Anxiety is one of the most common mental disorders among young adults. Social media use is associated with mental health problems, including anxiety, while physical activity has been shown to reduce anxiety.
This study was conducted to investigate the association between social media use, physical activity and anxiety in young adults. The study included 111 participants and used a correlation design to examine the effects of social media use and physical activity on anxiety, as well as the moderating role of physical activity on the relationship between social media use and anxiety. The study found that excessive social media use led to increased levels of anxiety and that individuals who were physically active had lower anxiety scores. Physical activity was also found to moderate the correlation between high social media use and anxiety, with individuals who engage in high levels of physical activity while using social media having low or moderate anxiety scores. The study also found an inverse relationship between physical activity and social media use. People who exercise a lot do not tend to overuse social media, while those who overuse social media tend to be less physically active. The study’s findings support previous research and extend previous findings on related topics where there is no research examining the same issues. The study highlights the importance of physical activity in reducing anxiety and suggests that reducing social media use and increasing physical activity may be beneficial for young adults’ mental health.
1. Introduction
In recent years, the prevalence of social media has undeniably increased, and its impact on people’s mental health should not be underestimated. While social media has opened up countless opportunities for communication and collaboration, it can also have a detrimental effect on mental health, especially among young people. Physical activity has been shown to reduce stress and anxiety, and a lack of physical activity can often increase stress and anxiety. Therefore, it is important to ensure a healthy balance between the influence of social media and physical activity to reduce anxiety.
1.1 Anxiety
Anxiety is an emotion characterized by feelings of fear, apprehension, and worry. It is an adaptive response that helps us identify and confront potential threats. While everyone experiences anxiety at some point in his/her lives, prolonged or excessive anxiety can lead to psychological distress, affecting one’s mental and physical health (Gross & Hen, 2004).
In some cases, anxiety can be a normal response to important life events such as an exam, medical examination, or a job interview. However, anxiety can become a disorder when the intrusive thoughts and worries become so pervasive that they interfere with normal daily functioning (NHS website, 2022). People with anxiety disorders often experience physical symptoms such as sweating, trembling, nausea, and accelerated heart rate (APA Dictionary of Psychology, n.d.). According to Thibaut (2022), anxiety disorders are the most common mental illnesses, with an estimated global prevalence of 7.3%.
According to the World Health Organisation (WHO, 2016), the prevalence of anxiety and/or depression has seen a staggering increase of 50% between 1990 and 2013, from 416 million to 615 million. This has severe implications for both individual and societal well-being and places a significant burden on humanity. Anxiety is the most prevalent of all mental disorders (Bandelow & Michaelis, 2022), has become a major public health problem worldwide (WHO, 2016), especially among young adults (Castaneda et al., 2008). It’s impact goes beyond the individual – it also imposes significant economic costs. In fact, the global economy loses an estimated $1 trillion annually due to anxiety and depressive disorders (WHO, 2016). This highlights the importance of understanding, treating and preventing anxiety, especially in its early stages. This is essential for both human and economic well-being.
Young adulthood is a critical period for the prevention and treatment of mental illness symptoms, as research has shown that anxiety and depression are a major public health issue in this age group (Kessler et al., 2005; Castaneda et al., 2008). In the last 25 years, the prevalence of anxiety and depression in young people has increased by a distressing 70%, according to the Royal Society for Public Health & Young Health Movement (2017). Many factors are associated with the manifestation of anxiety, both biological, social and cognitive. However, one seemingly innocuous habit appears to be a prominent factor in the current age of rapid technological development. Social media (SM) is an ever-growing branch of applications that has become the holy grail of modern communication and socialization, boasting easy access via smartphones and widespread acceptance across a range of age groups. Despite the numerous benefits that SM provides, there are also potential dangers associated with it, such as the risk of addiction and developing mental illnesses.
1.2. Social Media
According to the Global System for Mobile Communications Association, 5.2 billion people subscribed to mobile services in 2020, representing 67% of the world’s population. Smartphone users accounted for 68% of this user population. The adaptability of smartphones enables users to seamlessly integrate work, leisure, and social contact, leading to an improved quality of life in many ways (Longstreet and Brooks, 2017). Young people are more reliant on their smartphones for a variety of reasons, but also see them as a source of independence (Rashid et al, 2020). Smartphones offer convenience, connectivity and access to knowledge, and enable young people to pursue their dreams, keep up to date and stay connected to their social circles. University graduates, younger users, singles, people with professional degrees and urban users with higher incomes are more likely to use smartphones than their peers. These users also tend to use cutting-edge technologies such as SM, the internet, cameras and viewing photos. International data suggests that 83% of young adults use SM applications (Duggan & Brenner, 2013), with 98.5% of them using more than one (Datareportals, 2022). Time spent on social media platforms each day has increased from 96 minutes in 2012 to almost 135 minutes in 2018 (Tandon et al, 2021).
Smartphone use has been associated with negative consequences such as reduced work performance and productivity (Turel et al., 2011), poorer academic performance (Anderson et al., 2017) and distraction (Coursaris et al., 2012). Incoming messages, phone calls and notifications of posts on social media can become distractions (Brooks, 2015), and the cognitive demands associated with features such as social media can divert users’ attention and make it difficult for them to focus on work-related activities (Chu et al., 2021). The abundance of real-time information about events, activities and conversations taking place on social media platforms can lead to decision paralysis, affecting decision-making and well-being. Fear of missing out (FoMO) is a common concern among those who worry that others may enjoy pleasurable experiences that they are not part of (Milyavskaya et al., 2018). Younger people have been found to be more susceptible to FoMO (Przybylski et al., 2013), motivated by FoMO to stay constantly connected (Tandon et al., 2021), and it also acts as a mediator between anxiety and excessive social media use (Elhai et al., 2020). This can create a vicious cycle of compulsive social media use, where FoMO drives people to social media, which in turn can further increase young people’s FoMO (Beyens et al., 2016). Studies have shown that almost half of all adults in the United Kingdom (UK) feel uncomfortable or anxious when they do not have access to their email or social media (Srivastava et al., 2019). Furthermore, surveys by Rosen et al. (2013) found that younger generations check their social media accounts every hour, every 15 minutes or even all the time. This over-reliance on mobile phone use to achieve the same level of satisfaction can potentially lead to mobile phone addiction and mental health conditions such as anxiety (Choi & Lim, 2016; Chóliz, 2010).
Numerous studies have established a positive relationship between social media use (SM) and mental disorders, and anxiety in particular (Atroszko et al., 2018; Marino et al., 2018). This positive relationship appears to be cross-continental, with studies conducted in countries on different continents with different cultures. For example, Tsitsika and colleagues (2014) found a positive relationship between intensive SM use and anxiety in a study of 10,930 adolescents in six European countries, while Yan and colleagues (2017) confirmed this in a similar study in China. Vannucci and colleagues (2017) conducted a study with young adults in the USA and found a significant association between temporal SM use and dispositional anxiety, and that daily SM use was also significantly associated with a higher likelihood of an anxiety disorder.
In a recent systematic review, Keles and colleagues (2020) examined the existing evidence linking SM use and mental health problems in adolescents and found that time spent on SM was one of the most important risk factors for anxiety and depression. However, there is research which suggests that excessive use of SM may not be the cause of anxiety, but rather that socially anxious individuals tend to use SM more frequently and passively (O’Day & Heimberg, 2021). Alternatively, it has been suggested that the use of SM such as Facebook may be associated with less anxiety, depression and higher life satisfaction because it provides opportunities to socialise (Grieve et al., 2013). The displaced behavior theory offers an explanation for the correlation between social media (SM) use and mental health. The theory suggests that individuals who engage in more sedentary activities, like using social media, have less time for in-person social interactions. These interactions have been shown to provide protection against mental disorders, which may explain the link between SM use and negative mental health outcomes (Karim et al., 2020).
1.3. Physical activity
Digitalisation is one of the main barriers preventing young people from engaging in physical activity (PA) (Thompson et al., 2005). Even university students who follow health and fitness accounts on SM do not differ significantly from those who do not – the difference is only 42.9 minutes PA per week (Guthold et al., 2020). While social media is often associated with negative mental health effects and anxiety, PA has been scientifically proven to counteract these effects.
PA is any physical movement produced by the contraction of skeletal muscles that requires energy expenditure, and includes activities such as competitive sports, exercise, hobbies and daily life (Miles, 2007). Regular PA has many benefits, it is a key component in lifestyle modification for chronic disease management and is considered essential for maintaining a healthy brain (Noakes & Spedding, 2012). Our human physiology and biochemistry are designed to function best when we are physically active because that is what our ancestors did when our genome was selected (Eaton & Eaton, 2003). Today’s humans require about the same level of physical activity (PA) as our ancestors did 40,000 years ago, and PA has been shown to have a number of positive effects on biological and psychological mechanisms. Unfortunately, our current lifestyles are not as physically active as they once were, as many of us lead very sedentary lives. This has led to an increased risk of physical and mental illness (Booth et al., 2017; Malm et al., 2019).
Animal studies have shown that regular PA has a positive effect on the pathophysiological mechanisms underlying anxiety. Studies in humans have shown that anxiety levels following a stressful event are lower in the physically trained than in the untrained. This means that trained individuals find acute psychosocial stressors easier to cope with and less intimidating due to the reduced adrenocortical, autonomic and psychological responses they experience (Rimmele et al., 2007). In addition, physical activity can help improve a person’s overall physical health and psychological well-being and even reduce the risk of developing certain diseases, making it an important part of a healthy lifestyle.
A number of brain abnormalities have been linked to anxiety and the manifestation of anxiety symptoms, such as dysregulations of the HPA axis, including the release of excess glucocorticoids and alterations in adrenocorticotropic hormone (ACTH). Preclinical studies have shown that physical activity can alter stress and anxiety levels in humans by affecting the HPA axis and altering the release of corticotrophin-releasing factor (CRF) and ACTH (Anderson & Shivakumar, 2013). Furthermore, the pathophysiology of anxiety disorders has been linked to abnormalities in brain monoamine function. Animal studies have shown that regular aerobic activity increases serotonergic and noradrenergic levels in the brain and has an effect on anxiety comparable to the effect of antidepressants (Meeusen & De Meirleir, 1995). In addition, antidepressant effects have been observed following infusions of brain-derived neurotrophic factor (BDNF) into the dorsal raphe nucleus (Altar, 1999). Animal experiments have also shown that physical activity can lead to an increase in BDNF levels (Russo-Neustadt et al., 1999).
Research on university students has shown that physical activity (PA) can be beneficial against anxiety. Moderate PA can make a person 6.45 times less likely to suffer from anxiety, while vigorous PA can make them 10.42 times less likely to suffer from anxiety compared to physically inactive individuals (Ghrouz et al., 2019). Conversely, a lack of physical activity has been associated with higher levels of anxiety (Silva et al., 2020; Teychenne et al., 2015). Therefore, it is important to incorporate PA into daily routines to control anxiety. Despite the many benefits associated with PA, current research shows that adolescents and university students often do not reach the recommended levels of participation in PA (Folk & Kovacs, 2021).
A meta-analysis by Rebar and colleagues (2015) of 306 study effects and 10,755 non-clinical participants found that PA can reduce anxiety through a significant, small effect size (SMD = -0.38; 95% CI: -0.66 to -0.11), demonstrating the potential therapeutic effect of PA for clinical populations. In a separate meta-analysis of 6 randomised control trials with 262 participants, Stubbs and colleagues (2017) found that exercise was effective in reducing anxiety symptoms, with a significant moderate effect size of 0.582 (95% CI -1.0 to -0.76). In addition, Aylett and colleagues’ (2018) meta-analysis of patients with clinically elevated anxiety found that PA, particularly vigorous PA, is more effective than a control group, with a statistically significant moderate effect size of -0.41 (95% CI = -0.70 to -0.12), and that vigorous PA is more effective than low-intensity PA with a significant effect size of -0.38 (95% CI -0.68 to -0.08). These results suggest that PA is a suitable treatment option for anxiety, with vigorous PA being more beneficial than moderate PA.
While there is a large literature examining the factors of physical activity (PA) and social media (SM) in relation to anxiety, there is limited research examining the complex relationship between these factors and their effects on anxiety. Booker and colleagues (2015) found that adolescents with higher use of screen media were associated with greater socio-emotional difficulties and lower levels of happiness, reflecting a decrease in PA. According to Cao and colleagues (2011), in a study of 5000 adolescents in China, there is a positive association between high screen time and increased anxiety when physical activity levels (PA) are reduced. Zink and colleagues (2020) also found a moderating effect of intense PA on the association between sedentary screen time behavior and anxiety, but the study sample was small. Chen and colleagues (2022) discovered that during the COVID -19 pandemic, PA played a critical role in the association between screen time and anxiety because individuals who spend more time in front of screens tend to engage less with PA, leading to higher levels of anxiety. Foroughi and colleagues (2021) examined the moderating role of PA on Instagram addiction and found a positive effect of Instagram addiction on anxiety. Their findings suggest that individuals who engage in higher levels of physical activity are less likely to develop Instagram addiction as a result of their social and entertainment needs.
1.4 Aims and hypothesis
In summary, while there is a wealth of research examining the factors PA and SM in relation to anxiety, the relationship between these factors and their impact on anxiety is complex and varied. The studies discussed in this section provide evidence of the negative effects of SM and the positive effects of PA on anxiety. The findings support the theory that PA plays a crucial role in moderating the effects of SM on anxiety, and that individuals who engage in more PA are less likely to experience the negative effects of SM addiction.
The main objective of this study is to investigate the correlation between social media use, physical activity, and anxiety in young adults. It is hypothesized that: 1) excessive social media use will result in elevated anxiety scores; 2) individuals who engage in high physical activity will have lower anxiety scores; 3) physical activity will moderate the correlation between high social media use and anxiety, resulting in a) low or moderate anxiety scores when the individual engages in high levels of physical activity and b) moderate to high anxiety scores when the individual engages in low levels of physical activity; 4) individuals who engage in high levels of physical activity do not use social media excessively; and 5) excessive users of social media engage in low levels of physical activity. The study is particularly important because anxiety is increasing among young adults, a critical age for prevention and treatment. Some of our hypotheses have never been studied before. By understanding the relationship between the variables studied, we can suggest how to create a healthier society and help young adults become healthy adults.
2. Method
2.1. Participants
One hundred and eleven (111) participants were recruited from DEI University through a convenience sample. Recruitment was conducted through anonymous emails from the university registry, seeking 80-100 participants. In order to be able to participate, participants had to be aged between 18 and 39, be fluent in English and to own a smartphone.
2.2. Design
This study used a correlational design to examine the impact of social media use and physical activity on anxiety, and the moderating role of physical activity on the relationship between social media use and anxiety. The independent variables of the study included time spent on social media uses and intensity of physical activity, while the dependent variable was anxiety (low, moderate, and high).
2.3. Materials
Google Forms application was used to develop the online part of the study to present the questionnaires and collect participant data. Google Forms is an online form builder that allows users to create surveys and forms quickly and easily. With this free software, users are able to create, analyze, and manage surveys and questionnaires in their browser or on their mobile device. In order to conduct the survey, three (3) questionnaires were used – the Social Networking Time Use Scale (SONTUS) (Olufadi, 2016) for measuring the time spent on Social Media, the International Physical Activity Questionnaire (IPAQ) (IPAQ Group, 1998) for measuring the intensity of PA, and the Beck Anxiety Inventory (BAI) (Steer & Beck, 1997) for measuring the levels of Anxiety. Through these questionnaires, the data was collected and analyzed to produce results.
2.3.1. Social Networking Time Use Scale (SONTUS)
SONTUS is a self-report instrument developed to measure the time spent on social networking sites during five different subscale conditions: relaxation and free periods, academic-related periods, public-places-related use, stress-related periods, and motives for use. Participants are asked to indicate the frequency of their use on an 11-point scale, ranging from 1 (not applicable to me) to 11 (I have used it more than 3 times during the past week and spent at least 30 minutes each time). Furthermore, the instrument utilizes phrases to reflect the amount of time used, such as “when you are at home sitting idly” or “when you are in the class receiving lecture”.
All factors of the SONTUS construct have large and significant structural coefficients (> .82), indicating good construct validity. The coefficients for the five subscales ranged from 0.67 to 0.86, indicating acceptable to good internal consistency. The Cronbach’s alpha coefficient was used to assess the internal consistency of the SONTUS instrument. The results showed that the alpha coefficient for the total scale was .93, indicating excellent overall reliability of the five first-order factors in combination (Olufadi, 2016).
2.3.2. International Physical Activity Questionnaire (IPAQ)
The International Physical Activity Questionnaire (IPAQ) is a self-report instrument specifically designed to measure the intensity and duration of physical activity, as well as the amount of time spent sitting as part of daily life. It is suitable for people aged 15 years and over, and consists of seven items that ask participants to report how many minutes, hours and days they spend engaging in vigorous physical activities such as lifting, digging, aerobics, or bicycling, and how much time they spend sitting during a typical week. The questionnaire produces an estimation of total physical activity in MET-min/week (the ratio of working metabolic rate) and time spent sitting. Reliability analysis has shown good stability and high reliability with Cronbach’s alpha scores of less than .80. Test-retest reliability is also very good, with Spearman correlation coefficients clustered around 0.8 (Craig et al., 2003). In addition, the IPAQ-Gr has been shown to have acceptable validity properties in Greek young adults (Papapthanasiou et al., 2010).
2.3.3. Beck Anxiety Inventory (BAI)
The Beck Anxiety Inventory (BAI) is a widely-used self-report instrument designed to measure the severity levels of anxiety in both adolescents and adults. The participant is asked to rate their experience of 21 common anxiety symptoms that have occurred in the past week on a 4-point scale (not at all, mildly, moderately, severely). These symptoms are described in a straightforward and understandable manner, such as “feeling hot”, “hands trembling”, and “scared”. The BAI has been found to have a high internal consistency (Cronbach’s alpha of 0.94), as well as a strong reliability over an average period of 11 days (r = 0.67). Furthermore, a very strong convergent validity coefficient was established between the BAI and the Diary Anxiety Measure, with a correlation of 0.54 (Fydrich et al., 1992).The questionnaires used for the survey were available on the internet and could be used free of charge. The data were extracted in a comma separated values (csv) file. They were then cleaned and converted using Microsoft Excel software. Finally, the data was analysed with the free, open-source statistical software Jasp.
2.4. Procedure
This research was approved by the University of Sunderland. Invitations to participate in the study were sent between December 15, 2022 and January 15, 2023. The survey was open for participation between December 15, 2022 and February 20, 2023. To begin participation in the survey, participants read and agreed to the Participant Information Sheet, and pressed the “continue” button to proceed to the Participant Consent Form, where they confirmed that they met the requirements of the study. They confirmed that they were between 18 and 39 years old, had an English language certificate, understood the anonymity, voluntary nature and withdrawal option of the study. They also confirmed that they were able to contact the researcher, supervisor or the Chair of the University of Sunderland Research Ethics Group, Dr John Fulton, via the email address provided and that they agreed to participate in the study.
Once they consented, they were taken to the main part of the survey. This part included the three questionnaires analyzed in the material section that measured the level of anxiety, the time spent on social networking sites, and the intensity of physical activity. All questions were presented in a Likert-scale format for added simplicity. The first two questionnaires comprised all the questions in one page, and participants had to press a “next” button to move on to the following questionnaire. The last questionnaire was unique, in that some questions led to other questions depending on the participant’s answer. All questions were presented autonomously and had to be answered individually by pressing the “next” button. The order of the questions and the questionnaires was the same for all participants, and the survey took around fifteen to twenty minutes to complete.
All data collected were kept confidential and anonymous, and the option to save participants’ mails was deactivated in the Google Form settings. After extracting the data from Google Forms, all information was deleted by Google and will be stored on a password protected hard drive until the project is completed and graded. The data were then converted using Microsoft Excel software and analyzed using Jasp statistical software.
2.5. Ethics
This study was compliant with EU GDPR (2016). The survey had ensured the anonymity and confidentiality of participants throughout the online study process. Recruitment took place via anonymous emails. From the beginning to the end of the survey, no name, phone, email or other identity information was requested from the participants. After the data had been collected, all data was deleted from the servers on which the online study was conducted. The data was stored on a password protected hard drive where they will be kept until the project is graded, and then deleted. Before participating in the study, participants received an information sheet outlining the purpose of the study, the expected duration of the study and the procedures used. They were informed that they had the right to decline to participate in the study. If they agreed to participate, they were also informed that they could withdraw from the experiment at any time without giving a reason. Participants were informed that refusal or withdrawal from the study would not affect their academic grades or studies. It was made clear to participants that there was no way to delete their data after the completion of their participation as the database was completely anonymous and there was no way to trace their data. The personal contact details of the researcher and the supervisor were provided so that participants had the opportunity to get in touch. Participants were also informed that as the survey was concerned with anxiety symptoms and not clinical anxiety, the questionnaire did not provide a diagnosis of an anxiety disorder. Therefore, no feedback was provided after participation. Participants were given the contact details of a local mental health centre in case they felt distressed and wanted to ask for help.
3. Results
A total of 111 young adults participated in this study. There were no missing values but 9 outliers were found. Two participants were excluded according to the instructions of the IPAQ data processing protocol. Specifically, for the 2 participants, the total amount of time spent walking, moderately and vigorously was above the threshold of 16 hours given in the questionnaire, which assumes that a person sleeps 8 hours per day. In addition, 7 outliers were extracted because the time reported for physical activity and social media use exceeded the assumption that a person needs 8 hours per day to sleep, eat and take care of their personal hygiene.
The descriptive statistics for all the variables and the distribution of participants are shown in Table 1 and 2. In the sample, we observe that physical activity is inversely related to anxiety. That is, the highest anxiety is shown in the low physical activity group (M=18.762, SD= 13.511), dropping and reaching the lowest values in the high physical activity group (M=11.462, SD=11.659). On the contrary, anxiety is increasing as social media use is increasing. Specifically, we observe that anxiety has the lowest values when SM use is low (M=10.318, SD=10.572), rises and more than triples when social media use is high (M=32.600, SD=15.384).
We also see that of the 13 participants who engage in high levels of physical activity (12.7% of the sample), 8 (61.5%) make low use of SM, 4 (30.8%) make moderate use of SM and 1 (7.7%) makes high use of SM (Table 3). In the meanwhile of the 11 participants who make high use of Social Media (10.8% of the sample), 6 engage in low PA (54.5%), 4 engage in moderate PA (36.4%), and 1 engages in high PA (9.1%) (Table 4).
| Table 1. Descriptive statistics of Anxiety on Physical activity and Social media use levels | ||||||||
| Physical activity | Social media use | |||||||
| Low | Moderate | High | Low | Moderate | High | |||
| N* | 63 | 26 | 13 | 44 | 47 | 11 | ||
| Mean | 18.762 | 14.385 | 11.462 | 10.318 | 18.787 | 32.600 | ||
| SD | 13.511 | 14.106 | 11.659 | 10.572 | 11.823 | 15.384 | ||
| Min | 0.000 | 0.000 | 0.000 | 0.000 | 2.000 | 12.000 | ||
| Max | 49.000 | 55.000 | 40.000 | 40.000 | 46.000 | 55.000 | ||
| *N=number of participants | ||||||||
| Table 2. Mean, standard deviation and standard error of each variable | ||||||
| N | Mean | SD | SE | |||
| Anxiety | 102 | 16.716 | 13.602 | 1.347 | ||
| SM use | 102 | 10.137 | 3.478 | 0.344 | ||
| Table 3. Descriptive statistics of Physical activity levels on Social Media use levels | ||||||
| Social Media use levels | Total | |||||
| Low | Moderate | High | ||||
| Physical Activity levels | Low | Count | 27 | 30 | 6 | 63 |
| % within PAcat | 42.9% | 47.6% | 9.5% | 100.0% | ||
| Moderate | Count | 9 | 13 | 4 | 26 | |
| % within PAcat | 34.6% | 50.0% | 15.4% | 100.0% | ||
| High | Count | 8 | 4 | 1 | 13 | |
| % within PAcat | 61.5% | 30.8% | 7.7% | 100.0% | ||
| Total | Count | 44 | 47 | 11 | 102 | |
| % within PAcat | 43.1% | 46.1% | 10.8% | 100.0% | ||
| Table 4. Descriptive statistics of Social Media use levels on Physical activity levels | ||||||
| Physical Activity levels | Total | |||||
| Low | Moderate | High | ||||
| Social Media use levels | Low | Count | 27 | 9 | 8 | 44 |
| % within SMcat | 61.4% | 20.5% | 18.2% | 100.0% | ||
| Moderate | Count | 30 | 13 | 4 | 47 | |
| % within SMcat | 63.8% | 27.7% | 8.5% | 100.0% | ||
| High | Count | 6 | 4 | 1 | 11 | |
| % within SMcat | 54.5% | 36.4% | 9.1% | 100.0% | ||
| Total | Count | 63 | 26 | 13 | 102 | |
| % within SMcat | 61.8% | 25.5% | 12.7% | 100.0% | ||
The study assessed the moderating role of physical activity on the relationship between social media use and anxiety. A model 1 moderation analysis conducted using Hayes (2017) process macro, the model was statistically significant, explaining the .388 of anxiety (R2=.388, p<.05).
Differences in anxiety between moderate and low physical activity is significant (coeff=-6.771, p=.10). Individuals who engage in moderate physical activity, show low levels of anxiety. Differences in anxiety between high and low physical activity is also significant (coeff=-7.809, p=.26). Individuals who engage in high physical activity show even lower levels of anxiety than those who engage in moderate physical activity (table 5).
Interaction one, the interaction of moderate physical activity in the relationship between social media use and anxiety, is not significant suggesting that there is no interaction between anxiety moderate physical activity. However interaction two, the interaction of high physical activity in the relationship between social media use and anxiety, is significant. This means that the impact of social media use on anxiety is moderated by high physical activity (table 5).
| Table 5. Moderation of Physical Activity (PA) on the relationship between Social Media (SM) use and Anxiety | |||||||
| coefficients | p | LLCI | ULCI | ||||
| Social Media use | 2.202 | .000 | 1.455 | 2.950 | |||
| PA (Moderate) | -6.771 | .010 | -11.908 | -1.634 | |||
| PA (High) | -7.809 | .026 | -14.645 | -.973 | |||
| Interaction of moderate PA x SM use | .748 | .326 | -.757 | 2.253 | |||
| Interaction of high PA x SM use | -2.476 | .049 | -4.942 | -.010 | |||
Test of unconditional interaction shows that the change in R-Sq due to interaction (x*w), was not significant (R2-chng=.036, p=.064). The conditional effects show that for low physical activity, the effects of social media use on anxiety is significant (effect=2.202, p=.000). Also for moderate physical activity, the effects of social media use on anxiety is significant (effect=2.951, p=.000), but not for high physical activity (effect= -.274, p=.817) (table 6). The interaction of physical activity, social media use and anxiety is shown in Graph 1.
| Table 6. Conditional effects of the focal predictor at values of the moderator | ||||||
| Physical activity | Effect | p | LLCI | ULCI | ||
| Low | 2.202 | .000 | 1.455 | 2.950 | ||
| Moderate | 2.951 | .000 | 1.645 | 4.257 | ||
| High | -.274 | .817 | -2.624 | 2.076 | ||
Graph 1. The interaction of physical activity on the relationship between social media use and anxiety, in the moderation model.
* The dots and lines represent the participants and the regression line. The blue line shows the relationship between social media and anxiety in participants with low physical activity. Similarly, the red and green lines for participants with moderate and high physical activity.
4. Discussion
The aim of the present study was to examine the association between social media use, physical activity, and anxiety in young adults. Our results support the first hypothesis suggesting that excessive social media use leads to increased levels of anxiety. Although Grieve and colleagues (2013) suggest that SM may provide another social outlet with a variety of positive psychological effects, particularly for people who find it difficult to interact face-to-face, their study did not account for how much time is spent using SM. In addition, the researchers speculate that different motives for using social media could have an influence on the sense of social connectedness that individuals feel and that this could be reflected in the results of the factor analysis. Boursier and colleagues (2020) found in their study during the COVID -19 pandemic that overuse of SM was predicted by perceived feelings of loneliness. Furthermore, in line with our findings, excessive use of social media was found to increase anxiety levels.
Support for the positive effects of SM is also found in the study by Ellison and colleagues (2017). The researchers suggest that use of SM interacts with measures of psychological well-being and may provide greater benefits to individuals with low life satisfaction and self-esteem. However, the participants of the study reported spending a short amount of time on SM each day, specifically 10 to 30 minutes. In contrast to this study, Vannucci and colleagues (2017) found a significant association between SM usage time and anxiety symptoms in their study of young adults, indicating a probable anxiety disorder. They suggest that a more comprehensive clinical assessment should be undertaken when diagnosing anxiety, as social media use is widespread among young adults. A meta-analysis by Yan and colleagues (2017) showed a positive correlation between time spent using SM and Internet addiction and a negative correlation with self-esteem. The positive correlation between SM use and mental health, including anxiety, is also confirmed by Keles and colleagues (2020) in their systematic review that includes studies from almost every continent.
The second hypothesis, that individuals who engage in high physical activity have lower anxiety scores, is also confirmed. Our findings are consistent with previous studies, such as Rimmele and colleagues (2007), who found that anxiety scores following stressful situations were lower in individuals that have been working out than untrained individuals, suggesting that physically active individuals view acute psychosocial stress as less dangerous and more manageable than non-physically active individuals. Carter and colleagues (2021), in their systematic review and meta-analysis examining the effects of physical activity, found that high levels of physical activity reduced anxiety in young people compared with individuals who engaged in little or no physical activity. Coventry and colleagues (2021) reached the same conclusions in their systematic review and meta-analysis, finding that nature-based outdoor activities were effective in reducing anxiety during the pandemic COVID -19. The researchers recommend that there should be significant and long-lasting investment in community and place-based solutions such as nature-based interventions i.e. green exercise and group gardening. These interventions are expected to play a crucial role in addressing the increased demand for mental health support after the pandemic.
While most of the literature confirms that physical activity helps alleviate anxiety, Katula and colleagues (1999) discovered in their study of healthy older people that although anxiety scores decreased after mild physical activity, no significant changes in anxiety scores occurred after moderate physical activity. Interestingly, anxiety levels actually increased after intense physical activity. One possible explanation for the reported increase in anxiety scores among participants could be that it happens due to the increased arousal level caused by the maximal training task. This implies that although maximal intensity training may help reduce anxiety in older adults, who are relatively untrained, the effect may be masked by the increased arousal. Another factor to consider is the influence of the training environment on anxiety responses. Research shows that a socially enriched environment leads to more positive feelings such as increased arousal and a greater increase in self-efficacy than a socially uninteresting exercise environment (Turner et al. 1997). Finally, bias remains a concern in most research examining the effects of PA on anxiety outcomes, whether it involves adult or younger participants, clinical or nonclinical groups (Carter et al., 2021).
As already mentioned earlier there is no literature examining the moderating role of PA on the relationship between SM use and anxiety. Our third hypothesis examining this role was confirmed suggesting that physical activity can moderate the correlation between high social media use and anxiety. Specifically, individuals who engage in high levels of physical activity while using social media may have low or moderate anxiety scores. On the other hand, those who engage in low levels of physical activity while using social media may have moderate to high anxiety scores. Our results showed that the interaction of moderate physical activity in the relationship between social media use and anxiety is not significant. This was rather an expected result as according to the literature people tend to overstate PA, especially students using the IPAQ (Folk & Kovacs, 2021). This is the reason why we chose not to include such a hypothesis.
Our results confirm and extend previous findings on related topics, such as the study by Foroughi and colleagues (2021), who examined the moderating role of high PA on the association between Instagram addiction (other SM were not included in the study) and social anxiety, in a sample of 364 university students. Their study showed that PA can moderate the association between social and entertainment needs and Instagram addiction. For example, they found that individuals with high levels of PA were less likely to develop Instagram addiction because they could satisfy their social and entertainment needs through alternative means. Conversely, individuals with lower PA levels may be more prone to Instagram addiction because they rely heavily on the platform to meet these needs. Similarly, Cao and colleagues (2011), found that anxiety scores increased with increasing screen time when PA was low, while Zink and colleagues (2020) in their systematic review found that vigorous physical activity helped mitigate the association between sedentary screen behavior and anxiety.
As mentioned earlier, FoMO acts as a mediator between anxiety and excessive social media use (Elhai et al., 2020). According to Przybylski and colleagues (2013), people experience FoMO because of their psychological deficits in relationship and competence needs. As a result, SM has been suggested as an effective means to fulfill the desire to stay connected with others and improve social skills. In their study, Dadiotis and Roussos (2022), examined how exercise might act as a buffer in the link between FoMO and mental health. They conducted moderation analysis and found that exercise had a negative moderating effect on the association between FoMO and anxiety. The study suggests that more hours of physical activity may predict lower levels of FoMO. It is possible that exercise has a moderating effect because it increases BDNF levels, which could help alleviate anxiety symptoms, according to the findings of Asmundson and colleagues (2013).
The fourth and fifth hypotheses of our study are also novel to literature. They assume an inverse relationship between physical activity and social media use. Our study supports these hypotheses, showing that individuals who engage in high levels of physical activity do not tend to overuse social media, whereas those who overuse social media tend to be less physically active. Specifically, only a small minority (7.7%) of participants who reported high levels of physical activity also reported excessive use of social media. On the other hand, the majority (54.5%) of participants who reported excessive social media use reported low levels of physical activity.
This inverse relationship is also shown in previous research, but not directly, as we did not find a study that examined the relationship of the exact same variables of SM use and PA. Booker and colleagues (2015) found in their study of 4899 adolescents on social media, game use, and sports that those who played more sports spent less time on SM and game consoles. A cross-sectional study conducted in Norway aimed to determine the association between screen time and moderate-intensity physical activity among children and adolescents aged 9 to 15 years. The study analyzed self-reported data from 3,920 participants and found a negative association between total screen time and physical activity. The study found that when screen time increased by one hour per day, moderate-intensity physical activity decreased by an average of 2 minutes per day. This highlights the negative correlation between screen time and physical activity in children and adolescents (Hansen et al., 2019). Chen and colleagues (2022) also concluded that increased screen time often leads to sedentary behavior and lower physical activity, while lower physical activity is promoted by more screen time.
In contrast, a cross-sectional study of 187 middle and high school students conducted in Hong Kong found that increased use of messengers, social media and multimedia was positively correlated with moderate-intensity physical activity among male students. The study examined the relationship between the amount of time they were exposed to each media on smartphones and the amount of time they spent on moderate-intensity physical activity, and found that as the amount of time they spent on messengers and social media increased, the amount of time they spent on moderate-intensity physical activity also increased (Lee et al., 2021). As it is quite difficult to interpret the contradictory results of this particular study against the background of the literature, some of the limitations of this study should be mentioned, such as the fact that the study included only a small number of participants and that the average SM use for all age groups was only 24 minutes per day. The researchers suggest that people who were more physically active may also have spent more time using social networking and instant messaging applications to share their information and photos. In addition, some people may have used multimedia applications while engaging in PA, for example, watching a video while jogging on a treadmill.
4.1. Implications of the study for a social policy promoting youth welfare
Based on the results of our study, it is recommended to encourage young adults to be physically active to prevent and reduce anxiety. The study shows that vigorous physical activity can reduce the likelihood of suffering from anxiety compared to physically inactive individuals. Therefore, it is important to promote physical activity in young adults to prevent and treat mental illness, especially anxiety. In addition, the study highlights the negative effects of excessive social media use on anxiety levels. Therefore, it is recommended that young adults should be educated about the possible negative effects of excessive social media use on their mental health. They should be encouraged to limit their use of social media and engage in physical activity instead. In addition, the study suggests that physical activity can moderate the association between high social media use and anxiety. Therefore, it is recommended to encourage young adults to be physically active while using social media to reduce their anxiety. Overall, this study provides valuable insights into the complex relationship between social media use, physical activity and anxiety in young adults and highlights the importance of promoting physical activity as a means of reducing anxiety.
4.2. Limitations and Future research
Although our research work contributed in a substantial and novel way to understanding the relationship between SM use, PA and anxiety levels, we acknowledge some limitations in our study. Because the study sample was divided into subcategories, the high categories consisted of few participants. Due to their combination, the subcategories were small in terms of the number of participants. To improve the accuracy of the study, future research should target a much larger sample. In this way, the resulting categories will have more participants, making the study more robust and reliable.
A second limitation of our study might be that participating students subjectively measured their time spent on social media and their involvement in physical activities and sports. This may have led them to overestimate their physical activity and sports participation due to a desire for social approval or underestimate their time spent using social media due to a tendency toward social desirability. According to Fokl and Kovacs (2021), people, especially students, who use the IPAQ questionnaire have been shown to tend to overestimate their physical activity. It is possible that some of the associations examined in this study could be influenced by this tendency. To address the issue of participants’ over reporting of physical activity, it would be more advisable for future studies to use accelerometers to record participants’ daily activity.
Studies have shown that self-assessment of cell phone use in terms of hours is often overestimated, while the number of calls and text messages is underestimated. According to Montag and colleagues (2015), dependence on cell phones may be linked to real actions rather than information provided by individuals themselves like self report data. Therefore, it would be better to use reliable software to closely monitor participants’ social media activities. This approach would minimize participants’ self-report of physical activity and social media use and allow them to focus only on reporting their anxiety levels. This would not only facilitate participation but also increase the accuracy of the results.
The pandemic COVID -19 has a profound impact on the psychology of people worldwide and is therefore an important parameter to consider. Schafer and colleagues (2022), note that COVID -19 emerged in 2019 and has claimed over 2.5 million lives worldwide. Their research found that individuals of different age groups, medical backgrounds, races, and regions exhibited significantly more psychopathological symptoms during the COVID -19 pandemic. Wang et al (2022) reported that SARS-CoV-2 infection was self-reported by participants in several follow-up questionnaires. COVID-19 related symptoms and impairment of daily living were self-reported one year after baseline. Because of the impact of the pandemic, it is likely that the anxiety level of participants in our study is elevated, but future studies may be less affected by the pandemic because more time will pass since the virus outbreak.
Future studies should include not only young adults and college students, but also adolescents who own smartphones and are very active on social media. Youth participation will expand the sample and increase the value of the results for their future use. Also, this age group is considered particularly vulnerable to mobile phone addiction, and their inclusion is essential for understanding the effects of social media use on physical activity levels. In addition, studies should examine both passive and active social media use. Passive use includes activities such as scrolling through a newsfeed, whereas active use includes activities such as posting, commenting, and sending messages. Understanding the differences between these two types of use can provide valuable insights into the impact of social media on physical activity. Another important factor to consider is the gender of the participants. Different genders have different patterns of social media use and physical activity, so studies should ensure a balanced representation of both genders to avoid biased results.
In summary, future studies should expand the sample of participants, examine both passive and active use of social media, consider the gender of participants, consider the impact of the COVID -19 pandemic, and use more accurate measurement methods. By considering these factors, future studies may provide valuable insight into the complex relationship between anxiety, social media use, and physical activity.
4.2.Conclusion
The present study examined the relationship between social media use, physical activity and anxiety in young adults. The results support the hypothesis that excessive social media use leads to increased levels of anxiety and that individuals who engage in high physical activity have lower anxiety scores. In addition, the study found that physical activity can moderate the association between high social media use and anxiety. Specifically, individuals who engage in high levels of physical activity while using social media have low or moderate anxiety scores, while individuals who engage in low levels of physical activity while using social media have moderate to high anxiety scores. The study also supports the hypothesis that there is an inverse relationship between physical activity and social media use. Individuals who engage in high levels of physical activity tend not to overuse social media, while those who overuse social media tend to be less physically active. These findings are consistent with previous studies and provide valuable insight into the complex relationship between social media use, physical activity and anxiety in young adults.
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