hypothesis questions about social media

• Open access
• Published: 22 September 2023

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

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

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

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

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

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

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

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Introduction

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

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

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

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

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

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

Proposed moderated mediation model

Literature review and hypotheses development

Students’ social media usage and well-being.

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

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

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

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

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

Self-esteem and online social support as mediators

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

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

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

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

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

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

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

Cyberbullying as a moderator

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

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

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

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

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

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

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

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

Methodology

Participants and procedure.

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

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

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

Social media usage scale

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

Cyberbullying scale

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

Self-esteem scale

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

Online social support scale

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

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

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

Statistical analysis

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

Validity, construct reliability, and common method variance

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

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

Preliminary analyses

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

Testing for the mediating effect

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

Testing for moderated mediation

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

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

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

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

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

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

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

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

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

Limitations and future directions

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

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

Theoretical and practical implications

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

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

Availability of data and materials

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

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

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• Fergal W. Jones   ORCID: orcid.org/0000-0001-9459-6631 1  

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Qualitative research into adolescents’ experiences of social media use and well-being has the potential to offer rich, nuanced insights, but has yet to be systematically reviewed. The current systematic review identified 19 qualitative studies in which adolescents shared their views and experiences of social media and well-being. A critical appraisal showed that overall study quality was considered relatively high and represented geographically diverse voices across a broad adolescent age range. A thematic meta-synthesis revealed four themes relating to well-being: connections, identity, learning, and emotions. These findings demonstrated the numerous sources of pressures and concerns that adolescents experience, providing important contextual information. The themes appeared related to key developmental processes, namely attachment, identity, attention, and emotional regulation, that provided theoretical links between social media use and well-being. Taken together, the findings suggest that well-being and social media are related by a multifaceted interplay of factors. Suggestions are made that may enhance future research and inform developmentally appropriate social media guidance.

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Acknowlegement

We extend our gratitude to the authors of the original studies for bringing forth the perspectives of young people.

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The review protocol including review question, search strategy, inclusion criteria data extraction, quality assessment, data synthesis was preregistered and is accessible at: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=156922 .

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MS conceived of the study, participated in its design, coordination, interpretation of the data and drafted the manuscript; LH participated in the design and interpretation of the data; FWJ participated in the design and interpretation of the data. All authors read, helped to draft, and approved the final manuscript.

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Shankleman, M., Hammond, L. & Jones, F.W. Adolescent Social Media Use and Well-Being: A Systematic Review and Thematic Meta-synthesis. Adolescent Res Rev 6 , 471–492 (2021). https://doi.org/10.1007/s40894-021-00154-5

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Social media use and social connectedness among adolescents in the United Kingdom: a qualitative exploration of displacement and stimulation

• Lizzy Winstone 1 ,
• Becky Mars 1 , 2 ,
• Claire M. A. Haworth 2 , 3 , 4 &
• Judi Kidger 1  

BMC Public Health volume  21 , Article number:  1736 ( 2021 ) Cite this article

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Connectedness to family and peers is a key determinant of adolescent mental health. Existing research examining associations between social media use and social connectedness has been largely quantitative and has focused primarily on loneliness, or on specific aspects of peer relationships. In this qualitative study we use the displacement hypothesis and the stimulation hypothesis as competing theoretical lenses through which we examine the complex relationship between social media use and feelings of connectedness to family and peers.

In-depth paired and individual interviews were conducted with twenty-four 13–14-year-olds in two inner-city English secondary schools. Interviews were transcribed verbatim, coded and thematically analysed.

Analysis identified four themes: (i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’. Results indicated stronger support for the stimulation hypothesis than the displacement hypothesis. We found evidence of a complex set of reciprocal and circular relationships between social media use and connectedness consistent with a ‘rich-get-richer’ and a ‘poor-get-poorer’ effect for family and peer connectedness – and a ‘poor-get-richer’ effect in peer connectedness for those who find face-to-face interactions difficult.

Our findings suggest that parents should take a measured approach to social media use, providing clear guidance, promoting trust and responsible time management, and acknowledging the role of social media in making connections. Understanding and sharing in online experiences is likely to promote social connectedness. Supporting young people to negotiate breathing space in online interactions and prioritising trust over availability in peer relationships may optimise the role of social media in promoting peer connectedness.

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Introduction

Social connectedness is defined as feelings of belonging and closeness to others, as well as satisfaction with relationships and perceived support and opportunities for self-disclosure of personal information. It comprises different domains (peer, school, family and community/ neighbourhood) and is a key social determinant of adolescent mental health and well-being [ 1 , 2 , 3 ]. Family connectedness in particular has been found to buffer the negative effects of bullying and to be related to lower risk for suicide-related outcomes and depressive symptoms [ 3 , 4 ].

Social media use (SMU) is thought to have both positive and negative influences on the lives of young people, for whom it has become an integral part of daily life [ 5 ]. In 2018, 80% of 14-year-olds in the United Kingdom (UK) had a profile on a social media or messaging app [ 6 ]. For the purposes of this study, we include within social media social network sites as defined by boyd and Ellison [ 7 ], in addition to web-based messaging and microblogging services (such as WhatsApp and Tumblr) and social video platforms (such as YouTube). SMU has various functions, with users typically seeking entertainment, communication, inspiration and information. The use of social media to engage with others, either through direct communication or through the publication or consumption of content and its associated feedback, makes it an inherently social part of adolescence [ 8 ]. As such, SMU may have important implications for increasing connectedness with individuals and groups [ 9 ]. However, concerns have been raised by parents about screen-time interfering with other activities that may also be beneficial to connectedness [ 10 ], such as schoolwork, extra-curricular activities and engaging with others face-to-face. Through these competing processes of stimulation and displacement, SMU may simultaneously enhance and undermine social connectedness in adolescence [ 9 ].

The displacement and stimulation hypotheses

The displacement hypothesis was formulated on the basis of internet use rather than social media specifically [ 11 ]. The theory of displacement is two-fold, regarding both time displacement and displacement of strong social ties with weak ones. Use of the internet for entertainment purposes – as a solitary, socially disengaged activity comparable to passive consumption of social media content without active engagement – is thought to displace time spent socialising with others offline, subsequently undermining social connectedness [ 11 , 12 ]. Where used for communication purposes, online engagement and expansion of social networks were thought to be primarily with weak ties rather than with close family and friends, and as such, of little benefit to psychosocial well-being [ 11 , 13 ].

In line with this hypothesis, previous research has found that SMU is associated with increases in bridging but not bonding social capital, whereby vast expansion of social networks made possible through SMU enhances the number of weak social ties rather than improving relationships with close friends and family [ 5 ]. SMU may also displace time spent on other activities beneficial to well-being, including physical exercise and sleep [ 14 , 15 ]. With regards to family connectedness, an intensive longitudinal experience sampling study found little evidence that time spent using digital technology displaced time spent engaging offline with parents or resulted in problematic parent-adolescent offline interactions [ 16 ].

Evidence also exists in support of an opposing theory, the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships [ 17 , 18 ]. In direct contradiction to the displacement hypothesis (whereby strong social ties are displaced with weak ones) it has been suggested that adolescents are increasingly using social media to enhance the quality of existing friendships rather than seeking out new connections, leading to beneficial impacts on social connectedness and social and emotional support [ 17 ].

One study directly compared the two competing hypotheses and found that, rather than displacing time spent offline with friends, use of instant messenger was positively related to face-to-face socialising, in turn predicting better friendship quality and well-being [ 19 ]. This effect was specific to using instant messenger to communicate with friends and did not apply to use of chat rooms (primarily with strangers). The authors suggested that features of online communication – including asynchronous responding and absence of nonverbal cues or responses –could lower social inhibition and encourage sharing of personal information. These intimate self-disclosures can be beneficial to well-being and peer connectedness through enhancing feelings of support and trust [ 20 , 21 ].

Using experience sampling methodology, researchers have explored fluctuations in adolescents’ use of Instagram, Snapchat and WhatsApp with and without close friends [ 8 ]. Findings illustrated the complexity of the relationship between SMU and friendship closeness, with substantial differences at the within- and between-person level. Those who used Instagram or WhatsApp in the previous hour (whether with or without close friends) reported feeling slightly less close to close friends, however, those with a higher average frequency across a three-week period felt closer to their friends than those with less frequent use. Snapchat use was not found to be related to friendship closeness at either the within or between person level [ 8 ]. These findings were echoed in a study showing evidence for the displacement hypothesis at the within-person level – with increases in smartphone communication on a particular day reducing face-to-face interaction for a given individual – but not the between-person level – with no discernible difference in the level of face-to-face interaction for more or less prolific online communicators [ 22 ].

There is also evidence to suggest the relationship with SMU may be curvilinear, with only excessive levels of SMU found to be associated with lower levels of social capital [ 20 , 23 ] or poorer psychosocial functioning [ 24 ]. In a longitudinal study of adolescents in Belgium [ 23 ], Wang et al. found that low to moderate levels of active public Facebook use (that is broadcasting content publicly but not direct messaging with others) were associated with decreased loneliness over time, supporting the stimulation hypothesis. However, higher levels of broadcasting were associated with increased loneliness over time, indicating support for the displacement hypothesis. This indicates that rather than being mutually exclusive theories, both the stimulation and displacement hypotheses may be possible, depending on both the amount and type of SMU [ 17 ].

Objectives of the current study

Most existing research examining the displacement and stimulation hypotheses has been quantitative and has focused primarily on peer connectedness. Qualitative research, and research exploring the relationship between adolescent SMU and family connectedness is scarce. This qualitative study aimed to examine the relationship between SMU and social connectedness (encompassing peers and family) through the experiences and perspectives of a sample of 13–14-year-olds in south-west England.

Participants

Thirteen interviews were conducted with 24 Year 9 students aged 13–14 years (19 girls and five boys) in February–March 2020. Interviews took place at two English secondary schools in inner-city locations. One was in a particularly deprived area with an ethnically diverse and lower socio-economic status student population (measured by the proportion of students eligible for free school meals). The other was a single sex girls’ school with a higher-than-average socio-economic status population. Heads of Year 9 in each school were asked to advertise the study to all classes in the year group, with participant information sheets provided. The information sheets encouraged students with a range of social media experiences to take part, including those who considered themselves to be non-users. Two participants presented themselves as non-users of social media, describing their use of YouTube solely for entertainment purposes. Students volunteered to take part and all volunteers were selected for interview providing they returned signed parental consent forms by a cut-off date. In advance of the interviews, participants indicated on consent forms their preference for participation in an individual or paired interview with a friend (Table  1 ). Participants received a £10 Amazon voucher by way of thanks.

Design and procedure

Interviews were all conducted face-to-face by LW. LW is a female PhD student with some previous experience of conducting in-depth interviews with adults, and is trained in qualitative data analysis and conducting research with young people. JK oversaw the process and is a female academic with extensive qualitative research experience. The interviews were audio recorded, took place at school during lesson time and lasted between 45 min and an hour. A topic guide (available in Additional file  1 ) was used to ensure consistency in covering a number of core areas for discussion, including typical apps and activities used, family and school rules regarding SMU, online interactions with peers, family or strangers and SMU in those experiencing poor mental health. The guide was developed following consultation with a young people’s advisory board – a group of 11–18-year-olds with experience in advising on the design of health-related research materials. The group provided input into issues they felt most important relating to SMU and mental health. Flexibility in the topic guide allowed interview participants to take the conversation in any direction they felt to be relevant to the broad issue of social media and mental health, reflecting on their own SMU as well as that of their peers. This flexibility was felt to be important in mitigating the impact of the adult researchers’ preconceptions about adolescent SMU, social connectedness and mental health, enabling openness to experiences recognised as meaningful by participants themselves.

Data analysis

An inductive, reflexive approach to thematic analysis was used from a critical realist (contextualist) perspective [ 25 ]. SMU is so intertwined with one’s experience and perceptions of interpersonal and intergroup relationships that it would not make sense to refer to there being an authentic truth or reality. However, as researchers aspiring to improve public mental health through recommendations to stakeholders, we need to acknowledge young people’s experiences and feelings as an external reality, whilst recognising the prisms through which these are encountered by young people and interpreted by ourselves [ 25 ]. We interpreted the data as adults who experienced adolescence in a time before social media existed and we reflected on this throughout the analytic process.

Notes were taken during and after each interview. These were not coded but used in reflection during analysis. The interviews were transcribed verbatim and imported into NVivo version 12 for coding by LW. Analysis was conducted primarily by LW, from the perspective of an adult using social media for direct communication with existing friends and family. LW acknowledges that her own experiences – both positive and negative – of SMU will unavoidably frame her interpretation of the data.

A systematic and inclusive coding process was adopted, with coding applied flexibly to include unexpected data [ 25 ]. Codes were both descriptive (e.g., ‘nothing to do’) and interpretative (e.g., ‘privacy concerns’). Following coding of the complete dataset, initial themes were constructed and reviewed iteratively when examined against each interview, with thematic boundaries altered as necessary. Further amendments were made where appropriate following group discussion between the authors to review both codes and themes. During the review process codes considered irrelevant to the research question (e.g., ‘apps’) were discarded or included within other codes where appropriate (e.g., ‘memories’ was encapsulated within ‘friendships’). Two previously separate themes – ‘keeping in touch’ and ‘time displacement’ were merged into ‘displacement of face-to-face socialising’. Once themes were developed, they were examined in relation to the displacement and stimulation hypotheses to see whether findings confirmed, contradicted, or developed these theories. Participants were not asked to provide feedback on the findings.

Four themes were identified through analysis of the qualitative interview data with regard to SMU and social connectedness. Table  2 provides an overview of these themes and sub-themes with key illustrative data extracts. Each sub-theme is discussed in turn, along with implications for displacement and stimulation theories. There were no systematic differences in opinions and experiences between participants from the two different schools or those interviewed individually compared to with others, so comparisons are not presented here.

Displacement of face-to-face socialising

Elements of both displacement and stimulation were interwoven in discussions of online and offline socialising. Participants’ own SMU was sometimes felt to displace face-to-face social activities that promote feelings of connectedness. However, online peer interactions frequently took place when in-person socialising was not possible, helping to alleviate feelings of boredom and loneliness. Social network expansion was also highlighted as a key benefit of SMU, meeting new people, and maintaining contact with old friends outside of school and family members abroad.

Socialising with family

Several participants suggested that time spent socialising with family members would likely increase if they were to reduce their social media screen-time. Participant F5 spoke about recently breaking her phone and noted the positive impact it had on increasing time spent with her family.

Those participants who appeared to be minimal social media users reflected most on the importance of not ‘missing out’ on time with family (M3). Being with and ‘helping’ (M2) family was highlighted as a priority for these participants, with M2 suggesting that ‘talking to your family… is safer than talking on social media’. The strong family connectedness depicted by these participants appeared to have a protective effect against SMU displacing time spent together.

More frequently however, references to family connectedness and screen-time suggested increased SMU was a result rather than a cause of poor connectedness. Several participants alluded to their SMU at home as a means of reducing boredom or loneliness, because family members were not available to share meals or converse (F1, F2, M4, F6, F7, F12, F16). Some participants described family situations where disruption to home life, unsocial family dynamics or parents’ work patterns created time where they were left alone and turned to SMU because there was ‘nothing else to do’ (F1, F18, F19). F7 described sitting alone to eat dinner while using her phone and noted ‘…we just don’t do things as a family. It’s not social media, it’s just like, we just don’t do things.’

Consistent with the stimulation hypothesis, participants explained the benefits of communicating via social media to stay connected to family members who did not live close by, enhancing family connectedness beyond the nuclear family unit. This was felt to be particularly beneficial to those who would otherwise find the cost of overseas communication prohibitive. For some, this applied to one-to-one relationships with cousins of a similar age (F8). For others, group chats on social media enabled geographically disparate family members to come together as one to catch up or celebrate special occasions (F3).

Rather than displacing time spent socialising face-to-face with family, these comments showed how SMU was an important means of maintaining social interaction when in-person contact was not possible.

Socialising with friends

Across the sample, there were diverging opinions as to whether there was a difference between online and face-to-face socialising. In line with the displacement hypothesis, some found socialising through social media to be less rewarding than face-to-face, pointing particularly to the more genuine feel to in-person interactions where ‘you’ll see how they really are in person’ (F4) and can ‘gauge more’ (F6). Others gave opinions more aligned with the stimulation hypothesis, whereby online socialising facilitated offline interaction when they felt their own personalities to be ‘shy’ or socially ‘awkward’ (F6) – a social compensation effect [ 26 ]. As participant F10 put it, ‘I’m better friends with people because I’ve spoken to them more online and therefore in real life, we’re better friends. I wouldn’t say it’s different, no’.

As with family interactions, some participants pointed to the possibility of excessive SMU displacing time spent socialising in person with friends, leading some young people to ‘distance themselves from family and friends’ (M5). Some participants expressed a desire to reduce their own SMU to spend more time ‘meeting up with those people’ they were communicating with online (F5).

However, those who were more frequent users again indicated that online interactions generally replaced face-to-face out of necessity. Friends who were unable to socialise in person due to geographical constraints turned to social media to maintain peer-to-peer interaction. This applied to ‘long-distance friendships’ (F16), keeping in touch with friends at other schools, and those who did not live within walking distance to their close friends (F18).

Yes, that’s one of the reasons I use social media so much, it’s because all of my friends live so far away. I think my closest friend lives a 20-minute drive from me. So, I use social media to stay in contact with everyone, because that’s the only way you can really talk to people. (F19)

SMU was thus felt to strengthen or maintain peer connectedness for those with reduced opportunities for offline socialising, providing a protective effect from the risks of poor peer connectedness or loneliness.

SMU also promoted continuity of social networks, enabling young people to stay ‘connected’ (F12) with old friends from primary school, those who have moved away from the area, and friendships formed from extracurricular activities (F10). Without social media, there was a perceived risk that such ‘friendship[s] would just die’ (F16). Rather than ‘weak ties’ of vast online networks suggested by the displacement hypothesis [ 11 ], these were presented as close friendships whose enduring existence was stimulated by SMU in the absence of opportunities for offline interaction.

What social media is used for may influence whether it is perceived by the user to be displacing time spent with peers. Participant M1 pointed to the difference between playing PlayStation with a headset on, ‘talking to your friends… you are playing but also talking, so I feel more social, more talkative’ and ‘when you are using social media [passively], you feel isolated. You are just on your phone’ (M1). Whereas passive or excessive SMU may be perceived to displace face-to-face interaction, using social media explicitly for socialising may fulfil more of a stimulation function – enabling friends to ‘hang out’ (M4, M5) online when doing so in person is not possible.

In addition to maintaining stability within their social circle, SMU was also often credited with expansion of participants’ social circle through making new friends online, both by offering opportunities for new introductions, such as through a ‘mutual friend’ (F5), and by facilitating the development of friendships through initial online communication, which felt less intimidating than new face-to-face socialising (M4). Supporting the online enhanced self-disclosure or social compensation hypothesis [ 26 ] this was found to be particularly helpful to F6, who described herself as ‘shy’.

I feel like it’s easier for me because I feel like… if I’d just met someone, like, if someone just came to school now and we had to be friends, I feel like it would take me a while to, like, be able to talk to them without feeling… It depends. I think sometimes I’m really shy, and I think sometimes I’d rather just get to know someone online first… (F6)

As such, SMU was determined to be an important – and in some cases, critical – means of maintaining and expanding the size of young people’s social networks. SMU was explicitly credited by some participants for network expansion over and above friendship closeness. The network enhancing benefits they ascribed to SMU may be aligned to some extent with the ‘weak ties’ suggested by the displacement hypothesis, bringing limited psychosocial reward [ 11 , 13 ]. However, many young people in our sample referred to most of their online interactions and relationship maintenance being with existing close friends, illustrative of a stimulation effect. The importance of network size for well-being may vary across individuals, and a discussion between participants F6 and F7 noted the distinction between small numbers of ‘deep’ friendships (F6) that traverse online and offline worlds, and the tendency for some young people (including themselves at an earlier age) to place importance on having ‘loads of followers’ (F6) who were ‘fake friends’ (F7).

Social obligations

Whilst SMU enhanced feelings of connectedness through enabling participants to keep in touch with others, this was frequently accompanied by demanding expectations amongst peers. Participants reported feeling obliged – in line with social norms – to respond promptly to messages from peers and to provide positive feedback on peers’ social media posts. This was sometimes accompanied by feeling overwhelmed by multiple messages or group chats, guilt associated with making excuses for unavailability or outright peer conflict if expectations were not met. Rather than displacement or stimulation, we suggest this represents a situation of ‘over-stimulation’.

Obligation to be available

Most participants reflecting on their own active use of social media made implicit reference to a social media etiquette developed by their generation, to which they either adhered or chose to ignore. Participants felt they were expected to respond immediately to social media messages. Being available to take part in multiple online conversations simultaneously was felt to be ‘stressful’ and ‘a mess in my mind’ (M4), with ending conversations causing difficulty for several participants.

For me, it is actually hard, because I don’t have a way to end the conversation. I just go on another application and then after an hour or two, I check what they actually wrote and then they’re like, ‘Oh, you came back,’ and then I have to tell them a random explanation. I was like, ‘Oh, I went do something,’ or something, because I don’t want to tell them, ‘Oh, I couldn't be bothered to talk to you anymore,’ because that’s, kind of, a harsh way. (M4)

Participants often discussed their online communication in obligation-related terms as a means of avoiding conflict with peers, or as a chore necessary to adhere to social norms.

People don’t assume, “Oh, they're busy.” If my friend didn’t reply to me for a day, I’d instantly think, “Oh, have I done something wrong?” because I feel like a day is quite a long time to go without social media for us, so I’d just be like, “Oh, are they annoyed at me?” (F12)

This narrative of obligation or duty was underlined by terminology used by participants who reflected on the need to provide peers with an ‘excuse’ (F12, F15) to end online conversations or not to respond immediately to messages, with one participant ‘panicking’ (F14) when her phone was broken in case friends took offense to her lack of contact.

This aligns with neither the displacement nor stimulation hypothesis. These participants seemed to reveal a sense of ‘over-stimulation’ or ‘hyper-connectedness’ with peers, whereby perceived excessive or duty-bound online communication no longer enhanced friendship quality but became a burden attached to friendships.

Obligation to provide positive feedback

Several participants explained their motivation for commenting on a friend’s post as an act of altruism to boost others’ self-esteem, stimulating peer connectedness through provision of emotional support and mutual respect (F4, F5, F10). However, others conveyed a weight of expectation to do so to avoid negative consequences to the friendship. Failure to like or comment on pictures posted by friends was usually met with confusion (‘because it’s the normal thing to do’ (F11)), a need for justification, or conflict (M4).

While many participants accepted this etiquette as part of everyday peer relationships, others described it as time-consuming and ‘overwhelming’ (F15), with some feeling ‘forced’ (M4) to like or comment on a friend’s post. This emotive language seemed to convey a sense of excessive peer connectedness or over-stimulation emerging from unrealistic but increasingly normalised expectations of friendship.

Participant F12 described the process of commenting and liking on others’ posts as ‘trading’ to boost perceived popularity for enhanced peer status. This understanding that provision of positive feedback is expected rather than based on genuine positive evaluation of content may undermine the validating effect of receiving positive feedback oneself, leading some young people to view likes or comments received on their own content as a superficial form of popularity and undermining benefits to self-esteem.

In addition to extending the positive stimulation effect of online communication into negative feelings of oppressiveness, the concept of displacement is exemplified here through young people’s defining of friendship in the normative obligation to exchange likes and positive comments. These more potentially hollow popularity-based aspects of friendships are indicative of ‘weak’ ties – a superficial type of peer support compared to the deeper benefits of strong affective ties defined by close emotional, tangible support, mutual respect and trust [ 11 ]. However, peer popularity is a key aspect of identity development and sense of self in adolescence, and receipt of feedback to social media content may therefore still be an important contributor to well-being and peer connectedness for this age group [ 27 ].

The theme of (mis)trust encapsulated both positive and negative aspects of the role of SMU in social relationships. The dominant narrative presented social media as a vehicle through which participants’ parents could demonstrate their trust that they would behave safely and responsibly. This was generally reciprocated by participants, several whom trusted their parents or other family members to follow their social media accounts as a form of protection. One exception to this provided an example of a more complicated relationship with parents and felt a lack of trust to be left in charge of their own SMU, with implications for responding to adverse online experiences.

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship, and improving peer connectedness in a virtuous cycle. However, the fear of data misappropriation, such as screenshotting within broader peer networks, appeared to have led to widespread underlying feelings of mistrust, undermining peer connectedness. Rather than a linear effect of displacement or stimulation, displacement or undermining of social connectedness seemed to present in a poor-get-poorer effect, whereas good quality relationships were further stimulated by SMU in a rich-get-richer effect.

Opportunities for adults to demonstrate trust

With adolescents in control of their own online profiles and content, social media was felt by some to provide opportunities for adults in their lives to demonstrate they trust young people to be responsible online, nurturing their independence. Within the sample, there were positive examples of trusting parental relationships, in which parents had provided guidance and established boundaries, then let young people use social media without excessive interference (M1, F8, F10).

Several participants spoke of their parents or other family members following their social media accounts to keep an eye on them. This was generally framed positively as overseeing participants’ SMU for their protection, either in terms of giving advice about data privacy or inappropriate posts (F17), or in more practical terms, whereby geographical tags can help parents locate young people if they are unable to contact them (M4). Participant M4 also went on to discuss the barriers introduced by social media to prevent lying to his parents about his whereabouts. This was also framed positively as preventing potential damage to the relationship. The dominant narratives of mutual trust developing and being played out through parents’ navigation of young people’s SMU demonstrated the potential for stimulation of family connectedness.

However, one participant stood out in their portrayal of parents with strict attitudes to SMU, whereby access to certain apps or activities had been banned, describing a paternal relationship defined by restrictions and lies.

My mum gave [snapchat]to me when I was 10, and then my dad said I wasn’t allowed to have it. I kind of deleted it for a while, and then I discovered I could just hide it, so I had it on my phone. Then whenever he asked to use my phone, I’d delete it, and then download it again and put it back in when I got my phone back… (F1)

This participant also spoke of her parents looking over her shoulder as she used social media or taking her phone out of her hands to check what she was doing.

Those participants with parents who had demonstrated their trust reported feeling able to discuss and ask for advice on difficult issues encountered on social media, whereas those with less trusting parents felt reluctant to approach their parents for fear of repercussions. This is evident in contrasting comments from F14, who was comfortable approaching their mother for help with online peer relationships, and F1, who felt that her parents’ dogmatic approach to social media prevented her reporting online sexual harassment in case she was no longer allowed to use certain apps.

I mean she [mum] knows that you’re going to get follow requests from people you don’t necessarily know and she said, “You can accept them but just make sure you know what you’re getting into.” She’s like, “If anything gets too bad tell me because we’re not going to tell you off or anything. We want to understand and even if you’re in the wrong we’ll try to help you”. (F14)

But I wouldn’t tell my parents [about strangers’ sexual harassment online] because they wouldn’t let me have it any more, and I’m not really meant to have it anyway. (F1)

Participants who had established a sense of mutual trust with parents also noted an appreciation for constructive guidance and boundaries to SMU. This appeared particularly pertinent to night-time SMU and its potential to disrupt participants’ sleep patterns, where rules set by parents about SMU in bed were quickly found to be beneficial by participants F4 and F5. In this sense, an authoritative approach to setting sensible SMU boundaries – seemingly reflective of good family connectedness – seemed to be acceptable to young people. Family connectedness therefore has the potential to mitigate well-documented negative effects of night-time SMU on sleep [ 14 ].

Self-disclosure and fear of screenshotting (‘I don’t trust you’)

We found some evidence of online enhanced self-disclosure in our sample – in line with the stimulation hypothesis – whereby features of online communication facilitate sharing of intimate information, leading to better quality relationships [ 28 ]. Those participants who demonstrated online enhanced self-disclosure appeared to do so specifically because of perceived poor social skills. Participant F6 described herself as particularly lacking in social confidence and noted a preference for sharing sensitive disclosures via social media rather than at school where ‘everyone is always there’ (F6). In this case, the perceived privacy of direct messaging via social media with trusted close friends was felt to stimulate online self-disclosure and deepen the participant’s friendships. M1 also noted difficulties approaching friends face-to-face with a problem, but an ability to be ‘direct’ in doing so online. One participant gave a specific example of preferring online rather than face-to-face interaction in the case of a close bereavement, where giving condolences online would avoid an uncomfortable display of emotion (M4).

However, a more common perspective amongst our sample was a preference for face-to-face sharing when it came to sensitive or personal information. Reasons included the increased effort involved in typing long messages online (F5), ease of conversation and avoiding misunderstandings when able to gauge behavioural or vocal cues (F4, F7, F10, F11, F12, F14, F15, F18, F19), knowing who else is present and increased privacy offline (F2, M2, M3, M5, F8, F16, F17), and face-to-face as a less superficial and therefore more appropriate context for discussing serious problems (F9).

For many participants the risk of screenshots being taken and shared presented a substantial barrier to online self-disclosure (Fig.  1 ), with some saying they would not trust even close friends with sensitive information sent over social media. Others reserved any content sharing only for trusted close friends, and only using certain apps such as Snapchat where users are notified if someone has taken a screenshot. Fears included screenshots being used as ‘evidence’ (F13) or ‘proof’ (F15) within an argument, or to spread ‘rumours’ (F6), but also images being manipulated and used to ‘make fun’ of the subject (M3). Other participants blamed screenshotting for exacerbating peer conflict and for the potential ‘break[down]’ (M5) of friendships. For two participants (M2, M3), the risk of screenshotting and potential misappropriation of content put them off using any social media at all. In restricting online self-disclosure, this fear and mistrust of social media audiences represent a limit to online peer connectedness, aligned to the displacement of good quality face-to-face social interactions with less intimate ones online.

Implications of social media screenshotting for trust and poor peer connectedness

Concerns about deception and privacy issues appeared to be at the forefront of most participants’ minds as a result of their own or peers’ experiences, or anxieties raised by parents. These worries ranged from trusting (or not) their friends to sensitively handle content shared privately, feeling ‘suspicious’ (F8) when contacted by strangers as to their identity and intentions, to a general undercurrent of mistrust of social media audiences not to ‘hack’ (M4) their accounts, ‘steal’ (F18, F19) their data or identity or engage in other ‘scary’ (F2) behaviour.

Probably if I had to think of something off the top of mind, I would probably say the most important thing on social media is, don’t talk to someone you don’t know, because you don’t know what they’re capable of. (M4)

The young people in our sample were thus acutely aware of the risks of identity theft and of engaging online with potentially dangerous strangers. Combined with a general discomfort with online self-disclosure or fear of screenshotting among peers, this mistrust can simultaneously be perceived as a challenge to quality in peer relationships and interpreted as a constructive strategy for mitigating risk.

Personal and group identity

Social identity development and expression can be facilitated through SMU. Using social media to share experiences – messaging, viewing online content together with friends and family, and co-producing content such as TikTok videos – appeared to foster feelings of connectedness through stimulation of a sense of belonging. Participants described careful curation of their online profiles to construct and express their identity. Online social networking and microblogging enabled those with specific interests (such as art or music) or experiences (including mental health conditions) to find like-minded others and join communities without geographical constraints, thus enhancing peer connectedness.

In terms of family connectedness, frustrations with adults’ lack of understanding of young people’s SMU and overemphasis on online harms led to a perceived disconnect between generations. Rather than displacement weakening family connectedness here, an adult discourse of SMU displacing activities they perceived to be healthier had negative implications for highlighting differences between generational groups and reducing feelings of mutual respect and understanding.

Sense of belonging

SMU stimulated feelings of social connectedness via enhancing feelings of belonging and group membership. For some participants, this was achieved simply through inclusion in a group chat (F3, M4).

In other cases, appearing on Instagram stories, ‘slip stories’, or private stories of their friends – whether as actors within the content or as privileged audiences of this restricted content – helped to cement participants’ position as a trusted member of the peer group (M4) and was generally perceived to symbolise a close friendship (F1, F2, M4, F9, F11). In such cases, privacy settings became markers of group membership.

In line with the stimulation hypothesis, SMU enabled and made salient shared experiences with existing friends and family, an important part of social group membership. Several participants highlighted the shared enjoyment of passively consuming social media content in the presence of others. This included watching YouTube videos together with family members (M3), sharing funny memes with parents (M1, F8), and using content related to special shared interests (such as football) to enrich interactions with siblings and improve the closeness of the relationship (F6). In addition, active co-production of visual content with others was presented as an important part of friendship for some (F9) and a way to ‘make memories’ with friends (F5). This co-production could improve peer connectedness through collaboratively working to achieve a common creative goal and sharing in a sense of accomplishment.

For some participants (F18, F19, F2), social media represented an opportunity to express their opinions and share creative projects with like-minded others outside their immediate friendship groups, with whom they would otherwise be unlikely to interact because of differences in age or location. Using social media in this way gave them access to communities in which they could receive support in shaping their artistic identities as well as becoming active and supportive community members. Identity development and expression was thus supported by SMU, simultaneously stimulating connectedness to a wider peer network.

Generational disconnect

Many participants expressed a sense of frustration with what they perceived to be an adult obsession with screen-time and the negative effects of SMU, which seemed to impact negatively on family identity and connectedness. Growing up in a vastly different environment to their elders – largely but not exclusively related to the advent of social media – was felt to have led to a disconnect between generations, whereby adults were perceived as unable ‘to relate’ (F10, F14, F15). As such, there was a sense that adults fail to fully appreciate the significance of the online world for this generation, imposing arbitrary screen-time limitations rather than taking time to understand the positive and negative aspects of SMU.

Older generations were felt to overestimate the negative impacts of SMU (‘adults think it’s bad but it’s not that bad…’ (F13)) with too much importance placed on social media as a cause of bullying or harm, when the relationship as experienced by young people, is more complex.

I think the biggest problem with social media is adults say, “It’s evil, you shouldn’t do it,” but the thing is- and they’re like, “It creates argument, you bully each other.” It doesn’t. The thing is the arguments are going to happen anyway, it just doesn’t help you resolving it really. People are like, “Oh it creates arguments. It turns people into bullies. You’re vulnerable on there.” It isn’t really. That’s the thing. (F13)

Several participants relayed experiences whereby their parents or other family members had been critical of their SMU, with a general negative ‘stigma’ attached to social media (F10). While this was sometimes perceived as a justifiable concern around online harms (F4, M4), those who were told to simply ‘get off your phone’ (F12) felt misunderstood and some found this irritating or upsetting (F2, F10, F11, F12, F14, F15). Participant F14 described her mother’s dismissive attitude towards social media. Her mother suggested that her SMU displaced time better spent on healthier activities such as exercise and face-to-face socialising, but was felt to underestimate the social importance of SMU and the diverging priorities between generations. With social media often used strategically at times when such activities are logistically more difficult (as discussed under ‘displacement of face-to-face socialising’), this perceived inappropriate emphasis on displacement and screen-time restrictions appeared to underlie the sense of disconnect between young people and older generations. These age-related group differences – accentuated by divergent attitudes to SMU – have the potential to increase inter-generational discord, harming family connectedness through diminished feelings of mutual understanding and respect.

This qualitative study contributes to a growing literature on the psychosocial impacts of SMU in adolescence. We explored in depth the role of SMU in the broader social environment from the perspectives of adolescents themselves, examining both peer and family connectedness. Four themes were identified: i) ‘Displacement of face-to-face socialising’ (ii) ‘Social obligations’ (iii) ‘(Mis)Trust’ and (iv) ‘Personal and group identity’.

Findings in relation to displacement and stimulation hypotheses

We found some limited evidence in favour of the displacement hypothesis [ 11 ], whereby time spent using social media was felt by some participants to displace time spent socialising with family or friends face-to-face. However, it was often the case that online peer interactions took place mainly when in person socialising was not possible, providing opportunities to socialise and maintain peer relationships online in the absence of offline opportunities. Those experiencing increased SMU in place of family socialising tended to relay lower levels of family connectedness that preceded the SMU, with SMU used strategically to overcome feelings of loneliness in the home. This supports a ‘poor-get-poorer’ or ‘social deterioration’ effect, whereby those who feel less connected to their family are likely to rely more on SMU for social interactions or to alleviate boredom at home, further compounding a lack of connectedness within the household. Considering peer and family connectedness together, this is also illustrative of a ‘poor-get-richer’ or ‘social compensation’ effect, whereby poor family connectedness leads to increased online socialising with friends and subsequent improved peer connectedness. SMU may therefore serve as a protective tool in some circumstances to mitigate psychological risks associated with poor family connectedness or reduced face-to-face socialising. It is worth noting that these interviews took place before the COVID-19 pandemic led to school closures and lockdown, and SMU is likely to have served a particularly important function in this regard over the course of the pandemic.

One of few studies examining SMU and family connectedness, a cross-sectional survey of Canadian adolescents [ 29 ] found that heavy SMU (3 or more hours per day) was associated with greater odds of negative reported relationships between mothers and daughters, fathers and daughters and fathers and sons, but not mothers and sons. The authors explain their results as indicative of SMU displacing time spent engaging face-to-face with parents, with negative consequences for family relationships, However, our findings indicate that adolescents may also be motivated to turn to social media as a result of existing poor family connectedness.

Our study provides more evidence for the stimulation hypothesis, whereby SMU enhances the user’s existing social resources through increased contact and maintenance of relationships. Perceived benefits of SMU that emerged in this sample included the expansion of social networks, the ability to keep in touch with friends and family (including those for whom geographical constraints prevent offline socialising), enhanced self-disclosure for socially awkward young people or among very close friends, and supporting identity development and feelings of belonging. Consistent with a ‘poor-get-richer’ effect, those with reduced social resources offline – not only due to social awkwardness or anxiety but also loneliness or geographical barriers to offline interaction – find online support particularly beneficial [ 17 ,  27 ].

Where close friends were felt to be trustworthy, social media provided opportunities for self-disclosure, fostering intimacy in the relationship and improving peer connectedness in a ‘rich-get-richer’ or ‘social enhancement’ effect (Fig.  2 ). This is in line with previous research finding that adolescents’ time spent on instant messaging services enhances time spent face-to-face with friends, and subsequent quality of friendships [ 20 ]. SMU also provides opportunities for young people to construct, express, and develop identity in relation to their social world [ 30 ]. Young people in our sample reported using social media to share experiences, such as passively watching entertaining content together with friends and family members, as well as actively co-producing content, with privacy settings used to demarcate friendship group boundaries to different degrees of closeness (Fig. 2 ). This may foster feelings of connectedness and belonging, in line with the stimulation hypothesis.

Social enhancement (rich-get-richer) effect of social media in connectedness within close friendships

In addition to the positive aspects of SMU, young people reported feeling pressures of expectation around providing feedback on friends’ online posts and being constantly available for communication. For these young people, social media had created a normative environment of ‘over-stimulation’, which fostered feelings of stress. It may be that SMU for direct peer communication may stimulate connectedness and subsequent well-being to a point, whereas excessive communication and the associated expectations to respond might undermine these benefits. This aligns to the 'digital Goldilocks hypothesis' [ 24 ] and other evidence of a curvilinear relationship between SMU and psychosocial adjustment [ 23 ], whereby moderate SMU is beneficial to well-being (compared to no use at all) but excessive use is associated with negative outcomes. In addition, the fear of data misappropriation such as screenshotting within broader peer networks appeared to have led to widespread underlying feelings of mistrust, thus undermining peer connectedness, and lending weight to the suggestion that broader SMU may discourage development of ‘strong ties’. Screenshotting is a currently understudied aspect of SMU. Our findings suggest the role of screenshotting within relationships between SMU and psychosocial outcomes – including social connectedness – warrants further attention.

Parental understanding of social media use in young people

Where a family environment of mutual respect had been established and consideration had been given to understanding the indispensable role of social media in young people’s lives, with positive aspects acknowledged in addition to traditional e-safety concerns, young people were more accepting of advice and clear boundaries regarding healthy SMU. Young people felt they were trusted to behave responsibly online and in turn trusted authority figures to provide guidance regarding challenges encountered without fear of access to social media being removed or restricted. Risks to peer connectedness encountered online, such as cyber-ostracism or screenshotting, may thus be mitigated by strong family connectedness. With this supportive environment, young people are able to navigate online difficulties but also feel encouraged to share positive social media content with family members, promoting shared interests and family identity. A ‘rich-get-richer’ [ 19 ] effect appears to develop, with social media promoting further trust and family connectedness (Fig.  3 ).

Social enhancement (rich-get-richer) effect of social media in family connectedness

Conversely, an existing lack of trust in relationships between young people and their parents may underpin a rejection of screen-time restrictions and a reluctance to report exposure to online harms, adding further to a sense of social distance and further undermining connectedness, consistent with a ‘poor-get-poorer’ effect (Fig.  4 ). Future research might explore whether these findings can be generalised to the wider population of young people, and test the relationship between parental attitudes to social media and young people’s resilience or vulnerability to online harm.

Social deterioration (poor-get-poorer) effect of social media in family connectedness

Limitations

This study has some important limitations. Our sample size was somewhat smaller than planned due to the emergence of COVID-19, with boys in particular under-represented. However, a broad range of views and experiences were captured in the sample, which were sufficient to enable rich themes to be generated [ 31 ]. While our sample was diverse in their experiences of social media, they were not selected on the basis of how much they used SMU or for what reasons, therefore it is possible that some additional patterns of SMU may exist in this age group that were not captured. All participants were aged 13–14-years and attended inner-city secondary schools in one area of the country. Different offline experiences and circumstances are likely to be accompanied by different online experiences, and caution should therefore be exercised in generalising findings from this study to other populations.

Implications

The separation of the social environment offline and on social media is not clear cut. Focusing on developing trusting, attentive relationships with peers and parents offline is likely to optimise the potential for social media to further benefit social connectedness. Feeling understood and respected by adults should encourage young people to accept and appreciate healthy boundaries established regarding their digital activities. A balance must be sought between teaching young people about the risks to well-being that engaging with social media may lead to, without being alarmist and creating a culture in which confidence in others is discouraged. Healthy peer relationships in which there is trust, respect, and space to ignore digital notifications and messages are likely to benefit most from SMU that enables enhanced self-disclosure and increased closeness without feeling oppressive. Young people should be supported to re-prioritise trustworthiness over availability in defining meaningful and fulfilling friendships. If, as our evidence suggests, the online social environment is an extension of relationships in the real world, fostering healthy connectedness with others offline is likely to maximise the social benefits and minimise the potential harms of social media for young people.

Conclusions

Rather than a clear, unidirectional relationship in which SMU harms – through a process of displacement – or enhances – through stimulation – overall social connectedness in adolescence, we suggest a complex set of reciprocal and circular relationships in which social media can play both a beneficial role in reinforcing existing positive connections to peers and family, and a deleterious role in exacerbating an already poor social environment through the propagation of mistrust. The relationship between SMU and social connectedness cannot be viewed as independent of either content or context. In addition to quality of existing offline social resources, the different activities and ways in which adolescents use social media will partially determine the direction and valence of effects. Passive SMU, devoid of social interaction, is unlikely to confer the same social benefits as SMU for direct communication with friends. However, parents and other adults supporting young people should also take account of individual differences in how social media may benefit or undermine connectedness, supporting individuals to find ways to interact with social media that best supports their well-being.

Availability of data and materials

The qualitative datasets generated and analysed during the current study are not publicly available due to the data containing information that could compromise research participant privacy but are available from the corresponding author on reasonable request.

Abbreviations

Social media use

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Acknowledgements

We are extremely grateful to the young people who spoke to us about their experiences of adolescence in the age of social media, and to the teaching staff who took time to organise the interviews.

This study is funded by the National Institute for Health Research (NIHR) School for Public Health Research (SPHR) (Grant Reference Number PD-SPH-2015). CMAH is supported by a Philip Leverhulme Prize. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The funders had no involvement in study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication.

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LW coordinated the study, carried out the interviews and drafted the manuscript; All authors conceived of the study, and participated in its design and in interpretation of the data. BM, CMAH, and JK critiqued the output for important intellectual content. All authors read and approved the final manuscript.

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Winstone, L., Mars, B., Haworth, C.M.A. et al. Social media use and social connectedness among adolescents in the United Kingdom: a qualitative exploration of displacement and stimulation. BMC Public Health 21 , 1736 (2021). https://doi.org/10.1186/s12889-021-11802-9

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• Published: 05 March 2020

Social media, nature, and life satisfaction: global evidence of the biophilia hypothesis

• Chia-chen Chang 1   na1 ,
• Gwyneth Jia Yi Cheng 1   na1 ,
• Thi Phuong Le Nghiem 1 ,
• Xiao Ping Song   ORCID: orcid.org/0000-0002-8825-195X 2 , 4 ,
• Rachel Rui Ying Oh   ORCID: orcid.org/0000-0003-2716-7727 3 ,
• Daniel R. Richards   ORCID: orcid.org/0000-0002-8196-8421 4 &
• L. Roman Carrasco   ORCID: orcid.org/0000-0002-2894-1473 1  

Scientific Reports volume  10 , Article number:  4125 ( 2020 ) Cite this article

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• Human behaviour
• Psychology and behaviour

Humans may have evolved a need to connect with nature, and nature provides substantial cultural and social values to humans. However, quantifying the connection between humans and nature at a global scale remains challenging. We lack answers to fundamental questions: how do humans experience nature in different contexts (daily routines, fun activities, weddings, honeymoons, other celebrations, and vacations) and how do nature experiences differ across countries? We answer these questions by coupling social media and artificial intelligence using 31,534 social media photographs across 185 countries. We find that nature was more likely to appear in photographs taken during a fun activity, honeymoon, or vacation compared to photographs of daily routines. More importantly, the proportion of photographs with nature taken during fun activities is associated with national life satisfaction scores. This study provides global evidence of the biophilia hypothesis by showing a connection between humans and nature that contributes to life satisfaction and highlights how nature serves as background to many of our positive memories.

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Introduction

Ecosystems provide multiple benefits to humans, encompassing economic, ecological, cultural, and social values 1 , 2 . Despite these benefits, continuing environmental degradation has placed millions of animal and plant species under risk of extinction 3 , 4 . Removal and degradation of natural environments is expected to have negative consequences on human wellbeing 5 . This disparity between the overexploitation of natural resources and its importance to humans stems largely from the difficulty in integrating the value of nature’s benefits to people (“ecosystem services”) into policy 6 .

The value of ecosystem services is complex and multifaceted 6 . Although significant progress has been made in the economic and ecological valuation of ecosystem services, much less attention has been paid to cultural and social values, which are the most complex to capture 7 . Cultural ecosystem services are intangible benefits that people gain from experiencing nature 7 , 8 . The concept of “nature” is amorphous, so here we define nature as including biodiversity, ecosystems, living organisms, landscapes, and seascapes 5 . Nature provides an environmental space for cultural practices (including interacting with nature directly or using nature as background for other social activities) and yields various benefits 9 . These benefits include, among others, spiritual experiences, recreation, ecotourism, aesthetic appreciation, and further improved social cohesion and subjective wellbeing 5 , 6 , 7 , 8 , 9 .

Quantifying cultural ecosystem services is challenging as they represent immaterial benefits and the assessment involves untangling the reasons behind why people enjoy a particular space 7 , 10 . Collecting such information involves surveys or interviews that are resource-intensive and typically limited to small spatial scales 11 , 12 . Especially, how people experience nature in everyday lives (e.g., urban greenspace) and how people interact with nature under different contexts (e.g., relaxation, celebration, socialization, or daily routines) are particularly difficult to study in a large spatial scale. Recent breakthroughs in the study of cultural ecosystem services and understanding human-nature interactions have been possible through the use of social media. For instance, analyzing the user-defined “tags” of photographs can help understand the context under which the photograph was taken and potentially the self-reported emotional state of users. Analysis of social media photographs has been used, for instance, to study recreational 13 and aesthetic qualities of natural areas 14 , preferences for nature-based activities in protected areas 15 , and associations between the use of outdoor space and happiness 16 . Despite these advances, global multi-country comparisons of cultural ecosystem services are lacking. Coupling social media with artificial intelligence for automated approaches in image recognition opens up unique opportunities to carry out large-scale studies of cultural ecosystem services to advance our understanding in human-nature relationships 17 .

One discipline that has studied the relationships between the experience of nature and human wellbeing is environmental psychology. According to the biophilia hypothesis (i.e., humanity’s innate tendency to connect with nature), humans largely relied on natural resources for survival and reproduction in human history, leading humans to evolve a tendency to prefer being close to nature through an emotional connection 18 . Psychological studies have demonstrated the capacity of nature to increase life satisfaction and improve attention restoration and stress recovery 19 , 20 , 21 . The psychological benefits gained from experiencing nature provide an important aspect of cultural ecosystem services 5 . People’s favorite places tend to have high restorative potential 10 . The locations where individuals can feel relaxed, forget their worries, and reflect on personal matters are often natural spaces 10 . We hypothesize that nature may play a role as a backdrop for key social contexts in a human’s life.

To test this hypothesis, we integrate both the fields of ecosystem services and environmental psychology to study how humans experience nature in various contexts, and how this relates to life satisfaction scores at a national level. Using the concept of cultural ecosystem services, we aim to analyze the links between nature (background), cultural practices (various contexts and activities), and benefits (cultural association between nature and positive social contexts and further life satisfaction). Based on the biophilia hypothesis and the capacity of nature for psychological restoration 19 , 20 , 21 , we hypothesize that humans tend to associate nature with positive social contexts, such as fun activities, celebrations, weddings, honeymoons, and vacations. In addition, we also investigate whether the relationship between nature experience and life satisfaction holds true at a cross-cultural level. We hypothesize that a nation with a stronger culture of experiencing nature would show higher life satisfaction as compared to other nations with a weaker culture in nature experience. We do this at an unprecedented global scale by leveraging on social media data and image recognition using machine learning algorithms.

We analyzed a total of 31,534 social media photographs uploaded on Flickr—a popular social media platform—using the Google Cloud Vision API. We used Flickr as the source of data because there are a large number of users (over 70 million users) and geotagged photographs (over 197 million) 13 . Flickr contains information about the location where many of the uploaded photographs were taken. These geotagged photographs allowed us to identify which country photographs were taken in. The photographs used in this study were geo-located across 185 countries, over a period of 11 years. We first assessed nature labels (i.e., image contents detected and generated by Google Cloud Vision API as nature-related labels) in photographs tagged by the users as “nature” and later checked the frequency of those labels within photographs tagged with specific contexts by users: people’s daily routines (as a baseline for comparisons with other contexts), fun activities, weddings, celebrations, honeymoons, and vacations. These social contexts were selected as they are likely to reflect people’s choice of favorite places when holding memorable social events/activities in their lives.

Analyzing the content of 5,362 photographs tagged by users as “nature”, we listed the most common nature labels identified by the image content analysis. These common nature labels covered from 7.3% to 40.2% of photographs (Fig.  1 ). These labels were subsequently categorized as: water, terrestrial landscapes, plants, animals, and nature in general terms (Fig.  1 ).

Word cloud showing the 40 most common nature labels detected by the image content analysis in 5,362 nature-tagged photographs. Word size is proportional to the frequency of occurrence. Nature labels were subsequently categorized into five different nature categories (color-coded, green: plants, brown: terrestrial landscapes, black: general terms, blue: water, purple: animals).

Comparing the frequencies of these nature labels identified in photographs tagged with various contexts by users (n = 26,172 photographs), we found that, across all five nature categories, photographs tagged with fun activities, honeymoons, and vacations were more likely to have nature labels identified in them than photographs tagged with daily routines (Figs.  2 , 3 , Table  S1 ). Honeymoon and vacation photographs were more likely to have nature labels in them than fun activity photographs, with the exception of animals (Table  S1 ). However, there was no difference between honeymoon photographs and vacation photographs in terms of the frequency of nature labels identified (Table  S1 ). Celebration photographs were less likely to have nature labels than daily routine photographs, except for plants (Figs.  2 , 3 , Table  S1 ). There was generally no significant difference between wedding photographs and daily routine photographs, except that wedding photographs were likely to have more plants and less animals (Figs.  2 , 3 , Table  S1 ). This indicates that people tend to associate fun activities, honeymoons and vacations with nature, but not celebratory social events.

The relationship between social contexts and the presence of nature. The coefficient estimate (± SE) of the generalized linear mixed-effects models for each social context and nature category. A positive (negative) coefficient indicates a more (less) propensity for photographs to contain nature labels than the control photographs. Control photographs were used as the baseline (photographs tagged with “daily” or “routine”). Fun activity, honeymoon, and vacation photographs were more likely to contain nature labels as compared to daily routine photographs, for all categories of nature (Table  S1 ). Celebration photographs were less likely to have nature labels than daily routine photographs, except for plants (Table  S1 ).

The proportion of photographs with nature labels identified with different nature categories (plants, terrestrial landscapes, general terms, water, animals) for each social context (daily routines, fun activities, weddings, celebrations, honeymoons, and vacations). Each point represents one country, and the size of points is proportional to the total number of photographs, and grey points represent the total number of photographs that are less than 10.

There was a wide variation in terms of how commonly nature appeared in photographs across countries (Table  S2 , Fig.  3 ). Nature commonly appeared in the photographs taken in some countries (e.g., for general nature terms: Iceland, Tanzania, Maldives, New Zealand, and Montenegro), but not in others (e.g., for general nature terms: Russia, Myanmar, China, Czech Republic, and Singapore).

We found that, at a cross-national level, there was a positive association between the national life satisfaction score and the proportion of nature labels (plants) in the fun activity photographs (Fig.  4a , Table  S3 , Coefficient = 4.70 ± 1.29, t value = 3.64, unadjusted p value = 0.0006, FDR adjusted p value = 0.039). However, this relationship was not significant in the vacation photographs (Fig.  4b , Table  S3 , Coefficient = 1.95 ± 1.21, t value = 1.61, unadjusted p value = 0.113, FDR adjusted p value = 0.516), which may have been taken by a higher proportion of overseas tourists. This relationship was also not significant in daily routine photographs (Fig.  4c , Table  S3 , Coefficient = −1.95 ± 3.96, t value = −0.49, unadjusted p value = 0.626, FDR adjusted p value = 0.881). These results suggest that the context-dependent relationship between the national level of life satisfaction score and nature experience appears in the residents of the country.

The relationship between national life satisfaction scores and the proportion of photographs with plant-related labels identified in three social contexts ( a fun activity, b vacation, c daily routine). National life satisfaction was positively associated with the proportion of nature labels (plants) in fun activity photographs, but not associated in the context of vacations and daily routines. The size of the point is proportional to the number of photographs.

Our results reveal that people are more likely to interact with nature in the context of fun activities, honeymoons, and vacations, suggesting an association between nature and these fun or relaxing moments. We also find that countries with more nature (plant-related) in fun activity photographs had higher life satisfaction, such as Costa Rica and Finland. These results, taken together, suggest the importance of nature in providing the background to positive social contexts, presumably fond memories, as well as in contributing to life satisfaction in communities worldwide.

A preference for natural environments during fun activities supports the biophilia hypothesis 18 . This biophilic relationship is more evident in the context of vacations and honeymoons, as both social contexts are intended to provide relaxation from daily routines and the possibly stressful period of organizing weddings or other celebratory events. This implies that humans not only associate nature with emotional happiness but also desire to experience nature probably because of experiences of awe, relaxation, and stress relief  22 , 23 . For instance, visiting nature has been shown to improve cognitive ability, reduce stress, and lower the risk of depression 5 , 19 , 24 . These results further confirm the importance of nature for travel and tourism worldwide 25 , which not only provides economic value but also psychological and cultural values.

Landscape aesthetics as a cultural ecosystem service is particularly important given that the biophilic relationship is pervasive across cultures. Analyzing photographs allows us to understand what and when people want to capture as memories and share with other people. The high frequency of nature in photographs taken during fun activities and vacations implies the significance of nature in some of our fondest memories. For example, national parks in South Africa and marine sites in the UK provide cultural and social values by providing a place identity (a sense of place, such as “reliving childhood memories” and “I miss these sites when I have been away from them for a long time”) 26 , 27 . Similarly, the Satoyama landscape in Japan tends to be regarded as “home” for many Japanese people 28 . Some other famous natural landscapes have been identified as important cultural values to local communities, such as the Waikaraka Estuary in New Zealand 29 and the Arafura-Timor seascape in Southeast Asia 30 . The human influence and loss of nature could potentially lead to the loss of these natural backgrounds to fond memories as well as diminish the cultural values of ecosystem services 30 .

In contrast, wedding photographs were not significantly different from daily routine photographs in terms of the presence of nature labels, and celebration photographs were generally less likely to have nature than daily routine photographs. This suggests that, unlike honeymoons or vacations, urban areas and closed settings (e.g. hotels) are chosen presumably for the convenience to organize social gatherings through high accessibility and to conform to traditional ceremonies 31 , and are thus prioritized over biophilic needs.

People vary in their connectedness to nature 32 , 33 . For example, some people spend time interacting with nature and perceive nature as an important component to their lives, but other people do not. We found that the frequency of nature that appeared in photographs varied widely across countries. This variation could be related to cultural and sociodemographic differences 34 , 35 . For example, it has been shown that Menominee Native Americans spend more time interacting with nature directly in their outdoor activities, as compared to European Americans 34 . Another comparative study also showed that Swiss participants preferred forests with high biodiversity, while Chinese participants did not show such preference 35 . The cultural variation in nature connectedness is important to be considered in the assessment and research in cultural ecosystem services.

Our study further reveals a positive relationship between life satisfaction and the presence of nature in fun activity photographs across multiple countries. Being correlational, these results could either point towards nature contributing to life satisfaction through fun memories, or to the tendency of people satisfied with their lives to spend time in a natural setting. Further research should focus on disentangling the cause and effect behind the observed patterns, as this could be an opportunity to design better programs for interacting with nature and improving human wellbeing. This result also points to the potentially synergistic effect of having social activities in the presence of nature. Different from the other contexts analyzed, fun activities are likely to be a social setting where people tend to interact with each other in a group. The combination of both social interaction and nature connection can be more rewarding than having either element alone 36 , 37 , 38 . Being related to both humans and nature is likely to contribute to our life satisfaction. For instance, it has been shown that in natural environments people tend to behave more altruistically and less selfishly, and that nature enhances social cohesion in communities and increases life satisfaction 23 , 39 . Interactions with nature, or within a natural backdrop, could strengthen social cohesion and improve life satisfaction.

Our analyses present several limitations. Although we know the country where the photograph was taken, we do not know whether it was taken by a local or a foreigner travelling to the country. Also, our focus on English tags assigned by Flickr users biased our results toward English-speaking nations and users. Further research could attempt to replicate our methods across multiple languages and photograph-sharing platforms. Although we performed verification checks to ensure that user-assigned tags led to the intended photographs (e.g. we excluded “proposal” as a tag for a special life event because it turned out to be ambiguous), some tags may lead to unrelated pictures, thus introducing noise to the analysis.

Integrating both the fields of cultural ecosystem services and environmental psychology through a photograph analysis at an unprecedented scale, we showed that people have a preference for nature in their fun activities, vacations, and honeymoons globally. Although our study represents only small steps in this line of inquiry, the findings suggest there is a whole underestimated dimension of the relationship between humans and nature through positive social contexts, presumably in the form of fond memories ultimately associated with life satisfaction. The main implication is that the loss of nature may mean more than losing quantifiable economic and ecological benefits; it could also mean losing the background to our fondest memories.

Choice of tags and nature labels

To select suitable nature elements that people associate with nature, we used “nature” as the tag, which is a self-reported keyword added by social media users when they upload to increase the photographs’ visibility. The common nature-related labels detected and generated by the Google image recognition API within the nature-tagged photographs were used as the nature labels in subsequent analyses.

We considered six contexts in this study. These were daily routines (as the baseline for comparisons), fun activities, weddings, celebrations, honeymoons, and vacations. Similarly, we used “tags” to identify these contexts. Daily routine related tags “daily” and “routine”, on separate searches, were used to retrieve daily routine photographs to be used as the baseline for comparisons. To identify general fun activities, we used the tags “fun” and “activity” on separate searches to retrieve the fun activity photographs. To investigate whether nature labels were more likely to be present in critical life events (weddings and honeymoons), we used wedding-related tags “wedding” and “marriage” to retrieve wedding photographs. The tag “honeymoon” was used solely for the honeymoon photographs. To distinguish between weddings and other types of celebrations as well as between honeymoons and other types of vacations, we also used the tag “celebration” to correspond to the celebration photographs, and vacation-related tags “vacation”, “holiday”, and “travel” to retrieve vacation photographs. Contexts and the tags used are summarized in Table  S4 .

Image extraction and content detection

To extract photographs globally, we used Flickr’s public API to retrieve photographs with tags. We used the abovementioned 12 target tags, and retrieved photographs across 11 years, from 1 st of January 2008 to 31 st December 2018. As users varied in the number of photographs uploaded, we randomly selected one photograph from each Flickr user per returned tag search and therefore each photograph corresponds to an unique user in each tag search. We retrieved only photographs that users of Flickr had chosen to make publicly visible, by filtering the privacy setting. We also extracted all other tags that users added in the retrieved photographs to confirm that the retrieved photographs contained the target tags. Photographs without target tags were removed. To identify the geographical location of the photographs, we also extracted the GPS coordinates of the photographs and used the revgeo package with OpenStreetMap 40 to identify the country of origin (n = 185).

To automatically detect the content within photographs, we used the Google Cloud Vision API through the RoogleVision package in R v3.5.3 41 . We used the label detection function to detect the content in a photograph. The Vision API can detect and generate various labels such as general objects, activities, locations, and products. We extracted a maximum of 15 labels from each photograph with a minimum confidence score of 0.5 (ranging from 0 to 1).

We performed a random manual check of 200 photographs (10 photographs across 20 countries) to verify the tags linked with the intended photographs, locations of photographs, and the accuracy of label detection. Among 200 photographs, all photographs showed correct contexts and countries, and captured nature content correctly for 91% of photographs (182/200) with the use of our nature labels.

Statistical analyses

Association between the presence of natural labels and tags.

We obtained 5,362 nature-tagged photographs. To understand what natural elements people may associate with nature, we first identified the common natural labels in the nature-tagged photographs. The Google Cloud Vision API detected and generated a total number of 2,942 labels, and we selected the 50 most frequently shown labels (each label appeared at least in 389 photographs among nature-tagged photographs). After filtering out irrelevant and ambiguous labels (i.e., adaptation, evening, green, morning, photography, reflection, sky, cloud, atmosphere, and atmospheric phenomenon), we grouped the nature-related labels into five nature categories: water, terrestrial landscapes, plants, animals, and nature in general terms (Table  S5 with frequency). These natural labels were used as the labels to identify the presence of nature in the photographs with various contexts.

Photographs that were retrieved using the “celebration” tag may actually be wedding photographs and, similarly, the “vacation” tag may retrieve honeymoon photographs. To further refine the separation of wedding photographs from generic celebration photographs, we searched “wedding” tags in celebration-tagged photographs, and those photographs were then categorized as wedding photographs. Similarly, we searched “honeymoon” tags among vacation-tagged photographs and considered those photographs as honeymoon photographs. After the regrouping, some photographs that were tagged with multiple target tags (e.g., fun and holiday) were included in the sample of more than one contexts, as they may contain multiple contexts according to our definitions. In total, we obtained 26,172 photographs, and 3,781 of them were categorized into more than one contexts. We had 3,236 photographs classed as daily routine photographs, 8,589 photographs classed as fun activity photographs, 3,098 photographs classed as wedding photographs, 4,227 photographs classed as celebration photographs, 880 photographs classed as honeymoon photographs, and 10,129 photographs classed as vacation photographs. To evaluate the effect of including photographs in multiple contexts on the conclusions, a second analysis was run with the dataset after removing repeated photographs (n = 22,391, Table  S6 ).

We performed generalized linear mixed-effects models with a binomial error structure. The presence or absence of certain nature categories (according to previously identified nature labels) was coded as a response variable (e.g., a photograph in which it was detected the presence of the nature label “tree” was considered as an instance of “plants” in the nature category, Table  S5 ). The context was coded as the fixed effect, and country was considered as the random effect. The random effect for country attempted to account for national-level cultural differences and availability of natural space. The random effect for each country was extracted using the ranef function. We performed a total of four sets of analyses with different contexts as the baseline: 1) comparing fun activities, weddings, celebrations, honeymoons, and vacations against daily routines, 2) comparing weddings, celebrations, honeymoons, and vacations against fun activities, 3) comparing between weddings and celebrations, and 4) comparing honeymoons and vacations. We ran five models (for each nature category separately) in each set of analyses except for the natural category animal in 3) and 4) due to convergence failures. The p values were adjusted for multiple comparisons using the false discovery rate (FDR, with a total of 53 p values).

Association between life satisfaction and presence of natural labels in photographs

To investigate the association between the life satisfaction and proportion of photographs with the presence of nature at a cross-national level, we calculated the proportion of the photographs containing nature labels (for each nature category) in each context (i.e., daily routine, fun activity, wedding, celebration, honeymoon, and vacation) for each country. To ensure that each country is adequately represented, we removed countries that had less than 10 photographs for a given context.

We used life satisfaction in the Cantril Ladder scale (ranging from 0 to 10) with the average of survey responses from each country in 2017 42 , 43 . To control for the income of countries, we used GDP per capita based on purchasing power parities in 2017 42 , 43 , 44 . A total of 69 countries were used in the statistical analysis.

We ran linear regressions with life satisfaction as a response variable, and GDP per capita (to control for the relationship between wealth and life satisfaction), proportion of photographs with nature labels for each nature category, and the interaction between both variables were considered as the explanatory variables. We ran different models for different social contexts and each nature category was run separately. The p values were adjusted for multiple comparisons using the false discovery rate (with a total of 60 p values).

Data availability

All the photographs data can be retrieved using Flickr’s public API, and national life satisfaction and GDP data are available in Our World in Data (see ref. 43 ).

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Acknowledgements

We acknowledge research funds from the National Parks Board and the Ministry of National Development, Singapore.

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These authors contributed equally: Chia-chen Chang and Gwyneth Jia Yi Cheng.

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Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543, Singapore

Chia-chen Chang, Gwyneth Jia Yi Cheng, Thi Phuong Le Nghiem & L. Roman Carrasco

Department of Architecture, National University of Singapore, 117566, Singapore, Singapore

Xiao Ping Song

School of Biological Sciences, Centre for Biodiversity and Conservation Sciences, University of Queensland, 4072, Brisbane, Australia

Rachel Rui Ying Oh

ETH Zurich, Singapore-ETH Centre, 1 Create Way, 138602, Singapore, Singapore

Xiao Ping Song & Daniel R. Richards

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L.R.C. and D.R.R. conceptualized the research. C.C., G.J.Y.C., L.R.C. collected data and performed data analysis. C.C., and L.R.C. produced the first draft. All authors revised the manuscript.

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Chang, Cc., Cheng, G.J.Y., Nghiem, T.P.L. et al. Social media, nature, and life satisfaction: global evidence of the biophilia hypothesis. Sci Rep 10 , 4125 (2020). https://doi.org/10.1038/s41598-020-60902-w

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FEATURE 17 February 2017

A hypothesis-driven approach to social media insight

Bronwen Morgan

Data analytics Features Media Social media UK

Speaking at yesterday’s Social Media Research Summit, organised by the Market Research Society (MRS), Pulsar’s co-founder and vice president of product and research, Francesco D'Orazio, demonstrated how to use social media to validate a specific research hypothesis. 

Social media data has transformed the scope of research. The availability of 11 years of Twitter data at the touch of a button is just the tip of the iceberg, said D'Orazio, who went on to extol the benefits of both the granularity of publicly available data (Twitter and Instagram) and the aggregated nature of Facebook and LinkedIn data. 

But the sheer quantity of interactions can make analysis challenging, which is why D'Orazio believes in the value of an emerging research approach: using social data as a tool to validate specific research hypotheses, rather than as an exploratory tool. 

The traditional ‘emergence’ approach, said D'Orazio, relies on "seeing what crops up" and is based on keywords and stories. The ‘hypothesis’ approach involves framing data: looking at it through the lens of a specific question. In short, the hypothesis approach shifts much of the analysis to before data collection, rather than afterwards. 

The key advantages of this approach are as follows: 

• Keeps the data collection focused and reduces ‘noise'
• Makes analysis faster, more structured and standardised
• Makes it easier to replicate results across teams
• Makes it easier to integrate social data with third party sources such as surveys

D'Orazio took the audience through the process of this method: from client brief, to hypothesis, to data query, to insights. 

In order to move from the client brief to a research hypothesis, the researcher must break the brief down into three elements: What is the business objective? What is the target audience? What are we trying to understand? 

This is then further broken down into two elements: Who is the audience you're trying to reach? And what type of behaviour and moments should be investigated? 

The researcher can then create a hypothesis for each of these elements that can then be investigated in the data. The more focused this is, the better, said D'Orazio. It should be considered as a frame for looking at the data, rather than simply a theory to be validated. 

The next step is to transform the hypothesis into a study definition. A hypothesis will contain – and be related to – a number of elements: language; behaviours; attitudes; moments and occasions.

Transforming the hypothesis means defining the ‘signals’ to look out for, such as audience demographics and a list of terms (and sub-terms) to look out for.

For example, if you're investigating fast food consumption among UK/US millennials, a hypothesis could be that the UK/US millennial audience buy into authenticity and not the fast casual proposition. The terms to look out for could then be: ingredients, pairings, sustainability, price, health, occasions, behaviours and quality. Within quality, for example, there are terms to look out for such as: premium, chef, better, best, amazing, etc.

The last stage is to test the study outputs, including comparing the results across demographics for context, looking at the language used and how it compares to the hypothesis. 

This can offer insight into how consumers talk about a category, including how terms are conflated or distinguished, what behaviours and attitudes relate to the category (for different demographics), and what types of conversations people have. 

This can either validate the original hypothesis, disprove it or drive completely new insight, D'Orazio explained. 

Kathy Doering

7 years ago

Wow! What an excellent, insightful article. With social media monitoring softwares changing all the time, we are able to do more and more with social data and weed out the noise. Location based monitoring and digital image searching are both available and are a great additional resources for researchers and marketers.

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How to run and measure social media experiments

Written by by Jamia Kenan

Published on  February 22, 2023

Reading time  7 minutes

You already know that social moves fast. What worked for your brand a few months ago may not be relevant today. This is why social media managers thrive when they embrace a mindset of continual learning and development. Improving your social media marketing strategy requires frequent reevaluation and iteration, and running social media experiments is an essential part of the process.

Whenever you have a hypothesis, question or challenge related to your social media marketing strategy, social media experiments can provide actionable next steps. Their results provide concrete evidence to support your case for more resources or reasoning behind switching up your current content.

Social media experiments not only challenge your current strategy, but can also open opportunities to try something different—such as a new social media network or feature—and determine if it’s effective for your target audience. Experimentation can also reveal faster ways to reach your goals, help you avoid costly mistakes and uncover new information about your audience.

Grab your metaphorical safety goggles, lab coat and test tubes because in this article we’re going to walk through the steps for running and measuring successful social media experiments.

7 Steps for running a social media experiment

With these seven steps, you’ll be testing on social media with ease in no time:

• Formulate a hypothesis
• Choose the right type of social media experiment
• Select your metrics and the network you want to test
• Define the duration of the social media experiment
• Select your variables and control
• Conduct the social media experiment
• Analyze and share the results of your experiment

 1. Formulate a hypothesis

Before you begin, you’ll need a basic understanding of the following:

• The overall goals of your business
• Your current social strategy, including overarching goals per platform
• Your audiences by social network
• Your current social performance
• The questions, notions and ideas you wish to test

Prioritize a hypothesis that will result in the biggest impact on your team’s top-level social media goals . Avoid running several tests at once because it can lead to inconclusive results, especially if you’re focused on managing organic social.

If you’re using Sprout, you can learn about your audiences and performance by channel through our cross-network reports (like the Post Performance Report) or competitor reports (like the Instagram Competitors Report).

To dive even deeper into understanding your audience, use Sprout’s Advanced Listening tools. With Listening, you can build queries to track and analyze social conversations, pin down trends and view consumer sentiments. Seeing the data behind what your audience is talking about and the content they engage with will help you formulate a hypothesis.

2. Choose the right type of social media experiment

Now that you have a hypothesis, it’s time to select the type of social media experiment you will conduct to prove your theory.

There are two main types you can choose from: A/B testing and multivariable testing.

Social media experiment ideas for A/B tests

One of the most common types of social media experiments, an A/B test is an experiment where you change only one variable and keep everything else the same. These types of tests are an excellent way to pinpoint improvements that will make a measurable impact. Some common A/B tests on social include:

• Content types: video vs. a link, photo, GIF, etc.
• Captions: long vs. short
• Copy: question vs. statement, emojis or hashtags
• Images: illustrations vs. photography or animation
• Posting time: Monday at 9:00 a.m. vs. Friday at 4:00 p.m.

For example, if you wanted to test which content type is the most engaging on Instagram Stories, your team could test photo content against video content. The content type would change, but you would use the same caption and post at the same time and day of the week, one week apart.

Using Sprout, the Atlanta Hawks ‘ social team tested a casual approach to videos at community events. A player shot a hand-held video that was compared to the performance of more produced social videos. The casual video format proved to be more successful and sharing the performance data was a major win for the social team.

Social media experiment ideas for multivariable testing

As its name implies, multivariable testing alters two or three variables at once. However, since you’re experimenting with more elements, analyzing and interpreting data can be harder. You’ll also need a large audience to avoid skewing the test.

Some multivariable tests include:

• Short-form animated video vs. long-form live action video
• Varying tones of voice paired with or without emojis
• Multiple call-to-action buttons with different featured images
• Different content types with various captions
• Same content type but different days/times and platforms to see which resonates the most, like Instagram vs. TikTok

Sprout’s social team conducted several multivariable tests to help develop our TikTok marketing strategy , as you’re about to read in the next step.

3.  Select your metrics and the network you want to test

Establish the key metric you want to measure successful content against. This can include impressions, traffic to a particular page such as your brand’s website or a gated resource, and engagement metrics (Think: likes, clicks, comments or shares).

The channel you choose to conduct your experiment will depend on what you’re testing and the social media network you use the most to post that kind of content. Use your network-specific data to inform this decision. Read some of Sprout’s Insights resources to learn which content types perform the best on which platforms.

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When our social team started testing TikTok, the main goal was to increase awareness among our target audiences. Accordingly, we selected impressions, video views, profile views and audience growth as key performance indicators.

4. Define the duration of the social media experiment

Don’t fall into the common mistake of not defining a time frame for your social media experiment. Remember that social media strategy is a long game–give time for new initiatives to grow and develop.

Your reporting window depends on your budget, audience size and KPIs, but the most important factor is to reach statistical significance.

Statistical significance refers to the likelihood your test results are the outcome of a defined cause and not chance. To reach statistical significance, you’ll need a large sample size and a control. For example, a sample size of 1,000 is stronger than 100, and your control would be the piece of content you do not change.

Set a duration and look for statistical significance. What are the significance changes? After your testing period, consider optimizing content that didn’t work during that timeframe instead of hitting the breaks on posts that aren’t resonating immediately.

While experimenting with TikTok, the social team reported results after four months since there was enough data available to analyze. They also set a weekly update to our internal social dashboard to continue testing and learning, along with iterating strategy, if needed.

During the first four months, we discovered views for every TikTok remained consistent, with an average of 535 views per video. We were also able to confirm our thoughts/assumptions about the For You Page (FYP) and the TikTok algorithm—each consistently pushed out content to our target audience (social media specialists, managers, digital marketers, etc.).

5. Select your variables and control

If you’re using A/B testing, consider all of the elements of your content that could influence your test results to ensure you’re only testing one variable. Also select your control, which is the content that will not change. For example, if you’re testing images, make sure to not change the copy, audience, timing, etc.

In our social team’s multivariable TikTok experiments, they tested several variables including formats, themes and creative considerations like music, sounds and closed captions.

In the example below, 91% of views came from the FYP, 5% came from a personal profile view and 1% came from direct followers–confirming their hypothesis that the FYP and the algorithm were the key drivers pushing out content to our target audience.

@sproutsocial It’s no secret that social teams are on the path to extreme burnout. @J A Y D E shares why it’s time for leaders to take action. #foryou #socialmediamarketing #socialmediamanager #socialmediatips #socialmedia #foryoupage ♬ Cloudy Sky – Tundra Beats

If you use Sprout, you can use tagging to track the performance of your control and the test post.

6. Conduct the social media experiment

Now it’s time to execute! Use Sprout’s Publishing tools to seamlessly plan, create, optimize and post your content for the experiment. For example, you can use Sprout’s ViralPost® technology to post at optimal send times.

Use the Tag Performance Report to organize, run and analyze your social media experiment results, including your paid campaigns.

Read our guide on creative testing for more tips and examples for conducting social media experiments.

7. Analyze and share the results of your experiment

Review the results of your experiment to identify new opportunities or add insights to your records.

If you’re trying to gain executive buy-in, especially for further testing or resources, you’ll need to communicate and create an effective data story to highlight why your company will benefit from your suggested next steps.

Using Sprout, you can easily access automated, presentation-ready reports to help illustrate your data story. Create custom reports, like this Facebook Performance Summary that includes impressions, engagements, post link clicks and publishing behavior for various content types:

Use experiments to optimize engagement and growth

Here’s a quick overview of the seven steps:

Good luck on your journey to embracing curiosity and thinking like a scientist—your social strategy will thank you.

This article is an excellent first step, but there’s so much more to learn about social media experiments. Step into the (virtual) lab yourself and get a hands-on experience, by signing up for a free trial .

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Adolescence

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

Posted August 10, 2023 | Reviewed by Gary Drevitch

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

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

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

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

What Researchers Found

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

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

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

Time Trend Data Are Inconclusive

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

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

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

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

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

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

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

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Here are the 42 questions on the juror questionnaire in Trump's hush money case

Ximena Bustillo

Former President Donald Trump speaks to the press at Manhattan criminal court after a hearing on Feb. 15. Angela Weiss/AFP via Getty Images hide caption

Former President Donald Trump speaks to the press at Manhattan criminal court after a hearing on Feb. 15.

The search for 18 fair and impartial jurors will begin next week in former President Donald Trump's first criminal trial.

Trump faces a 34-count felony indictment alleging that he falsified New York business records in order to conceal damaging information to influence the 2016 presidential election. Monday kicks off jury selection for the trial that is expected to last about six weeks — even as Trump campaigns to be president once again. Trump has pleaded not guilty to the charges.

In total, 42 questions will be used to select 12 jurors and six alternates for the first-ever criminal trial featuring a former or sitting president. And this will be Trump's first appearance in a trial since winning enough delegates to receive the GOP nomination.

Read the juror questionnaire:

Still, jurors will not be asked for whom they have voted or will vote, nor will lawyers question them about their political affiliations or campaign contributions. New York Judge Juan Merchan, who is overseeing the trial, believes those views will be made clear through other questions.

Jurors will be asked to identify the online media, news and social media programs they use, podcasts they listen to and if they have ever considered themselves a supporter or a member of any of six white supremacist and extremist groups — including the QAnon movement, Proud Boys and Antifa.

See where the big Trump cases stand in the months leading to the election

They will also be asked about their business and political relationships with the former president and New York business mogul. Lawyers will ask if prospective jurors, a relative or a close friend ever worked for any company or organization that is owned or run by Trump or anyone in his family. And they will be asked if they have ever attended a rally or campaign event for Trump, volunteered for his campaign or been a part of any "anti-Trump" efforts.

These have all been questions similarly asked in Trump's previous jury trials in Manhattan.

Trump's Trials

Here's what you need to know about the new york hush money case, correction april 9, 2024.

A previous version of this story said Trump pleaded guilty to the 34-count felony indictment. He has pleaded not guilty.

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Trump Deposition in SPAC Suit Scrapped Ahead of Criminal Trial

(Bloomberg) -- Donald Trump won’t be deposed on Monday after all in the case filed against him by two co-founders of his social-media startup, a person familiar with the matter said, resolving questions over a potentially significant conflict with the start of the former president’s first criminal trial.

Trump Media & Technology Group Corp.’s co-founders Andy Litinsky and Wes Moss, who sued Trump for allegedly trying to dilute their 8.6% stake, will still seek to depose the former president at another time, said the person, who didn’t want to be identified discussing the plan before it’s public.

The person said the plan to depose the presumptive Republican nominee for the November presidential election changed because the Delaware judge handling the case, Sam Glasscock III, is retiring and will be replaced. 

Lawyers for Litinsky and Moss — former contestants on Trump’s TV show The Apprentice who joined forces with him to form Trump Media — had said in a court filing last week they were questioning Trump under oath April 15 in Manhattan. The filing didn’t address the conflict with the trial starting in Manhattan District Attorney Alvin Bragg’s indictment accusing Trump of falsifying business records to conceal a hush money payment to a porn star before the 2016 election.

Ted Kittila, a Delaware-based lawyer for Trump Media, said earlier this week that Glasscock hadn’t approved the deposition date, though under Delaware court rules, judicial approval isn’t needed for deposition requests. Judges often get involved, however, when parties refuse to sit for questioning.

The civil suit is progressing as shares of Trump’s startup, which runs his Truth Social platform, are struggling to retain interest among frenzied traders who helped fuel a rally last month. The company, trading under the DJT ticker, has lost nearly half of its value from a March 27 peak, erasing roughly $4.3 billion.

Read More: Trump Media Co-Founders Challenging Six-Month Share Lockup

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Risk Factors Associated With Social Media Addiction: An Exploratory Study

1 School of Education, Guangzhou University, Guangzhou, China

2 Department of Psychiatry, 987th Hospital of PLA, Baoji, China

Xiuming Wang

Yiming xiao.

3 School of Economics and Statistics, Guangzhou University, Guangzhou, China

Associated Data

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

The use of social media is becoming a necessary daily activity in today’s society. Excessive and compulsive use of social media may lead to social media addiction (SMA). The main aim of this study was to investigate whether demographic factors (including age and gender), impulsivity, self-esteem, emotions, and attentional bias were risk factors associated with SMA. The study was conducted in a non-clinical sample of college students ( N = 520), ranging in age from 16 to 23 years, including 277 females (53%) and 243 males (47%). All participants completed a survey measuring impulsivity, self-esteem, anxiety, depression, social anxiety, loneliness, and attentional bias. The final hierarchical regression model indicated significant risk factors for SMA with an accuracy of 38%. The identified set of associated risk factors included female gender (β = −0.21, t = −4.88, p < 0.001), impulsivity (β = 0.34, t = 8.50, p < 0.001), self-esteem (β = −0.20, t = −4.38, p < 0.001), anxiety (β = 0.24, t = 4.43, p < 0.001), social anxiety (β = 0.25, t = 5.79, p < 0.001), and negative attentional biases (β = 0.31, t = 8.01, p < 0.001). Finally, a discussion of the results is presented, followed by corresponding recommendations for future studies.

Introduction

Social media (e.g., Facebook, WeChat, Tik Tok) have attracted substantial public interest to the point that they are becoming a cornerstone of modern communication. It has been argued that social media promote social interaction, help in maintaining relationships, and allow for self-expression ( Baccarella et al., 2018 ). According to a survey by the China Internet Network Information Center, there are 900 million users of social media in China. College students are freer than others to control the use of their time and the use of social media is thus becoming an integral part of their lives. However, social media, if used immoderately, may lead to social media addiction (SMA), which refers to the excessive and compulsive use of social media platforms, resulting in severe impairment in all aspects of life ( Kuss and Griffiths, 2017 ). Addicted users of social media tend to spend too much time on social media, to be overly concerned about social media and to be driven by uncontrollable urges to use social media ( Andreassen and Pallesen, 2014 ). SMA can be viewed as a specific form of digital technology addiction, in which the conceptualizations all center on these addictive behaviors as pathological forms of necessary and normal behaviors ( Moreno et al., 2021 ). SMA may affect users’ mental health, leading to anxiety, depression, lower subjective wellbeing, and poor academic performance ( Lin et al., 2016 ). The present study will examine potential risk factors associated with SMA focusing on demographic factors, impulsivity, self-esteem, emotions, and attentional bias.

In general, the impact of demographic factors such as age and gender has been considered in previous studies. Young individuals maintain an online presence and develop addictive behaviors more often than older individuals ( Abbasi, 2019 ). Furthermore, women are more likely to indulge in social media more than men in order to enhance their social connections ( Andreassen et al., 2017 ).

Impulsivity is an important personality trait that plays a major part in the occurrence, development, and maintenance of addiction ( Cerniglia et al., 2019 ). However, the link between impulsivity and SMA is controversial. It has been found that trait impulsivity is a marker for vulnerability to SMA ( Sindermann et al., 2020 ). The most influential theoretical explanation for this is Dual System Theory, which is also known as reflective–impulsive theory. The reflective system includes the prefrontal cortex, which plays a key role in a wide range of executive and inhibitory behaviors, such as short-term memory, planning, attention, and resistance to immediate rewards for the sake of long-term rewards. By contrast, the impulsive system includes the subcortical brain areas, accounts for pleasure and addictive behaviors, and responds to quickly acquired cues regardless of long-term negative results. Imbalance between the reflective and impulsive systems leads to addictive behaviors ( Droutman et al., 2019 ). However, another empirical study based on a Go/Stop Impulsivity task found impulsivity was not significantly associated with SMA ( Chung et al., 2019 ). This inconsistency of results may be caused by the use of different measurement approaches. Therefore, the association between impulsivity and SMA needs further exploration.

Self-esteem impacts the predisposition to SMA and there is a negative association between the frequency of Facebook use, the meaning attributed to Facebook use, and users’ levels of self-esteem ( Błachnio et al., 2016 ). People with low levels of self-esteem prefer to avoid face-to-face communication and escape into the virtual world where they can behave anonymously and do what they want. Also, negative feedback from social media will reduce users’ levels of self-esteem ( Andreassen et al., 2017 ).

Concerns over the negative emotions of social media addicts have not abated. Prior studies have mainly considered the influence of anxiety, depression, social anxiety, and loneliness on SMA. Atroszko et al. (2018) reported that SMA is positively associated with anxiety and depression. Additionally, social anxiety and loneliness are the emotions generated in the process of interpersonal communication ( O’Day et al., 2019 ). People with social anxiety prefer online communication as a way to avoid uncomfortable real interactions and social tensions. Caplan (2007) used privacy to explain this phenomenon: privacy can be better protected through online communication. However, the relationship between SMA and loneliness is controversial. Primack et al. (2017) regarded loneliness as a risk factor associated with SMA, indicating that high levels of loneliness may lead to addiction. Another study by Baltacı (2019) suggested that loneliness was not significantly associated with SMA. Thus, more studies examining the links between loneliness and SMA are needed.

In terms of cognitive factors, attentional bias has been considered as a potential causative factor of SMA. Attentional bias refers to a situation in which individuals are highly sensitive and allocate attentional resources to specific stimuli ( Gao et al., 2011 ). Generally, substance and behavioral addicts display an attentional bias mainly toward negative information ( Hu et al., 2020 ). Furthermore, attention to negative information (ANI) may further aggravate addictive behaviors ( Cheetham et al., 2010 ). An important theoretical explanation for addicts’ ANI is the self-schema theory ( Becker and Leinenger, 2011 ). Schemas are relatively stable and lasting cognitive templates for individual storage, organization, integration and information processing. A negative schema will make individuals pay attention to information consistent with the schema, resulting in a processing bias. It is not yet clear whether the attentional bias effect generalizes to SMA as a specific form of digital technology addiction. To our knowledge, no studies have specifically revealed a relationship between ANI and SMA.

Prior studies have focused on only one or two independent factors without considering the hierarchical importance of risk variables. Undoubtedly, identifying the hierarchical importance of risks has implications for the treatment and intervention of SMA. In the present study, an attempt was made to explore the risk factors for SMA considering their hierarchical importance. Also, this is the first report to specifically look at ANI and SMA with self-reported questionnaires, which provide the advantages of saving time and the capability to conduct large-scale investigations. It was hypothesized that each variable would be a significant predictor for SMA at each step.

Materials and Methods

Participants.

A total of 532 college students attending a state university in China participated in the present study. 12 participants did not meet the inclusion criteria and were excluded. The final study sample consisted of 520 participants including 277 females (53%) and 243 males (47%). The ages of all participants ranged from 16 to 23 years ( M = 19.68, SD = 1.07). Inclusion criteria for participants included fluency in Chinese and having at least one social media application account. Exclusion criteria included current psychiatric conditions and a history of mental illness (e.g., anxiety, depression, schizophrenia or bipolar disorder), as well as other addictive behaviors or a family history of addictions (e.g., alcohol use disorder, nicotine abuse, illegal drug dependence, etc.).

All participants completed paper-and-pencil surveys in class. Written consent was obtained from the participants before the survey. The survey took approximately 20 min. Data collection took place from April to June 2021.

Ethics Statement

Approval for the research was granted by the ethics committee of Guangzhou University. All participants were informed of the purpose and procedures of the study, and that participation was anonymous and voluntary.

Socio-demographics information: The survey recorded questions concerning age, gender, presence of social media accounts, current and prior of mental illness, as well as the presence of other addictive behaviors and a family history of addiction.

Bergen Social Media Addiction Scale

The Chinese version ( Leung et al., 2020 ), adapted from Andreassen et al. (2017) , was used to evaluate levels of SMA with higher scores indicating greater SMA. It consists of six items (e.g., “How often have you felt an urge to use social media more and more during the last year?”) measured on a 5-point scale (1 = very rarely , 5 = very often ). According to the gold standard of clinical diagnosis, a BSMAS score of 24 was taken to be the optimal cut-off point ( Luo et al., 2021 ). If the BSMAS score was 24 or above, the participant was considered to be addicted. Otherwise, the participant was considered to be non-addicted. The Cronbach’s alpha was 0.78 in the current study.

Brief Barratt Impulsivity Scale

The Chinese version ( Luo et al., 2020 ), adapted from Morean et al. (2014) , was used to measure trait impulsivity. It consists of eight items (e.g., “I do things without consideration”) rated on a 4-point scale (1 = very inconsistent , 4 = very consistent ). Higher scores indicate poor self-regulation and impulsive behaviors. The Cronbach’s alpha was 0.81 in the current study.

Rosenberg Self-Esteem Scale

The Chinese version ( Wang et al., 2010 ), adapted from Rosenberg (1965) , was used to evaluate levels of self-esteem. It is rated on a 4-point scale (1 = strongly disagree , 4 = strongly agree ) with 10 items (e.g., “I feel that I have a number of good qualities”). Higher scores indicate higher levels of self-esteem. The Cronbach’s alpha was 0.91 in the current study.

Self-Rating Anxiety Scale

The Chinese version ( Liu et al., 1995 ), adapted from Zung (1971) , was used to measure anxiety. It is rated on a 4-point scale (1 = never or very rarely , 4 = most or all of the time ) with 20 items (e.g., “I feel more nervous and anxious than usual”). Higher scores indicate more severe anxiety symptoms. The Cronbach’s alpha was 0.84 in the current study.

Self-Rating Depression Scale

The Chinese version ( Liu et al., 1994 ), adapted from Zung (1965) , was used to assess depression. It consists of 20 items (e.g., “I feel gloomy and depressed”) rated on a 4-point scale (1 = never or rarely , 4 = most or all of the time ). Higher scores indicate more severe depressive symptoms. The Cronbach’s alpha was 0.85 in the current study.

Interaction Anxiety Scale

The Chinese version ( Peng et al., 2004 ), adapted from Leary (1983) , was used to assess social anxiety. It consists of 15 items (e.g., “I will be nervous during an interview”) rated on a 5-point scale (1 = not at all consistent , 5 = extremely consistent ) where higher scores represent greater social anxiety. The Cronbach’s alpha was 0.88 in the current study.

UCLA Loneliness Scale

The Chinese version ( Liu, 1999 ), adapted from Russell (1996) , was used to assess loneliness. It is composed of 20 items (e.g., “Do you often feel that no one can be trusted?”) rated on a 4-point scale (1 = never , 4 = always ). Higher scores indicate higher levels of loneliness. The Cronbach’s alpha was 0.91 in the current study.

Attention to Positive and Negative Inventory

The Chinese version ( Dai et al., 2015 ), adapted from Noguchi et al. (2006) , was used to assess attentional bias. The inventory is composed of 22 items rated on a 5-point scale (1 = totally inconsistent , 5 = totally consistent ) and includes two dimensions: attention to positive information with 12 items and ANI with 10 items (e.g., “I can’t forget the harm that others have done to me”). This study focused on the impact of ANI on SMA, thus only the ANI subscale was used. Higher scores on the ANI subscale indicate greater ANI. The Cronbach’s alpha was 0.73 in the current study.

Data Analysis

Data were analyzed using the SPSS 24.0 software package program. Initially, the effects of demographic information (age and gender) on SMA in the total sample were checked with one-way ANOVAs. The Pearson correlation coefficient was conducted to reveal the links between gender, impulsivity, self-esteem, emotions, attentional biases and SMA. Finally, a hierarchical regression analysis was used to explore whether independent variables (i.e., gender, impulsivity, self-esteem, emotions, and attentional biases) could predict the dependent variable (SMA).

Descriptive Data and Inter-Correlations Between Variables

First, one-way ANOVAs were used to investigate effects of age and gender on SMA in the total sample. Univariate analyses indicated that there is no significant difference by age [ F (7, 512) = 1.74, p = 0.09] but that the samples differed by gender [ F (1, 518) = 23.79, p < 0.001]. Females are more likely than males to be addicted to social media. Thus, the first step was to control for the effects of gender in the regression analyses. Next, a correlation analysis was performed on the influencing factors of SMA in the total sample. Bivariate correlations between variables are presented in Table 1 .

Descriptive data and inter-correlations between variables.

N = 520. **p < 0.01 and ***p < 0.001.

a Dummy variable is coded as male = 1, female = 0. The proportion of females in the sample is 53%.

ANI, attention to negative information; SMA, social media addiction.

Hierarchical Regressions

Hierarchical regressions are presented in Table 2 . Gender was included in Step 1 ( R 2 = 0.04). It was found that gender was significantly related to SMA (β = −0.21, t = −4.88, p < 0.001) and that females are more prone to addictive use of social media. In Step 2, gender and impulsivity remained risk factors ( R 2 = 0.16). Impulsivity was positively associated with SMA (β = 0.34, t = 8.50, p < 0.001). In Step 3, gender, impulsivity and self-esteem were included ( R 2 = 0.19). A higher level of self-esteem proved to be a protective factor associated with SMA (β = −0.20, t = −4.38, p < 0.001). Gender and impulsivity were still risk factors. In Step 4, negative emotions were added to the model ( R 2 = 0.30) and risk factors associated with SMA were found to include gender (β = −0.14, t = −3.79, p < 0.001), impulsivity (β = 0.18, t = 4.01, p < 0.001), anxiety (β = 0.24, t = 4.43, p < 0.001), and social anxiety (β = 0.25, t = 5.79, p < 0.001). Depression, loneliness and self-esteem were not risk factors. In Step 5, ANI was shown to be positively correlated with SMA (β = 0.31, t = 8.01, p < 0.001). The final model accounted for 38% of the variance [ F (9, 510) = 36.61, p < 0.001]. In the final model, gender, impulsivity, anxiety, social anxiety, and ANI were all found to be risk factors associated with SMA.

Regression analyses.

N = 520. ***p < 0.001.

a Dummy variable is coded as male = 1, female = 0.

ANI, attention to negative information.

The main objective of this study was to examine whether demographic factors, impulsivity, self-esteem, emotions, and attentional biases were potential risk factors associated with SMA. It was found that females were more susceptible to SMA than males. Additionally, impulsivity, low levels of self-esteem, anxiety, social anxiety, and ANI were found to be risk factors for SMA.

Demographic Factors

Gender was found to be associated with SMA. In the present sample, 2.9% of the participants scored 24 or above in BSMAS and thus met the criteria for SMA. The proportion was similar to the previous report (3.5%) in a Chinese sample ( Luo et al., 2021 ). The prevalence of SMA in males and females in the current study was 1.2 and 4.3%, respectively. Females showed higher addiction rate and greater levels of SMA than males. This result is in agreement with prior research ( Monacis et al., 2020 ). Females focus more attention on social activities for enhancing communication and prefer to share more selfies on social applications and social networking sites ( Dhir et al., 2016 ). Interestingly, it was found that age had no significant effect on SMA. This finding is inconsistent with the prior study that young people are more likely to develop SMA ( Abbasi, 2019 ). The lack of association between age and SMA can possibly be attributed to the selected sample in which participants were relatively young and the age span was small, resulting in no age effect.

Impulsivity

Although, the association between impulsivity and SMA is still controversial, this study supports the hypothesis that impulsivity is positively associated with SMA. This finding is in agreement with the study by Sindermann et al. (2020) , which indicated that trait impulsivity was positively associated with the severity of SMA. It contradicts the study by Chung et al. (2019) , which indicated that impulsivity was not associated with SMA. Our finding underlines the importance of impulsivity as a risk factor related with SMA. This result may be supported by Dual System Theory ( Droutman et al., 2019 ). Higher levels of impulsivity in social media addicts are rooted in an imbalance between the reflective and impulsive systems. Higher levels of impulsivity might be associated with SMA due to attentional fluctuation, i.e., individuals engage in social media when they lose attention to another task. Addictive uses of social media can thus be regarded as a form of urgency relevant behaviors displayed to regulate (suppress and/or exacerbate) emotional states in the short term despite the delayed negative consequences ( Rothen et al., 2018 ). Similarly, a study by Minhas et al. (2021) explored the links between alcohol abuse and food addiction in relation to impulsive personality traits, impulsive choices and impulsive action. It was found that alcohol problems and food addiction showed parallel associations, indicating common underlying impulsivity mechanisms. Likewise, the present study also found that a higher level of impulsivity is a risk factor for SMA. Collectively, the multiple lines of evidence suggest that SMA, food addiction, and alcohol abuse may have similar underlying impulsivity mechanisms.

Self-Esteem

Levels of self-esteem were found to be negatively correlated with SMA in the current study. This is consistent with a prior study that found higher levels of self-esteem are a protective factor against addictive behaviors ( Andreassen et al., 2017 ). In the research on Internet addiction, people with low levels of self-esteem tend to use the Internet for social support, and the social support gained from the Internet could compensate for the lack of social support offline. Also, SMA showed a negative correlation with levels of self-esteem. Individuals use more social media to obtain higher levels of self-esteem (e.g., harvesting “likes”), and/or to get rid of feelings of low self-esteem ( Błachnio et al., 2016 ). Notably, after emotions were incorporated into the model, self-esteem was no longer a risk factor for SMA in hierarchical regressions. Consistent with prior research, this suggests that the influence of self-esteem on SMA is regulated by emotions ( Andreassen et al., 2017 ).

The results of this study show that emotions, particularly, anxiety and social anxiety, are the strongest risk factors associated with SMA. This is consistent with prior research showing that anxiety is a risk factor for SMA ( Keles et al., 2019 ). Anxious individuals prefer to use social media platforms to alleviate unfavorable emotions, for example, by seeking attention, support, or a sense of belonging on social media ( Vannucci et al., 2017 ). Additionally, in line with the study by Baltacı (2019) , this study found that social anxiety is positively associated with SMA. Individuals who experience difficulty communicating with others in social environments prefer social media for interaction. Privacy is an important feature of the Internet ( Caplan, 2007 ). Compared to face-to-face communication, interaction through a virtual environment is perceived to be less risky.

The relationships between depression, loneliness, and SMA were found to be relatively low. Neither loneliness nor depression was significantly associated with SMA in this study. This is consistent with prior research that has shown that depression and loneliness were not predictors of SMA ( Baltacı, 2019 ; Marttila et al., 2021 ). The reason for the lack of a link may be the marginal effect caused by these moderate relationships. When depression and loneliness were analyzed as psychosocial variables in terms of SMA, it was found that depression and loneliness are both the reasons for Primack et al. (2017) and the consequences of SMA ( Dossey, 2014 ).

Attention to Negative Information

This was the first study to look at the association between ANI and SMA. This study used hierarchical regressions to find that ANI is one of the risk factors associated with SMA. Previously, a study by Aguilar de Arcos et al. (2008) reported that opioid users have higher arousal responses to negative and unpleasant emotional images compared with healthy individuals. Similarly, another study by Hu et al. (2020) used eye tracking technology to find that mobile phone addicts show a processing bias toward negative emotional clues. Although, unlike substance and behavioral addiction, the availability of social media is so high. Social media addicts also displayed negative attentional bias effect. This indicates that a processing bias toward negative information may be the common underlying mechanism that incurs and maintains addictive behavior. The abovementioned phenomenon can be explained by self-schema theory ( Becker and Leinenger, 2011 ). Addicts mainly demonstrate attentional biases toward negative emotions because they often experience negative emotions such as anxiety and depression. Information consistent with the negative schema will automatically capture the individual’s attention, leading to negative attentional bias. ANI is also an important reason for the occurrence, development, and maintenance of social anxiety and depression ( Brailovskaia and Margraf, 2020 ). Individuals with high levels of social anxiety specifically allocate attentional resources to negative information in the environment and social interactions, resulting in depression.

Implications

Our study can not only provide theoretical and practical support for prevention and intervention into SMA, but also contribute to improving individuals’ physical and mental health. It was found that female gender, impulsivity, self-esteem, anxiety, social anxiety, and ANI exhibited significant risk effects for SMA. In future studies, alleviating users’ anxiety, actively organizing social activities, and correcting attentional bias with attention training programs could be used to reduce the risk of SMA.

Limitations and Future Directions

The current study has some limitations. First, since this research was based on a single classroom survey, it was a relatively small study in terms of scope, and the sample was potentially unrepresentative. Second, less information was collected from the participants in the demographic characteristics portion of the survey, resulting in a lack of some sociodemographic and clinical information about participants. Third, data were collected near the end of the semester, when senior students were preparing for internship and/or employment. Thus, participants mainly belonged to junior grades. The age span is relatively narrow, which may have affected our ability to detect an effect of age on SMA. Fourth, this research was based on questionnaires and was limited by self-report measurement methods. The validity of the research may depend on the accuracy of participants’ reports. Finally, as this study was cross-sectional design, the causality between variables could not be determined.

In future studies, the scope of sampling can be further expanded to enhance the representativeness of the sample and explore the effect of age on SMA. Also, a wide range of other information about participants should be gathered through the survey to explore the effect of demographic characteristics on SMA: e.g., average daily time spent on social media, the number of social media applications, discipline background, etc. Moreover, research focused on the relationship between impulsivity, attentional biases and SMA could be combined with empirical research. For example, the Go/Stop paradigm and Stroop task could be used to assess impulsive action and attentional bias, respectively. Finally, longitudinal tracking research could be used to determine the causality between variables.

Data Availability Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of Guangzhou University. Participants provided written informed consent to participate in the study.

Author Contributions

JZ designed the project and collected the data. TJ, XWa, and YX conducted statistical analyses. XWu was involved in supervision and edit manuscript drafts. All authors approved the final manuscript before submission.

Conflict of Interest

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

Publisher’s Note

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

All authors are grateful for the financial support from the National Natural Science Foundation of China (Grant No. 31970993).

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