the impact of social media on students research paper pdf

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Effects of Social Media Use on Psychological Well-Being: A Mediated Model

Dragana ostic.

1 School of Finance and Economics, Jiangsu University, Zhenjiang, China

Sikandar Ali Qalati

Belem barbosa.

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

Syed Mir Muhammad Shah

3 Department of Business Administration, Sukkur Institute of Business Administration (IBA) University, Sukkur, Pakistan

Esthela Galvan Vela

4 CETYS Universidad, Tijuana, Mexico

Ahmed Muhammad Herzallah

5 Department of Business Administration, Al-Quds University, Jerusalem, Israel

6 Business School, Shandong University, Weihai, China

Associated Data

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

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 ):

Conceptual model.

• 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.

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.

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.

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 .

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

Discriminant validity and correlation.

Bold values are the square root of the AVE .

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 ).

Summary of path coefficients and hypothesis testing.

Structural model.

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

Goodness of fit → SRMR = 0.063; d_ULS = 1.589; d_G = 0.512; chi-square = 2,910.744 .

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

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.

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.

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

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CONCEPTUAL ANALYSIS article

The effect of social media on the development of students’ affective variables.

• 1 Science and Technology Department, Nanjing University of Posts and Telecommunications, Nanjing, China
• 2 School of Marxism, Hohai University, Nanjing, Jiangsu, China
• 3 Government Enterprise Customer Center, China Mobile Group Jiangsu Co., Ltd., Nanjing, China

The use of social media is incomparably on the rise among students, influenced by the globalized forms of communication and the post-pandemic rush to use multiple social media platforms for education in different fields of study. Though social media has created tremendous chances for sharing ideas and emotions, the kind of social support it provides might fail to meet students’ emotional needs, or the alleged positive effects might be short-lasting. In recent years, several studies have been conducted to explore the potential effects of social media on students’ affective traits, such as stress, anxiety, depression, and so on. The present paper reviews the findings of the exemplary published works of research to shed light on the positive and negative potential effects of the massive use of social media on students’ emotional well-being. This review can be insightful for teachers who tend to take the potential psychological effects of social media for granted. They may want to know more about the actual effects of the over-reliance on and the excessive (and actually obsessive) use of social media on students’ developing certain images of self and certain emotions which are not necessarily positive. There will be implications for pre- and in-service teacher training and professional development programs and all those involved in student affairs.

Introduction

Social media has turned into an essential element of individuals’ lives including students in today’s world of communication. Its use is growing significantly more than ever before especially in the post-pandemic era, marked by a great revolution happening to the educational systems. Recent investigations of using social media show that approximately 3 billion individuals worldwide are now communicating via social media ( Iwamoto and Chun, 2020 ). This growing population of social media users is spending more and more time on social network groupings, as facts and figures show that individuals spend 2 h a day, on average, on a variety of social media applications, exchanging pictures and messages, updating status, tweeting, favoring, and commenting on many updated socially shared information ( Abbott, 2017 ).

Researchers have begun to investigate the psychological effects of using social media on students’ lives. Chukwuere and Chukwuere (2017) maintained that social media platforms can be considered the most important source of changing individuals’ mood, because when someone is passively using a social media platform seemingly with no special purpose, s/he can finally feel that his/her mood has changed as a function of the nature of content overviewed. Therefore, positive and negative moods can easily be transferred among the population using social media networks ( Chukwuere and Chukwuere, 2017 ). This may become increasingly important as students are seen to be using social media platforms more than before and social networking is becoming an integral aspect of their lives. As described by Iwamoto and Chun (2020) , when students are affected by social media posts, especially due to the increasing reliance on social media use in life, they may be encouraged to begin comparing themselves to others or develop great unrealistic expectations of themselves or others, which can have several affective consequences.

Considering the increasing influence of social media on education, the present paper aims to focus on the affective variables such as depression, stress, and anxiety, and how social media can possibly increase or decrease these emotions in student life. The exemplary works of research on this topic in recent years will be reviewed here, hoping to shed light on the positive and negative effects of these ever-growing influential platforms on the psychology of students.

Significance of the study

Though social media, as the name suggests, is expected to keep people connected, probably this social connection is only superficial, and not adequately deep and meaningful to help individuals feel emotionally attached to others. The psychological effects of social media on student life need to be studied in more depth to see whether social media really acts as a social support for students and whether students can use social media to cope with negative emotions and develop positive feelings or not. In other words, knowledge of the potential effects of the growing use of social media on students’ emotional well-being can bridge the gap between the alleged promises of social media and what it actually has to offer to students in terms of self-concept, self-respect, social role, and coping strategies (for stress, anxiety, etc.).

Exemplary general literature on psychological effects of social media

Before getting down to the effects of social media on students’ emotional well-being, some exemplary works of research in recent years on the topic among general populations are reviewed. For one, Aalbers et al. (2018) reported that individuals who spent more time passively working with social media suffered from more intense levels of hopelessness, loneliness, depression, and perceived inferiority. For another, Tang et al. (2013) observed that the procedures of sharing information, commenting, showing likes and dislikes, posting messages, and doing other common activities on social media are correlated with higher stress. Similarly, Ley et al. (2014) described that people who spend 2 h, on average, on social media applications will face many tragic news, posts, and stories which can raise the total intensity of their stress. This stress-provoking effect of social media has been also pinpointed by Weng and Menczer (2015) , who contended that social media becomes a main source of stress because people often share all kinds of posts, comments, and stories ranging from politics and economics, to personal and social affairs. According to Iwamoto and Chun (2020) , anxiety and depression are the negative emotions that an individual may develop when some source of stress is present. In other words, when social media sources become stress-inducing, there are high chances that anxiety and depression also develop.

Charoensukmongkol (2018) reckoned that the mental health and well-being of the global population can be at a great risk through the uncontrolled massive use of social media. These researchers also showed that social media sources can exert negative affective impacts on teenagers, as they can induce more envy and social comparison. According to Fleck and Johnson-Migalski (2015) , though social media, at first, plays the role of a stress-coping strategy, when individuals continue to see stressful conditions (probably experienced and shared by others in media), they begin to develop stress through the passage of time. Chukwuere and Chukwuere (2017) maintained that social media platforms continue to be the major source of changing mood among general populations. For example, someone might be passively using a social media sphere, and s/he may finally find him/herself with a changed mood depending on the nature of the content faced. Then, this good or bad mood is easily shared with others in a flash through the social media. Finally, as Alahmar (2016) described, social media exposes people especially the young generation to new exciting activities and events that may attract them and keep them engaged in different media contexts for hours just passing their time. It usually leads to reduced productivity, reduced academic achievement, and addiction to constant media use ( Alahmar, 2016 ).

The number of studies on the potential psychological effects of social media on people in general is higher than those selectively addressed here. For further insights into this issue, some other suggested works of research include Chang (2012) , Sriwilai and Charoensukmongkol (2016) , and Zareen et al. (2016) . Now, we move to the studies that more specifically explored the effects of social media on students’ affective states.

Review of the affective influences of social media on students

Vygotsky’s mediational theory (see Fernyhough, 2008 ) can be regarded as a main theoretical background for the support of social media on learners’ affective states. Based on this theory, social media can play the role of a mediational means between learners and the real environment. Learners’ understanding of this environment can be mediated by the image shaped via social media. This image can be either close to or different from the reality. In the case of the former, learners can develop their self-image and self-esteem. In the case of the latter, learners might develop unrealistic expectations of themselves by comparing themselves to others. As it will be reviewed below among the affective variables increased or decreased in students under the influence of the massive use of social media are anxiety, stress, depression, distress, rumination, and self-esteem. These effects have been explored more among school students in the age range of 13–18 than university students (above 18), but some studies were investigated among college students as well. Exemplary works of research on these affective variables are reviewed here.

In a cross-sectional study, O’Dea and Campbell (2011) explored the impact of online interactions of social networks on the psychological distress of adolescent students. These researchers found a negative correlation between the time spent on social networking and mental distress. Dumitrache et al. (2012) explored the relations between depression and the identity associated with the use of the popular social media, the Facebook. This study showed significant associations between depression and the number of identity-related information pieces shared on this social network. Neira and Barber (2014) explored the relationship between students’ social media use and depressed mood at teenage. No significant correlation was found between these two variables. In the same year, Tsitsika et al. (2014) explored the associations between excessive use of social media and internalizing emotions. These researchers found a positive correlation between more than 2-h a day use of social media and anxiety and depression.

Hanprathet et al. (2015) reported a statistically significant positive correlation between addiction to Facebook and depression among about a thousand high school students in wealthy populations of Thailand and warned against this psychological threat. Sampasa-Kanyinga and Lewis (2015) examined the relationship between social media use and psychological distress. These researchers found that the use of social media for more than 2 h a day was correlated with a higher intensity of psychological distress. Banjanin et al. (2015) tested the relationship between too much use of social networking and depression, yet found no statistically significant correlation between these two variables. Frison and Eggermont (2016) examined the relationships between different forms of Facebook use, perceived social support of social media, and male and female students’ depressed mood. These researchers found a positive association between the passive use of the Facebook and depression and also between the active use of the social media and depression. Furthermore, the perceived social support of the social media was found to mediate this association. Besides, gender was found as the other factor to mediate this relationship.

Vernon et al. (2017) explored change in negative investment in social networking in relation to change in depression and externalizing behavior. These researchers found that increased investment in social media predicted higher depression in adolescent students, which was a function of the effect of higher levels of disrupted sleep. Barry et al. (2017) explored the associations between the use of social media by adolescents and their psychosocial adjustment. Social media activity showed to be positively and moderately associated with depression and anxiety. Another investigation was focused on secondary school students in China conducted by Li et al. (2017) . The findings showed a mediating role of insomnia on the significant correlation between depression and addiction to social media. In the same year, Yan et al. (2017) aimed to explore the time spent on social networks and its correlation with anxiety among middle school students. They found a significant positive correlation between more than 2-h use of social networks and the intensity of anxiety.

Also in China, Wang et al. (2018) showed that addiction to social networking sites was correlated positively with depression, and this correlation was mediated by rumination. These researchers also found that this mediating effect was moderated by self-esteem. It means that the effect of addiction on depression was compounded by low self-esteem through rumination. In another work of research, Drouin et al. (2018) showed that though social media is expected to act as a form of social support for the majority of university students, it can adversely affect students’ mental well-being, especially for those who already have high levels of anxiety and depression. In their research, the social media resources were found to be stress-inducing for half of the participants, all university students. The higher education population was also studied by Iwamoto and Chun (2020) . These researchers investigated the emotional effects of social media in higher education and found that the socially supportive role of social media was overshadowed in the long run in university students’ lives and, instead, fed into their perceived depression, anxiety, and stress.

Keles et al. (2020) provided a systematic review of the effect of social media on young and teenage students’ depression, psychological distress, and anxiety. They found that depression acted as the most frequent affective variable measured. The most salient risk factors of psychological distress, anxiety, and depression based on the systematic review were activities such as repeated checking for messages, personal investment, the time spent on social media, and problematic or addictive use. Similarly, Mathewson (2020) investigated the effect of using social media on college students’ mental health. The participants stated the experience of anxiety, depression, and suicidality (thoughts of suicide or attempts to suicide). The findings showed that the types and frequency of using social media and the students’ perceived mental health were significantly correlated with each other.

The body of research on the effect of social media on students’ affective and emotional states has led to mixed results. The existing literature shows that there are some positive and some negative affective impacts. Yet, it seems that the latter is pre-dominant. Mathewson (2020) attributed these divergent positive and negative effects to the different theoretical frameworks adopted in different studies and also the different contexts (different countries with whole different educational systems). According to Fredrickson’s broaden-and-build theory of positive emotions ( Fredrickson, 2001 ), the mental repertoires of learners can be built and broadened by how they feel. For instance, some external stimuli might provoke negative emotions such as anxiety and depression in learners. Having experienced these negative emotions, students might repeatedly check their messages on social media or get addicted to them. As a result, their cognitive repertoire and mental capacity might become limited and they might lose their concentration during their learning process. On the other hand, it should be noted that by feeling positive, learners might take full advantage of the affordances of the social media and; thus, be able to follow their learning goals strategically. This point should be highlighted that the link between the use of social media and affective states is bi-directional. Therefore, strategic use of social media or its addictive use by students can direct them toward either positive experiences like enjoyment or negative ones such as anxiety and depression. Also, these mixed positive and negative effects are similar to the findings of several other relevant studies on general populations’ psychological and emotional health. A number of studies (with general research populations not necessarily students) showed that social networks have facilitated the way of staying in touch with family and friends living far away as well as an increased social support ( Zhang, 2017 ). Given the positive and negative emotional effects of social media, social media can either scaffold the emotional repertoire of students, which can develop positive emotions in learners, or induce negative provokers in them, based on which learners might feel negative emotions such as anxiety and depression. However, admittedly, social media has also generated a domain that encourages the act of comparing lives, and striving for approval; therefore, it establishes and internalizes unrealistic perceptions ( Virden et al., 2014 ; Radovic et al., 2017 ).

It should be mentioned that the susceptibility of affective variables to social media should be interpreted from a dynamic lens. This means that the ecology of the social media can make changes in the emotional experiences of learners. More specifically, students’ affective variables might self-organize into different states under the influence of social media. As for the positive correlation found in many studies between the use of social media and such negative effects as anxiety, depression, and stress, it can be hypothesized that this correlation is induced by the continuous comparison the individual makes and the perception that others are doing better than him/her influenced by the posts that appear on social media. Using social media can play a major role in university students’ psychological well-being than expected. Though most of these studies were correlational, and correlation is not the same as causation, as the studies show that the number of participants experiencing these negative emotions under the influence of social media is significantly high, more extensive research is highly suggested to explore causal effects ( Mathewson, 2020 ).

As the review of exemplary studies showed, some believed that social media increased comparisons that students made between themselves and others. This finding ratifies the relevance of the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ) and Festinger’s (1954) Social Comparison Theory. Concerning the negative effects of social media on students’ psychology, it can be argued that individuals may fail to understand that the content presented in social media is usually changed to only represent the attractive aspects of people’s lives, showing an unrealistic image of things. We can add that this argument also supports the relevance of the Social Comparison Theory and the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ), because social media sets standards that students think they should compare themselves with. A constant observation of how other students or peers are showing their instances of achievement leads to higher self-evaluation ( Stapel and Koomen, 2000 ). It is conjectured that the ubiquitous role of social media in student life establishes unrealistic expectations and promotes continuous comparison as also pinpointed in the Interpretation Comparison Model ( Stapel and Koomen, 2000 ; Stapel, 2007 ).

Implications of the study

The use of social media is ever increasing among students, both at school and university, which is partly because of the promises of technological advances in communication services and partly because of the increased use of social networks for educational purposes in recent years after the pandemic. This consistent use of social media is not expected to leave students’ psychological, affective and emotional states untouched. Thus, it is necessary to know how the growing usage of social networks is associated with students’ affective health on different aspects. Therefore, we found it useful to summarize the research findings in recent years in this respect. If those somehow in charge of student affairs in educational settings are aware of the potential positive or negative effects of social media usage on students, they can better understand the complexities of students’ needs and are better capable of meeting them.

Psychological counseling programs can be initiated at schools or universities to check upon the latest state of students’ mental and emotional health influenced by the pervasive use of social media. The counselors can be made aware of the potential adverse effects of social networking and can adapt the content of their inquiries accordingly. Knowledge of the potential reasons for student anxiety, depression, and stress can help school or university counselors to find individualized coping strategies when they diagnose any symptom of distress in students influenced by an excessive use of social networking.

Admittedly, it is neither possible to discard the use of social media in today’s academic life, nor to keep students’ use of social networks fully controlled. Certainly, the educational space in today’s world cannot do without the social media, which has turned into an integral part of everybody’s life. Yet, probably students need to be instructed on how to take advantage of the media and to be the least affected negatively by its occasional superficial and unrepresentative content. Compensatory programs might be needed at schools or universities to encourage students to avoid making unrealistic and impartial comparisons of themselves and the flamboyant images of others displayed on social media. Students can be taught to develop self-appreciation and self-care while continuing to use the media to their benefit.

The teachers’ role as well as the curriculum developers’ role are becoming more important than ever, as they can significantly help to moderate the adverse effects of the pervasive social media use on students’ mental and emotional health. The kind of groupings formed for instructional purposes, for example, in social media can be done with greater care by teachers to make sure that the members of the groups are homogeneous and the tasks and activities shared in the groups are quite relevant and realistic. The teachers cannot always be in a full control of students’ use of social media, and the other fact is that students do not always and only use social media for educational purposes. They spend more time on social media for communicating with friends or strangers or possibly they just passively receive the content produced out of any educational scope just for entertainment. This uncontrolled and unrealistic content may give them a false image of life events and can threaten their mental and emotional health. Thus, teachers can try to make students aware of the potential hazards of investing too much of their time on following pages or people that publish false and misleading information about their personal or social identities. As students, logically expected, spend more time with their teachers than counselors, they may be better and more receptive to the advice given by the former than the latter.

Teachers may not be in full control of their students’ use of social media, but they have always played an active role in motivating or demotivating students to take particular measures in their academic lives. If teachers are informed of the recent research findings about the potential effects of massively using social media on students, they may find ways to reduce students’ distraction or confusion in class due to the excessive or over-reliant use of these networks. Educators may more often be mesmerized by the promises of technology-, computer- and mobile-assisted learning. They may tend to encourage the use of social media hoping to benefit students’ social and interpersonal skills, self-confidence, stress-managing and the like. Yet, they may be unaware of the potential adverse effects on students’ emotional well-being and, thus, may find the review of the recent relevant research findings insightful. Also, teachers can mediate between learners and social media to manipulate the time learners spend on social media. Research has mainly indicated that students’ emotional experiences are mainly dependent on teachers’ pedagogical approach. They should refrain learners from excessive use of, or overreliance on, social media. Raising learners’ awareness of this fact that individuals should develop their own path of development for learning, and not build their development based on unrealistic comparison of their competences with those of others, can help them consider positive values for their activities on social media and, thus, experience positive emotions.

At higher education, students’ needs are more life-like. For example, their employment-seeking spirits might lead them to create accounts in many social networks, hoping for a better future. However, membership in many of these networks may end in the mere waste of the time that could otherwise be spent on actual on-campus cooperative projects. Universities can provide more on-campus resources both for research and work experience purposes from which the students can benefit more than the cyberspace that can be tricky on many occasions. Two main theories underlying some negative emotions like boredom and anxiety are over-stimulation and under-stimulation. Thus, what learners feel out of their involvement in social media might be directed toward negative emotions due to the stimulating environment of social media. This stimulating environment makes learners rely too much, and spend too much time, on social media or use them obsessively. As a result, they might feel anxious or depressed. Given the ubiquity of social media, these negative emotions can be replaced with positive emotions if learners become aware of the psychological effects of social media. Regarding the affordances of social media for learners, they can take advantage of the potential affordances of these media such as improving their literacy, broadening their communication skills, or enhancing their distance learning opportunities.

A review of the research findings on the relationship between social media and students’ affective traits revealed both positive and negative findings. Yet, the instances of the latter were more salient and the negative psychological symptoms such as depression, anxiety, and stress have been far from negligible. These findings were discussed in relation to some more relevant theories such as the social comparison theory, which predicted that most of the potential issues with the young generation’s excessive use of social media were induced by the unfair comparisons they made between their own lives and the unrealistic portrayal of others’ on social media. Teachers, education policymakers, curriculum developers, and all those in charge of the student affairs at schools and universities should be made aware of the psychological effects of the pervasive use of social media on students, and the potential threats.

It should be reminded that the alleged socially supportive and communicative promises of the prevalent use of social networking in student life might not be fully realized in practice. Students may lose self-appreciation and gratitude when they compare their current state of life with the snapshots of others’ or peers’. A depressed or stressed-out mood can follow. Students at schools or universities need to learn self-worth to resist the adverse effects of the superficial support they receive from social media. Along this way, they should be assisted by the family and those in charge at schools or universities, most importantly the teachers. As already suggested, counseling programs might help with raising students’ awareness of the potential psychological threats of social media to their health. Considering the ubiquity of social media in everybody’ life including student life worldwide, it seems that more coping and compensatory strategies should be contrived to moderate the adverse psychological effects of the pervasive use of social media on students. Also, the affective influences of social media should not be generalized but they need to be interpreted from an ecological or contextual perspective. This means that learners might have different emotions at different times or different contexts while being involved in social media. More specifically, given the stative approach to learners’ emotions, what learners emotionally experience in their application of social media can be bound to their intra-personal and interpersonal experiences. This means that the same learner at different time points might go through different emotions Also, learners’ emotional states as a result of their engagement in social media cannot be necessarily generalized to all learners in a class.

As the majority of studies on the psychological effects of social media on student life have been conducted on school students than in higher education, it seems it is too soon to make any conclusive remark on this population exclusively. Probably, in future, further studies of the psychological complexities of students at higher education and a better knowledge of their needs can pave the way for making more insightful conclusions about the effects of social media on their affective states.

Suggestions for further research

The majority of studies on the potential effects of social media usage on students’ psychological well-being are either quantitative or qualitative in type, each with many limitations. Presumably, mixed approaches in near future can better provide a comprehensive assessment of these potential associations. Moreover, most studies on this topic have been cross-sectional in type. There is a significant dearth of longitudinal investigation on the effect of social media on developing positive or negative emotions in students. This seems to be essential as different affective factors such as anxiety, stress, self-esteem, and the like have a developmental nature. Traditional research methods with single-shot designs for data collection fail to capture the nuances of changes in these affective variables. It can be expected that more longitudinal studies in future can show how the continuous use of social media can affect the fluctuations of any of these affective variables during the different academic courses students pass at school or university.

As already raised in some works of research reviewed, the different patterns of impacts of social media on student life depend largely on the educational context. Thus, the same research designs with the same academic grade students and even the same age groups can lead to different findings concerning the effects of social media on student psychology in different countries. In other words, the potential positive and negative effects of popular social media like Facebook, Snapchat, Twitter, etc., on students’ affective conditions can differ across different educational settings in different host countries. Thus, significantly more research is needed in different contexts and cultures to compare the results.

There is also a need for further research on the higher education students and how their affective conditions are positively and negatively affected by the prevalent use of social media. University students’ psychological needs might be different from other academic grades and, thus, the patterns of changes that the overall use of social networking can create in their emotions can be also different. Their main reasons for using social media might be different from school students as well, which need to be investigated more thoroughly. The sorts of interventions needed to moderate the potential negative effects of social networking on them can be different too, all requiring a new line of research in education domain.

Finally, there are hopes that considering the ever-increasing popularity of social networking in education, the potential psychological effects of social media on teachers be explored as well. Though teacher psychology has only recently been considered for research, the literature has provided profound insights into teachers developing stress, motivation, self-esteem, and many other emotions. In today’s world driven by global communications in the cyberspace, teachers like everyone else are affecting and being affected by social networking. The comparison theory can hold true for teachers too. Thus, similar threats (of social media) to self-esteem and self-worth can be there for teachers too besides students, which are worth investigating qualitatively and quantitatively.

Probably a new line of research can be initiated to explore the co-development of teacher and learner psychological traits under the influence of social media use in longitudinal studies. These will certainly entail sophisticated research methods to be capable of unraveling the nuances of variation in these traits and their mutual effects, for example, stress, motivation, and self-esteem. If these are incorporated within mixed-approach works of research, more comprehensive and better insightful findings can be expected to emerge. Correlational studies need to be followed by causal studies in educational settings. As many conditions of the educational settings do not allow for having control groups or randomization, probably, experimental studies do not help with this. Innovative research methods, case studies or else, can be used to further explore the causal relations among the different features of social media use and the development of different affective variables in teachers or learners. Examples of such innovative research methods can be process tracing, qualitative comparative analysis, and longitudinal latent factor modeling (for a more comprehensive view, see Hiver and Al-Hoorie, 2019 ).

Author contributions

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

This study was sponsored by Wuxi Philosophy and Social Sciences bidding project—“Special Project for Safeguarding the Rights and Interests of Workers in the New Form of Employment” (Grant No. WXSK22-GH-13). This study was sponsored by the Key Project of Party Building and Ideological and Political Education Research of Nanjing University of Posts and Telecommunications—“Research on the Guidance and Countermeasures of Network Public Opinion in Colleges and Universities in the Modern Times” (Grant No. XC 2021002).

Conflict of interest

Author XX was employed by China Mobile Group Jiangsu Co., Ltd.

The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords : affective variables, education, emotions, social media, post-pandemic, emotional needs

Citation: Chen M and Xiao X (2022) The effect of social media on the development of students’ affective variables. Front. Psychol. 13:1010766. doi: 10.3389/fpsyg.2022.1010766

Received: 03 August 2022; Accepted: 25 August 2022; Published: 15 September 2022.

Reviewed by:

Copyright © 2022 Chen and Xiao. 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: Miao Chen, [email protected] ; Xin Xiao, [email protected]

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