33 , 34 , 35 , 36 . Because social media is inherently social and relational 37 , it potentially overlaps and interacts with the developmental changes that make adolescents vulnerable to the onset of mental health problems 38 , 39 (Fig. 2 ). Thus, it has been intensely debated whether the increase in social media use during the past decade has a causal role in the decline of adolescent mental health 40 . Indeed, rapid changes to the environment experienced before and during adolescence might be a fruitful area to explore when examining current mental health trends 41 .

During adolescence, the interaction between genetic programming (yellow), social determinants (red) and environmental factors (blue), as well as the developmental changes discussed in this Review, increases the risk for onset of mental health conditions. Digital environments, mediated behaviours and experiences, and the impact that this technology has on society and economy more generally, are one aspect of the complex forces that might lead to the declines in adolescent mental health observed in the last decade. Adapted from ref. 259 , Springer Nature Limited.

Although there are many environmental changes that could be relevant, a substantial body of research has emerged to investigate the potential link between social media use and declines in adolescent mental health 42 , 43 using various research approaches, including cross-sectional studies 44 , longitudinal observational data analyses 45 , 46 , 47 and experimental studies 48 , 49 . However, the scientific results have been mixed and inconclusive (for reviews, see refs. 43 , 50 , 51 , 52 , 53 ), which has made it difficult to establish evidence-based recommendations, regulations and interventions aimed at ensuring that social media use is not harmful to adolescents 54 , 55 , 56 , 57 .

Many researchers attribute the mixed results to insufficient study specificity. For instance, the relationship between social media use and mental health varies notably across individuals 45 , 58 and developmental time windows 59 . Yet studies often examine adolescents without differentiating them based on age or developmental stage 60 , which prevents systematic accounts of individual and subgroup differences. Additionally, most studies only rely on self-reported measures of time spent on social media 61 , 62 , and overlook more nuanced aspects of social media use such as the nature of the activities 63 and the content or features that users engage with 52 . These factors need to be considered to unpack any broader relationships 35 , 64 , 65 , 66 . Furthermore, the measurement of mental health often conflates positive and negative mental health outcomes as well as various mental health conditions, which could all be differentially related to social media use 52 , 67 .

This research space presents substantial complexity 68 . There is an ever-increasing range of potential combinations of social media predictors, well-being and mental health outcomes and participant groups of varying backgrounds and demographics that can become the target of scientific investigation. However, the pressure to deliver policy and public-facing recommendations and interventions leaves little time to investigate comprehensively each of these combinations. Researchers need to be able to pinpoint quickly the research programmes with the maximum potential to create translational and real-world impact for adolescent mental health.

In this Review, we aim to delineate potential avenues for future research that could lead to concrete interventions to improve adolescent mental health by considering mechanisms at the nexus between pre-existing processes known to increase adolescent mental health vulnerability and digital affordances introduced by social media. First, we describe the affordance approach to understanding the effects of social media. We then draw upon research on adolescent development, mental health and social media to describe behavioural, cognitive and neurobiological mechanisms by which social media use might amplify changes during adolescent development to increase mental health vulnerability during this period of life. The specific mechanisms within each category were chosen because they have a strong evidence base showing that they undergo substantive changes during adolescent development, are implicated in mental health risk and can be modulated by social media affordances. Although the ways in which social media can also improve mental health resilience are not the focus of our Review and therefore are not reviewed fully here, they are briefly discussed in relation to each mechanism. Finally, we discuss future research focused on how to systematically test the intersection between social media and adolescent mental health.

Social media affordances

To study the impact of social media on adolescent mental health, its diverse design elements and highly individualized uses must be conceptualized. Initial research predominately related access to or time spent on social media to mental health outcomes 46 , 69 , 70 . However, social media is not similar to a toxin or nutrient for which each exposure dose has a defined link to a health-related outcome (dose–response relationship) 56 . Social media is a diverse environment that cannot be summarized by the amount of time one spends interacting with it 71 , 72 , and individual experiences are highly varied 45 .

Previous psychological reviews often focused on social media ‘features’ 73 and ‘affordances’ 74 interchangeably. However, these terms have distinct definitions in communication science and information systems research. Social media features are components of the technology intentionally designed to enable users to perform specific actions, such as liking, reposting or uploading a story 75 , 76 . By contrast, affordances describe the perceptions of action possibilities users have when engaging with social media and its features, such as anonymity (the difficulty with which social media users can identify the source of a message) and quantifiability (how countable information is).

The term ‘affordance’ came from ecological psychology and visuomotor research, and was described as mainly determined by human perception 77 . ‘Affordance’ was later adopted for design and human–computer interaction contexts to refer to the action possibilities that are suggested to the user by the technology design 78 . Communication research synthesizes both views. Affordances are now typically understood as the perceived — and therefore flexible — action possibilities of digital environments, which are jointly shaped by the technology’s features and users’ idiosyncratic perceptions of those features 79 .

Latent action possibilities can vary across different users, uses and technologies 79 . For example, ‘stories’ are a feature of Instagram designed to share content between users. Stories can also be described in terms of affordances when users perceive them as a way to determine how long their content remains available on the platform (persistence) or who can see that content (visibility) 80 , 81 , 82 , 83 , 84 . Low persistence (also termed ephemerality) and comparatively low visibility can be achieved through a technology feature (Instagram stories), but are not an outcome of technology use itself; they are instead perceived action possibilities that can vary across different technologies, users and designs 79 .

The affordances approach is particularly valuable for theorizing at a level above individual social media apps or specific features, which makes this approach more resilient to technological changes or shifts in platform popularity 79 , 85 . However, the affordances approach can also be related back to specific types of social media by assessing the extent to which certain affordances are ‘built into’ a particular platform through feature design 35 . Furthermore, because affordances depend on individuals’ perceptions and actions, they are more aligned than features with a neurocognitive and behavioural perspective to social media use. Affordances, similar to neurocognitive and behavioural research, emphasize the role of the user (how the technology is perceived, interpreted and used) rather than technology design per se. In this sense, the affordances approach is essential to overcome technological determinism of mental health outcomes, which overly emphasizes the role of technology as the driver of outcomes but overlooks the agency and impact of the people in question 86 . This flexibility and alignment with psychological theory has contributed to the increasing popularity of the affordance approach 35 , 73 , 74 , 85 , 87 and previous reviews have explored relevant social media affordances in the context of interpersonal communication among adults and adolescents 35 , 88 , 89 , adolescent body image concerns 73 and work contexts 33 . Here, we focus on the affordances of social media that are relevant for adolescent development and its intersection with mental health (Table  1 ).

Behavioural mechanisms

Adolescents often use social media differently to adults, engaging with different platforms and features and, potentially, perceiving or making use of affordances in distinctive ways 35 . These usage differences might interact with developmental characteristics and changes to amplify mental health vulnerability (Fig.  3 ). We examine two behavioural mechanisms that might govern the impact of social media use on mental health: risky posting behaviours and self-presentation.

Social media affordances can amplify the impact that common adolescent developmental mechanisms (behavioural, cognitive and neurobiological) have on mental health. At the behavioural level (top), affordances such as permanence and publicness lead to an increased impact of risk-taking behaviour on mental health compared with similar behaviours in non-mediated environments. At the cognitive level (middle), high quantifiability influences the effects of social comparison. At the neurobiological level (bottom), low synchronicity can amplify the effects of stress on the developing brain.

Risky posting behaviour

Sensation-seeking peaks in adolescence and self-regulation abilities are still not fully developed in this period of life 90 . Thus, adolescents often engage in more risky behaviours than other age groups 91 . Adolescents are more likely to take risks in situations involving peers 92 , 93 , perhaps because they are motivated to avoid social exclusion 94 , 95 . Whether adolescent risk-taking behaviour is inherently adaptive or maladaptive is debated. Although some risk-taking behaviours can be adaptive and part of typical development, others can increase mental health vulnerability. For example, data from a prospective UK panel study of more than 5,500 young people showed that engaging in more risky behaviours (including social and health risks) at age 16 years increases the odds of a range of adverse outcomes at age 18 years, such as depression, anxiety and substance abuse 96 .

Social media can increase adolescents’ engagement in risky behaviours both in non-mediated and mediated environments (environments in which the behaviour is executed in or through a technology, such as a mobile phone and social media). First, affordances such as quantifiability in conjunction with visibility and association (the degree with which links between people, between people and content or between a presenter and their audience can be articulated) can promote more risky behaviours in non-mediated environments and in-person social interactions. For example, posts from university students containing references to alcohol gain more likes than posts not referencing alcohol and liking such posts predicts an individual’s subsequent drinking habits 97 . Users expecting likes from their audience are incentivized to engage in riskier posting behaviour (such as more frequent or more extreme posts containing references to alcohol). The relationship between risky online behaviour and offline behaviour is supported by meta-analyses that found a positive correlation between adolescents’ social media use and their engagement in behaviours that might expose them to harm or risk of injury (for example, substance use or risky sexual behaviours) 98 . Further, affordances such as persistence and visibility can mean that risky behaviours in mediated and non-mediated environments remain public for long periods of time, potentially influencing how an adolescent is perceived by peers over the longer term 39 , 99 .

Adolescence can also be a time of more risky social media use. For most forms of semi-public and public social media use, users typically do not know who exactly will be able to see their posts. Thus, adolescents need to self-present to an ‘imagined audience’ 100 and avoid posting the wrong kind of content as the boundaries between different social spheres collapse (context collapse 101 ). However, young people can underestimate the risks of disclosing revealing information in a social media environment 102 . Affordances such as visibility, replicability (social media posts remain in the system and can be screenshotted and shared even if they are later deleted 39 ), association and persistence could heighten the risk of experiencing cyberbullying, victimization and online harassment 103 . For example, adolescents can forward privately received sexual images to larger friendship groups, increasing the risk of online harassment over the subject of the sexual images 104 . Further, low bandwidth (a relative lack of socio-emotional cues) and high anonymity have the potential to disinhibit interactions between users and make behaviours and reactions more extreme 105 , 106 . For example, anonymity was associated with more trolling behaviours during an online group discussion in an experiment with 242 undergraduate students 107 .

Thus, social media might drive more risky behaviours in both mediated and non-mediated contexts, increasing mental health vulnerability. However, the evidence is still not clear cut and often discounts adolescent agency and understanding. For example, mixed-methods research has shown that young people often understand the risks of posting private or sexual content and use social media apps that ensure that posts are deleted and inaccessible after short periods of time to counteract them 39 (even though posts can still be captured in the meantime). Future work will therefore need to investigate how adolescents understand and balance such risks and how such processes relate to social media’s impact on mental health.

Self-presentation and identity

The adolescent period is characterized by an abundance of self-presentation activities on social media 74 , where the drive to present oneself becomes a fundamental motivation for engagement 108 . These activities include disclosing, concealing and modifying one’s true self, and might involve deception, to convey a desired impression to an audience 109 . Compared with adults, adolescents more frequently take part in self-presentation 102 , which can encompass both realistic and idealized portrayals of themselves 110 . In adults, authentic self-presentation has been associated with increased well-being, and inauthentic presentation (such as when a person describes themselves in ways not aligned with their true self) has been associated with decreased well-being 111 , 112 , 113 .

Several social media affordances shape the self-presentation behaviours of adolescents. For example, the editability of social media profiles enables users to curate their online identity 84 , 114 . Editability is further enhanced by highly visible (public) self-presentations. Additionally, the constant availability of social media platforms enables adolescents to access and engage with their profiles at any time, and provides them with rapid quantitative feedback about their popularity among peers 89 , 115 . People receive more direct and public feedback on their self-presentation on social media than in other types of environment 116 , 117 . The affordances associated with self-presentation can have a particular impact during adolescence, a period characterized by identity development and exploration.

Social media environments might provide more opportunities than offline environments for shaping one’s identity. Indeed, public self-presentation has been found to invoke more prominent identity shifts (substantial changes in identity) compared with private self-presentation 118 , 119 . Concerns have been raised that higher Internet use is associated with decreased self-concept clarity. Only one study of 101 adolescents as well as adults reviewed in a 2021 meta-analysis 120 showed that the intensity of Facebook use (measured by the Facebook Intensity Scale) predicted a longitudinal decline in self-concept clarity 3 months later, but the converse was not the case and changes in self-concept clarity did not predict Facebook use 121 . This result is still not enough to show a causal relationship 121 . Further, the affordances of persistence and replicability could also curtail adolescents’ ability to explore their identity freely 122 .

By contrast, qualitative research has highlighted that social media enables adolescents to broaden their horizons, explore their identity and identify and reaffirm their values 123 . Social media can help self-presentation by enabling adolescents to elaborate on various aspects of their identity, such as ethnicity and race 124 or sexuality 125 . Social media affordances such as editability and visibility can also facilitate this process. Adolescents can modify and curate self-presentations online, try out new identities or express previously undisclosed aspects of their identity 126 , 127 . They can leverage social media affordances to present different facets of themselves to various social groups by using different profiles, platforms and self-censorship and curation of posts 128 , 129 . Presenting and exploring different aspects of one’s identity can have mental health implications for minority teens. Emerging research shows a positive correlation between well-being and problematic Internet use in transgender, non-binary and gender-diverse adolescents (age 13–18 years), and positive sentiment has been associated with online identity disclosures in transgender individuals with supportive networks (both adolescent and adult) 130 , 131 .

Cognitive mechanisms

Adolescents and adults might experience different socio-cognitive impacts from the same social media activity. In this section, we review four cognitive mechanisms via which social media and its affordances might influence the link between adolescent development and mental health vulnerabilities (Fig.  3 ). These mechanisms (self-concept development, social comparison, social feedback and exclusion) roughly align with a previous review that examined self-esteem and social media use 115 .

Self-concept development

Self-concept refers to a person’s beliefs and evaluations about their own qualities and traits 132 , which first develops and becomes more complex throughout childhood and then accelerates its development during adolescence 133 , 134 , 135 . Self-concept is shaped by socio-emotional processes such as self-appraisal and social feedback 134 . A negative and unstable self-concept has been associated with negative mental health outcomes 136 , 137 .

Perspective-taking abilities also develop during adolescence 133 , 138 , 139 , as does the processing of self-relevant stimuli (measured by self-referential memory tasks, which assess memory for self-referential trait adjectives 140 , 141 ). During adolescence, direct self-evaluations and reflected self-evaluations (how someone thinks others evaluate them) become more similar. Further, self-evaluations have a distinct positive bias during childhood, but this positivity bias decreases in adolescence as evaluations of the self are integrated with judgements of other people’s perspectives 142 . Indeed, negative self-evaluations peak in late adolescence (around age 19 years) 140 .

The impact of social media on the development of self-concept could be heightened during adolescence because of affordances such as personalization of content 143 (the degree to which content can be tailored to fit the identity, preferences or expectations of the receiver), which adapts the information young people are exposed to. Other affordances with similar impacts are quantifiability, availability (the accessibility of the technology as well as the user’s accessibility through the technology) and public visibility of interactions 89 , which render the evaluations of others more prominent and omnipresent. The prominence of social evaluation can pose long-term risks to mental health under certain conditions and for some users 144 , 145 . For example, receiving negative evaluations from others or being exposed to cyberbullying behaviours 146 , 147 can, potentially, have heightened impact at times of self-concept development.

A pioneering cross-sectional study of 150 adolescents showed that direct self-evaluations are more similar to reflected self-evaluations, and self-evaluations are more negative, in adolescents aged 11–21 years who estimate spending more time on social media 148 . Further, longitudinal data have shown bidirectional negative links between social media use and satisfaction with domains of the self (such as satisfaction with family, friends or schoolwork) 47 .

Although large-scale evidence is still unavailable, these findings raise the interesting prospect that social media might have a negative influence on perspective-taking and self-concept. There is less evidence for the potential positive influence of social media on these aspects of adolescent development, demonstrating an important research gap. Some researchers hypothesize that social media enables self-concept unification because it provides ample opportunity to find validation 89 . Research has also discussed how algorithmic curation of personalized social media feeds (for example, TikTok algorithms tailoring videos viewed to the user’s interests) enables users to reflect on their self-concept by being exposed to others’ experiences and perspectives 143 , an area where future research can provide important insights.

Social comparison

Social comparison (thinking about information about other people in relation to the self 149 ) also influences self-concept development and becomes particularly important during adolescence 133 , 150 . There are a range of social media affordances that can amplify the impact of social comparison on mental health. For example, quantifiability enables like or follower counts to be easily compared with others as a sign of status, which facilitates social ranking 151 , 152 , 153 , 154 . Studies of older adolescents and adults aged, on average, 20 years have also found that the number of likes or reactions received predict, in part, how successful users judge their self-presentation posts on Facebook 155 . Furthermore, personalization enables the content that users see on social media to be curated so as to be highly relevant and interesting for them, which should intensify comparisons. For example, an adolescent interested in sports and fitness content will receive personalized recommendations fitting those interests, which should increase the likelihood of comparisons with people portrayed in this content. In turn, the affordance of association can help adolescents surround themselves with similar peers and public personae online, enhancing social comparison effects 63 , 156 . Being able to edit posts (via the affordance of editability) has been argued to contribute to the positivity bias on social media: what is portrayed online is often more positive than the offline experience. Thus, upward comparisons are more likely to happen in online spaces than downward or lateral comparisons 157 . Lastly, the verifiability of others’ idealized self-presentations is often low, meaning that users have insufficient cues to gauge their authenticity 158 .

Engaging in comparisons on social media has been associated with depression in correlational studies 159 . Furthermore, qualitative research has shown that not receiving as many positive evaluations as expected (or if positive evaluations are not provided quickly enough) increases negative emotions in children and adolescents aged between age 9 and 19 years 39 . This result aligns with a reinforcement learning modelling study of Instagram data, which found that the likes a user receives on their own posts become less valuable and less predictive of future posting behaviour if others in their network receive more likes on their posts 160 . Although this study did not measure mood or mental health, it shows that the value of the likes are not static but inherently social; their impact depends on how many are typically received by other people in the same network.

Among the different types of social comparison that adolescents engage in (comparing one’s achievements, social status or lifestyle), the most substantial concerns have been raised about body-related comparisons. One review suggested that social media affordances create a ‘perfect storm’ for body image concerns that can contribute to both socio-emotional and eating disorders 73 . Social media affordances might increase young people’s focus on other people’s appearances as well as on their own appearance by showing idealized, highly edited images, providing quantified feedback and making the ability to associate and compare oneself with peers constantly available 161 , 162 . The latter puts adolescents who are less popular or receive less social support at particular risk of low self-image and social distress 35 .

Affordances enable more prominent and explicit social comparisons in social media environments relative to offline environments 158 , 159 , 163 , 164 , 165 . However, this association could have a positive impact on mental health 164 , 166 . Initial evidence suggests beneficial outcomes of upward comparisons on social media, which can motivate behaviour change and yield positive downstream effects on mental health 164 , 166 . Positive motivational effects (inspiration) have been observed among young adults for topics such as travelling and exploring nature, as well as fitness and other health behaviours, which can all improve mental health 167 . Importantly, inspiration experiences are not a niche phenomenon on social media: an experience sampling study of 353 Dutch adolescents (mean age 13–15 years) found that participants reported some level of social media-induced inspiration in 33% of the times they were asked to report on this over the course of 3 weeks 168 . Several experimental and longitudinal studies show that inspiration is linked to upward comparison on social media 157 , 164 , 166 . However, the positive, motivating side of social comparison on social media has only been examined in a few studies and requires additional investigation.

Social feedback

Adolescence is also a period of social reorientation, when peers tend to become more important than family 169 , peer acceptance becomes increasingly relevant 170 , 171 , 172 and young people spend increasing amounts of time with peers 173 . In parallel, there is a heightened sensitivity to negative socio-emotional or self-referential cues 140 , 174 , higher expectation of being rejected by others 175 and internalization of such rejection 142 , 176 compared with other phases in life development. A meta-analysis of both adolescents and adults found that oversensitivity to social rejection is moderately associated with both depression and anxiety 177 .

Social media affordances might amplify the potential impact of social feedback on mental health. Wanting to be accepted by peers and increased susceptibility to social rewards could be a motivator for using social media in the first place 178 . Indeed, receiving likes as social reward activated areas of the brain (such as the nucleus accumbens) that are also activated by monetary reward 179 . Quantifiability amplifies peer acceptance and rejection (via like counts), and social rejection has been linked to adverse mental health outcomes 170 , 180 , 181 , 182 . Social media can also increase feelings of being evaluated, the risk of social rejection and rumination about potential rejection due to affordances such as quantifiability, synchronicity (the degree to which an interaction happens in real time) and variability of social rewards (the degree to which social interaction and feedback occur on variable time schedules). For example, one study of undergraduate students found that active communication such as messaging was associated with feeling better after Facebook use; however, this was not the case if the communication led to negative feelings such as rumination (for example, after no responses to the messages) 183 .

In a study assessing threatened social evaluation online 184 , participants were asked to record a statement about themselves and were told their statements would be rated by others. To increase the authenticity of the threat, participants were asked to rate other people’s recordings. Threatened social evaluation online in this study decreased mood, most prominently in people with high sensitivity to social rejection. Adolescents who are more sensitive to social rejection report more severe depressive symptoms and maladaptive ruminative brooding in both mediated and non-mediated social environments, and this association is most prominent in early adolescence 185 . Not receiving as much online social approval as peers led to more severe depressive symptoms in a study of American ninth-grade adolescents (between age 14 and 15 years), especially those who were already experiencing peer victimization 153 . Furthermore, individuals with lower self-esteem post more negative and less positive content than individuals with higher self-esteem. Posted negative content receives less social reward and recognition from others than positive content, possibly creating a vicious cycle 186 . Negative experiences pertaining to social exclusion and status are also risk factors for socio-emotional disorders 180 .

The impact of social media experiences on self-esteem can be very heterogeneous, varying substantially across individuals. As a benefit, positive social feedback obtained via social media can increase users’ self-esteem 115 , an association also found among adolescents 187 . For instance, receiving likes on one’s profile or posted photographs can bolster self-esteem in the short term 144 , 188 . A study linking behavioural data and self-reports from Facebook users found that receiving quick responses on public posts increased a sense of social support and decreased loneliness 189 . Furthermore, a review of reviews consistently documented that users who report more social media use also perceive themselves to have more social resources and support online 52 , although this association has mostly been studied among young adults using social network sites such as Facebook. Whether such social feedback benefits extend to adolescents’ use of platforms centred on content consumption (such as TikTok or Instagram) is an open question.

Social inclusion and exclusion

Adolescents are more sensitive to the negative emotional impacts of being excluded than are adults 170 , 190 . It has been proposed that, as the importance of social affiliation increases during this period of life 134 , 191 , 192 , adolescents are more sensitive to a range of social stimuli, regardless of valence 193 . These include social feedback (such as compliments or likes) 95 , 194 , negative socio-emotional cues (such as negative facial expressions or social exclusion) 174 and social rejection 172 , 185 . By contrast, social inclusion (via friendships in adolescence) is protective against emotional disorders 195 and more social support is related to higher adolescent well-being 196 .

Experiencing ostracism and exclusion online decreases self-esteem and positive emotion 197 . This association has been found in vignette experiments where participants received no, only a few or a lot of likes 198 , or experiments that used mock-ups of social media sites where others received more likes than participants 153 . Being ostracized (not receiving attention or feedback) or rejected through social media features (receiving dislikes and no likes) is also associated with a reduced sense of belonging, meaningfulness, self-esteem and control 199 . Similar results were found when ostracism was experienced over messaging apps, such as not receiving a reply via WhatsApp 200 .

Evidence on whether social media also enables adolescents to experience positive social inclusion is mostly indirect and mixed. Some longitudinal surveys have found that prosocial feedback received on social media during major life events (such as university admissions) helps to buffer against stress 201 . Adult participants of a longitudinal study reported that social media offered more informational support than offline contexts, but offline contexts more often offered emotional or instrumental support 202 . Higher social network site use is, on average, associated with a perception of having more social resources and support in adults (for an overview of meta-analyses, see ref. 52 ). However, most of these studies have not investigated social support among adolescents, and it is unclear whether early findings (for example, on Facebook or Twitter) generalize to a social media landscape more strongly characterized by content consumption than social interaction (such as Instagram or TikTok).

Still, a review of social media use and offline interpersonal outcomes among adolescents documents both positive (sense of belonging and social capital) and negative (alienation from peers and perceived isolation) correlates 203 . Experience sampling research on emotional support among young adults has further shown that online social support is received and perceived as effective, and its perceived effectiveness is similar to in-person social support 204 . Social media use also has complex associations with friendship closeness among adolescents. For example, one experience sampling study found that greater use of WhatsApp or Instagram is associated with higher friendship closeness among adolescents; however, within-person examinations over time showed small negative associations 205 .

Neurobiological mechanisms

The long-term impact of environmental changes such as social media use on mental health might be amplified because adolescence is a period of considerable neurobiological development 95 (Fig.  3 ). During adolescence, overall cortical grey matter declines and white matter increases 206 , 207 . Development is particularly protracted in brain regions associated with social cognition and executive functions such as planning, decision-making and inhibiting prepotent responses. The changes in grey and white matter are thought to reflect axonal growth, myelination and synaptic reorganization, which are mechanisms of neuroplasticity influenced by the environment 208 . For example, research in rodents has demonstrated that adolescence is a sensitive period for social input, and that social isolation in adolescence has unique and more deleterious consequences for neural, behavioural and mental health development than social isolation before puberty or in adulthood 206 , 209 . There is evidence that brain regions involved in motivation and reward show greater activation to rewarding and motivational stimuli (such as appetitive stimuli and the presence of peers) in early and/or mid adolescence compared with other age groups 210 , 211 , 212 , 213 , 214 .

Little is known about the potential links between social media and neurodevelopment due to the paucity of research investigating these associations. Furthermore, causal chains (for example, social media increasing stress, which in turn influences the brain) have not yet been accurately delineated. However, it would be amiss not to recognize that brain development during adolescence forms part of the biological basis of mental health vulnerability and should therefore be considered. Indeed, the brain is proposed to be particularly plastic in adolescence and susceptible to environmental stimuli, both positive and negative 208 . Thus, even if adults and adolescents experienced the same affective consequences from social media use (such as increases in peer comparison or stress), these consequences might have a greater impact in adolescence.

A cross-sectional study (with some longitudinal elements) suggested that habitual checking of social media (for example, checking for rewards such as likes) might exacerbate reward sensitivity processes, leading to long-term hypersensitization of the reward system 215 . Specifically, frequently checking social media was associated with reduced activation in brain regions such as the dorsolateral prefrontal cortex and the amygdala in response to anticipated social feedback in young people. Brain activation during the same social feedback task was measured over subsequent years. Upon follow-up, anticipating feedback was associated with increased activation of the same brain regions among the individuals who checked social media frequently initially 215 . Although longitudinal brain imaging measurements enabled trajectories of brain development to be specified, the measures of social media use were only acquired once in the first wave of data collection. The study therefore cannot account for confounds such as personality traits, which might influence both social media checking behaviours and brain development. Other studies of digital screen use and brain development have found no impact on adolescent functional brain organization 216 .

Brain development and heightened neuroplasticity 208 render adolescence a particularly sensitive period with potentially long-term impacts into adulthood. It is possible that social media affordances that underpin increased checking and reward-seeking behaviours (such as quantifiability, variability of social rewards and permanent availability of peers) might have long-term consequences on reward processing when experienced during adolescence. However, this suggestion is still speculative and not backed up by evidence 217 .

Stress is another example of the potential amplifying effect of social media on adolescent mental health vulnerability due to neural development. Adolescents show higher stress reactivity because of maturational changes to, and increased reactivity in, the hypothalamic–pituitary–adrenal axis 218 , 219 . Compared with children and adults, adolescents experience an increase in self-consciousness and associated emotional states such as self-reported embarrassment and related physiological measures of arousal (such as skin conductance), and heightened neural response patterns compared with adults, when being evaluated or observed by peers 220 . Similarly, adolescents (age 13–17 years) show higher stress responses (higher levels of cortisol or blood pressure) compared with children (age 7–12 years) when they perform in front of others or experience social rejection 221 .

Such changes in adolescence might confer heightened risk for the onset of mental health conditions, especially socio-emotional disorders 6 . Both adolescent rodents and humans show prolonged hypothalamic–pituitary–adrenal activation after experiencing stress compared with conspecifics of different ages 218 , 219 . In animal models, stress during adolescence has been shown to result in increased anxiety levels in adulthood 222 and alterations in emotional and cognitive development 223 . Furthermore, human studies have linked stress in adolescence to a higher risk of mental health disorder onset 218 and reviews of cross-species work have illustrated a range of brain changes due to adolescent stress 224 , 225 .

There is still little conclusive neurobiological evidence about social media use and stress, and a lack of understanding about which affordances might be involved (although there has been a range of work studying digital stress; Box  1 ). Studies of changes in cortisol levels or hypothalamic–pituitary–adrenal functioning and their relation to social media use have been mixed and inconclusive 226 , 227 . These results could be due to the challenge of studying stress responses in adolescents, particularly as cortisol fluctuates across the day and one-point readings can be unreliable. However, the increased stress sensitivity during the adolescent developmental period might mean that social media use can have a long-term influence on mental health due to neurobiological mechanisms. These processes are therefore important to understand in future research.

Box 1 Digital stress

Digital stress is not a unified construct. Thematic content analyses have categorized digital stress into type I stressors (for example, mean attacks, cyberbullying or shaming) and type II stressors (for example, interpersonal stress due to pressure to stay available) 260 . Other reviews have noted its complexity, and categorized digital stress into availability stress (stress that results from having to be constantly available), approval anxiety (anxiety regarding others’ reaction to their own profile, posts or activities online), fear of missing out (stress about being absent from or not experiencing others’ rewarding experiences) and communication overload (stress due to the scale, intensity and frequency of online communication) 261 .

Digital stress has been systematically linked to negative mental health outcomes. Higher digital stress was longitudinally associated with higher depressive symptoms in a questionnaire study 262 . Higher social media stress was also longitudinally related to poorer sleep outcomes in girls (but not boys) 263 . Studies and reviews have linked cyberbullying victimization (a highly stressful experience) to decreased mental health outcomes such as depression, and psychosocial outcomes such as self-esteem 103 , 146 , 147 , 264 , 265 . A systematic review of both adolescents and adults found a medium association ( r  = 0.26–0.34) between different components of digital stress and psychological distress outcomes such as anxiety, depression or loneliness, which was not moderated by age or sex (except for connection overload) 266 . However, the causal structure giving rise to such results is still far from clear. For example, surveys have linked higher stress levels to more problematic social media use and fear of missing out 267 , 268 .

Thus, the impact of digital stress on mental health is probably complex and influenced by the type of digital stressor and various affordances. For example, visibility and availability increase fear of negative public evaluation 269 and high availability and a social norm of responding quickly to messages drive constant monitoring in adolescents due to a persistent fear of upsetting friends 270 .

A range of relevant evidence from qualitative and quantitative studies documents that adolescents often ruminate about online interactions and messages. For example, online salience (constantly thinking about communication, content or events happening online) was positively associated with stress on both between-person and within-person levels in a cross-sectional quota sample of adults and three diary studies of young adults 271 , 272 . Online salience has also been associated with lower well-being in a pre-registered study of momentary self-reports from young adults with logged online behaviours. However, this study also noted that positive thoughts were related to higher well-being 273 . Furthermore, although some studies found no associations between the amount of communication and digital stress 272 , a cross-sectional study found that younger users’ (age 14–34 years and 35–49 years) perception of social pressure to be constantly available was related to communication load (measured by questions about the amount of use, as well as the urge to check email and social media) and Internet multitasking, whereas this was not the case for older users aged 50–85 years 274 . By contrast, communication load and perceived stress were associated only among older users.

Summary and future directions

To help to understand the potential role of social media in the decline of adolescent mental health over the past decade, researchers should study the mechanisms linking social media, adolescent development and mental health. Specifically, social media environments might amplify the socio-cognitive processes that render adolescents more vulnerable to mental health conditions in the first place. We outline various mechanisms at three levels of adolescent development — behavioural, cognitive and neurobiological — that could be involved in the decline of adolescent mental health as a function of social media engagement. To do so, we delineate specific social media affordances, such as quantification of social feedback or anonymity, which can also have positive impacts on mental health.

Our Review sets out clear recommendations for future research on the intersection of social media and adolescent mental health. The foundation of this research lies in the existing literature investigating the underlying processes that heighten adolescents’ risk of developing socio-emotional disorders. Zooming in on the potential mechanistic targets impacted by social media uses and affordances will produce specific research questions to facilitate controlled and systematic scientific inquiry relevant for intervention and translation. This approach encourages researchers to pinpoint the mechanisms and levels of explanation they want to include and will enable them to identify what factors to additionally consider, such as participants’ age 60 , the specific mental health outcomes being measured, the types of social media being examined and the populations under study 52 , 228 . Targeted and effective research should prioritize the most promising areas of study and acknowledge that all research approaches have inherent limitations 229 . Researchers must embrace methodological diversity, which in turn will facilitate triangulation. Surveys, experience sampling designs in conjunction with digital trace data, as well as experimental or neuroimaging paradigms and computational modelling (such as reinforcement learning) can all be used to address research questions comprehensively 230 . Employing such a multi-method approach enables the convergence of evidence and strengthens the reliability of findings 231 .

Mental health and developmental research can also become more applicable to the study of social media by considering how studies might already be exploring features of the digital environment, such as its design features and perceived affordances. Many cognitive neuroscience studies that investigate social processes and mental health during adolescence necessarily design tasks that can be completed in controlled experimental or brain scanning environments. Consequently, they tend to focus on digitally mediated interactions. However, researchers conceptualize and generalize their results to face-to-face interactions. For example, it is common across the discipline to not explicitly describe the interactions under study as being about social processes in digital environments (such as studies that assess social feedback based on the number of ‘thumbs up’ or ‘thumbs down’ received in social media 232 ). Considering whether cognitive neuroscience studies include key affordances of mediated (or non-mediated) environments, and discussing these in published papers, will make studies searchable within the field of social media research, enabling researchers to broaden the impact of their work and systematically specify generalizations to offline environments 233 .

To bridge the gap between knowledge about mediated and non-mediated social environments, it is essential to directly compare the two 233 . It is often assumed that negative experiences online have a detrimental impact on mental health. However, it remains unclear whether this mechanism is present in both mediated and non-mediated spaces or whether it is specific to the mediated context. For instance, our Review highlights that the quantification of social feedback through likes is an important affordance of social media 160 . Feedback on social media platforms might therefore elicit a greater sense of certainty because it is quantified compared with the more subjective and open-to-interpretation feedback received face to face 151 . Conducting experiments in which participants receive feedback that is more or less quantified and uncertain, specifically designed to compare mediated and non-mediated environments, would provide valuable insights. Such research efforts could also establish connections with computational neuroscience studies demonstrating that people tend to learn faster from stimuli that are less uncertain 234 .

We have chosen not to make recommendations concerning interventions targeting social media use to improve adolescent mental health for several reasons. First, we did not fully consider the bidirectional interactions between environment and development 35 , 235 , or the factors modulating adolescents’ differential susceptibility to the effects of social media 45 , 58 . For example, mental health status also influences how social media is used 47 , 58 , 59 , 236 , 237 (Box  2 ). These bidirectional interactions could be addressed using network or complexity science approaches 238 . Second, we do not yet know how the potential mechanisms by which social media might increase mental health vulnerability compare in magnitude, importance, scale and ease and/or cost of intervention with other factors and mechanisms that are already well known to influence mental health, such as poverty or loneliness. Last, social media use will probably interact with these predictors in ways that have not been delineated and can also support mental health resilience (for example, through social support or online self-help programmes). These complexities should be considered in future research, which will need to pinpoint not just the existence of mechanisms but their relative importance, to identify policy and intervention priorities.

Our Review has used a broad definition of mental health. Focusing on specific diagnostic or transdiagnostic symptomatology might reveal different mechanisms of interest. Furthermore, our Review is limited to mechanisms related to behaviour and neurocognitive development, disregarding other levels of explanation (such as genetics and culture) 34 , and also studying predominately Western-centric samples 239 . Mechanisms do not operate solely in linear pathways but exist within networks of interacting risk and resilience factors, characterized by non-linear and complex dynamics across diverse timescales 9 . Mechanisms and predisposing factors can interact and combine, amplifying mental health vulnerability. Mental health can be considered a dynamic system in which gradual changes to external conditions can have substantial downstream consequences due to system properties such as feedback loops 240 , 241 , 242 . These consequences are especially prominent in times of change and pre-existing vulnerability, such as adolescence 10 .

Indeed, if social media is a contributing factor to the current decline in adolescent mental health, as is commonly assumed, then it is important to identify and investigate mechanisms that are specifically tailored to the adolescent age range and make the case for why they matter. Without a thorough examination of these mechanisms and policy analysis to indicate whether they should be a priority to address, there is insufficient evidence to support the hypothesis that social media is the primary — or even just an influential and important — driver of mental health declines. Researchers need to stop studying social media as monolithic and uniform, and instead study its features, affordances and outcomes by leveraging a range of methods including experiments, questionnaires, qualitative research and industry data. Ultimately, this comprehensive approach will enhance researchers’ ability to address the potential challenges that the digital era poses on adolescent mental health.

Box 2 Effects of mental health on social media use

Although a lot of scientific discussion has focused on the impact of social media use on mental health, cross-sectional studies cannot differentiate between whether social media use is influencing mental health or mental health is influencing social media use, or a third factor is influencing both 51 . It is likely that mental health status influences social media use creating reinforcing cycles of behaviour, something that has been considered in the communication sciences literature under the term ‘transactional media effects’ 58 , 236 , 237 . According to communication science models, media use and its consequences are components of reciprocal processes 275 .

There are similar models in mental health research. For example, people’s moods influence their judgements of events, which can lead to self-perpetuating cycles of negativity (or positivity); a mechanism called ‘mood congruency’ 276 . Behavioural studies have also shown that people experiencing poor mental health behave in ways that decrease their opportunity to experience environmental reward such as social activities, maintaining poor mental health 277 , 278 . Although for many people these behaviours are a form of coping (for example, by avoiding stressful circumstances), they often worsen symptoms of mental health conditions 279 .

Some longitudinal studies found that a decrease in adolescent well-being predicted an increase in social media use 1 year later 47 , 59 . However, other studies have found no relationships between well-being and social media use over long-term or daily time windows 45 , 46 . One reason behind the heterogeneity of the results could be that how mental health impacts social media use is highly individual 45 , 280 .

Knowledge on the impact of mental health on social media use is still in its infancy and studies struggle to reach coherent conclusions. However, findings from the mental health literature can be used to generate hypotheses about how aspects of mental health might impact social media use. For example, it has been repeatedly found that young people with anxiety or eating disorders engage in more social comparisons than individuals without these disorders 281 , 282 , and adolescents with depression report more unfavourable social comparisons on social media than adolescents without depression 283 . Similar results have been found for social feedback seeking (for example, reassurance), including in social media environments 159 . Specifically, depressive symptoms were more associated with social comparison and feedback seeking, and these associations were stronger in women and in adolescents who were less popular. Individuals from the general population with lower self-esteem post more negative and less positive content than individuals with higher self-esteem, which in turn is associated with receiving less positive feedback from others 185 . There are therefore a wide range of possible ways in which diverse aspects of mental health might influence specific facets of how social media is used — and, in turn, how it ends up impacting the user.

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Acknowledgements

A.O. and T.D. were funded by the Medical Research Council (MC_UU_00030/13). A.O. was funded by the Jacobs Foundation and a UKRI Future Leaders Fellowship (MR/X034925/1). S.-J.B. is funded by Wellcome (grant numbers WT107496/Z/15/Z and WT227882/Z/23/Z), the MRC, the Jacobs Foundation, the Wellspring Foundation and the University of Cambridge.

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Just How Harmful Is Social Media? Our Experts Weigh-In.

A recent investigation by the Wall Street Journal revealed that Facebook was aware of mental health risks linked to the use of its Instagram app but kept those findings secret. Internal research by the social media giant found that Instagram worsened body image issues for one in three teenage girls, and all teenage users of the app linked it to experiences of anxiety and depression. It isn’t the first evidence of social media’s harms. Watchdog groups have identified Facebook and Instagram as avenues for cyberbullying , and reports have linked TikTok to dangerous and antisocial behavior, including a recent spate of school vandalism .

As social media has proliferated worldwide—Facebook has 2.85 billion users—so too have concerns over how the platforms are affecting individual and collective wellbeing. Social media is criticized for being addictive by design and for its role in the spread of misinformation on critical issues from vaccine safety to election integrity, as well as the rise of right-wing extremism. Social media companies, and many users, defend the platforms as avenues for promoting creativity and community-building. And some research has pushed back against the idea that social media raises the risk for depression in teens . So just how healthy or unhealthy is social media?

Two experts from Columbia University Mailman School of Public Health and Columbia Psychiatry share their insights into one crucial aspect of social media’s influence—its effect on the mental health of young people and adults. Deborah Glasofer , associate professor of psychology in psychiatry, conducts psychotherapy development research for adults with eating disorders and teaches about cognitive behavioral therapy. She is the co-author of the book Eating Disorders: What Everyone Needs to Know. Claude Mellins , Professor of medical psychology in the Departments of Psychiatry and Sociomedical Sciences, studies wellbeing among college and graduate students, among other topics, and serves as program director of CopeColumbia, a peer support program for Columbia faculty and staff whose mental health has been affected by the COVID-19 pandemic. She co-led the SHIFT research study to reduce sexual violence among undergraduates. Both use social media.

What do we know about the mental health risks of social media use?

Mellins : Facebook and Instagram and other social media platforms are important sources of socialization and relationship-building for many young people. Although there are important benefits, social media can also provide platforms for bullying and exclusion, unrealistic expectations about body image and sources of popularity, normalization of risk-taking behaviors, and can be detrimental to mental health. Girls and young people who identify as sexual and gender minorities can be especially vulnerable as targets. Young people’s brains are still developing, and as individuals, young people are developing their own identities. What they see on social media can define what is expected in ways that is not accurate and that can be destructive to identity development and self-image. Adolescence is a time of risk-taking, which is both a strength and a vulnerability. Social media can exacerbate risks, as we have seen played out in the news. 

Although there are important benefits, social media can also provide platforms for bullying and exclusion, unrealistic expectations about body image and sources of popularity, normalization of risk-taking behaviors, and can be detrimental to mental health. – Claude Mellins

Glasofer : For those vulnerable to developing an eating disorder, social media may be especially unhelpful because it allows people to easily compare their appearance to their friends, to celebrities, even older images of themselves. Research tells us that how much someone engages with photo-related activities like posting and sharing photos on Facebook or Instagram is associated with less body acceptance and more obsessing about appearance. For adolescent girls in particular, the more time they spend on social media directly relates to how much they absorb the idea that being thin is ideal, are driven to try to become thin, and/or overly scrutinize their own bodies. Also, if someone is vulnerable to an eating disorder, they may be especially attracted to seeking out unhelpful information—which is all too easy to find on social media.

Are there any upsides to social media?

Mellins : For young people, social media provides a platform to help them figure out who they are. For very shy or introverted young people, it can be a way to meet others with similar interests. During the pandemic, social media made it possible for people to connect in ways when in-person socialization was not possible.  Social support and socializing are critical influences on coping and resilience. Friends we couldn’t see in person were available online and allowed us important points of connection. On the other hand, fewer opportunities for in-person interactions with friends and family meant less of a real-world check on some of the negative influences of social media.

Whether it’s social media or in person, a good peer group makes the difference. A group of friends that connects over shared interests like art or music, and is balanced in their outlook on eating and appearance, is a positive. – Deborah Glasofer

Glasofer : Whether it’s social media or in person, a good peer group makes the difference. A group of friends that connects over shared interests like art or music, and is balanced in their outlook on eating and appearance, is a positive. In fact, a good peer group online may be protective against negative in-person influences. For those with a history of eating disorders, there are body-positive and recovery groups on social media. Some people find these groups to be supportive; for others, it’s more beneficial to move on and pursue other interests.

Is there a healthy way to be on social media?

Mellins : If you feel social media is a negative experience, you might need a break. Disengaging with social media permanently is more difficult­—especially for young people. These platforms are powerful tools for connecting and staying up-to-date with friends and family. Social events, too. If you’re not on social media then you’re reliant on your friends to reach out to you personally, which doesn’t always happen. It’s complicated.

Glasofer : When you find yourself feeling badly about yourself in relation to what other people are posting about themselves, then social media is not doing you any favors. If there is anything on social media that is negatively affecting your actions or your choices­—for example, if you’re starting to eat restrictively or exercise excessively—then it’s time to reassess. Parents should check-in with their kids about their lives on social media. In general, I recommend limiting social media— creating boundaries that are reasonable and work for you—so you can be present with people in your life. I also recommend social media vacations. It’s good to take the time to notice the difference between the virtual world and the real world.

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Thesis Statements about Social Media: 21 Examples and Tips

• by Judy Jeni
• January 27, 2024

A thesis statement is a sentence in the introduction paragraph of an essay that captures the purpose of the essay. Using thesis statements about social media as an example, I will guide you on how to write them well.

It can appear anywhere in the first paragraph of the essay but it is mostly preferred when it ends the introduction paragraph. learning how to write a thesis statement for your essay will keep you focused.

A thesis statement can be more than one sentence only when the essay is on complex topics and there is a need to break the statement into two. This means, a good thesis statement structures an essay and tells the reader what an essay is all about.

A good social media thesis statement should be about a specific aspect of social media and not just a broad view of the topic.

The statement should be on the last sentence of the first paragraph and should tell the reader about your stand on the social media issue you are presenting or arguing in the essay.

Reading an essay without a thesis statement is like solving a puzzle. Readers will have to read the conclusion to at least grasp what the essay is all about. It is therefore advisable to craft a thesis immediately after researching an essay.

Throughout your entire writing, every point in every paragraph should connect to the thesis.  In case it doesn’t then probably you have diverged from the main issue of the essay.

How to Write a Thesis Statement?

Writing a thesis statement is important when writing an essay on any topic, not just about social media. It is the key to holding your ideas and arguments together into just one sentence.

The following are tips on how to write a good thesis statement:

Start With a Question and Develop an Answer

If the question is not provided, come up with your own. Start by deciding the topic and what you would like to find out about it.

Secondly, after doing some initial research on the topic find the answers to the topic that will help and guide the process of researching and writing.

Consequently, if you write a thesis statement that does not provide information about your research topic, you need to construct it again.

Be Specific

The main idea of your essay should be specific. Therefore, the thesis statement of your essay should not be vague. When your thesis statement is too general, the essay will try to incorporate a lot of ideas that can contribute to the loss of focus on the main ideas.

Similarly, specific and narrow thesis statements help concentrate your focus on evidence that supports your essay. In like manner, a specific thesis statement tells the reader directly what to expect in the essay.

Make the Argument Clear

Usually, essays with less than one thousand words require the statement to be clearer. Remember, the length of a thesis statement should be a single sentence, which calls for clarity.

In these short essays, you do not have the freedom to write long paragraphs that provide more information on the topic of the essay.

Likewise, multiple arguments are not accommodated. This is why the thesis statement needs to be clear to inform the reader of what your essay is all about.

If you proofread your essay and notice that the thesis statement is contrary to the points you have focused on, then revise it and make sure that it incorporates the main idea of the essay. Alternatively, when the thesis statement is okay, you will have to rewrite the body of your essay.

Question your Assumptions

Before formulating a thesis statement, ask yourself the basis of the arguments presented in the thesis statement.

Assumptions are what your reader assumes to be true before accepting an argument. Before you start, it is important to be aware of the target audience of your essay.

Thinking about the ways your argument may not hold up to the people who do not subscribe to your viewpoint is crucial.

Alongside, revise the arguments that may not hold up with the people who do not subscribe to your viewpoint.

Take a Strong Stand

A thesis statement should put forward a unique perspective on what your essay is about. Avoid using observations as thesis statements.

In addition, true common facts should be avoided. Make sure that the stance you take can be supported with credible facts and valid reasons.

Equally, don’t provide a summary, make a valid argument. If the first response of the reader is “how” and “why” the thesis statement is too open-ended and not strong enough.

Make Your Thesis Statement Seen

The thesis statement should be what the reader reads at the end of the first paragraph before proceeding to the body of the essay. understanding how to write a thesis statement, leaves your objective summarized.

Positioning may sometimes vary depending on the length of the introduction that the essay requires. However, do not overthink the thesis statement. In addition, do not write it with a lot of clever twists.

Do not exaggerate the stage setting of your argument. Clever and exaggerated thesis statements are weak. Consequently, they are not clear and concise.

Good thesis statements should concentrate on one main idea. Mixing up ideas in a thesis statement makes it vague. Read on how to write an essay thesis as part of the steps to write good essays.

A reader may easily get confused about what the essay is all about if it focuses on a lot of ideas. When your ideas are related, the relation should come out more clearly.

21 Examples of Thesis Statements about Social Media

• Recently, social media is growing rapidly. Ironically, its use in remote areas has remained relatively low.
• Social media has revolutionized communication but it is evenly killing it by limiting face-to-face communication.
• Identically, social media has helped make work easier. However,at the same time it is promoting laziness and irresponsibility in society today.
• The widespread use of social media and its influence has increased desperation, anxiety, and pressure among young youths.
• Social media has made learning easier but its addiction can lead to bad grades among university students.
• As a matter of fact, social media is contributing to the downfall of mainstream media. Many advertisements and news are accessed on social media platforms today.
• Social media is a major promoter of immorality in society today with many platforms allowing sharing of inappropriate content.
• Significantly, social media promotes copycat syndrome that positively and negatively impacts the behavior adapted by different users.
• In this affluent era, social media has made life easy but consequently affects productivity and physical strength.
• The growth of social media and its ability to reach more people increases growth in today’s business world.
• The freedom on social media platforms is working against society with the recent increase in hate speech and racism.
• Lack of proper verification when signing up on social media platforms has increased the number of minors using social media exposing them to cyberbullying and inappropriate content.
• The freedom of posting anything on social media has landed many in trouble making the need to be cautious before posting anything important.
• The widespread use of social media has contributed to the rise of insecurity in urban centers
• Magazines and journals have spearheaded the appreciation of all body types but social media has increased the rate of body shaming in America.
• To stop abuse on Facebook and Twitter the owners of these social media platforms must track any abusive post and upload and ban the users from accessing the apps.
• Social media benefits marketing by creating brand recognition, increasing sales, and measuring success with analytics by tracking data.
• Social media connects people around the globe and fosters new relationships and the sharing of ideas that did not exist before its inception.
• The increased use of social media has led to the creation of business opportunities for people through social networking, particularly as social media influencers.
• Learning is convenient through social media as students can connect with education systems and learning groups that make learning convenient.
• With most people spending most of their free time glued to social media, quality time with family reduces leading to distance relationships and reduced love and closeness.

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How to Write a Thesis Statement About Social Media

Writing a thesis statement requires good research and creating a concise yet very informative point. Writing one about social media is no different. Due to the scope of the study, the information to gather and discuss is even more expansive.

• What is a Social Media Thesis Statement?

Social Media Essay Outline

Social media essay titles, thesis on social media, argumentative essay on social media, social networking thesis statement, summing up the thesis statement.

Social media uses mobile technologies that are Internet-based to run communication across different parts of the world. It gives  people  worldwide the opportunity to communicate and socialize, unlike past means of communication which were only one-way.

The evolution of technology has made social media more efficient and prevalent than any other form of communication today. With technology’s continued evolution, social media will continue to evolve, and so will topics and thesis statements about it. A good  thesis statement about social media  must meet some requirements, and we will look through most of them.

What is a Social Media Thesis Statement Supposed to Look Like?

Before understanding how a  thesis statement on social media  should look like, we should familiarize ourselves with what thesis statements properly entail. A thesis statement is typically written in the introductory portion of a paper.

It provides an apt and rapid summary of the main point or aim of the research paper or thesis. As the name implies, it is a statement, mainly written in just one sentence.

A thesis statement briefly combines the topic and the main ideas of the paper. Usually, there are two types of thesis statements: indirect and direct. The indirect thesis statements do not mention the core areas or reason of the thesis like the direct statement does.

A direct statement mentions the main topic and discusses the reasons for the paper, while an indirect statement mentions the statement and points out three reasons for it.

For instance, an indirect  social media thesis  statement could go like this; “Effects of social media on youth and the reasons for its abuse.” Here the topic is clearly stated, along with the central claim of the thesis paper.

Thesis statements are created, backed up, and expatiated in the remaining parts of the paper by citing examples and bringing up other related topics that support their claim. Through this, the thesis statement then goes to help structure and develop the entire body of the writing piece.

A  thesis about social media  should contain a good thesis statement that would  impact  and organize the body of the thesis work. Thesis statements do not necessarily control the entire essay but complement it in numerous aspects.

In writing a social media essay, there is a wide variety of topics to talk about. The points are nearly endless, from information collection to technology, its impacts, and adverse effects to its evolution. Nevertheless, there is always a basic outline for an essay, and it will be structured to follow the same format.

Here is an outline for a social media essay;

• Introduction 

Here, you begin with the topic, state its objective, provide reasons to support its claims and finalize with a precise and accurate thesis statement.

• Thesis statement

This statement should support and complement your main topic of discussion. It should provide a concise and cut-out message of the essay.

This section systematically lays out the arguments to support your topic while splitting them into paragraphs. This will gradually develop your points in a structured manner.

Each paragraph in this section must start with the topic sentence which relates directly to the thesis statement. Naturally, a paragraph should focus on one idea and be connected to the essay’s central argument.

Students must also conduct research and provide evidence to support the claims presented in the topic sentence. They can achieve this by using proper explanation methods to merge all their findings carefully.

In the conclusion  of the social media essay ,   you restate your statement in a way that completely complements and brings all your previous arguments together. It must have a concluding paragraph that reiterates the main point discussed in the body of the content. It should also add a call to action to bring the essay into a logical closure that effortlessly lays bare all the ideas previously presented.

The social media field is continuously expanding, and there are various variations to how it can be operated and observed. Choosing a topic is easy, but choosing the right one may not be as unchallenging.

Before you begin writing an essay, the correct approach will be to review as many samples as you can. This way, you can easily understand the general concept and the adequate writing flow required to outline or develop your arguments carefully.

Picking the wrong titles can go on to make your  thesis for a social media essay  unnecessarily tricky to write. This can occur when you pick a topic too complex or choose one too vaguely and undervalued. This could make you get stuck when writing, so you should always pick titles that are easy to research, analyze and expand upon.

With all these in view, here are some social media essay titles;

• Impact of social media on general education
• Effects of using social media on businesses
• Adverse effects of social media on personal relationships
• The effect of government on social media and their potential restrictions
• How a  thesis about the effects of social media can  positively impact society.

A thesis on social media should easily resemble other academic papers and concentrate on various topics in various subjects. Papers like this should take social media as their primary focus.

Keeping that in mind, a compelling social media thesis should contain specific parts like an introduction, thesis statement, body, and conclusion. Each part is essential and has its contribution and functions to the entire content of the thesis. Some students may find writing a thesis statement about social media difficult, so you can always ask our professional writers to “ write my thesis ” and we will be happy to help you.

The introduction usually contains a hook, a summary of the core points, and a concise thesis statement. The body section must carefully develop each argument and idea in a paragraph, while the conclusion should completely close all the arguments.

The tone, style, and approach to each argument should be precise and well laid out to quickly understand the general idea the thesis is trying to build upon. Depending on the level of education you are writing your thesis, you may need to conduct specific direct research on some points and be required to portray them in an encompassing manner.

Generally, thesis writing on any topic requires hard work, extensive research periods, and a good understanding of writing methods. Hence it should be approached with determination and passion. As a student in higher education, you should learn how to improve your writing skills.

An argumentative essay on social media is typically more engaging with active points of discussion and analysis. Communication is an integral aspect of human life when connecting and moving society as a whole forward. Now technology has upgraded communication to a social media age, which has become an advantage and disadvantage in many aspects of life.

An argumentative social media essay generally possesses a strong argument. The essay’s topic must be designed to prompt a person to pick a side or a discussion and provide the necessary support to back up their decision. This type of essay also requires one to research accurate facts for proper argumentative purposes.

Social media   argumentative essays  target the harmful effects of this brilliant innovation in communication and its uses worldwide. It is only natural as negative discussions might elicit a sense of debate and argumentation. Some examples of argumentative essay topics on social media include;

• The negative effects of social media on education in different nations
• Effects of social media and its impacts on the older and younger generation
• How social media has taken over people
• The adverse effects of social media and the digital space on our  mental health
• The pros and cons of social media in this society.

Social networking is an integral aspect of social media. It uses Internet-based social media sites to create connections and stay connected with friends, customers, family, and even business partners.

Social networking usually performs a primary purpose in communication with actual avenues like Twitter, Instagram, Facebook, and LinkedIn. These sites and applications enable people to connect to develop relationships and share messages, ideas, and information.

Most social networking forms entail developing and maintaining relationships using communication technology, whether it is the relationship between clients, business partners, or even students.

For example, with the development of the Internet, most students can easily find services to help write dissertations on media space, or social media marketing. All you have to do is invite me to write my dissertation and they will immediately find the best service to solve their problem.

Writing is  a social networking thesis statement  similar to that of a social media thesis statement. They essentially involve rational discussion, and they can be approached in the same manner. The only slight difference will be the particular attention to social media relationships. How they are developed, what it takes to maintain them, and the various merits they could provide. These would typically form the structure of a  social networking thesis statement.

Writing a good thesis statement on social media involves a good understanding of the topic chosen and an accurate idea of the reasons, factors, and discussions that impact the main idea of the thesis. With all these discussed, you should be well on your way to writing good thesis statements on social media.

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Argumentative Essays About Social Media

This is a comprehensive resource to help you find the perfect social media essay topic. Whether you're navigating the complexities of digital communication, exploring the impact of social media on society, or examining its effects on personal identity, the right topic can transform your essay into a captivating and insightful exploration. Remember, selecting a topic that resonates with your personal interests and academic goals not only makes the writing process more enjoyable but also enriches your learning experience. Let's dive into a world of creativity and critical thinking!

Essay Types and Topics

Below, you'll find a curated list of essay topics organized by type. Each section includes diverse topics that touch on technology, society, personal growth, and academic interests, along with introduction and conclusion paragraph examples to get you started.

Argumentative Essays

Introduction Example: "In the digital age, social media platforms have become central to our daily interactions and self-perception, particularly among teenagers. This essay explores the impact of social media on teen self-esteem, arguing that while it offers a space for expression and connection, it also presents significant challenges to self-image. "

Conclusion Example: "Having delved into the complex relationship between social media and teen self-esteem, it is clear that the digital landscape holds profound effects on individual self-perception. This essay reaffirms the thesis that social media can both uplift and undermine teen self-esteem, calling for a balanced approach to digital engagement."

Introduction Example: "As political landscapes evolve, social media has emerged as a powerful tool for political mobilization and engagement. This essay investigates the role of social media in shaping political movements, positing that it significantly enhances communication and organizational capabilities, yet raises questions about information authenticity. "

Conclusion Example: "Through examining the dual facets of social media in political mobilization, the essay concludes that while social media is a pivotal tool for engagement, it necessitates critical scrutiny of information to ensure a well-informed public discourse."

Compare and Contrast Essays

Introduction Example: "In the competitive realm of digital marketing, Instagram and Twitter stand out as leading platforms for brand promotion. This essay compares and contrasts their effectiveness, revealing that each platform caters to unique marketing strengths due to its specific user engagement and content dissemination strategies. "

Conclusion Example: "The comparative analysis of Instagram and Twitter highlights distinct advantages for brands, with Instagram excelling in visual storytelling and Twitter in real-time engagement, underscoring the importance of strategic platform selection in digital marketing."

Descriptive Essays

Introduction Example: "Today's social media landscape is a vibrant tapestry of platforms, each contributing to the digital era's social fabric. This essay describes the characteristics and cultural significance of current social media trends, illustrating that they reflect and shape our societal values and interactions. "

Conclusion Example: "In portraying the dynamic and diverse nature of today's social media landscape, this essay underscores its role in molding contemporary cultural and social paradigms, inviting readers to reflect on their digital footprints."

Persuasive Essays

Introduction Example: "In an era where digital presence is ubiquitous, fostering positive social media habits is essential for mental and emotional well-being. This essay advocates for mindful social media use, arguing that intentional engagement can enhance our life experiences rather than detract from them. "

Conclusion Example: "This essay has championed the cause for positive social media habits, reinforcing the thesis that through mindful engagement, individuals can navigate the digital world in a way that promotes personal growth and well-being."

Narrative Essays

Introduction Example: "Embarking on a personal journey with social media has been both enlightening and challenging. This narrative essay delves into my experiences, highlighting how social media has influenced my perception of self and community. "

Conclusion Example: "Reflecting on my social media journey, this essay concludes that while it has significantly shaped my interactions and self-view, it has also offered invaluable lessons on connectivity and self-awareness, affirming the nuanced role of digital platforms in our lives."

Engagement and Creativity

As you explore these topics, remember to approach your essay with an open mind and creative spirit. The purpose of academic writing is not just to inform but to engage and provoke thought. Use this opportunity to delve deep into your topic, analyze different perspectives, and articulate your own insights.

Educational Value

Each essay type offers unique learning outcomes. Argumentative essays enhance your analytical thinking and ability to construct well-founded arguments. Compare and contrast essays develop your skills in identifying similarities and differences. Descriptive essays improve your ability to paint vivid pictures through words, while persuasive essays refine your ability to influence and convince. Finally, narrative essays offer a platform for personal expression and storytelling. Embrace these opportunities to grow academically and personally.

Some Easy Argumentative Essay Topics on Social Media

• The Impact of Social Media: Advantages and Disadvantages
• Is Social Media Enhancing or Eroding Our Real-Life Social Skills?
• Should There Be Stricter Regulations on Social Media Content to Protect Youth?
• Social Media's Role in Relationships: Communication Enhancer or Barrier
• Does Social Media Contribute to Political Polarization?
• The Role of Social Media in Shaping Perceptions of Divorce
• The Impact of Social Media on Mental Health: Benefit or Harm?
• Can Social Media Be Considered a Reliable Source of News and Information?
• Is Social Media Responsible for the Rise in Cyberbullying?
• Impact of Social Media on Mental Health
• Does Social Media Promote Narcissism and Self-Centered Behaviors?
• The Role of Social Media in Business Marketing: Is It Indispensable?

The Impact of Social Media: Causes and Effects

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Pros and Cons of Social Media: Social Networking

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Social Media Cons and Prons: Evaluating Its Advantages and Disadvantage

The importance of staying safe on social media, impact of social media on our lives, social media: negative effects and addiction, discussion on whether is social media beneficial or harmful for society, negative effects of social media: relationships and communication, social media pros and cons, social media - good and bad sides, a study of the role of social media concerning confidentiality of personal data, how social media causes stereotyping, social media addiction: consequences and strategies for recovery, the role of social media in making us more narcissistic, the effect social media is having on today's society and political atmosphere, digital/social media, censorship in social media, why teenagers are addicted to social media and how it affects them, advantages and disadvantages of social media for society, enormous impact of mass media on children, the role of social media in the current business world, social media is the reason for many of the world’s problems and solutions.

Social media refers to dynamic online platforms that enable individuals to actively engage in the generation and dissemination of various forms of content, including information, ideas, and personal interests. These interactive digital channels foster virtual communities and networks, allowing users to connect, communicate, and express themselves. By harnessing the power of technology, social media platforms provide a space for individuals to share and exchange content, fostering connections and facilitating the flow of information in an increasingly digital world.

In a peculiar manner, the inception of social media can be traced back to May 24, 1844, when a sequence of electronic dots and dashes was manually tapped on a telegraph machine. Although the origins of digital communication have deep historical roots, most contemporary narratives regarding the modern beginnings of the internet and social media often point to the emergence of the Advanced Research Projects Agency Network (ARPANET) in 1969. The year 1987 witnessed the establishment of the direct precursor to today's internet, as the National Science Foundation introduced the more robust and expansive NSFNET, a nationwide digital network. A significant milestone occurred in 1997 when Six Degrees, the first genuine social media platform, was launched.

Mark Zuckerberg is a notable figure in the realm of social media as the co-founder and CEO of Facebook. Zuckerberg played a pivotal role in transforming Facebook from a small networking platform for college students into a global social media giant with billions of users. His innovative ideas and strategic decisions have reshaped the way people connect and share information online, making him one of the most influential individuals in the digital age. Jack Dorsey is recognized as one of the key pioneers of social media, notably for co-founding Twitter. Dorsey's creation revolutionized online communication by introducing the concept of microblogging, allowing users to share short messages in real-time. Twitter quickly gained popularity, becoming a powerful platform for news dissemination, public conversations, and social movements. Dorsey's entrepreneurial spirit and vision have contributed significantly to the evolution of social media and its impact on society. Sheryl Sandberg is a prominent figure in the social media landscape, known for her influential role as the Chief Operating Officer (COO) of Facebook.Sandberg played a crucial part in scaling and monetizing Facebook's operations, transforming it into a global advertising powerhouse. She is also recognized for her advocacy of women's empowerment and leadership in the tech industry, inspiring countless individuals and promoting diversity and inclusion within the social media sphere. Sandberg's contributions have left an indelible mark on the growth and development of social media platforms worldwide.

Social Networking Sites: Facebook, LinkedIn, and MySpace. Microblogging Platforms: Twitter. Media Sharing Networks: Instagram, YouTube, and Snapchat. Discussion Forums and Community-Based Platforms: Reddit and Quora. Blogging Platforms: WordPress and Blogger. Social Bookmarking and Content Curation Platforms: Pinterest and Flipboard. Messaging Apps: WhatsApp, Facebook Messenger, and WeChat.

Facebook (2004), Reddit (2005), Twitter (2006), Instagram (2010), Pinterest (2010), Snapchat (2011), TikTok (2016)

1. Increased Connectivity 2. Information Sharing and Awareness 3. Networking and Professional Opportunities 4. Creativity and Self-Expression 5. Supportive Communities and Causes

1. Privacy Concerns 2. Cyberbullying and Online Harassment 3. Information Overload and Misinformation 4. Time and Productivity Drain 5. Comparison and Self-Esteem Issues

The topic of social media holds significant importance for students as it plays a prominent role in their lives, both academically and socially. Social media platforms provide students with opportunities to connect, collaborate, and share knowledge with peers, expanding their learning networks beyond the confines of the classroom. It facilitates communication and access to educational resources, allowing students to stay updated on academic trends and research. Additionally, social media enhances digital literacy and prepares students for the realities of the digital age. However, it is crucial for students to develop critical thinking skills to navigate the potential pitfalls of social media, such as misinformation and online safety, ensuring a responsible and balanced use of these platforms.

The topic of social media is worthy of being explored in an essay due to its profound impact on various aspects of society. Writing an essay on social media allows for an in-depth examination of its influence on communication, relationships, information sharing, and societal dynamics. It offers an opportunity to analyze the advantages and disadvantages, exploring topics such as privacy, online identities, social activism, and the role of social media in shaping cultural norms. Additionally, studying social media enables a critical evaluation of its effects on mental health, politics, and business. By delving into this subject, one can gain a comprehensive understanding of the complex and ever-evolving digital landscape we inhabit.

1. Social media users spend an average of 2 hours and 25 minutes per day on social networking platforms. This amounts to over 7 years of an individual's lifetime spent on social media, highlighting its significant presence in our daily lives. 2. Instagram has over 1 billion monthly active users, with more than 500 million of them using the platform on a daily basis. 3. YouTube has over 2 billion logged-in monthly active users. On average, users spend over 1 billion hours watching YouTube videos every day, emphasizing the platform's extensive reach and the power of video content. 4. Social media has become a major news source, with 48% of people getting their news from social media platforms. This shift in news consumption highlights the role of social media in shaping public opinion and disseminating information in real-time. 5. Influencer marketing has grown exponentially, with 63% of marketers planning to increase their influencer marketing budget in the coming year. This showcases the effectiveness of influencers in reaching and engaging with target audiences, and the value brands place on leveraging social media personalities to promote their products or services.

1. Schober, M. F., Pasek, J., Guggenheim, L., Lampe, C., & Conrad, F. G. (2016). Social media analyses for social measurement. Public opinion quarterly, 80(1), 180-211. (https://academic.oup.com/poq/article-abstract/80/1/180/2593846) 2. Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing science, 48(1), 79-95. (https://link.springer.com/article/10.1007/s11747-019-00695-1?error=cookies_not_support) 3. Aichner, T., Grünfelder, M., Maurer, O., & Jegeni, D. (2021). Twenty-five years of social media: a review of social media applications and definitions from 1994 to 2019. Cyberpsychology, behavior, and social networking, 24(4), 215-222. (https://www.liebertpub.com/doi/full/10.1089/cyber.2020.0134) 4. Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063-1064. (https://www.science.org/doi/abs/10.1126/science.346.6213.1063) 5. Hou, Y., Xiong, D., Jiang, T., Song, L., & Wang, Q. (2019). Social media addiction: Its impact, mediation, and intervention. Cyberpsychology: Journal of psychosocial research on cyberspace, 13(1). (https://cyberpsychology.eu/article/view/11562) 6. Auxier, B., & Anderson, M. (2021). Social media use in 2021. Pew Research Center, 1, 1-4. (https://www.pewresearch.org/internet/wp-content/uploads/sites/9/2021/04/PI_2021.04.07_Social-Media-Use_FINAL.pdf) 7. Al-Samarraie, H., Bello, K. A., Alzahrani, A. I., Smith, A. P., & Emele, C. (2021). Young users' social media addiction: causes, consequences and preventions. Information Technology & People, 35(7), 2314-2343. (https://www.emerald.com/insight/content/doi/10.1108/ITP-11-2020-0753/full/html) 8. Bhargava, V. R., & Velasquez, M. (2021). Ethics of the attention economy: The problem of social media addiction. Business Ethics Quarterly, 31(3), 321-359. (https://www.cambridge.org/core/journals/business-ethics-quarterly/article/ethics-of-the-attention-economy-the-problem-of-social-mediaaddiction/1CC67609A12E9A912BB8A291FDFFE799)

Relevant topics

• Effects of Social Media
• Media Analysis
• Discourse Community
• Sex, Gender and Sexuality
• Cultural Appropriation
• Social Justice
• Sociological Imagination
• American Identity

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Media exposure to climate change information and pro-environmental behavior: the role of climate change risk judgment

• Ivana Vrselja   ORCID: orcid.org/0000-0002-7740-7023 1 ,
• Mario Pandžić   ORCID: orcid.org/0000-0002-8099-2964 1 ,
• Martina Lotar Rihtarić   ORCID: orcid.org/0000-0003-0666-0299 2 &
• Maria Ojala   ORCID: orcid.org/0000-0002-6613-5974 3  

BMC Psychology volume  12 , Article number:  262 ( 2024 ) Cite this article

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The aim of this study was to examine the relationships between exposure to climate change information in traditional and modern media, cognitive and emotional aspects of climate change risk judgment, and pro-environmental behavior (PEB).

A cross-sectional online study was conducted on a quota sample of 1,075 participants (51.9% women) aged 18–79 years. Participants self-reported their exposure to climate change-related information in traditional (e.g. television) and modern media (e.g. social networks), cognitive assessment of climate change risk, level of worry about climate change, and the frequency of PEB.

Structural equation modeling showed a good fit for the parallel mediation model, involving cognitive risk judgment and worry as mediators between exposure to climate change information in traditional and modern media and PEB. Exposure to climate change information in traditional media had indirect effect on PEB through heightened worry, but not cognitive risk judgment. In contrast, exposure to climate change information in modern media had no indirect effect on PEB.

Since the link between exposure to climate change information in traditional media and PEB has been shown to be mediated by climate change worry, it is important to enhance the coverage of climate change in traditional media in Croatia, taking care to offer solutions to reduce possible negative impact on people’s well-being.

Peer Review reports

Introduction

Although the Intergovernmental Panel on Climate Change and the majority of scientific communities have agreed that human activities persistently modify the Earth’s climate, which could have disastrous effects on specific groups and economic sectors [ 1 ], the general public does not always perceive the risk of climate change [ 2 ].

In academia, risk perception has been approached and defined in many ways [ 3 ]. Due to the interchangeable use of various terms related to risk, such as attitudes, beliefs, cognitions and emotions, Dunwoody and Neuwirth [ 3 ] recognised the need to clarify the study of risk. The authors [ 3 ] suggested replacing the term “risk perception” with “risk judgement” and emphasised the need to distinguish between the cognitive and emotional dimensions of risk judgment. The cognitive dimension is concerned with whether the risk is voluntary or involuntary, whether it can lead to catastrophic events and the extent to which it poses a threat to future generations [ 3 ]. The affective dimension of risk assessment refers to the emotional response, such as worry, anxiety or fear, that people feel in relation to hazards [ 3 ].

Identifying the factors that influence climate change risk judgment is crucial, as it has been shown to be one of the most important predictors of whether people will engage in pro-environmental behavior [ 4 ]. Pro-environmental behaviors can be defined as individual efforts undertaken with the aim of reducing the impact of human activities on the environment [ 5 ]. In recent years, the categorisation of pro-environmental behavior has become more diverse and complex as researchers have broadened and shifted their focus and objectives [ 6 ]. ​Stern [ 5 ], for example, has divided pro-environmental behavior into four dimensions: Environmental activism (e.g. protests, petitions), non-activist behavior in the public sphere (e.g. volunteering for environmental causes, lobbying for environmental policies), private sphere environmentalism(e.g. use and maintenance of environmentally relevant goods, disposal of household waste and environmentally friendly consumption) and other environmentally significant behaviors (e.g. behaviors that influence organisational decisions). While there is a wide range of pro-environmental behaviors, they share a comparable connotation to behaviors in personal (private) and public domains [ 6 ]. This categorization of pro-environmental behavior into private and public is utilised in many empirical studies [e.g., 6 , 7 , 8 , 9 ], and the extent of association between these two forms of pro-environmental behavior and various factors were analysed in several meta-analyses [ 10 , 11 ].

In this study, the focus is on pro-environmental behavior in the private sphere, which includes everyday actions such as waste avoidance, environmentally conscious consumption and the use of energy-efficient products and services [ 6 , 7 , 8 , 9 ]. In contrast to public behaviors, which can influence the behavior of many individuals and organisations but whose impact on the environment is primarily indirect through their influence on environmental policy, behaviors in the private sphere have a direct impact on the environment [ 12 ].

Studies have shown that private sphere pro-environmental behavior is significantly predicted by a more pronounced cognitive dimension of climate change risk judgement [ 13 , 14 ] and that people with more pronounced worry and climate anxiety engage in more private pro-environmental behavior [ 11 , 15 , 16 , 17 ]. In the present study, we capture the cognitive aspect of climate change risk judgment by assessing the risk of climate change having a negative impact on people’s health, safety or wealth. We also capture the emotional aspect of climate change risk judgment through experienced worries about climate change. This is in line with, for instance, pioneer work by Sjöberg [ 18 ] who already in the late 1990’s conceptualized the emotional part of risk judgment as worry, which he showed was different from pure cognitive risk judgements [ 18 ]. We define worry as a cognitive-emotional concept consisting of brooding about an uncertain future accompanied with anxiety-like affect [ 19 ]. Worry has been used as an emotional reaction to climate change, distinct from for example anxiety and concern in many studies [see, for example 15 , 20 ].

These two dimensions of risk judgement are not only associated with pro-environmental behavior, but studies have shown that they are also related to exposure to climate change information in the media [ 21 , 22 , 23 ]. The primary rationale behind these findings is that many risks are brought to people’s attention solely through the media, rather than through personal experience [ 24 ]. According to the social amplification of risk framework [ 25 , 26 , 27 , 28 , 29 , 30 , 31 ], when risk information is communicated, the media can either amplify or mitigate the perceived risk. Regardless of the accuracy and particular content of the information, a large flow of information can serve as a risk amplifier [ 25 ]. Repeated reports naturally draw the public’s attention to specific risk issues and away from competing sources of attention. According to Mazur [ 32 ], “what is said in news stories matters relatively little compared to the amount and saliency of exposure” (p.151). For this reason, in this study we focused on the amount or frequency of exposure to climate change information in the media.

Present study

Recent research [ 24 , 33 , 34 ] suggest that it is not valid to assume a direct link between exposure to climate change information in the media and pro-environmental behavior. A cross-sectional study by Paek and Hove [ 24 ] found that risk perception and negative emotions such as despair, anxiety and fear are mediators between exposure to climate change information in the media and the intention to engage in pro-environmental behavior. Greaves and associates [ 33 ] reported that participants showed a significant increase in their negative emotions and intention to engage in pro-environmental behavior after watching a video about climate change compared to those who had not seen the video. Shao and Yu [ 34 ] demonstrated that eco- anxiety acts as a mediator between climate change coverage in everyday life and pro-environmental behavior.

To date, there are no studies that simultaneously examine the cognitive dimension of risk judgment and worry as a mediators between exposure to climate change information in different media and pro-environmental behavior. In this study, we distinguish between exposure to climate change information in traditional media (television and radio) and in modern media (social networks and video content sharing channels), which is consistent with the approach of classifying media channels proposed by other researchers [ 35 , 36 ]. Different approaches are employed in categorising media within research on climate change risk judgment. Some studies [ 21 ] analyse media in its most comprehensive form, encompassing all sorts of media, whereas others [ 22 ] concentrate on specific media channels. Based on a survey in 110 countries, Thaker [ 21 ] reported that exposure to climate change news in the media in general (television, newspapers, social media or conversations with family and friends) is related to the personal cognitive aspect of climate change risk judgment. Another study showed that exposure to climate change information through television predicted higher risk perception in India, but internet use showed a negative effect and newspaper use showed no effect [ 22 ]. It could be that these contradictory results are related to the varying degrees of trust in the media examined. Trust in the media conveying risk information is the key factor in whether amplification occurs [ 37 ]. Amplification effects are more likely to occur when risk information comes from sources that are highly trusted [ 37 ]. Conversely, media sources that are viewed as untrustworthy or as sensationalizing information may have a smaller effect on reinforcing or reducing risk perceptions [ 37 ]. These mechanisms contribute to the diffusion of the understanding of a risk, both among individuals directly impacted and within the broader society [ 31 ]. In the Croatian context, traditional media such as radio and television are reported to enjoy a higher level of trust than modern media such as social networks [ 38 ].

Therefore, this study attempts to answer two key research questions that have not been in focus before. The first research question was whether there is an indirect effect of exposure to climate change information in traditional media on pro-environmental behavior through the cognitive aspect of climate change risk judgment and worry about climate change (R1). The second research question was whether there is an indirect effect of climate change information in modern media on pro-environmental behavior through the cognitive aspect of climate change risk judgment and worry about climate change (R2).

Participants

A total of 1075 participants (51.9% women) aged 18 to 79 years participated in this study. Most participants (53.6%) reported a monthly household income of between €1,131 and €2,720. Both high (€2,721 or more) and low income households (€1,130 or less) were less frequently represented in the sample (24.4% and 22% respectively). Furthermore, most participants (66.2%) rated their standard of living as average, with only a handful of them rating their standard of living as far below average (1.2%) or far above average (1.2%).

We employed a quota sampling approach for our research, whereby we selected participants from the adult population of Croatia. The selection was based on specific quotas established according to the geographic location and sex of the participants.

Croatia is administratively divided into 21 counties, each treated as distinct categories for the sampling process. This categorization was done to consider climatic variations within the country, as Croatia is exposed to three different climatic zones [ 39 ], and these climatic differences are associated with varying impacts of climate change, such as experiences with extreme weather events [ 40 ]. Indeed, previous research has shown that personal experiences with extreme weather events can influence an individual’s engagement with environmental issues [ 41 ]. Within each county, the participants were divided by sex to ensure that the proportion of males and females in the sample matched that of the overall population.

The required total sample size was first calculated for a confidence level of 95% and a margin of error of 3%, assuming a population size of 3,204,957 legal adults. The required sample size was estimated at 1,075 participants. To determine the size of each subgroup, a proportional allocation method was adopted. This method entailed allocating a proportionate number of participants based on the respective population sizes within each county and sex category. By following this approach, the intention was to construct a sample that accurately mirrored the distribution of the overall population concerning both geographical location (county) and sex.

To establish the precise number of respondents within each subgroup for both participant’s county and sex criteria, authoritative data from the State Agency for Statistics was utilized. Specifically, information gleaned from the most recent census of the Republic of Croatia, conducted in 2021 by Croatian Bureau of Statistics [ 42 ], was employed as the basis for these determinations.

Instruments

Exposure to climate change information in the media was measured using four questions developed specifically for this research. Respondents were asked if they had seen, heard, or read anything about climate change in a list of possible channels: Television, radio, social media (Twitter, Facebook, Twitter, etc.), and video content sharing channels (e.g., YouTube). Respondents indicated their answers on a 5-point scale ranging from 0 (never) to 4 (at least once a day). Based on this list, we specified two-factor CFA measurement model of exposure to climate change in traditional and modern media, where both factors were represented with two indicators (television and radio for traditional, and social networks and video content sharing channels for modern media) and allowed to covary. This model showed good overall fit to the data ( χ2 (1) = 7.417; p  < .05; CFI = 0.99; TLI = 0.96; RMSEA = 0.08; SRMR = 0.01).

The cognitive aspect in assessing the risk judgment of climate change (CRJ) was measured with three questions constructed for this research and based on measurement of climate change risk perception used in Kahan et al. [ 43 ]. In original, this measure asks respondents to indicate “How much risk’ they believed ‘climate change’ pose to human health, safety, or prosperity” on a 0 (no risk) to 10 (extreme risk) scale. In this modified version, respondents were asked to give answers to three questions on the level of risk that climate change will pose negative influence to (1) human health, (2) safety and (3) prosperity. Participants indicated their answers on a 11-point scale (0- no risk; 10- extreme risk). To assess construct validity of this measure we specified three-item one-factor measurement model. However, since this model was just-identified and had zero degrees of freedom, the goodness-of-fit of this model could not be analyzed separately and was further explored in the overall measurement model with all latent variables used in the study. SEM-based reliability coefficient for CRJ scale was 0.916, indicating excellent reliability.

Worry about climate change was measured with five items taken from Ojala [ 44 ]. This measure was applied for the first time to a Croatian sample and back translation was carried out. This measure involved asking respondents about their worries regarding the adverse outcomes stemming from climate change, encompassing concerns for themselves, their loved ones, future generations, people in economically disadvantaged nations, and the animals and nature. Each item was rated on a 5-point scale (1 – not at all; 5 - very much. To assess construct validity of the worry about climate change latent construct, five-item one-factor CFA measurement model was specified. This model showed poor fit to the data ( χ2 (5) = 761.431; p  < .05; CFI = 0.82; TLI = 0.64; RMSEA = 0.38; SRMR = 0.08). Inspecting modification indices suggestions revealed that specification of residual covariance between first (“I worry about that I myself will be negatively affected by the climate change problem”) and second (“I worry about that my friends and/or my family will be negatively affected by the climate change problem”) indicator would improve the model fit to a great extent. It seems that participants could potentially be equally worried about negative consequence caused by climate change for themselves and their close ones implying that those two variables could share some of their unique variance. In other words, it seems that some of the variance of these two indicators, could be explained with this possibility, besides the proportion explained by underlying common factor. After allowing the covariance between error terms of these two indicators, the model fit improved greatly on most used goodness-of-fit indices ( χ2 (4) = 49.013; p  < .05; CFI = 0.99; TLI = 0.97; RMSEA = 0.10; SRMR = 0.02), where only RMSEA index was over the suggested 0.06 threshold. Also, all the standardized factor loadings were high, indicating that each of the five indicators had high saturations with the latent construct. SEM-based reliability coefficient of this scale was 0.865, implying very good reliability.

Pro-environmental behavior was measured with 8 items taken from Ojala [ 44 , 45 ]. This measure was applied for the first time to a Croatian sample and back translation was carried out. The items contained both everyday behavior (e.g., “cycling or walking instead of being driven by car”) and communicating the need to do something about the environment to other people (e.g., “trying to influence one’s friends or/and peers to care more for the environment”) (see Supplementary Material 1 for descriptive statistics and intercorrelations among pro-environmental behavior scale items). Each item was assessed on a 5-point scale (1 - almost never; 5 - almost always). To assess construct validity of this scale, eight-item one-factor measurement CFA model was specified. Goodness-of-fit indices suggested poor fit of the model ( χ2 (20) = 341.890; p  < .05; CFI = 0.81; TLI = 0.73; RMSEA = 0.12; SRMR = 0.07). Most indicators were poorly saturated with this latent construct, where standardized factor loadings were under or just around 0.50. Hence, only the three indicators with highest factor loadings were kept (i.e., Try to influence my family and friends to act in a climate-friendly way ; Save energy in the household ; Make climate-friendly food choices ), and a new three-item one-factor measurement model was inspected. The goodness-of-fit of this model, however, could not be analyzed since the model had zero degrees of freedom and was just-identified, and it was further explored in the overall measurement model with all used latent variables. After removing five indicators the SEM-based reliability coefficient slightly dropped, from 0.745 to 0.705, indicating that reliability of this shorter measure was still good.

The study was part of a larger research project entitled Sociopsychological Determinants of Climate Change Risk Perception and Possibilities for its Amplification, funded by the Catholic University of Croatia.

This study was approved by the Ethics Committee of the Catholic University of Croatia and was conducted online between March and June 2023. The survey instrument was created using the SoSci Survey application [ 46 ] and was accessible to participants through the website www.soscisurvey.de . Study participants were recruited with the active participation of the research team members, who used social media platforms (Facebook, Twitter, Instagram, LinkedIn, etc.) to distribute recruitment flyers with the link on the research. In addition, the researchers sent these recruitment flyers via communication applications (e.g. Whatsapp, Viber, etc.) to share the invitation with their friends and colleagues. After accessing the link to the study, participants were informed about the aims of the study, the procedures and their rights as participants before completing the questionnaire. They were assured that their answers would remain anonymous and that no data would be collected during the research that could potentially reveal their identity. Participants were informed that their data would only be aggregated at group level and would only be used for research purposes. It was explicitly stated that participants could withdraw from the study at any time and contact the researchers if they had any concerns or questions. After reading this section, participants were asked to give their consent to participate in the study by clicking the ‘Continue’ button. Those who agreed to participate in the study then completed the questionnaire. The questionnaire took approximately 20 min to complete.

Data analysis

To explore the research questions, structural equation modeling (SEM) was implemented. All analyses for hypothesis testing were conducted using the lavaan package [ 47 ] in R [ 48 ], while figures were produced using the semPlot [ 49 ] and semptools [ 50 ] packages. Model fit assessments were not solely based on chi-square statistic given its high sensitivity to sample size [ 51 ]. Hence, other goodness-of-fit indices (CLI, TLI, RMSEA and SRMR) based on this statistic were inspected following cut-off values guidelines proposed by Hu and Bentler [ 52 ]. Reliability coefficient of the used scales was SEM-based, and it was calculated as a ratio of explained and total variance of the latent variable indicators. (for more information on composite reliability see [ 53 ]).

Table  1 shows the distribution of participants according to how often they received information about climate change through traditional or modern media.

When traditional media is considered, television exposure to climate change information, in comparison to radio exposure, seems to be higher, since almost one quarter of participants (24.8%) indicated that they received climate change information through this media several times per week or at least once a day in comparison to only 15% of the radio listeners. Furthermore, almost 30% of the participants indicated that they were never exposed to climate change information through radio. When we consider modern media channels, exposure to climate change information was more frequent through social media in comparison to video platforms. About 45% of the participants indicated that they were exposed to such information several times per week or at least once a day using social media platforms, in comparison to only 24.3% of them when video platforms are considered. Taken overall, participants were most likely to receive information about climate change through social media and least likely to receive it through radio.

The descriptive statistics for the other variables included in the study is presented in Table  2 .

On average, participants judged the risk of climate change to be fairly high. Furthermore, mean level of worry about climate change was above the midpoint of the scale range, while mean value of pro-environmental behaviors was in the middle of the scale range.

Table  3 contains the intercorrelations between the averaged constructs of the study. As can be seen, all correlation coefficients were statistically significant and positive. The relationship between two types of media exposure to climate change information was moderate in strength, while the strength of the relationship between cognitive aspects of climate change risk judgment and worry about climate change was moderate to high.

Exposure to climate change information in both types of media channels had a weak correlation with both cognitive aspects of climate change risk judgment and worry about climate change, with relationship between exposure to climate change information in traditional media and worry about climate change was slightly stronger than the rest. Furthermore, pro-environmental behavior had a moderate correlation with both cognitive aspects of climate change risk judgment and worry about climate change. Also, it had low correlation with exposure to climate change information in modern media, and low to moderate correlation with exposure to climate change information in traditional media.

Before assessing the responses to our research questions, overall measurement model (see Supplementary Material 2 ) that incorporated all constructs in the study and that allowed for inter-latent covariances was specified. This model showed good fit to the data ( χ2 (79) = 273.471; p  < .05; CFI = 0.98; TLI = 0.97; RMSEA = 0.05; SRMR = 0.04). There was significant positive relationship between most study constructs. In the case of traditional media, exposure to climate change information showed a significant positive relationship with both worry about climate change and cognitive aspect of climate change risk judgment. In the case of modern media, on the other hand, exposure to climate change information showed to be non-related to cognitive aspect of climate change risk judgment, while the relationship with worry about climate change was positive. Finally, there was a significant positive relationship between exposure to climate change information in traditional and modern media, as well as between cognitive aspect of climate change risk judgment and worry about climate change, while all the aforementioned constructs were also positively related to pro-environmental behavior.

Next, we defined a full structural equation model specifying eight directional paths, and two covariances (between two predictors and between two mediators) among latent variables (Fig.  1 ).

Parameter estimates for the full parallel mediation model. Note. * p  < .05, ** p  < .01, *** p  < .001. Standardized coefficients are presented. Measurement part of the model is omitted. TRA – exposure to climate change information in traditional media, MOD – exposure to climate change information in modern media, CRJ – cognitive aspect of climate change risk judgment, WO – worry about climate change, PEB – pro-environmental behavior

This parallel mediation model showed good fit ( χ2 (79) = 273.471; p  < .05; CFI = 0.98; TLI = 0.97; RMSEA = 0.05; SRMR = 0.04). Because there are different approaches to measuring pro-environmental behavior [ 8 , 9 ], we conducted additional analyzes using individual items underlying the latent construct of pro-environmental behavior as outcome variables (see Supplementary Material 3 , 4 , 5 , and 6 for more details). The results of these analyzes are consistent with the results of the analysis with pro-environmental behavior as a latent variable.

Finally, we tested whether there are indirect effects of exposure to climate change information in traditional and modern media on pro-environmental behaviors through the cognitive aspect of climate change risk judgment and worry about climate change (Table  4 ).

In the case of traditional media, it was shown that there is an indirect effect of exposure to climate change information on pro-environmental behavior, through worry about climate change, but not through the cognitive aspect of climate change risk judgment. Specifically, higher exposure to climate change information in traditional media was found to be associated with greater worry about climate change, which in turn was associated with more frequent pro-environmental behaviors (Table  4 ). These results suggest a partial positive answer to our research question R1.

In relation to research question R2, the results show that there is no indirect effect of exposure to climate change information in modern media on pro-environmental behavior, neither through the cognitive aspect of climate change risk judgment nor worry about climate change (Table  4 ).

This cross-sectional analysis of a relatively large sample of Croatian adults shows that exposure to information about climate change in traditional media was associated with people’s increased worry about climate change. Next, this increased worry about climate change was found to be positively associated with people’s pro-environmental behaviors. Interestingly, however, the study found no evidence that exposure to climate change information in traditional media is indirectly associated with pro-environmental behavior through the cognitive aspect of climate change risk judgment.

We found a significant relationship between the cognitive aspect of climate change risk judgment and pro-environmental behavior in our sample. However, exposure to climate change information in traditional media was not significantly associated with the cognitive aspect of risk judgment. One plausible explanation for these results is that television broadcasters are a major source of information for Croatians [ 54 , 55 ], and these broadcasters are controlled by political actors [ 56 ] who have not prioritized climate change [ 57 , 58 ]. Our results also suggest that only a quarter of our participants regularly received climate change information via TV programs, while the exposure rate via social media channels was almost double that of TV programs. The resulting scarcity of information about climate change in television and other traditional media may create uncertainty in the public [ 59 ], which in turn may induce worry about the future [ 60 ].

While worrying about climate change might motivate pro-environmental behaviors, as demonstrated in the present work and previous studies, such worry can reduce well-being. Climate anxiety has been linked to depressive symptoms as well as reduced mental health and psychological well-being [ 61 , 62 , 63 , 64 , 65 ]. To counteract these negative effects, media can shift the focus of climate change information away from potential impacts to potential solutions [ 17 ]. Future research should systematically examine where the focus of climate change information lies in Croatia and other countries in order to ensure that emerging climate journalism leads to behavioral change without adverse psychological consequences.

The lack of a significant relationship between exposure to climate change information in modern media and pro-environmental behavior in our sample likely reflects Croats’ lack of trust in social media and online news, due in part to concerns about misinformation and disinformation [ 38 ]. This mistrust is understandable in light of the sensationalist tone with which topics in climate change have recently been covered in online news portals in the country [ 66 ]. That analysis of climate change information in media before and after the UN Climate Summit in 2019 showed that much of the information centered around Greta Thunberg and the climate strikes with which she was associated, rather than on the Summit itself [ 66 ]. Many articles focused on the personality of Thunberg and the conflictual aspect of climate strikes without delving into the underlying issues of climate change. Media outlets adopting an active, sometimes alarmist stance on climate change were more likely to focus on positive representations of Thunberg, while those treating climate change with skepticism or outright denial were more likely to focus on negative representations.

Some limitations of this study need to be mentioned. First, our analysis was based on cross-sectional online survey data, and the conclusions about causality cannot be drawn. Further studies that could establish causal relationships between variables are warranted. Second, our measurement of exposure to climate change information in traditional and modern media may be problematic, since the use of retrospective recall to gauge respondents’ average exposure to information about climatic change on media may introduce biases and inaccuracies. Future research should employ real-time measurements and other more accurate assessment methods of media usage.

Third, although the measure of pro-environmental behavior used in this study is widely accepted and has been used in numerous studies outside Croatia [ 17 , 61 ], our results show that certain indicators within this measure are poorly aligned with the underlying latent construct of pro-environmental behavior. Studies measure pro-environmental behavior in different ways. In this study, we measured different types of pro-environmental behavior that can be grouped under the umbrella term of pro-environmental behavior in the private sphere [ 5 , 6 , 7 , 8 , 9 ]. However, our results suggest that only three of the eight indicators of the pro-environmental measure used are satisfactorily related to the underlying latent construct of pro-environmental behavior. Seemingly different behaviors, such as trying to persuade family and friends to behave in a climate-friendly way, saving energy in the household and eating a climate-conscious diet, form a single behavioral construct. At this point, it is also important to note that we conducted an additional structural equation analysis with these three specific pro-environmental behaviors as outcomes. The results of these analyzes were consistent with those of the analysis using the latent construct of pro-environmental behaviors as outcome. However, as some studies [ 67 ] have shown discrepancies in the relationships between the variables studied and different types of pro-environmental behavior, it is crucial for future research to determine whether the relationships observed in this study can be replicated in other types of pro-environmental behavior.

Nevertheless, this study offers some notable advantages. In our online research, we used a quota sampling strategy in which we set specific quotas based on the geographic location and gender of the participants. We chose this sampling method to circumvent some of the common limitations associated with online research, particularly the well-documented tendency for male participants to have lower response rates compared to female participants in previous studies [ 68 ]. In addition, this study stands out in the literature because it examines two dimensions of risk judgment-emotional and cognitive-a relatively rare approach. It also makes a valuable contribution to our understanding of how different media relate to risk judgment and pro-environmental behavior.

This study also has practical implications. In Croatia and in other countries where traditional media is more trusted than modern media, it is advisable to use traditional media channels for climate change communication. It is, however, crucial that such communication not only highlights the negative impacts of climate change, but also emphasizes possible solutions to prevent worry about climate change from negatively affecting people’s well-being.

Data availability

The datasets analyzed in the current study are available from the corresponding author on reasonable request.

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IV, MP, MLR, MO contributed to the study conception and design and material preparation. IV, MP, MLR contributed to data collection and data analysis. IV, MP, MLR, MO contributed to the first draft of the manuscript and previous versions of the manuscript. IV, MP, MLR, MO read and approved the final manuscript.

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Vrselja, I., Pandžić, M., Rihtarić, M.L. et al. Media exposure to climate change information and pro-environmental behavior: the role of climate change risk judgment. BMC Psychol 12 , 262 (2024). https://doi.org/10.1186/s40359-024-01771-0

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Erie School District vs. Big Tech? Approval given to explore lawsuit over social media use

Erie school board signs off on having law firms look into potential litigation against facebook, instagram, tiktok, snapchat, youtube, other social media companies..

• Facebook parent company Meta is already facing lawsuit by states over claims that social media use harms students
• Erie School District's potential litigation would target Meta, other companies over claims that student social media use has created nuisances in schools
• Suit would be similar to case the Erie School District settled a year ago with electronic cigarette maker Juul

The Erie School District is exploring whether to sue Facebook, TikTok and other tech giants over claims that student use of social media platforms has created costly problems in district schools.

The potential litigation would seek payments "for the nuisance and other damages caused to the School District by virtue of student use and misuse of social media," according to an agreement the Erie School Board approved over a possible lawsuit.

A suit would "look at the negative side effects of social media in the school environment," said the Erie School District's solicitor, Tim Wachter. He said the 10,000-student district would want the social media companies to compensate the district for money it has spent addressing issues related to social media when that "money could have gone to education."

The School Board unanimously signed off on the deal on a possible lawsuit at its regular meeting on Wednesday night . The agreement authorizes the Erie law firm of Knox, McLaughlin, Gornall & Sennett, which includes Wachter, to partner with the Frazer law firm, of Nashville, Tennessee, "in connection with potential litigation" against the tech companies.

The potential defendants, according to the agreement, include Meta Platforms Inc., which owns Facebook and Instagram; Snap Inc., which owns Snapchat; TikTok; and Alphabet Inc., the parent organization of Google, which owns YouTube.

Scores of states are already suing Meta

The Erie School District is considering a lawsuit at the same time that 33 states, including Pennsylvania, are suing Meta over claims that Facebook and Instagram violate consumer protection laws by subjecting young users to "harmful, manipulative and addictive content," the Pennsylvania Attorney General's Office said in announcing that it was part of the lawsuit, filed Oct. 24 in U.S. District Court for the Northern District of California.

The suit claims, among other things, that "Meta specifically targets young users" and that "Meta prioritizes maximizing engagement over young users' safety."

Meta is seeking a dismissal of the case, which is before U.S. District Judge Yvonne Gonzalez Rogers, in Oakland. In a statement issued when the suit was filed, Meta said it shares the "commitment to providing teens with safe, positive experiences online, and have already introduced over 30 tools to support teens and their families," according to USA Today .

“We’re disappointed that instead of working productively with companies across the industry to create clear, age-appropriate standards for the many apps teens use, the attorneys general have chosen this path,” Meta also said.

Possible litigation resembles district's case against Juul

The Erie School District's exploration of a lawsuit against big tech echoes a strategy it pursued against Juul Labs Inc., the nation's largest electronic cigarette company.

With Erie School Board approval in 2021, the Erie School District joined thousands of of other school districts, as well as municipalities and states, in suing Juul.

The plaintiffs claimed Juul wrongfully marketed its products to youth, spurring a vaping epidemic among students, harming their health and adding to the costs of the school districts and other government entities.

Juul settled the Erie School District's claims for $239,171 a year ago . About $99,000 of the settlement proceeds went toward legal fees and costs, according to district records. The settlement agreement requires the district to use the rest of the money for public health initiatives and related measures.

The Knox firm partnered with the Frazer law firm on the Juul case. The two firms are once again deciding whether to sue big businesses — this time, Big Tech.

"It's very similar to what we did in the Juul case," Wachter said.

Contact Ed Palattella at  [email protected] or 814-870-1813. Follow him on X  @ETNpalattella .