Relationships Between Social Media Addiction, Fear of Missing Out Developments and Body Image

Relationships Between Social Media Addiction, Fear of Missing Out Developments and Body Image | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationships Between Social Media Addiction, Fear of Missing Out Developments and Body Image Sinem TOÇOĞLU, Ahmet DÖNMEZ, Cengiz BAYKARA, Sezgin HEPSERT, Murat SARIKABAK, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4383457/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim The research aimed to reveal the existence of relationships between social media addiction, fear of missing out developments, and body image in student athletes. Method A total of 313 student athletes, 133 females and 180 males, enrolled in the sports sciences faculties undergraduate programs of three different state universities, participated in the research in which the relational screening model was adopted. The data was obtained by using the "Personal Information Form", "Social Media Addiction Scale", "Fear of Missing Out in Social Environments Scale" and "Body Appreciation Scale". Data were analyzed by using Pearson correlation and Regression analyses. Findings : The results obtained in the study showed a negative relationship between social media addiction and body image (p < .05); There is a positive relationship between social media addiction and fear of missing out (p < .05); It was determined that there were negative (p < .05) significant relationships between fear of missing out and body image perception. Moreover, it has been revealed that social media addiction negatively predicted body image (p < .05); fear of missing out positively predicted social media addiction (p < .05); the fear of missing out predicted body image negatively (p < .05). Conclusion As a result, it may be possible to state that addiction to social media in student athletes negatively affects their body image, and having the fear of missing out leads to social media addiction and lowers their body image. Introduction Thanks to the rapid and extraordinary changes in today's technology, individuals' access to the internet has increased and their access to the internet has become inevitable [ 1 ]. As of October 2023, there are 5.3 billion internet users worldwide, corresponding to 65.7 percent of the world's population. Of this total, 4.95 billion, that is, 61.4 percent of the world's population, are social media users [ 2 ]. According to TSI (Turkish Statistical Institute) data, it has been observed that 87.1% of individuals used the internet regularly in 2023. Most of the time spent on the internet is spent on social media applications. The most used social media and messaging applications by individuals in Turkey are WhatsApp with 84.9%, YouTube with 69.0% and Instagram with 61.4% [ 3 ]. Previous studies have documented a variety of positive outcomes associated with the use of social media platforms, including improved communication efficiency, self-promotion opportunities, entertainment, and a sense of belonging [ 4 , 5 , 6 ]. However, excessive use of technology leads to a wide range of negative consequences such as sleep disorders, anxiety, depression, hopelessness, unhappiness and decreased social functionality, life satisfaction and productivity, among other factors, and for some individuals, the use of social media sites has turned into an addiction. According to recent data, more than 210 million people worldwide meet the criteria for social media addiction [ 7 , 8 , 9 ]. Social media addiction is defined as directing vital activities through the social media applications used and using these applications in a way that excessively challenges "real life", relationships with other people, and performance [ 10 ]. Some of the social media users are starting to spend more and more time and energy on social media to achieve the feelings and mood they experienced when they started using it [ 11 ]. Studies have found that as the time spent on social media increases, the likelihood of addiction increases [ 12 , 1 ]. However, as social media platforms have become commonplace and inevitable in our daily lives, it is becoming increasingly difficult for many people to know whether they are addicted to social media [ 13 ]. Social media companies tailor content to users using adaptive algorithms and specifically design themselves to make users more addicted [ 14 ]. Developing dependency can increase anxiety about social exclusion when people experience anxiety about relationships [ 15 ]. This is because humans are social creatures with an innate need for psychosocial connection [ 16 ]. In the absence of social relationships, individuals may experience maladaptive emotions due to concerns that others are having pleasurable experiences [ 17 ]. Przybylski et al., [ 18 ] examined the fear of missing out (FoMO) in the field of social media and defined it as "a widespread concern that others may be having rewarding experiences that someone else is not". Social media is reported to be an ideal tool to alleviate this anxiety because this fear is characterized by the desire to constantly stay in touch with what others are doing [ 19 ]. There are many studies on FoMO and social media use, social media addiction, and problematic smartphone use [ 20 , 21 , 15 , 22 ]. The studies are generally based on self-determination theory, self-construal theory and social comparison theories [ 16 , 23 , 17 ]. Brailovskaia & Margraf [ 24 ] also examined FoMO and addictive social media use and found that there was a positive relationship between them. When an individual disconnects from the virtual world, he or she worries about missing potentially important information. The absence of this information can lead to feelings of anxiety, distress and anger. Experiencing significant levels of Fear of Missing Out (FoMO) can lead to maladaptive coping mechanisms that can have negative effects on an individual's mental and physical well-being. One of these strategies is excessive use of social media. In the short term, excessive use of social media can alleviate negative emotions associated with Fear of Missing Out (FoMO) and promote good emotions. However, over time, these positive experiences can foster the formation of a strong emotional bond with social media, which is closely linked to an intense drive to constantly stay connected online [ 25 , 24 ]. Body image, a variable affected by social media, refers to the individual's personal evaluation of his or her physical attractiveness [ 26 ]. Body image is related to a person's perceptions, feelings and thoughts about their body, and the scope of this phenomenon may vary depending on the person's unique body size, shape and appearance, as well as the level of exposure to standards of physical attractiveness in the society in which he or she lives [ 27 , 28 ]. Social media platforms allow users to share photos and videos and like and comment on others' posts. Unlike traditional media, users can share instantly and sincerely on social media, that is, in real time. In addition, users can apply filters to their photos to make their images better and ideal. Thus, users can share photos by creating the image they desire to be. Many variables related to social media have been examined within the scope of body image research. For example, people are exposed to unreal body images of each other on social media and may become unhappy with their own bodies by comparing their physical appearance with others. It has been a variable of interest for body image studies because these unique types of social comparison can be much more harmful than traditional media [29, 30, 31, 32). Another variable frequently encountered in studies on body image in the literature is internalization, which is defined as individuals taking external cues about appearance ideals and adapting them to their own internal views [ 33 , 34 , 30 ]. In previous studies, it is seen that the sample group consists mostly of adolescents and young females [ 35 , 29 , 33 , 34 ]. It is noteworthy that the studies conducted with student athletes are quite limited. It can be said that individuals who do sports have higher body image satisfaction than those who do not do sports, but this satisfaction may vary depending on gender, sports branch and sport level [ 36 ]. For example, in a study conducted through semi-structured interviews with female hockey athletes, it was reported that their body image was positive in the sports environment due to the athletic structure of their bodies, but their social body image perception was negative because they could not meet the attractiveness standards expected from the female body in the social environment [ 37 ]. In the literature review, the existence of research on social media addiction [ 38 , 39 , 40 , 41 , 42 ], fear of missing out [ 43 , 44 , 24 ] and body image [ 45 , 46 , 47 ] is evident in different disciplines. However, the limited number of studies conducted on athletes on these subjects has revealed the need for current research. As a matter of fact, conducting research on individuals who struggle at every stage of life and continue their sports and student life can not only enrich the literature, but also serve as a resource for scientists who want to conduct research in this field. In this context, the aim of the research to fill the gap in the literature and add richness is to reveal whether there is a relationship between social media addiction, fear of missing out and body image in athletes. Method Research Model The research was conducted using the " relational survey model ", one of the quantitative research models, in terms of its purpose and scope. Relational screening model is defined as a scientific approach that " aims to reveal the relationship or effect between two different quantitative variables " [ 48 ]. The relationships between social media addiction, fear of missing out and body image in athletes were examined relationally within the scope of this research. Research Group A total of 313 student athletes, 133 females and 180 males, enrolled in the sports sciences faculties undergraduate programs of three different state universities, participated in the research. The convenience sampling method was used to determine the sample group in the research. The mentioned sampling method is expressed as "the shortest way to obtain data quickly and cheaply" [ 49 ]. The average age of the students is 19.76 ± 1.57; The average year of sports experience was calculated as 7.86 ± 3.35. Descriptive statistics results for the sample are given in Table 1 . Table 1 Descriptive statistics of the participants Gender n % Female 133 42,5 Male 180 57,5 University n % A University 96 30,7 B University 171 54,6 C University 46 14,7 Total 313 100,0 According to Table 1 , 42.5% of the participants in the study were females (n = 133); 57.5% (n = 180) were males. When the distribution in terms of university is examined, 30.7% are at A-University (n = 96), 54.6% are at B-University (n = 171), and 14.7% are at C-University (n = 46). Sample Size In this research, where the relationships between social media addiction, fear of missing out and body image were tried to be revealed, the number of samples was decided by applying power analysis. When calculating the effect size, the required minimum sample size was calculated with the effect sizes recommended by Cohen [ 50 ]. As a result of A Priori power analysis, the required sample size was determined to be 295 people in total. However, in the research, 313 people were reached in case of waste data. When calculating the sample size, Correlation: Bivariate normal model, p H1 = 0.19, α err prob = 0.05, Power (1-β err prob) = 0.95, p H0 = 0, Tail(s) = one. A Priori power analysis applied when calculating the sample size was done with the G*Power 3.1.9.7 (Franz Faul, Unversitat Kiel, Germany) program [ 51 ]. Data Collection Tools "Personal Information Form", "Social Media Addiction Scale", "Fear of Missing Out in Social Environments Scale", and "Body Appreciation Scale" were used as data collection tools in the research. Detailed information about the structures of measurement tools is given below. Personal Information Form In the personal information form prepared for the student athletes included in the sample, gender, age, sports year and university information where they were enrolled in the undergraduate program were included. Social Media Addiction Scale In order to measure the social media addiction of the participants, the social media addiction scale developed by Günüç [ 52 ] and revised by Çömlekçi and Başol [ 53 ] was used. The measurement tool is a seven-item, five-point Likert type. Scoring in the measurement tool in question is 1 = Never; 2 = Rarely; 3 = Sometimes; 4 = Often; 5 = Always. It has been stated that as the score from the scale increases, social media addiction increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .85 [ 53 ]. As a result of the research, the calculated results regarding the measurement tool are presented in Table 2 . Table 2 Results of the social media addiction scale Number of Emoticons Skewness Kurtosis Croncbach α ± SD Social Media Addiction 7 ,889 ,161 ,833 12,69±4,78 As a result of the analysis in Table 2 , the skewness and kurtosis values of the social media addiction scale vary between − 1.…..+1 and are in accordance with the normal distribution [ 54 ]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .833, and this result is quite reliable according to Karagöz [ 49 ]. When looking at the average score of the measurement tool, it was determined that the average score was 12,69±4,78. Fear of Missing Out in Social Environments Scale In order to measure the participants' fear of missing out, the fear of missing out scale in social environments developed by Gökler, Aydın, Ünal and Metintaş [ 55 ] was used. The measurement tool is a 10-item five-point Likert type. Scoring in the measurement tool in question is made as follows: 1 = Not at all true, 2 = Not true, 3 = Undecided, 4 = True, 5 = Extremely true. It has been stated that as the score obtained from the scale increases, the fear of missing out on developments in social environments increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .81 [ 55 ]. As a result of the research, the calculated results regarding the measurement tool are presented in Table 3 . Table 3 Results of the fear of missing out on developments in social environments scale Number of Emoticons Skewness Kurtosis Croncbach α ± SD FoMOSES 10 -,003 -,107 ,767 25,77±6,58 As a result of the analysis in Table 2 , the skewness and kurtosis values of the fear of missing out scale in social environments vary between − 1.…..+1 and are in accordance with the normal distribution [ 54 ]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .767, and this result is quite reliable according to Karagöz [ 49 ]. When looking at the average score of the measurement tool, it was determined that the average score was 25,77±6,58. Body Appreciation Scale To measure the participants' body images, the body appreciation scale, developed by Tylka and Wood-Barcalow [ 56 ] and adapted into Turkish by Anlı, Akın, Eker and Özçelik [ 57 ], was used. The measurement tool is a 10-item five-point Likert type. Scoring in the measurement tool in question is made as follows: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Always. It has been stated that as the score obtained from the scale increases, body image increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .88 [ 57 ]. As a result of the research, the calculated results regarding the measurement tool are presented in Table 4 . Table 4 Results of the body appreciation scale Number of Emoticons Skewness Kurtosis Croncbach α ± SD Body Appreciation Scale 10 -,749 ,073 ,922 37,93±6,11 As a result of the analysis in Table 4 , the skewness and kurtosis values of the body appreciation scale vary between − 1.…..+1 and are in accordance with the normal distribution [ 54 ]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .922, and this result is quite reliable according to Karagöz [ 49 ]. When looking at the average score of the measurement tool, it was determined that the average score was 37,93±6,11. Data Collection Written permission was obtained from the ethics committee of a state university (E-26428519-044-65445) to collect data. After obtaining permission, the measurement tools determined according to the characteristics to be measured in the research were transferred to the online environment with the help of Google Forms. At the beginning of the form, written explanations about the purpose of the research and its importance were included. A voluntary participation confirmation button has been added to the end of the written explanations. Data were collected from student athletes who read the explanations and approved the voluntary participation confirmation button. During data collection, although there was no attempt to interfere with the student athletes' lessons, a relevant faculty member was present in the classroom environment. Research data was collected in November and December of the 2023–2024 academic fall semester. Data Analysis First of all, the data collected electronically was checked. Following the checks, the data were numerically coded and transferred to the SPSS program. Before deciding on the analyzes to be applied, descriptive statistics, reliability and normality analyzes were performed. The results obtained showed that the measurement tools had reliable values and were suitable for normal distribution [ 54 ]. Following the results, Pearson correlation and regression analyzes were applied to the data. Results Table 5 Relationship results between variables Social Media Addiction Fear of Missing Out Social Media Addiction r --- p Fear of Missing Out r ,218 ** --- p ,000 Body Image r -,265 ** -,124 * p ,000 ,028 When the results of the "Pearson correlation" analysis in Table 5 were examined, it was found that there were low-level positive relationships between social media addiction and fear of missing out (r=,218; p = 000), and low-level negative relationships with body image (r=-,124; p = 028). Table 6 Regression analysis results for predicting social media addiction Model B Std. Error β t p Stable 8,608 1,070 --- 8,047 ,000 Fear of Missing Out ,158 ,040 ,218 3,935 ,000 Dependent variable = Social Media Addiction; R= ,22; R 2 adj = ,04; F (1,311) = 15,487; p= ,000; Method: Enter As a result of the simple linear regression analysis conducted on the prediction of social media addiction in Table 6 , it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that the fear of missing out (β = .218; t = 3.935; p = .000) had a significant positive predictive power on social media addiction. It can be said that 4% of the variance regarding social media addiction is explained by the fear of missing out. Table 7 Regression analysis results regarding the prediction of body image by social media addiction Model B Std. Error β t p Stable 42,231 ,947 --- 44,612 ,000 Social Media Addiction -,338 ,070 -,265 -4,844 ,000 Dependent variable = Body Image; R= ,27; R 2 adj = ,07; F (1,311) = 23,468; p= ,000; Method: Enter As a result of the simple linear regression analysis performed on the prediction of body image in Table 7 , it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that social media addiction (β=-.265; t=-4.844; p = .000) had a significant positive predictive power on body image. It can be said that 7% of the variance related to body image is explained by social media addiction. Table 8 Regression analysis results regarding the prediction of body image by fear of missing out Model B Std. Error β t p Stable 40,908 1,389 --- 29,453 ,000 Fear of Missing Out -,115 ,052 -,124 -2,206 ,028 Dependent variable = Body Image; R= ,12; R 2 adj = ,02; F (1,311) = 4,866; p= ,028; Method: Enter As a result of the simple linear regression analysis performed on the prediction of body image in Table 8 , it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that the fear of missing out (β=-.124; t=-2.206; p = .028) had a significant positive predictive power on body image. It can be said that 2% of the variance regarding body image is explained by the fear of missing out. Discussion and Conclusion Recent technological developments have caused an increase in the time individuals spend on social media through different online applications. As a result, testing the relationships between social media addiction, fear of missing out and body image in student athletes arouses curiosity in researchers. For this reason, an attempt was made to reveal the predictive effects of these parameters, as well as their relationships with each other, within the scope of the current research. When the findings were examined, it was determined that there was a positive relationship between fear of missing out (Fomo) and social media addiction. Does Fomo predict social media addiction? Or can the opposite be said? In fact, there is a great contradiction in analyzing this issue in the literature. Despite the considerable number of studies emphasizing that the predictive parameter is social media addiction [ 58 , 59 , 60 ], there are also studies advocating the opposite [ 61 , 62 , 63 ]. In this research, the relevant problem situation was examined with the athlete sample group, which is stated to be a predictor of Fomo and has been examined in a limited number [ 64 ]. Rewarding experiences have a desirable quality for the individual [ 65 ]. Meeting these desires by the social environment may cause the individual to feel anxious and uneasy [ 66 ]. In the literature, this situation is expressed as the Fomo phenomenon [ 67 ]. In order to improve the mood and get rid of mental depression, knowing what people are busy with and wanting to be informed about the activities of others by staying constantly connected and updated can create a feeling of safe haven [ 68 ]. However, the current scenario has a tendency to addiction, and the time an individual spends on social media turns into a positive interaction with Fomo [ 69 ]. The addiction tendency in athletes is not much different from sedentary individuals. The series, which differs only for branding purposes, eliminates the difference between athlete and sedentary in terms of addiction for relaxation, distraction and social connection purposes [ 70 ]. In general, in this research, the fact that Fomo predicts social media use in athletes with a positive relationship is parallel to the literature information. It was determined that there was a negative relationship between social media addiction and body image among the participants. The use of social media undoubtedly attracts the attention of researchers with its dark reflections as well as its bright side [ 71 ]. In particular, the fact that these reflections increase psychological stress factors in people and cause permanent deterioration makes the issue more specific [ 72 ]. Although it is stated in the literature that social media use does not affect body image perception [ 73 ], it is emphasized that increasing social media addiction leads to a decrease in people's body image perception, with a negative relationship, especially according to the results of research conducted in recent years [ 39 , 74 , 75 ]. It is possible to consider the effect of related addiction on body image from different perspectives. Examples of these perspectives include people taking different views and lives as criteria through the use of social media [ 76 ], as well as having an unhealthy body image perception [ 77 ] as a result of negative self-evaluation through intense cognitive internalization [ 78 ]. It is understood that the result of the current research is generally compatible with the literature information. It was determined that there was a negative relationship between Fomo and body image perception in the participants. There are studies in the literature where Fomo's relationship with negative self-perception and body image is emphasized [ 79 , 80 ] and also examined in terms of personality, motivational, emotional and behavioral aspects [ 81 , 82 ]. However, in the conducted studies, the sample group generally consists of sedentary individuals of different ages. In studies where participants are athletes and body image is examined, the relationship between physical activity should also be taken into consideration. Likewise, it is known that physical activity has a positive relationship with body image, regardless of male or female [ 83 , 84 ]. In this regard, especially athletes' exercise participation for the purpose of losing weight, increasing muscle tone and increasing their attractiveness provides health benefits, but a negative aspect of this is that the increase in the desire to be liked in the individual triggers the formation of psychologically negative emotions [ 85 ]. The individual, whose body image perception decreases, turns to Fomo-related social media addiction in order not to miss the social environment or global interests and to suppress the physical anxiety at his core. This situation triggers side effects that negatively affect the individual's sports and routine quality of life, such as irregular sleep, excessive food consumption, and lack of focus [ 86 ]. In this study, it was determined that the negative relationship between Fomo and body image perception works in line with literature information and that increasing Fomo score negatively predicts body image perception. As a result, it has been determined that social media addiction predicts body image negatively in athletes, Fomo predicts social media addiction positively, and Fomo predicts body image negatively. Thanks to the rapid and extraordinary changes in today's technology, the sources of access to the internet have increased and it has become inevitable for individuals to meet with the internet. With the increase in the time spent on social media, it becomes easier to increase the likelihood of addiction. According to current data, it is known that more than 210 million people worldwide meet the criteria for social media addiction. In this context, it is important to investigate the parameters underlying social media addiction, especially on a limited sample group of athletes. In this study, addiction was tried to be analyzed with a detailed approach by using concepts in the psychology literature such as fear of missing developments (Fomo) and body image. Based on the findings, it was determined that social media addiction predicts body image negatively, fomo predicts social media addiction positively, and fomo predicts body image negatively in athletes. As a result, it can be stated that low body image perception leads the individual to social media addiction, individuals with fomo tend to compensate for the related deficiency on social media, and low body image perception leads the individual to social media addiction. This type of research will help to determine the psychopathological factors underlying addiction as a result of psychometric measurements in today's world where individuals are in close relationship with technology. The findings obtained undoubtedly have the potential to be published in the scientific literature to serve public health. Declarations Authors’ contributions Research Design ST, AD; Statistical analysis AD, CB; Preparation of the article, ST, AD, CB, SH; Data Collection was carried out by MS, YY, AK, Critical reading MS, AD Funding The study has no external fundings. Availability of data and materials The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate All procedures performed in this study involving human participants were in accordance with the ethical standards of the Department of Psychology, the University of Hong Kong, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Sakarya University of Applied Sciences Social and Human Sciences Ethics Committee (number: E.65445, Date: 03/11/2022). Informed consent form was obtained from all participating in the study. Consent for publication Not Applicable. Competing interests The authors declare no competing interests. Corresponding author: Ahmet DÖNMEZ, [email protected] References Güney M, Taştepe T. Social media usage and social media addiction in adolescents. Journal of Ankara Health Sciences (JAHS), 2020; 9(2), 183-190. https://doi.org/10.46971/ausbid.757713. Statista. Number of internet and social media users worldwide as of July 2022. https://www.statista.com/statistics/617136/digital-population-worldwide/, 2022. Turkish Statistical Institute [TSI], 2023 https://www.tse.org.tr/ A.D. 29.08.2023 Bayer J, Ellison N, Schoenebeck S, Brady E, Falk EB. Facebook in context(s): Measuring emotional responses across time and space. New Media & Society, 2018; 20(3), 1047–1067. https://doi.org/10.1177/1461444816681522 Hosen M, Ogbeibu S, Giridharan B, Cham TH, Lim WM, Paul J. Individual motivation and social media influence on student knowledge sharing and learning performance: Evidence from an emerging economy. Computers & Education, 2021; 172, 104262. https://doi.org/10.1016/j.compedu.2021.104262 Verduyn P, Ybarra O, Résibois M, Jonides J, Kross E. Do social network sites enhance or undermine subjective well‐being? A critical review. Social Issues and Policy Review, 2017; 11(1), 274–302. https://doi.org/10.1111/sipr.12033 Arora S, Mehta M. Love it or hate it, but can you ignore social media? - A bibliometric analysis of social media addiction. Computers in Human Behavior, 2023; 147. https://doi.org/10.1016/j.chb.2023.107831 Liao CP, Sher CY, Liu YH. Progress and future directions for research on social media addiction: Visualization-based bibliometric analysis. Telematics and Informatics, 2023; 80. https://doi.org/10.1016/j.tele.2023.101968 Miranda S, Trigo I, Rodrigues R, Duarte M. Addiction to social networking sites: Motivations, flow, and sense of belonging at the root of addiction. Technological Forecasting and Social Change, 2023; 188. https://doi.org/10.1016/j.techfore.2022.122280 Hou Y, Xiong D, Jiang T, Song L, Wang Q. Social media addiction: Its impact, mediation, and intervention. Cyberpsychology, 2019; 13(1). https://doi.org/10.5817/CP2019-1-4 Kuss DJ. Griffiths MD. Social networking sites and addiction: Ten lessons learned. In International Journal of Environmental Research and Public Health 2017; (Vol. 14, Issue 3). MDPI. https://doi.org/10.3390/ijerph14030311 Brailovskaia J, Schillack H, Margraf J. Facebook addiction disorder in Germany. Cyberpsychology, Behavior, and Social Networking, 2018; 21(7), 450–456. https://doi.org/10.1089/cyber.2018.0140 Andreassen C, Pallesen S. Social Network Site Addiction - An Overview. Current Pharmaceutical Design, 2014; 20(25), 4053–4061. https://doi.org/10.2174/13816128113199990616 Bhargava VR, Velasquez M. Ethics of the attention economy: The problem of social media addiction. Business Ethics Quarterly, 2021; 31(3), 321–359. https://doi.org/10.1017/beq.2020.32 Blackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences, 2017; 116, 69–72. https://doi.org/10.1016/j.paid.2017.04.039 Ryan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 2000; 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68 Wu-Ouyang B. Are smartphones addictive? Examining the cognitive-behavior model of motivation, leisure boredom, extended self, and fear of missing out on possible smartphone addiction. Telematics and Informatics, 2022; 71. https://doi.org/10.1016/j.tele.2022.101834 Przybylski AK, Murayama K, Dehaan CR, Gladwell V. Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 2013; 29(4), 1841–1848. https://doi.org/10.1016/j.chb.2013.02.014 Casale S, Rugai L, Fioravanti G. Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addictive Behaviors, 2018; 85, 83–87. https://doi.org/10.1016/j.addbeh.2018.05.020 Servidio R, Sinatra M, Griffiths MD, Monacis L. Social comparison orientation and fear of missing out as mediators between self-concept clarity and problematic smartphone use. Addictive Behaviors, 2021; 122, 107014. https://doi.org/10.1016/j.addbeh.2021.107014 Reer F, Tang WY, Quandt T. Psychosocial well-being and social media engagement: The mediating roles of social comparison orientation and fear of missing out. New Media & Society, 2019; 21(7), 1486–1505. https://doi.org/10.1177/1461444818823719 Balta S, Emirtekin E, Kircaburun K, Griffiths MD. Neuroticism, trait fear of missing out, and phubbing: The mediating role of state fear of missing out and problematic ınstagram use. International Journal of Mental Health and Addiction, 2020; 18(3), 628–639. https://doi.org/10.1007/s11469-018-9959-8 Tandon A, Dhir A, Almugren I, AlNemer GN, Mäntymäki M. Fear of missing out (FoMO) among social media users: a systematic literature review, synthesis and framework for future research. Internet Research, 2021; 31(3), 782–821. https://doi.org/10.1108/INTR-11-2019-0455 Brailovskaia J, Margraf J. From fear of missing out (FoMO) to addictive social media use: The role of social media flow and mindfulness. Computers in Human Behavior, 2024; 150, 107984. Brailovskaia J, Margraf J. Less sense of control, more anxiety, and addictive social media use: cohort trends in German university freshmen between 2019 and 2021. Current Research in Behavioral Sciences, 2023; 4, 100088. Thompson JK, Heinberg LJ, Altabe M, Tantleff-Dunn S. Exacting beauty: Theory, assessment, and treatment of body image disturbance. American Psychological Association. 1999; https://doi.org/10.1037/10312-000 Forbes GB, Jung J, Vaamonde JD, Omar A, Paris L, Formiga NS. Body Dissatisfaction and Disordered Eating in Three Cultures: Argentina, Brazil, and the U.S. Sex Roles, 2012; 66(9–10), 677–694. https://doi.org/10.1007/s11199-011-0105-3 Grogan S. Body image and health: Contemporary perspectives. In Journal of Health Psychology 2006; (Vol. 11, Issue 4, pp. 523–530). https://doi.org/10.1177/1359105306065013 Hogue JV, Mills JS. The effects of active social media engagement with peers on body image in young women. Body Image, 2019; 28, 1–5. https://doi.org/10.1016/j.bodyim.2018.11.002 Saiphoo AN, Vahedi Z. A meta-analytic review of the relationship between social media use and body image disturbance. In Computers in Human Behavior, 2019; (Vol. 101, pp. 259–275). https://doi.org/10.1016/j.chb.2019.07.028 Simon PD, Cu SMO, De Jesus KEM, Go NTS, Lim KTF, Say CLC. Worried about being imperfect? The mediating effect of physical appearance perfectionism between Instagram addiction and body esteem. Personality and Individual Differences, 2022; 186. https://doi.org/10.1016/j.paid.2021.111346 Tiggemann M, Slater A. NetGirls: The internet, facebook, and body image concern in adolescent girls. International Journal of Eating Disorders, 2013; 46(6), 630–633. https://doi.org/10.1002/eat.22141 Jung J, Barron D, Lee YA, Swami V. Social media usage and body image: Examining the mediating roles of internalization of appearance ideals and social comparisons in young women. Computers in Human Behavior, 2022; 135. https://doi.org/10.1016/j.chb.2022.107357 Roberts SR, Maheux AJ, Hunt RA, Ladd BA, Choukas-Bradley S. Incorporating social media and muscular ideal internalization into the tripartite influence model of body image: Towards a modern understanding of adolescent girls’ body dissatisfaction. Body Image, 2022; 41, 239–247. https://doi.org/10.1016/j.bodyim.2022.03.002 Choukas-Bradley S, Nesi J, Widman L, Higgins MK. Camera-ready: Young women’s appearance-related social media consciousness. Psychology of Popular Media Culture, 2019; 8(4), 473–481. https://doi.org/10.1037/ppm0000196 Burgon RH, Beard J, Waller G. Body image concerns across different sports and sporting levels: A systematic review and meta-analysis. In Body Image 2023; (Vol. 46, pp. 9–31). https://doi.org/10.1016/j.bodyim.2023.04.007 Russell KM. On versus off the pitch: The transiency of body satisfaction among female rugby players, cricketers, and netballers. Sex Roles, 2004; 51, 561-574. Nikolinakou A, Phua J, Kwon ES. What drives addiction on social media sites? The relationships between psychological well-being states, social media addiction, brand addiction and impulse buying on social media. Computers in Human Behavior, 2024; 153, 108086. Sarman A, Çiftci N. Relationship between social media addiction and appearance-related social media consciousness in Turkish adolescents. Journal of Pediatric Nursing, 2024; 76, 99-105. Yue H, Yue X, Zhang X, Liu B, Bao H. Exploring the relationship between social exclusion and social media addiction: The mediating roles of anger and impulsivity. Acta Psychologica, 2023; 238, 103980. Khan NA, Khan AN, Moin MF. Self-regulation and social media addiction: A multi-wave data analysis in China. Technology in Society, 2021; 64, 101527. Çimke S, Cerit E. Social media addiction, cyberbullying and cyber victimization of university students. Archives of psychiatric nursing, 2021; 35(5), 499-503. Balcerowska JM, Brailovskaia J. Psychopathological Symptoms and Social Networking Sites Addiction in Poland and Germany: The Role of Fear of Missing Out and Preference for Online Social Interaction. Computers in Human Behavior, 2024; 108240. Tuna R, Alan H, Saritas M, Bacaksiz FE. Touch-operated world of teenagers in the distance education process: A cross-sectional study on nomophobia, netlessphobia and fear of missing out in nursing students. Nurse Education in Practice, 2023; 71, 103728. Behrend N, Webb JB, Warschburger P. Explaining the prospective paths from body appreciation to intuitive eating facets: Does body image flexibility serve as a mediator?. Body Image, 2024; 49, 101710. Rodgers RF, Hewett RC, Nowicki GP. A sociocultural model of the relationships between social media use and body image in midlife women. Eating Behaviors, 2024; 101867. Craddock N, Budhraja M, Garbett KM, Nasution K, Gentili C, Rizkiah C, Haime Z, Saraswati LA, Medise BE, White P, Diedrichs PC, Williamson, H. Evaluating a school-based body image lesson in Indonesia: A randomised controlled trial. Body Image, 2024; 48, 101654. Franekel RJ, Wallen EN, Hyun HH. How to design and evaluate research in education. (Eighth Edition). New York: McGraw-Hill, 2012. Karagöz Y. SPSS ve AMOS uygulamalı nitel-nicel-karma bilimsel araştırma yöntemleri ve yayın etiği (1. Baskı). İstanbul: Nobel Kitabevi, 2017. Cohen J. Methods in psychology. A power primer. Psychological Bulletin, 1992; 112(1), 155-159. Gignac GE, Szodorai ET. Effect Size guidelines for individual differences researchers. Personality and Individual Differences, 2016; 102, 74–78. Günüç S. İnternet bağımlılık ölçeğinin geliştirilmesi ve bazı demografik değişkenler ile internet bağımlılığı arasındaki ilişkilerin incelenmesi. (Yüksek Lisans Tezi). Yüzüncü Yıl Üniversitesi, Sosyal Bilimler Enstitüsü, Van, 2009. Çömlekçi MF, Başol O. Gençlerin sosyal medya kullanım amaçları ile sosyal medya bağımlılığı ilişkisinin incelenmesi. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 2019; 17(4), 173-188. George D, Mallery P. IBM SPSS statistics 26 step by step: A simple guide and reference. (Sixteenth edition). Routledge, New York, NY 10017, 2019. Gökler ME, Aydın R, Ünal E, Metintaş S. Sosyal ortamlarda gelişmeleri kaçırma korkusu ölçeğinin Türkçe sürümünün geçerlilik ve güvenilirliğinin değerlendirilmesi. Anadolu Psikiyatri Dergisi, 2016; 17(1), 52-59. Tylka TL, Wood-Barcalow NL. The body appreciation scale-2: Item refinement and psychometric evaluation. Body Image, 2015; 12(1), 53-67. Anlı G, Akın A, Eker H, Özçelik B. Bedeni beğenme ölçeği: geçerlik ve güvenirlik çalışması. The Journal of Academic Social Science Studies, 2015; 36, 505-511. Echeburua E, De Corral P. Addictionto new technologies andto online social networking in young people: A new challenge. Adicciones, 2010; 22, 91-95. Erdoğan P, Şanlı Y. Gelişmeleri kaçırma korkusunun sosyal medya tutumları üzerine etkisi. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi, 2019; 22 (2), 615-627. Karadağ A, Akçinar B. Üniversite öğrencilerinde sosyal medya bağımlılığı ve psikolojik semptomlar arasındaki ilişki. Bağımlılık Dergisi. 2019; 20(3):154-166. Oberst U, Wegmann E, Stodt B, Brand M, Chamarro A. Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out. Journal of adolescence, 2017; 55, 51-60. https://doi.org/10.1016/j.adolescence.2016.12.008 Fioravanti G, Casale S, Benucci SB, Prostamo A, Falone A, Ricca V, Rotella F. Fear of missing out and social networking sites use and abuse: A meta-analysis. Computers in Human Behavior, 2021; 122, 106839. https://doi.org/10.1016/j.chb.2021.106839 Zhang Y, Li S, Yu G. The relationship between social media use and fear of missing out: A meta-analysis. Acta Psychologica Sinica, 2021; 53(3), 273. https://doi.org/10.3724/SP.J.1041.2021.00273 Stoyel H, Shanmuganathan-Felton V, Meyer C, Serpell L. Psychological risk indicators of disordered eating in athletes. PloS one, 2020; 15(5), e0232979. Doi:10.1371/journal.pone.0232979 Vargas T, Maloney J, Gupta T, Damme KS, Kelley NJ, Mittal VA. Measuring facets of reward sensitivity, inhibition, and impulse control in individuals with problematic Internet use. Psychiatry research, 2019; 275, 351-358. Akat M, Arslan C, Hamarta E. Dark triad personality and phubbing: The mediator role of fomo. Psychological Reports, 2023; 126(4), 1803-1821. Doi:10.1177/00332941221109119 Tandon A, Dhir A, Talwar S, Kaur P, Mäntymäki M. Social media induced fear of missing out (FoMO) and phubbing: Behavioural, relational and psychological outcomes. Technological Forecasting and Social Change, 2022; 174, 121149. Doi: 10.1016/j.techfore.2021.121149 Beyens I, Frison E, Eggermont S. “I don’t want to miss a thing”: Adolescents’ fear of missing out and its relationship to adolescents’ social needs, Facebook use, and Facebook related stress. Computers in human behavior, 2016; 64, 1-8. Doi: 10.1016/j.chb.2016.05.083 Brailovskaia J, Schillack H, Margraf J. Tell me why are you using social media (SM)! Relationship between reasons for use of SM, SM flow, daily stress, depression, anxiety, and addictive SM use–An exploratory investigation of young adults in Germany. Computers in Human Behavior, 2020; 113, 106511. Doi: 10.1016/j.chb.2020.106511 Hayes M. Social media usage among elite athletes: An exploration of athlete usage during major events. PhD diss., Griffith University, Australia. 2019. Bevan JL, Gomez R, Sparks L. Disclosures about important life events on Facebook: Relationships with stress and quality of life. Computers in Human Behavior, 2014; 39, 246-253. Chen W, Lee KH. Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychology, behavior, and social networking, 2013; 16(10), 728-734. Özbey H, Gültekin M. Lise öğrencilerinde beden algısı ve benlik saygısı arasındaki ilişkinin medya ve farklı değişkenler açısından incelenmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, (2021; 23(2), 429-441. https://doi.org/10.32709/akusosbil.746383 Tayhan F. Üniversite öğrencilerinde sosyal medya bağımlılığı, beden algısı, vücut kompozisyonu ve yeme bozuklukları arasındaki ilişkinin incelenmesi. Karya Journal of Health Science, 2023; 4(2), 139-145. Özgür M, Uçar A. Üniversitede eğitim gören kız öğrencilerde sosyal medya bağımlılığı ve beden algısı ile beslenme bilgi düzeylerinin karşılaştırılması. Ankara Sağlık Bilimleri Dergisi, 2020; 9(2), 46-54. Fox J, Moreland JJ. The dark side of social networking sites: An exploration of the relational and psychological stressors associated with Facebook use and affordances. Computers in human behavior, 2015; 45, 168-176. Yang H, Wang JJ, Tng GY, Yang S. Effects of social media and smartphone use on body esteem in female adolescents: Testing a cognitive and affective model. Children, 2020; 7(9), 148. Jarman HK, Marques MD, McLean SA, Slater A, Paxton SJ. Social media, body satisfaction and well-being among adolescents: A mediation model of appearance-ideal internalization and comparison. Body Image, 2021; 36, 139-148. https://doi.org/10.1016/j.bodyim.2020.11.005 Barry CT, Wong MY. Fear of missing out (FoMO): A generational phenomenon or an individual difference?. Journal of Social and Personal Relationships, 2020; 37(12), 2952-2966. Doi:10.1177/0265407520945394. Burnell K, George MJ, Vollet JW, Ehrenreich SE, Underwood MK. Passive social networking site use and well-being: The mediating roles of social comparison and the fear of missing out.Cyberpsychol J Psychosoc Res Cybersp 2019, 13 http://dx. doi.org/10.5817/cp2019-3-5 Hamutoglu NB, Topal M, Gezgin DM. Investigating Direct and Indirect Effects of Social Media Addiction, Social Media Usage and Personality Traits on FOMO. International Journal of Progressive Education, 2020; 16(2), 248-261. Doi:10.29329/ijpe.2020.241.17 Elhai JD, Levine JC, Alghraibeh AM, Alafnan AA, Aldraiweesh AA, Hall BJ. Fear of missing out: Testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Computers in Human Behavior, 2018; 89, 289-298. Doi:10.1016/j.chb.2018.08.020 Bassett-Gunter R, McEwan D, Kamarhie A. Physical activity and body image among men and boys: A meta-analysis. Body image, 2017; 22, 114-128. Fallon EA, Hausenblas HA. Media images of the “ideal” female body: Can acute exercise moderate their psychological impact?. Body İmage, 2005; 2(1), 62-73. Tylka TL, Homan KJ. Exercise motives and positive body image in physically active college women and men: Exploring an expanded acceptance model of intuitive eating. Body İmage, 2015; 15, 90-97. Mccoy M. 3 steps for gettin grid of FOMO. https://carlytheprepster. com/2016/07/3-steps-for-getting-rid-of-fomo.html, 2016. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4383457","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308461785,"identity":"6fcb3ef1-559d-41a5-81b0-2c34a64dec2c","order_by":0,"name":"Sinem TOÇOĞLU","email":"","orcid":"","institution":"Dokuz Eylül University","correspondingAuthor":false,"prefix":"","firstName":"Sinem","middleName":"","lastName":"TOÇOĞLU","suffix":""},{"id":308461786,"identity":"9e75872c-7855-4292-9d23-c9186164b595","order_by":1,"name":"Ahmet DÖNMEZ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYDACCRBR8Z+xgQHCkANRBx4Q0nLgDDNUyxlmY7CWBEJaDrZBtTC2MSeCGfi08M/uTnz8gY1Ntl+6O/HhDza29Plhhx8CbbGT023AYcmds5sNDvDwGM+cA2RI8PDkbrydZgDUkmxsdgCHNTdyt0kckJBI3ABiGEhI5G6cnQDSciBxGw4t8jdyt/84YGAA0rL9R4KBQbrh7PQPeLUYAA0HBlAC2BYQI0FeOge/LYY3cjdLnDlwwHjmjNzNkg0HDhhukM4pOJBggNsvcjdyN36o/HdAth/oi48//x2Ql5+dvvnDhwo7OZzex3QqWKUBscpBQL6BFNWjYBSMglEwEgAAbz5uVo9qqJgAAAAASUVORK5CYII=","orcid":"","institution":"Alanya Alaaddin Keykubat University","correspondingAuthor":true,"prefix":"","firstName":"Ahmet","middleName":"","lastName":"DÖNMEZ","suffix":""},{"id":308461787,"identity":"d2229c17-39db-475f-9d7a-4fac2403d81b","order_by":2,"name":"Cengiz BAYKARA","email":"","orcid":"","institution":"Ministry of National Education","correspondingAuthor":false,"prefix":"","firstName":"Cengiz","middleName":"","lastName":"BAYKARA","suffix":""},{"id":308461788,"identity":"40722fe1-eefc-4a79-a01e-de2b35726f29","order_by":3,"name":"Sezgin HEPSERT","email":"","orcid":"","institution":"Fırat University","correspondingAuthor":false,"prefix":"","firstName":"Sezgin","middleName":"","lastName":"HEPSERT","suffix":""},{"id":308461789,"identity":"eede799c-393c-4005-8e74-eef0e221d115","order_by":4,"name":"Murat SARIKABAK","email":"","orcid":"","institution":"Bartin University","correspondingAuthor":false,"prefix":"","firstName":"Murat","middleName":"","lastName":"SARIKABAK","suffix":""},{"id":308461790,"identity":"bbab67c8-c4cb-430b-bd47-bdb009daab08","order_by":5,"name":"Yavuz YILDIRIM","email":"","orcid":"","institution":"Sakarya University of Applied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yavuz","middleName":"","lastName":"YILDIRIM","suffix":""},{"id":308461791,"identity":"43403aa6-5036-42cf-8972-e028ee9177df","order_by":6,"name":"Abdulmenaf KORKUTATA","email":"","orcid":"","institution":"Çanakkale Onsekiz Mart University","correspondingAuthor":false,"prefix":"","firstName":"Abdulmenaf","middleName":"","lastName":"KORKUTATA","suffix":""}],"badges":[],"createdAt":"2024-05-07 13:49:43","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4383457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4383457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":67085650,"identity":"b37dc489-a4cd-4525-b64d-ae46d5a444d3","added_by":"auto","created_at":"2024-10-21 05:56:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":633203,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4383457/v1/ccfcf013-96b6-4739-a87c-9a029dd02443.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eRelationships Between Social Media Addiction, Fear of Missing Out Developments and Body Image\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThanks to the rapid and extraordinary changes in today's technology, individuals' access to the internet has increased and their access to the internet has become inevitable [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As of October 2023, there are 5.3\u0026nbsp;billion internet users worldwide, corresponding to 65.7 percent of the world's population. Of this total, 4.95\u0026nbsp;billion, that is, 61.4 percent of the world's population, are social media users [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. According to TSI (Turkish Statistical Institute) data, it has been observed that 87.1% of individuals used the internet regularly in 2023. Most of the time spent on the internet is spent on social media applications. The most used social media and messaging applications by individuals in Turkey are WhatsApp with 84.9%, YouTube with 69.0% and Instagram with 61.4% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have documented a variety of positive outcomes associated with the use of social media platforms, including improved communication efficiency, self-promotion opportunities, entertainment, and a sense of belonging [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, excessive use of technology leads to a wide range of negative consequences such as sleep disorders, anxiety, depression, hopelessness, unhappiness and decreased social functionality, life satisfaction and productivity, among other factors, and for some individuals, the use of social media sites has turned into an addiction. According to recent data, more than 210\u0026nbsp;million people worldwide meet the criteria for social media addiction [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSocial media addiction is defined as directing vital activities through the social media applications used and using these applications in a way that excessively challenges \"real life\", relationships with other people, and performance [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Some of the social media users are starting to spend more and more time and energy on social media to achieve the feelings and mood they experienced when they started using it [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Studies have found that as the time spent on social media increases, the likelihood of addiction increases [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, as social media platforms have become commonplace and inevitable in our daily lives, it is becoming increasingly difficult for many people to know whether they are addicted to social media [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Social media companies tailor content to users using adaptive algorithms and specifically design themselves to make users more addicted [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDeveloping dependency can increase anxiety about social exclusion when people experience anxiety about relationships [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This is because humans are social creatures with an innate need for psychosocial connection [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In the absence of social relationships, individuals may experience maladaptive emotions due to concerns that others are having pleasurable experiences [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Przybylski et al., [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] examined the fear of missing out (FoMO) in the field of social media and defined it as \"a widespread concern that others may be having rewarding experiences that someone else is not\". Social media is reported to be an ideal tool to alleviate this anxiety because this fear is characterized by the desire to constantly stay in touch with what others are doing [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. There are many studies on FoMO and social media use, social media addiction, and problematic smartphone use [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The studies are generally based on self-determination theory, self-construal theory and social comparison theories [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Brailovskaia \u0026amp; Margraf [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] also examined FoMO and addictive social media use and found that there was a positive relationship between them. When an individual disconnects from the virtual world, he or she worries about missing potentially important information. The absence of this information can lead to feelings of anxiety, distress and anger. Experiencing significant levels of Fear of Missing Out (FoMO) can lead to maladaptive coping mechanisms that can have negative effects on an individual's mental and physical well-being. One of these strategies is excessive use of social media. In the short term, excessive use of social media can alleviate negative emotions associated with Fear of Missing Out (FoMO) and promote good emotions. However, over time, these positive experiences can foster the formation of a strong emotional bond with social media, which is closely linked to an intense drive to constantly stay connected online [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBody image, a variable affected by social media, refers to the individual's personal evaluation of his or her physical attractiveness [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Body image is related to a person's perceptions, feelings and thoughts about their body, and the scope of this phenomenon may vary depending on the person's unique body size, shape and appearance, as well as the level of exposure to standards of physical attractiveness in the society in which he or she lives [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Social media platforms allow users to share photos and videos and like and comment on others' posts. Unlike traditional media, users can share instantly and sincerely on social media, that is, in real time. In addition, users can apply filters to their photos to make their images better and ideal. Thus, users can share photos by creating the image they desire to be. Many variables related to social media have been examined within the scope of body image research. For example, people are exposed to unreal body images of each other on social media and may become unhappy with their own bodies by comparing their physical appearance with others. It has been a variable of interest for body image studies because these unique types of social comparison can be much more harmful than traditional media [29, 30, 31, 32). Another variable frequently encountered in studies on body image in the literature is internalization, which is defined as individuals taking external cues about appearance ideals and adapting them to their own internal views [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In previous studies, it is seen that the sample group consists mostly of adolescents and young females [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. It is noteworthy that the studies conducted with student athletes are quite limited. It can be said that individuals who do sports have higher body image satisfaction than those who do not do sports, but this satisfaction may vary depending on gender, sports branch and sport level [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. For example, in a study conducted through semi-structured interviews with female hockey athletes, it was reported that their body image was positive in the sports environment due to the athletic structure of their bodies, but their social body image perception was negative because they could not meet the attractiveness standards expected from the female body in the social environment [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the literature review, the existence of research on social media addiction [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], fear of missing out [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and body image [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] is evident in different disciplines. However, the limited number of studies conducted on athletes on these subjects has revealed the need for current research. As a matter of fact, conducting research on individuals who struggle at every stage of life and continue their sports and student life can not only enrich the literature, but also serve as a resource for scientists who want to conduct research in this field. In this context, the aim of the research to fill the gap in the literature and add richness is to reveal whether there is a relationship between social media addiction, fear of missing out and body image in athletes.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch Model\u003c/h2\u003e \u003cp\u003eThe research was conducted using the \"\u003cem\u003erelational survey model\u003c/em\u003e\", one of the quantitative research models, in terms of its purpose and scope. Relational screening model is defined as a scientific approach that \"\u003cem\u003eaims to reveal the relationship or effect between two different quantitative variables\u003c/em\u003e\" [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The relationships between social media addiction, fear of missing out and body image in athletes were examined relationally within the scope of this research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eResearch Group\u003c/h2\u003e \u003cp\u003eA total of 313 student athletes, 133 females and 180 males, enrolled in the sports sciences faculties undergraduate programs of three different state universities, participated in the research. The convenience sampling method was used to determine the sample group in the research. The mentioned sampling method is expressed as \u003cem\u003e\"the shortest way to obtain data quickly and cheaply\"\u003c/em\u003e [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The average age of the students is 19.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.57; The average year of sports experience was calculated as 7.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35. Descriptive statistics results for the sample are given in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42,5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57,5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUniversity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e313\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e100,0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 42.5% of the participants in the study were females (n\u0026thinsp;=\u0026thinsp;133); 57.5% (n\u0026thinsp;=\u0026thinsp;180) were males. When the distribution in terms of university is examined, 30.7% are at A-University (n\u0026thinsp;=\u0026thinsp;96), 54.6% are at B-University (n\u0026thinsp;=\u0026thinsp;171), and 14.7% are at C-University (n\u0026thinsp;=\u0026thinsp;46).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSample Size\u003c/h2\u003e \u003cp\u003eIn this research, where the relationships between social media addiction, fear of missing out and body image were tried to be revealed, the number of samples was decided by applying power analysis. When calculating the effect size, the required minimum sample size was calculated with the effect sizes recommended by Cohen [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. As a result of A Priori power analysis, the required sample size was determined to be 295 people in total. However, in the research, 313 people were reached in case of waste data. When calculating the sample size, Correlation: Bivariate normal model, p H1\u0026thinsp;=\u0026thinsp;0.19, α err prob\u0026thinsp;=\u0026thinsp;0.05, Power (1-β err prob)\u0026thinsp;=\u0026thinsp;0.95, p H0\u0026thinsp;=\u0026thinsp;0, Tail(s)\u0026thinsp;=\u0026thinsp;one. A Priori power analysis applied when calculating the sample size was done with the G*Power 3.1.9.7 (Franz Faul, Unversitat Kiel, Germany) program [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Collection Tools\u003c/h2\u003e \u003cp\u003e\"Personal Information Form\", \"Social Media Addiction Scale\", \"Fear of Missing Out in Social Environments Scale\", and \"Body Appreciation Scale\" were used as data collection tools in the research. Detailed information about the structures of measurement tools is given below.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePersonal Information Form\u003c/h2\u003e \u003cp\u003eIn the personal information form prepared for the student athletes included in the sample, gender, age, sports year and university information where they were enrolled in the undergraduate program were included.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSocial Media Addiction Scale\u003c/h2\u003e \u003cp\u003eIn order to measure the social media addiction of the participants, the social media addiction scale developed by G\u0026uuml;n\u0026uuml;\u0026ccedil; [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] and revised by \u0026Ccedil;\u0026ouml;mlek\u0026ccedil;i and Başol [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] was used. The measurement tool is a seven-item, five-point Likert type. Scoring in the measurement tool in question is 1\u0026thinsp;=\u0026thinsp;Never; 2\u0026thinsp;=\u0026thinsp;Rarely; 3\u0026thinsp;=\u0026thinsp;Sometimes; 4\u0026thinsp;=\u0026thinsp;Often; 5\u0026thinsp;=\u0026thinsp;Always. It has been stated that as the score from the scale increases, social media addiction increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .85 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. As a result of the research, the calculated results regarding the measurement tool are presented in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the social media addiction scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Emoticons\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCroncbach α\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Media Addiction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12,69\u0026plusmn;4,78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs a result of the analysis in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the skewness and kurtosis values of the social media addiction scale vary between \u0026minus;\u0026thinsp;1.\u0026hellip;..+1 and are in accordance with the normal distribution [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .833, and this result is quite reliable according to Karag\u0026ouml;z [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. When looking at the average score of the measurement tool, it was determined that the average score was 12,69\u0026plusmn;4,78.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eFear of Missing Out in Social Environments Scale\u003c/h2\u003e \u003cp\u003eIn order to measure the participants' fear of missing out, the fear of missing out scale in social environments developed by G\u0026ouml;kler, Aydın, \u0026Uuml;nal and Metintaş [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] was used. The measurement tool is a 10-item five-point Likert type. Scoring in the measurement tool in question is made as follows: 1\u0026thinsp;=\u0026thinsp;Not at all true, 2\u0026thinsp;=\u0026thinsp;Not true, 3\u0026thinsp;=\u0026thinsp;Undecided, 4\u0026thinsp;=\u0026thinsp;True, 5\u0026thinsp;=\u0026thinsp;Extremely true. It has been stated that as the score obtained from the scale increases, the fear of missing out on developments in social environments increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .81 [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. As a result of the research, the calculated results regarding the measurement tool are presented in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the fear of missing out on developments in social environments scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Emoticons\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCroncbach α\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFoMOSES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25,77\u0026plusmn;6,58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs a result of the analysis in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the skewness and kurtosis values of the fear of missing out scale in social environments vary between \u0026minus;\u0026thinsp;1.\u0026hellip;..+1 and are in accordance with the normal distribution [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .767, and this result is quite reliable according to Karag\u0026ouml;z [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. When looking at the average score of the measurement tool, it was determined that the average score was 25,77\u0026plusmn;6,58.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eBody Appreciation Scale\u003c/h2\u003e \u003cp\u003eTo measure the participants' body images, the body appreciation scale, developed by Tylka and Wood-Barcalow [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and adapted into Turkish by Anlı, Akın, Eker and \u0026Ouml;z\u0026ccedil;elik [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], was used. The measurement tool is a 10-item five-point Likert type. Scoring in the measurement tool in question is made as follows: 1\u0026thinsp;=\u0026thinsp;Never, 2\u0026thinsp;=\u0026thinsp;Rarely, 3\u0026thinsp;=\u0026thinsp;Sometimes, 4\u0026thinsp;=\u0026thinsp;Often, 5\u0026thinsp;=\u0026thinsp;Always. It has been stated that as the score obtained from the scale increases, body image increases. There are no reverse scored items from the measurement tool. Cronbach's Alpha reliability coefficient for the scale was found to be .88 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. As a result of the research, the calculated results regarding the measurement tool are presented in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of the body appreciation scale\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Emoticons\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCroncbach α\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody Appreciation Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e,922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37,93\u0026plusmn;6,11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs a result of the analysis in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the skewness and kurtosis values of the body appreciation scale vary between \u0026minus;\u0026thinsp;1.\u0026hellip;..+1 and are in accordance with the normal distribution [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]; Additionally, it can be said that the Cronbach's Alpha coefficient for the scale is .922, and this result is quite reliable according to Karag\u0026ouml;z [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. When looking at the average score of the measurement tool, it was determined that the average score was 37,93\u0026plusmn;6,11.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eWritten permission was obtained from the ethics committee of a state university (E-26428519-044-65445) to collect data. After obtaining permission, the measurement tools determined according to the characteristics to be measured in the research were transferred to the online environment with the help of Google Forms. At the beginning of the form, written explanations about the purpose of the research and its importance were included. A voluntary participation confirmation button has been added to the end of the written explanations. Data were collected from student athletes who read the explanations and approved the voluntary participation confirmation button. During data collection, although there was no attempt to interfere with the student athletes' lessons, a relevant faculty member was present in the classroom environment. Research data was collected in November and December of the 2023\u0026ndash;2024 academic fall semester.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eFirst of all, the data collected electronically was checked. Following the checks, the data were numerically coded and transferred to the SPSS program. Before deciding on the analyzes to be applied, descriptive statistics, reliability and normality analyzes were performed. The results obtained showed that the measurement tools had reliable values and were suitable for normal distribution [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Following the results, Pearson correlation and regression analyzes were applied to the data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship results between variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSocial Media Addiction\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFear of Missing Out\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSocial Media Addiction\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFear of Missing Out\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,218\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBody Image\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-,265\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,124\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,028\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eWhen the results of the \u003cem\u003e\"Pearson correlation\"\u003c/em\u003e analysis in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e were examined, it was found that there were low-level positive relationships between social media addiction and fear of missing out (r=,218; p = 000), and low-level negative relationships with body image (r=-,124; p = 028).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis results for predicting social media addiction\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,608\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,070\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,047\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFear of Missing Out\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e,158\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,040\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e,218\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,935\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDependent variable = Social Media Addiction; R= ,22; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e= ,04; F\u003csub\u003e(1,311)\u003c/sub\u003e = 15,487; p= ,000; Method: Enter\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eAs a result of the simple linear regression analysis conducted on the prediction of social media addiction in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that the fear of missing out (β = .218; t = 3.935; p = .000) had a significant positive predictive power on social media addiction. It can be said that 4% of the variance regarding social media addiction is explained by the fear of missing out.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis results regarding the prediction of body image by social media addiction\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42,231\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,947\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44,612\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial Media Addiction\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-,338\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,070\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,265\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4,844\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDependent variable = Body Image; R= ,27; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e= ,07; F\u003csub\u003e(1,311)\u003c/sub\u003e = 23,468; p= ,000; Method: Enter\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eAs a result of the simple linear regression analysis performed on the prediction of body image in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that social media addiction (β=-.265; t=-4.844; p = .000) had a significant positive predictive power on body image. It can be said that 7% of the variance related to body image is explained by social media addiction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression analysis results regarding the prediction of body image by fear of missing out\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40,908\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,389\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29,453\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,000\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFear of Missing Out\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-,115\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e,052\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-,124\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2,206\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e,028\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDependent variable = Body Image; R= ,12; R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e= ,02; F\u003csub\u003e(1,311)\u003c/sub\u003e = 4,866; p= ,028; Method: Enter\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eAs a result of the simple linear regression analysis performed on the prediction of body image in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, it is seen that the regression model is statistically significant. When the t-test results regarding the significance of the regression coefficients were examined, it was determined that the fear of missing out (β=-.124; t=-2.206; p = .028) had a significant positive predictive power on body image. It can be said that 2% of the variance regarding body image is explained by the fear of missing out.\u003c/p\u003e "},{"header":"Discussion and Conclusion","content":"\u003cp\u003eRecent technological developments have caused an increase in the time individuals spend on social media through different online applications. As a result, testing the relationships between social media addiction, fear of missing out and body image in student athletes arouses curiosity in researchers. For this reason, an attempt was made to reveal the predictive effects of these parameters, as well as their relationships with each other, within the scope of the current research.\u003c/p\u003e\u003cp\u003eWhen the findings were examined, it was determined that there was a positive relationship between fear of missing out (Fomo) and social media addiction. Does Fomo predict social media addiction? Or can the opposite be said? In fact, there is a great contradiction in analyzing this issue in the literature. Despite the considerable number of studies emphasizing that the predictive parameter is social media addiction [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], there are also studies advocating the opposite [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. In this research, the relevant problem situation was examined with the athlete sample group, which is stated to be a predictor of Fomo and has been examined in a limited number [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Rewarding experiences have a desirable quality for the individual [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Meeting these desires by the social environment may cause the individual to feel anxious and uneasy [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. In the literature, this situation is expressed as the Fomo phenomenon [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. In order to improve the mood and get rid of mental depression, knowing what people are busy with and wanting to be informed about the activities of others by staying constantly connected and updated can create a feeling of safe haven [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. However, the current scenario has a tendency to addiction, and the time an individual spends on social media turns into a positive interaction with Fomo [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The addiction tendency in athletes is not much different from sedentary individuals. The series, which differs only for branding purposes, eliminates the difference between athlete and sedentary in terms of addiction for relaxation, distraction and social connection purposes [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. In general, in this research, the fact that Fomo predicts social media use in athletes with a positive relationship is parallel to the literature information.\u003c/p\u003e\u003cp\u003eIt was determined that there was a negative relationship between social media addiction and body image among the participants. The use of social media undoubtedly attracts the attention of researchers with its dark reflections as well as its bright side [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. In particular, the fact that these reflections increase psychological stress factors in people and cause permanent deterioration makes the issue more specific [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Although it is stated in the literature that social media use does not affect body image perception [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], it is emphasized that increasing social media addiction leads to a decrease in people's body image perception, with a negative relationship, especially according to the results of research conducted in recent years [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. It is possible to consider the effect of related addiction on body image from different perspectives. Examples of these perspectives include people taking different views and lives as criteria through the use of social media [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e], as well as having an unhealthy body image perception [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] as a result of negative self-evaluation through intense cognitive internalization [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. It is understood that the result of the current research is generally compatible with the literature information.\u003c/p\u003e\u003cp\u003eIt was determined that there was a negative relationship between Fomo and body image perception in the participants. There are studies in the literature where Fomo's relationship with negative self-perception and body image is emphasized [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] and also examined in terms of personality, motivational, emotional and behavioral aspects [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. However, in the conducted studies, the sample group generally consists of sedentary individuals of different ages. In studies where participants are athletes and body image is examined, the relationship between physical activity should also be taken into consideration. Likewise, it is known that physical activity has a positive relationship with body image, regardless of male or female [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. In this regard, especially athletes' exercise participation for the purpose of losing weight, increasing muscle tone and increasing their attractiveness provides health benefits, but a negative aspect of this is that the increase in the desire to be liked in the individual triggers the formation of psychologically negative emotions [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The individual, whose body image perception decreases, turns to Fomo-related social media addiction in order not to miss the social environment or global interests and to suppress the physical anxiety at his core. This situation triggers side effects that negatively affect the individual's sports and routine quality of life, such as irregular sleep, excessive food consumption, and lack of focus [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. In this study, it was determined that the negative relationship between Fomo and body image perception works in line with literature information and that increasing Fomo score negatively predicts body image perception. As a result, it has been determined that social media addiction predicts body image negatively in athletes, Fomo predicts social media addiction positively, and Fomo predicts body image negatively.\u003c/p\u003e\u003cp\u003eThanks to the rapid and extraordinary changes in today's technology, the sources of access to the internet have increased and it has become inevitable for individuals to meet with the internet. With the increase in the time spent on social media, it becomes easier to increase the likelihood of addiction. According to current data, it is known that more than 210\u0026nbsp;million people worldwide meet the criteria for social media addiction. In this context, it is important to investigate the parameters underlying social media addiction, especially on a limited sample group of athletes. In this study, addiction was tried to be analyzed with a detailed approach by using concepts in the psychology literature such as fear of missing developments (Fomo) and body image. Based on the findings, it was determined that social media addiction predicts body image negatively, fomo predicts social media addiction positively, and fomo predicts body image negatively in athletes. As a result, it can be stated that low body image perception leads the individual to social media addiction, individuals with fomo tend to compensate for the related deficiency on social media, and low body image perception leads the individual to social media addiction. This type of research will help to determine the psychopathological factors underlying addiction as a result of psychometric measurements in today's world where individuals are in close relationship with technology. The findings obtained undoubtedly have the potential to be published in the scientific literature to serve public health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch Design ST, AD; Statistical analysis AD, CB; Preparation of the article, ST, AD, CB, SH; Data Collection was carried out by MS, YY, AK, Critical reading MS, AD\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study has no external fundings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study involving human participants were in accordance with the ethical standards of the Department of Psychology, the University of Hong Kong, and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Sakarya University of Applied Sciences Social and Human Sciences Ethics Committee (number: E.65445, Date: 03/11/2022). Informed consent form was obtained from all participating in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author:\u003c/strong\u003e Ahmet D\u0026Ouml;NMEZ, [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eG\u0026uuml;ney M, Taştepe T. Social media usage and social media addiction in adolescents. Journal of Ankara Health Sciences (JAHS), 2020; 9(2), 183-190. https://doi.org/10.46971/ausbid.757713.\u003c/li\u003e\n\u003cli\u003eStatista. Number of internet and social media users worldwide as of July 2022. https://www.statista.com/statistics/617136/digital-population-worldwide/, 2022.\u003c/li\u003e\n\u003cli\u003eTurkish Statistical Institute [TSI], 2023 https://www.tse.org.tr/ A.D. 29.08.2023\u003c/li\u003e\n\u003cli\u003eBayer J, Ellison N, Schoenebeck S, Brady E, Falk EB. Facebook in context(s): Measuring emotional responses across time and space. New Media \u0026amp; Society, 2018; 20(3), 1047\u0026ndash;1067. https://doi.org/10.1177/1461444816681522\u003c/li\u003e\n\u003cli\u003eHosen M, Ogbeibu S, Giridharan B, Cham TH, Lim WM, Paul J. Individual motivation and social media influence on student knowledge sharing and learning performance: Evidence from an emerging economy. Computers \u0026amp; Education, 2021; 172, 104262. https://doi.org/10.1016/j.compedu.2021.104262\u003c/li\u003e\n\u003cli\u003eVerduyn P, Ybarra O, R\u0026eacute;sibois M, Jonides J, Kross E. Do social network sites enhance or undermine subjective well‐being? A critical review. Social Issues and Policy Review, 2017; 11(1), 274\u0026ndash;302. https://doi.org/10.1111/sipr.12033\u003c/li\u003e\n\u003cli\u003eArora S, Mehta M. Love it or hate it, but can you ignore social media? - A bibliometric analysis of social media addiction. Computers in Human Behavior, 2023; 147. https://doi.org/10.1016/j.chb.2023.107831\u003c/li\u003e\n\u003cli\u003eLiao CP, Sher CY, Liu YH. Progress and future directions for research on social media addiction: Visualization-based bibliometric analysis. Telematics and Informatics, 2023; 80. https://doi.org/10.1016/j.tele.2023.101968\u003c/li\u003e\n\u003cli\u003eMiranda S, Trigo I, Rodrigues R, Duarte M. Addiction to social networking sites: Motivations, flow, and sense of belonging at the root of addiction. Technological Forecasting and Social Change, 2023; 188. https://doi.org/10.1016/j.techfore.2022.122280\u003c/li\u003e\n\u003cli\u003eHou Y, Xiong D, Jiang T, Song L, Wang Q. Social media addiction: Its impact, mediation, and intervention. Cyberpsychology, 2019; 13(1). https://doi.org/10.5817/CP2019-1-4\u003c/li\u003e\n\u003cli\u003eKuss DJ. Griffiths MD. Social networking sites and addiction: Ten lessons learned. In International Journal of Environmental Research and Public Health 2017; (Vol. 14, Issue 3). MDPI. https://doi.org/10.3390/ijerph14030311\u003c/li\u003e\n\u003cli\u003eBrailovskaia J, Schillack H, Margraf J. Facebook addiction disorder in Germany. Cyberpsychology, Behavior, and Social Networking, 2018; 21(7), 450\u0026ndash;456. https://doi.org/10.1089/cyber.2018.0140\u003c/li\u003e\n\u003cli\u003eAndreassen C, Pallesen S. Social Network Site Addiction - An Overview. Current Pharmaceutical Design, 2014; 20(25), 4053\u0026ndash;4061. https://doi.org/10.2174/13816128113199990616\u003c/li\u003e\n\u003cli\u003eBhargava VR, Velasquez M. Ethics of the attention economy: The problem of social media addiction. Business Ethics Quarterly, 2021; 31(3), 321\u0026ndash;359. https://doi.org/10.1017/beq.2020.32\u003c/li\u003e\n\u003cli\u003eBlackwell D, Leaman C, Tramposch R, Osborne C, Liss M. Extraversion, neuroticism, attachment style and fear of missing out as predictors of social media use and addiction. Personality and Individual Differences, 2017; 116, 69\u0026ndash;72. https://doi.org/10.1016/j.paid.2017.04.039\u003c/li\u003e\n\u003cli\u003eRyan RM, Deci EL. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 2000; 55(1), 68\u0026ndash;78. https://doi.org/10.1037/0003-066X.55.1.68\u003c/li\u003e\n\u003cli\u003eWu-Ouyang B. Are smartphones addictive? Examining the cognitive-behavior model of motivation, leisure boredom, extended self, and fear of missing out on possible smartphone addiction. Telematics and Informatics, 2022; 71. https://doi.org/10.1016/j.tele.2022.101834\u003c/li\u003e\n\u003cli\u003ePrzybylski AK, Murayama K, Dehaan CR, Gladwell V. Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior, 2013; 29(4), 1841\u0026ndash;1848. https://doi.org/10.1016/j.chb.2013.02.014\u003c/li\u003e\n\u003cli\u003eCasale S, Rugai L, Fioravanti G. Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addictive Behaviors, 2018; 85, 83\u0026ndash;87. https://doi.org/10.1016/j.addbeh.2018.05.020\u003c/li\u003e\n\u003cli\u003eServidio R, Sinatra M, Griffiths MD, Monacis L. Social comparison orientation and fear of missing out as mediators between self-concept clarity and problematic smartphone use. Addictive Behaviors, 2021; 122, 107014. https://doi.org/10.1016/j.addbeh.2021.107014\u003c/li\u003e\n\u003cli\u003eReer F, Tang WY, Quandt T. Psychosocial well-being and social media engagement: The mediating roles of social comparison orientation and fear of missing out. New Media \u0026amp; Society, 2019; 21(7), 1486\u0026ndash;1505. https://doi.org/10.1177/1461444818823719\u003c/li\u003e\n\u003cli\u003eBalta S, Emirtekin E, Kircaburun K, Griffiths MD. Neuroticism, trait fear of missing out, and phubbing: The mediating role of state fear of missing out and problematic ınstagram use. International Journal of Mental Health and Addiction, 2020; 18(3), 628\u0026ndash;639. https://doi.org/10.1007/s11469-018-9959-8\u003c/li\u003e\n\u003cli\u003eTandon A, Dhir A, Almugren I, AlNemer GN, M\u0026auml;ntym\u0026auml;ki M. Fear of missing out (FoMO) among social media users: a systematic literature review, synthesis and framework for future research. Internet Research, 2021; 31(3), 782\u0026ndash;821. https://doi.org/10.1108/INTR-11-2019-0455\u003c/li\u003e\n\u003cli\u003eBrailovskaia J, Margraf J. From fear of missing out (FoMO) to addictive social media use: The role of social media flow and mindfulness. Computers in Human Behavior, 2024; 150, 107984.\u003c/li\u003e\n\u003cli\u003eBrailovskaia J, Margraf J. Less sense of control, more anxiety, and addictive social media use: cohort trends in German university freshmen between 2019 and 2021. Current Research in Behavioral Sciences, 2023; 4, 100088.\u003c/li\u003e\n\u003cli\u003eThompson JK, Heinberg LJ, Altabe M, Tantleff-Dunn S. Exacting beauty: Theory, assessment, and treatment of body image disturbance. American Psychological Association. 1999; https://doi.org/10.1037/10312-000\u003c/li\u003e\n\u003cli\u003eForbes GB, Jung J, Vaamonde JD, Omar A, Paris L, Formiga NS. Body Dissatisfaction and Disordered Eating in Three Cultures: Argentina, Brazil, and the U.S. Sex Roles, 2012; 66(9\u0026ndash;10), 677\u0026ndash;694. https://doi.org/10.1007/s11199-011-0105-3\u003c/li\u003e\n\u003cli\u003eGrogan S. Body image and health: Contemporary perspectives. In Journal of Health Psychology 2006; (Vol. 11, Issue 4, pp. 523\u0026ndash;530). https://doi.org/10.1177/1359105306065013\u003c/li\u003e\n\u003cli\u003eHogue JV, Mills JS. The effects of active social media engagement with peers on body image in young women. Body Image, 2019; 28, 1\u0026ndash;5. https://doi.org/10.1016/j.bodyim.2018.11.002\u003c/li\u003e\n\u003cli\u003eSaiphoo AN, Vahedi Z. A meta-analytic review of the relationship between social media use and body image disturbance. In Computers in Human Behavior, 2019; (Vol. 101, pp. 259\u0026ndash;275). https://doi.org/10.1016/j.chb.2019.07.028\u003c/li\u003e\n\u003cli\u003eSimon PD, Cu SMO, De Jesus KEM, Go NTS, Lim KTF, Say CLC. Worried about being imperfect? The mediating effect of physical appearance perfectionism between Instagram addiction and body esteem. Personality and Individual Differences, 2022; 186. https://doi.org/10.1016/j.paid.2021.111346\u003c/li\u003e\n\u003cli\u003eTiggemann M, Slater A. NetGirls: The internet, facebook, and body image concern in adolescent girls. International Journal of Eating Disorders, 2013; 46(6), 630\u0026ndash;633. https://doi.org/10.1002/eat.22141\u003c/li\u003e\n\u003cli\u003eJung J, Barron D, Lee YA, Swami V. Social media usage and body image: Examining the mediating roles of internalization of appearance ideals and social comparisons in young women. Computers in Human Behavior, 2022; 135. https://doi.org/10.1016/j.chb.2022.107357\u003c/li\u003e\n\u003cli\u003eRoberts SR, Maheux AJ, Hunt RA, Ladd BA, Choukas-Bradley S. Incorporating social media and muscular ideal internalization into the tripartite influence model of body image: Towards a modern understanding of adolescent girls\u0026rsquo; body dissatisfaction. Body Image, 2022; 41, 239\u0026ndash;247. https://doi.org/10.1016/j.bodyim.2022.03.002\u003c/li\u003e\n\u003cli\u003eChoukas-Bradley S, Nesi J, Widman L, Higgins MK. Camera-ready: Young women\u0026rsquo;s appearance-related social media consciousness. Psychology of Popular Media Culture, 2019; 8(4), 473\u0026ndash;481. https://doi.org/10.1037/ppm0000196\u003c/li\u003e\n\u003cli\u003eBurgon RH, Beard J, Waller G. Body image concerns across different sports and sporting levels: A systematic review and meta-analysis. In Body Image 2023; (Vol. 46, pp. 9\u0026ndash;31). https://doi.org/10.1016/j.bodyim.2023.04.007\u003c/li\u003e\n\u003cli\u003eRussell KM. On versus off the pitch: The transiency of body satisfaction among female rugby players, cricketers, and netballers. Sex Roles, 2004; 51, 561-574.\u003c/li\u003e\n\u003cli\u003eNikolinakou A, Phua J, Kwon ES. What drives addiction on social media sites? The relationships between psychological well-being states, social media addiction, brand addiction and impulse buying on social media. Computers in Human Behavior, 2024; 153, 108086.\u003c/li\u003e\n\u003cli\u003eSarman A, \u0026Ccedil;iftci N. Relationship between social media addiction and appearance-related social media consciousness in Turkish adolescents. Journal of Pediatric Nursing, 2024; 76, 99-105.\u003c/li\u003e\n\u003cli\u003eYue H, Yue X, Zhang X, Liu B, Bao H. Exploring the relationship between social exclusion and social media addiction: The mediating roles of anger and impulsivity. Acta Psychologica, 2023; 238, 103980.\u003c/li\u003e\n\u003cli\u003eKhan NA, Khan AN, Moin MF. Self-regulation and social media addiction: A multi-wave data analysis in China. Technology in Society, 2021; 64, 101527.\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;imke S, Cerit E. Social media addiction, cyberbullying and cyber victimization of university students. Archives of psychiatric nursing, 2021; 35(5), 499-503.\u003c/li\u003e\n\u003cli\u003eBalcerowska JM, Brailovskaia J. Psychopathological Symptoms and Social Networking Sites Addiction in Poland and Germany: The Role of Fear of Missing Out and Preference for Online Social Interaction. Computers in Human Behavior, 2024; 108240.\u003c/li\u003e\n\u003cli\u003eTuna R, Alan H, Saritas M, Bacaksiz FE. Touch-operated world of teenagers in the distance education process: A cross-sectional study on nomophobia, netlessphobia and fear of missing out in nursing students. Nurse Education in Practice, 2023; 71, 103728.\u003c/li\u003e\n\u003cli\u003eBehrend N, Webb JB, Warschburger P. Explaining the prospective paths from body appreciation to intuitive eating facets: Does body image flexibility serve as a mediator?. Body Image, 2024; 49, 101710.\u003c/li\u003e\n\u003cli\u003eRodgers RF, Hewett RC, Nowicki GP. A sociocultural model of the relationships between social media use and body image in midlife women. Eating Behaviors, 2024; 101867.\u003c/li\u003e\n\u003cli\u003eCraddock N, Budhraja M, Garbett KM, Nasution K, Gentili C, Rizkiah C, Haime Z, Saraswati LA, Medise BE, White P, Diedrichs PC, Williamson, H. Evaluating a school-based body image lesson in Indonesia: A randomised controlled trial. Body Image, 2024; 48, 101654.\u003c/li\u003e\n\u003cli\u003eFranekel RJ, Wallen EN, Hyun HH. How to design and evaluate research in education. (Eighth Edition). New York: McGraw-Hill, 2012.\u003c/li\u003e\n\u003cli\u003eKarag\u0026ouml;z Y. SPSS ve AMOS uygulamalı nitel-nicel-karma bilimsel araştırma y\u0026ouml;ntemleri ve yayın etiği (1. Baskı). İstanbul: Nobel Kitabevi, 2017.\u003c/li\u003e\n\u003cli\u003eCohen J. Methods in psychology. A power primer. Psychological Bulletin, 1992; 112(1), 155-159.\u003c/li\u003e\n\u003cli\u003eGignac GE, Szodorai ET. Effect Size guidelines for individual differences researchers. Personality and Individual Differences, 2016; 102, 74\u0026ndash;78.\u003c/li\u003e\n\u003cli\u003eG\u0026uuml;n\u0026uuml;\u0026ccedil; S. İnternet bağımlılık \u0026ouml;l\u0026ccedil;eğinin geliştirilmesi ve bazı demografik değişkenler ile internet bağımlılığı arasındaki ilişkilerin incelenmesi. (Y\u0026uuml;ksek Lisans Tezi). Y\u0026uuml;z\u0026uuml;nc\u0026uuml; Yıl \u0026Uuml;niversitesi, Sosyal Bilimler Enstit\u0026uuml;s\u0026uuml;, Van, 2009.\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;\u0026ouml;mlek\u0026ccedil;i MF, Başol O. Gen\u0026ccedil;lerin sosyal medya kullanım ama\u0026ccedil;ları ile sosyal medya bağımlılığı ilişkisinin incelenmesi. Manisa Celal Bayar \u0026Uuml;niversitesi Sosyal Bilimler Dergisi, 2019; 17(4), 173-188.\u003c/li\u003e\n\u003cli\u003eGeorge D, Mallery P. IBM SPSS statistics 26 step by step: A simple guide and reference. (Sixteenth edition). Routledge, New York, NY 10017, 2019.\u003c/li\u003e\n\u003cli\u003eG\u0026ouml;kler ME, Aydın R, \u0026Uuml;nal E, Metintaş S. Sosyal ortamlarda gelişmeleri ka\u0026ccedil;ırma korkusu \u0026ouml;l\u0026ccedil;eğinin T\u0026uuml;rk\u0026ccedil;e s\u0026uuml;r\u0026uuml;m\u0026uuml;n\u0026uuml;n ge\u0026ccedil;erlilik ve g\u0026uuml;venilirliğinin değerlendirilmesi. Anadolu Psikiyatri Dergisi, 2016; 17(1), 52-59.\u003c/li\u003e\n\u003cli\u003eTylka TL, Wood-Barcalow NL. The body appreciation scale-2: Item refinement and psychometric evaluation. Body Image, 2015; 12(1), 53-67.\u003c/li\u003e\n\u003cli\u003eAnlı G, Akın A, Eker H, \u0026Ouml;z\u0026ccedil;elik B. Bedeni beğenme \u0026ouml;l\u0026ccedil;eği: ge\u0026ccedil;erlik ve g\u0026uuml;venirlik \u0026ccedil;alışması. The Journal of Academic Social Science Studies, 2015; 36, 505-511.\u003c/li\u003e\n\u003cli\u003eEcheburua E, De Corral P. Addictionto new technologies andto online social networking in young people: A new challenge. Adicciones, 2010; 22, 91-95.\u003c/li\u003e\n\u003cli\u003eErdoğan P, Şanlı Y. Gelişmeleri ka\u0026ccedil;ırma korkusunun sosyal medya tutumları \u0026uuml;zerine etkisi. Sel\u0026ccedil;uk \u0026Uuml;niversitesi Sosyal Bilimler Meslek Y\u0026uuml;ksekokulu Dergisi, 2019; 22 (2), 615-627.\u003c/li\u003e\n\u003cli\u003eKaradağ A, Ak\u0026ccedil;inar B. \u0026Uuml;niversite \u0026ouml;ğrencilerinde sosyal medya bağımlılığı ve psikolojik semptomlar arasındaki ilişki. Bağımlılık Dergisi. 2019; 20(3):154-166.\u003c/li\u003e\n\u003cli\u003eOberst U, Wegmann E, Stodt B, Brand M, Chamarro A. Negative consequences from heavy social networking in adolescents: The mediating role of fear of missing out. Journal of adolescence, 2017; 55, 51-60. https://doi.org/10.1016/j.adolescence.2016.12.008\u003c/li\u003e\n\u003cli\u003eFioravanti G, Casale S, Benucci SB, Prostamo A, Falone A, Ricca V, Rotella F. Fear of missing out and social networking sites use and abuse: A meta-analysis. Computers in Human Behavior, 2021; 122, 106839. https://doi.org/10.1016/j.chb.2021.106839\u003c/li\u003e\n\u003cli\u003eZhang Y, Li S, Yu G. The relationship between social media use and fear of missing out: A meta-analysis. Acta Psychologica Sinica, 2021; 53(3), 273. https://doi.org/10.3724/SP.J.1041.2021.00273\u003c/li\u003e\n\u003cli\u003eStoyel H, Shanmuganathan-Felton V, Meyer C, Serpell L. Psychological risk indicators of disordered eating in athletes. PloS one, 2020; 15(5), e0232979. Doi:10.1371/journal.pone.0232979\u003c/li\u003e\n\u003cli\u003eVargas T, Maloney J, Gupta T, Damme KS, Kelley NJ, Mittal VA. Measuring facets of reward sensitivity, inhibition, and impulse control in individuals with problematic Internet use. Psychiatry research, 2019; 275, 351-358.\u003c/li\u003e\n\u003cli\u003eAkat M, Arslan C, Hamarta E. Dark triad personality and phubbing: The mediator role of fomo. Psychological Reports, 2023; 126(4), 1803-1821. Doi:10.1177/00332941221109119\u003c/li\u003e\n\u003cli\u003eTandon A, Dhir A, Talwar S, Kaur P, M\u0026auml;ntym\u0026auml;ki M. Social media induced fear of missing out (FoMO) and phubbing: Behavioural, relational and psychological outcomes. Technological Forecasting and Social Change, 2022; 174, 121149. Doi: 10.1016/j.techfore.2021.121149\u003c/li\u003e\n\u003cli\u003eBeyens I, Frison E, Eggermont S. \u0026ldquo;I don\u0026rsquo;t want to miss a thing\u0026rdquo;: Adolescents\u0026rsquo; fear of missing out and its relationship to adolescents\u0026rsquo; social needs, Facebook use, and Facebook related stress. Computers in human behavior, 2016; 64, 1-8. Doi: 10.1016/j.chb.2016.05.083\u003c/li\u003e\n\u003cli\u003eBrailovskaia J, Schillack H, Margraf J. Tell me why are you using social media (SM)! Relationship between reasons for use of SM, SM flow, daily stress, depression, anxiety, and addictive SM use\u0026ndash;An exploratory investigation of young adults in Germany. Computers in Human Behavior, 2020; 113, 106511. Doi: 10.1016/j.chb.2020.106511\u003c/li\u003e\n\u003cli\u003eHayes M. Social media usage among elite athletes: An exploration of athlete usage during major events. PhD diss., Griffith University, Australia. 2019.\u003c/li\u003e\n\u003cli\u003eBevan JL, Gomez R, Sparks L. Disclosures about important life events on Facebook: Relationships with stress and quality of life. Computers in Human Behavior, 2014; 39, 246-253.\u003c/li\u003e\n\u003cli\u003eChen W, Lee KH. Sharing, liking, commenting, and distressed? The pathway between Facebook interaction and psychological distress. Cyberpsychology, behavior, and social networking, 2013; 16(10), 728-734.\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;zbey H, G\u0026uuml;ltekin M. Lise \u0026ouml;ğrencilerinde beden algısı ve benlik saygısı arasındaki ilişkinin medya ve farklı değişkenler a\u0026ccedil;ısından incelenmesi. Afyon Kocatepe \u0026Uuml;niversitesi Sosyal Bilimler Dergisi, (2021; 23(2), 429-441. https://doi.org/10.32709/akusosbil.746383\u003c/li\u003e\n\u003cli\u003eTayhan F. \u0026Uuml;niversite \u0026ouml;ğrencilerinde sosyal medya bağımlılığı, beden algısı, v\u0026uuml;cut kompozisyonu ve yeme bozuklukları arasındaki ilişkinin incelenmesi. Karya Journal of Health Science, 2023; 4(2), 139-145.\u003c/li\u003e\n\u003cli\u003e\u0026Ouml;zg\u0026uuml;r M, U\u0026ccedil;ar A. \u0026Uuml;niversitede eğitim g\u0026ouml;ren kız \u0026ouml;ğrencilerde sosyal medya bağımlılığı ve beden algısı ile beslenme bilgi d\u0026uuml;zeylerinin karşılaştırılması. Ankara Sağlık Bilimleri Dergisi, 2020; 9(2), 46-54.\u003c/li\u003e\n\u003cli\u003eFox J, Moreland JJ. The dark side of social networking sites: An exploration of the relational and psychological stressors associated with Facebook use and affordances. Computers in human behavior, 2015; 45, 168-176.\u003c/li\u003e\n\u003cli\u003eYang H, Wang JJ, Tng GY, Yang S. Effects of social media and smartphone use on body esteem in female adolescents: Testing a cognitive and affective model. Children, 2020; 7(9), 148.\u003c/li\u003e\n\u003cli\u003eJarman HK, Marques MD, McLean SA, Slater A, Paxton SJ. Social media, body satisfaction and well-being among adolescents: A mediation model of appearance-ideal internalization and comparison. Body Image, 2021; 36, 139-148. https://doi.org/10.1016/j.bodyim.2020.11.005\u003c/li\u003e\n\u003cli\u003eBarry CT, Wong MY. Fear of missing out (FoMO): A generational phenomenon or an individual difference?. Journal of Social and Personal Relationships, 2020; 37(12), 2952-2966. Doi:10.1177/0265407520945394.\u003c/li\u003e\n\u003cli\u003eBurnell K, George MJ, Vollet JW, Ehrenreich SE, Underwood MK. Passive social networking site use and well-being: The mediating roles of social comparison and the fear of missing out.Cyberpsychol J Psychosoc Res Cybersp 2019, 13 http://dx. doi.org/10.5817/cp2019-3-5\u003c/li\u003e\n\u003cli\u003eHamutoglu NB, Topal M, Gezgin DM. Investigating Direct and Indirect Effects of Social Media Addiction, Social Media Usage and Personality Traits on FOMO. International Journal of Progressive Education, 2020; 16(2), 248-261. Doi:10.29329/ijpe.2020.241.17\u003c/li\u003e\n\u003cli\u003eElhai JD, Levine JC, Alghraibeh AM, Alafnan AA, Aldraiweesh AA, Hall BJ. Fear of missing out: Testing relationships with negative affectivity, online social engagement, and problematic smartphone use. Computers in Human Behavior, 2018; 89, 289-298. Doi:10.1016/j.chb.2018.08.020\u003c/li\u003e\n\u003cli\u003eBassett-Gunter R, McEwan D, Kamarhie A. Physical activity and body image among men and boys: A meta-analysis. Body image, 2017; 22, 114-128.\u003c/li\u003e\n\u003cli\u003eFallon EA, Hausenblas HA. Media images of the \u0026ldquo;ideal\u0026rdquo; female body: Can acute exercise moderate their psychological impact?. Body İmage, 2005; 2(1), 62-73.\u003c/li\u003e\n\u003cli\u003eTylka TL, Homan KJ. Exercise motives and positive body image in physically active college women and men: Exploring an expanded acceptance model of intuitive eating. Body İmage, 2015; 15, 90-97.\u003c/li\u003e\n\u003cli\u003eMccoy M. 3 steps for gettin grid of FOMO. https://carlytheprepster. com/2016/07/3-steps-for-getting-rid-of-fomo.html, 2016.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4383457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4383457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research aimed to reveal the existence of relationships between social media addiction, fear of missing out developments, and body image in student athletes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 313 student athletes, 133 females and 180 males, enrolled in the sports sciences faculties undergraduate programs of three different state universities, participated in the research in which the relational screening model was adopted. The data was obtained by using the \"Personal Information Form\", \"Social Media Addiction Scale\", \"Fear of Missing Out in Social Environments Scale\" and \"Body Appreciation Scale\". Data were analyzed by using Pearson correlation and Regression analyses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFindings\u003c/strong\u003e: The results obtained in the study showed a negative relationship between social media addiction and body image (p \u0026lt; .05); There is a positive relationship between social media addiction and fear of missing out (p \u0026lt; .05); It was determined that there were negative (p \u0026lt; .05) significant relationships between fear of missing out and body image perception. Moreover, it has been revealed that social media addiction negatively predicted body image (p \u0026lt; .05); fear of missing out positively predicted social media addiction (p \u0026lt; .05); the fear of missing out predicted body image negatively (p \u0026lt; .05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs a result, it may be possible to state that addiction to social media in student athletes negatively affects their body image, and having the fear of missing out leads to social media addiction and lowers their body image.\u003c/p\u003e","manuscriptTitle":"Relationships Between Social Media Addiction, Fear of Missing Out Developments and Body Image","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 13:46:43","doi":"10.21203/rs.3.rs-4383457/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"195acf94-aa4c-476e-8e62-c034f2f5bcde","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-21T05:54:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-03 13:46:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4383457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4383457","identity":"rs-4383457","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}