The Relationship Between FoMO, Social Comparison, and Depression in the Context of Instagram Use

The Relationship Between FoMO, Social Comparison, and Depression in the Context of Instagram Use | 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 The Relationship Between FoMO, Social Comparison, and Depression in the Context of Instagram Use Abdulkadir KARABULUT, Furkan ARI This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8722751/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 Introduction: Frequent Instagram use is linked to increased FoMO and social comparison, both of which may contribute to depression. This study explores how usage patterns relate to FoMO, comparison types, and depressive symptoms. Methods. Cross-sectional data were collected from 449 adults living in Turkey using a personal information form and the FoMO, social comparison and Beck Depression scales. The predictive relationships between the variables were then tested using descriptive statistics, reliability analyses, group comparisons and multiple regression models. Results: Spending more time on Instagram significantly increases feelings of FOMO, social comparison and depression, particularly among those who use the platform intensively. Analyses showed that upward social comparison and FoMO significantly predicted higher depression scores, whereas downward social comparison had a protective effect. Additionally, although young adults, singles and students are more vulnerable groups, a focus on sharing reinforces feelings of FOMO and social comparison. Discussion: This study shows that social comparison in digital environments creates intense cognitive cycles that weaken young users' self-perception. It is understood that FOMO perpetuates this cycle, pressuring users to stay online constantly and increasing their psychological burden. In general, it is seen that Instagram's showcase-like structure transforms social media use from a superficial activity into a decisive psychosocial factor on subjective well-being. Conclusion : Based on the research findings, programmes focusing on psycho-education, digital awareness and social media literacy should be developed. These programmes should focus on themes such as FoMO, social comparison and digital well-being. Protective interventions should also be created for at-risk user groups. 1. INTRODUCTION In recent years, the use of social media platforms has increased significantly worldwide. These platforms have become an indispensable part of people's daily routines. Users communicate and interact with others on social media, while also keeping up with current events and accessing the latest content (Parveiz et al., 2023 ). A similar picture emerges in Turkey. Current data shows that there are 57.5 million active social media users and that social media penetration is quite high. Of all the social media platforms, Instagram stands out as one of the most popular in Turkey. Its monthly usage time is 32 hours and 41 minutes, and 91.8% of people in Turkey are Instagram users (We Are Social, 2024 ). People tend to show others the most beautiful and special aspects of their lives, as if displaying them in a showcase. One of the social media platforms that most clearly fulfills this showcase function is Instagram. On Instagram, people present themselves and seek emotional satisfaction by viewing others' posts (Goffman, 2009 ; Young & Quan-Haase, 2009 ; Walther, 2007 ). In Turkey, people also tend to use Instagram primarily to express themselves and follow others (Sezgin & Güler, 2020 ). Instagram's visually-heavy structure allows individuals to share their identities and create continuously updatable profiles. Along with its Stories and Reels formats, this leads users to feel caught up in a fast-paced flow, afraid of missing out on what is being shared on social media (Yılmaz, 2025 ). Nowadays, people feel the need to check the Instagram posts of the accounts they follow frequently, so as not to miss anything (Hoşgör et al., 2017 ). This desire to check is often explained in the literature by the concept of FoMO (fear of missing out).vFoMO is defined as the desire not to fall behind other social media users, and the anxiety individuals feel when they think that the people they follow may be having a better time than them when they are not using social media (Przybylski et al., 2013 ). Sharing successes, happiness and positive aspects of one's life on Instagram can accelerate FOMO among other users, thereby reducing their life satisfaction and potentially undermining their well-being (Al-Menayes, 2016 ; Stead & Bibby, 2017 ; Yin et al., 2021 ). The tendency to make social comparisons with others is also triggered by FoMO behaviour on Instagram (Eitan & Gazit, 2023 : 2; Reer et al., 2019 ; Steinberger & Kim, 2023 ). Social comparison is defined as the process by which individuals evaluate themselves by comparing themselves with others (Festinger, 1954 ), and it often occurs unconsciously (Asıcı, 2022 ). Social comparisons made through social media are based on variables such as users' happiness (Chou & Edge, 2012 ), physical appearance, career and status (Haferkamp & Krämer, 2010). There are two main types of social comparison (Wood,1989). Individuals on Instagram who believe that the users they follow are better off than themselves make upward social comparisons (Collins, 1996 ), while those who feel that others are worse off make downward social comparisons (Wills, 1981 ). As people on Instagram mostly share the best versions of themselves, followers tend to engage in upward social comparison when viewing these profiles (Chou & Edge, 2012 ). Studies have shown that passive Instagram use involving upward social comparisons can reduce self-esteem and pose a threat to mental health. (Aubry et al., 2024 ; Tosun & Kaşdarma, 2019 ; Verduyn et al., 2015 ). 2. OBJECTIVES It is important to examine the relationship between Instagram usage characteristics (e.g. usage duration and purpose) and FoMO (fear of missing out), types of social comparison (e.g. upward and downward) and depression, in order to understand the effects of digitalised social relationships on psychosocial well-being. The primary objective of this study is to examine the relationship between the duration and purposes of Instagram usage and FoMO, social comparison and depression, and to reveal the patterns formed by FoMO and social comparison tendencies in relation to depression. Based on the relevant literature, the following hypotheses have been developed: H1: An increase in time spent using Instagram leads to an increase in individuals' FoMO levels. H2: The more time individuals spend on Instagram, the more they engage in upward social comparison. H3: As FoMO levels increase, so do depression levels. H4: Depression levels increase with upward social comparison and decrease with downward social comparison. H5: There is a positive correlation between increased Instagram usage and increased depression levels. 3. METHODS This quantitative study aims to examine the relationship between social media usage habits and indicators of psychological well-being. The study was designed using both a correlational survey model and a cross-sectional approach. The study did not involve any interventions, such as training or workshops. Relationships between variables were measured using scales and questionnaires over the same time period. The study focuses on adults aged 18 and over who live in Turkey. As a sampling strategy, convenience sampling was adopted, which allows data to be collected from participants who are easy to reach. Participants were recruited via Google Forms, an online survey platform, and social media channels (Instagram, Twitter and Facebook). The inclusion criteria for the study are: being aged 18 or over; and agreeing to participate voluntarily. Those who did not meet these criteria were excluded from the study. A minimum of 300 participants was targeted to ensure the power of the statistical analyses, and a total of 449 individuals participated. To ensure a balanced demographic distribution among participants, attention was paid to factors such as age, gender, education level and geographic region. Data collection took place between 10 May and 10 June 2025. Ethical approval for the study was obtained from the Hitit University Non-Interventional Research Ethics Committee on 30 April 2025 (decision number 2025-09). All participants were informed about the purpose of the study before starting the survey, and electronic voluntary consent was obtained. 3.1. Measures Researchers collected the data using three different scales and a personal information form, which were applied in a single stage. Demographics characteristics: It consists of questions covering participants' demographic characteristics, such as age, gender and educational status, as well as their social media usage habits, such as daily usage time, the most frequently used platforms and the purpose of using Instagram. Fear of Missing Out Scale (FoMOS): To measure individuals' levels of fear of missing out (FOMO), the 10-item scale developed by Przybylski et al. ( 2013 ) and adapted into Turkish by Çelik & Özkara ( 2022 ) was used. Social Comparison Scale on Instagram: The eight-item scale developed by Asıcı ( 2022 ) based on the Frequency of Social Comparisons Scale on Facebook (Kaşdarma, 2016 ) was used. The scale includes sub-dimensions of both upward and downward social comparisons. Beck Depression Inventory (BDI): The severity of depressive symptoms among participants was measured using a 21-item form developed by Beck et al. ( 1961 ) and validated in Turkish by Hisli ( 1989 ). 3 .2. Data analysis The collected data were analysed using IBM SPSS Statistics version 25. The statistical significance level was set at p < 0.05. The analyses were performed in the following order: Descriptive statistics (frequency, percentage, mean and standard deviation). Skewness and kurtosis coefficients to examine the distribution of variables; Cronbach's alpha reliability coefficients were used to assess the internal consistency of the scales. T-tests and one-way analysis of variance (ANOVA) were used for group comparisons based on demographic variables. Multiple linear regression analysis was employed to identify the predictors of depression and FoMO levels. The multicollinearity problem in regression analyses was examined by evaluating the tolerance, VIF and CI values. 4. RESULTS A total of 449 individuals took part in the study. Their socio-demographic characteristics are presented in Table 1 . According to this table: The vast majority of participants are women (78.0%) aged between 18 and 29 (also 78.0%). In terms of educational attainment, around half of the participants have an associate degree (49.9%). In terms of marital status, 81.1% of participants are single and the highest proportion of students are found among occupational groups (67.7%). The highest income bracket is 22,105–30,000 TL (28.5%). In terms of place of residence, a significant proportion of participants live in districts (32.7%) or metropolitan cities (27.2%). Instagram use is most prevalent among those who use it for 1–2 hours (38.1%) or 3–5 hours (35.0) per day. The most frequent reason for using Instagram is to relieve boredom (38.3%) (see Table 1 ). Table 1 Participants' socio-demographic characteristics (N = 449) Variable Category N % Gender Male 99 22.0 Female 350 78.0 Age 18–29 350 78.0 30–39 37 8.2 40–49 30 6.7 50+ 32 7.1 Educational attainment High School 31 6.9 Associate degree 224 49.9 Bachelor’s degree 159 35.4 Graduate degree 35 7.8 Marital status Married 85 18.9 Single 364 81.1 Occupation Educator 35 7.8 Civil servant 37 8.2 Self-employed 40 8.9 Retired 33 7.3 Student 304 67.7 Income 0–22.104 TL 99 22.0 22.105–30.000 TL 128 28.5 30.001–50.000 TL 93 20.7 50.001–100.000 TL 91 20.3 100.000 + TL 38 8.5 Place of residence Village 61 13.6 District 147 32.7 Province 119 26.5 Metropolitan city 122 27.2 Instagram usage duration Less than 1 hour 66 14.7 1–2 hours 171 38.1 3–5 hours 157 35.0 6–8 hours 39 8.7 More than 8 hours 16 3.6 Purpose of Instagram use Information seeking 35 7.8 Following current events 116 25.8 Boredom relief 172 38.3 Consuming video/music content 90 20.0 Posting content 36 8.0 Normality of the study variables was assessed using skewness and kurtosis values. Following the guidelines of George and Mallery ( 2010 ), values within the range of ± 2 were considered indicative of normal distribution. All study variables met this criterion; therefore, parametric statistical analyses were conducted. Descriptive statistics and reliability coefficients for the study variables are shown in Table 2 . The mean FoMO score was 17.62 (SD = 10.62). The mean scores for upward and downward social comparison were 6.75 (SD = 2.79) and 6.76 (SD = 2.71), respectively. The mean Beck Depression Inventory score was 14.40 (SD = 9.58). All scales demonstrated high internal consistency, with Cronbach’s alpha coefficients ranging from .849 to .951. Table 2 Descriptive statistics and reliability of study variables Variable Mean SD Cronbach’s α FoMO 17.62 10.62 .951 Upward social comparison 6.75 2.79 .849 Downward social comparison 6.76 2.71 .849 Depression (BDI) 14.40 9.58 .891 The mean FoMO score was 17.62 (SD = 10.62). The mean scores for upward and downward social comparison were 6.75 (SD = 2.79) and 6.76 (SD = 2.71), respectively. The mean Beck Depression Inventory score was 14.40 (SD = 9.58). All scales demonstrated high internal consistency, with Cronbach’s alpha coefficients ranging from .849 to .951. Table 3 The Effects of Depression, Social Media Usage Duration, Purpose of Social Media Use, and Social Comparison Levels on FoMO Variable B Std. Error β t p Constant 2,799 2,005 - 1,396 0,163 Social media usage duration 2,527 0,488 0,230 5,174 0,000 Purpose of social media use -0,375 0,443 -0,037 -0,847 0,398 Upward social comparison 1,039 0,202 0,274 5,152 0,000 Downward social comparison 0,103 0,197 0,026 0,523 0,601 Depression 0,135 0,051 0,122 2,655 0,008 R = .451, R² = .203, Adjusted R² = .194, F(5, 443) = 22.615, p < .001. The regression model predicting total FoMO scores was found to be significant (R = .451, R² = .203, adjusted R² = .194, F(5, 443) = 22.615, p < .001). Accordingly: Social media usage duration (B = 2.527, p < .001), upward social comparison (B = 1.039, p < .001), and depression scores (B = 0.135, p = .008). Significantly and positively predicted FoMO levels. In contrast, purpose of social media use and downward social comparison did not have a significant effect on FoMO (p > .05). Table 4 The Effects of FoMO, Social Media Usage Duration, Purpose of Social Media Use, and Social Comparison Levels on Depression Variable B Std. Error β t p Constant 7,965 1,826 - 4,361 0,000 Social media usage duration 1,103 0,464 0,111 2,376 0,018 Purpose of social media use -0,311 0,411 -0,034 -0,756 0,450 Upward social comparison. 1,182 0,184 0,345 6,405 0,000 Downward social comparison -0,799 0,179 -0,226 -4,459 0,000 Total FoMO 0,116 0,044 0,129 2,655 0,008 R = .396, R² = .157, adjusted R² = .147, F(5, 443) = 16.452, p < .001. The regression model predicting depression scores was found to be significant.Upward social comparison (B = 1.182, p < .001) and total FoMO (B = 0.116, p = .008) were identified as positive predictors that increased depression scores.In contrast, downward social comparison had a negative and significant effect on depression (B = − 0.799, p < .001). Social media usage duration also significantly increased depression scores (B = 1.103, p = .018). However, purpose of social media use did not have a significant effect on depression (p = .450). The regression model predicting depression scores was also significant (R = .396, R² = .157, adjusted R² = .147, F(5, 443) = 16.452, p < .001). Accordingly: Upward social comparison (B = 1.182, p < .001), total FoMO score (B = 0.116, p = .008), and social media usage duration (B = 1.103, p = .018) positively predicted depression.In contrast, downward social comparison had a negative and significant effect on depression (B = − 0.799, p .05).These findings indicate that longer usage duration, higher FoMO, and more intensive upward social comparison constitute a risk pattern associated with depression. Conversely, downward social comparison appears to play a protective role against depressive symptoms. DISCUSSION In this study, the relationships between Instagram usage characteristics, FoMO, social comparison, and depression were examined. Additional group comparisons based on demographic variables are provided in the Supplementary Materials. These results are briefly discussed here to contextualize the main findings. Overall, the findings align with the existing literature demonstrating the adverse effects of social media use, FoMO, and social comparison on psychosocial well-being (Przybylski et al., 2013 ; Reer et al., 2019 ; Steinberger & Kim, 2023 ; Parveiz et al., 2023 ). At the same time, the findings provide important insights into the distinct roles of upward and downward social comparison within the context of Instagram, as well as the heightened vulnerability observed in certain demographic groups. One of the key findings of the study is that the amount of time spent on Instagram is significantly and positively associated with both FoMO and depression. In the regression analyses, social media usage duration significantly predicted both FoMO and depression. The ANOVA results support this pattern as well. The group that used Instagram for more than 8 hours per day had significantly higher FoMO and depression scores than all other groups. This finding is consistent with studies showing that FoMO levels increase as social media usage duration rises (Blackwell et al., 2017 ; Franchina et al., 2018 ; Yıldız & Yürekli, 2024 ). Considering that FoMO is defined as the desire to remain constantly online to monitor what others are doing and the anxiety of missing out on experiences (Przybylski et al., 2013 ), the fast-paced and repeatedly checkable structure of Instagram provides a fertile ground that reinforces this cycle (Sepetçi et al., 2021 ).Similarly, numerous studies have demonstrated that problematic social media use is associated with adverse psychological symptoms such as depression and anxiety (Huang, 2022 ; Shannon et al., 2022 ). In the present study, the significantly elevated depression scores observed particularly among heavy users (≥ 6–8 hours) further support this body of literature. From the perspective of usage purpose, participants who used Instagram for posting had higher FoMO and upward social comparison scores compared to those who used it for information-seeking. This finding aligns with studies emphasizing that Instagram functions as an ideal ‘showcase’ for self-presentation and the pursuit of social approval (Goffman, 2009 ; Walther, 2007 ; Sezgin & Güler, 2020 ). Individuals who frequently share their own content may experience a stronger need to monitor others’ posts and to track reactions to their own posts in real time; this may function as a mechanism that reinforces the FoMO cycle (Stead & Bibby, 2017 ; Yin et al., 2021 ). Another important finding of the study is that the relationships between FoMO, social comparison, and depression exhibit a bidirectional pattern. In the first regression model, upward social comparison and depression significantly increased FoMO; whereas in the second model, FoMO and upward social comparison positively predicted depression, while downward social comparison negatively predicted it. This pattern is consistent with the literature indicating that, within social media environments, upward social comparison—believing that others lead happier, more successful, or more attractive lives—undermines self-esteem and is associated with depressive symptoms (Chou & Edge, 2012 ; Haferkamp & Krämer, 2011; Appel et al., 2016 ; Aubry et al., 2024 ). The results of the study indicate that higher levels of upward social comparison are associated with increases in both FoMO and depression scores. This suggests that social comparison processes may constitute a shared cognitive mechanism underlying both FoMO and depression (Burnell et al., 2019 ; Reer et al., 2019 ). In contrast, downward social comparison (perceiving others as being worse off than oneself) appears to have a protective effect against depression. The findings show that higher levels of downward social comparison are associated with lower depression scores. The literature has noted that downward comparison can, at times, enhance subjective well-being and contribute to a greater sense of personal adequacy (Kim & Kim, 2021 ). From this perspective, the present finding aligns with previous research. However, it should also be noted that, in the long term, reliance on downward comparison may carry the risk of fostering insensitivity toward others or promoting generalized negative attitudes. The relationship between FoMO and social comparison is another noteworthy aspect of the findings. When the regression results and descriptive analyses are considered together, it becomes evident that higher FoMO levels are associated with a greater tendency toward upward social comparison. The literature suggests that FoMO drives individuals to seek validation and approval through online platforms, thereby triggering social comparison behaviors in the process (Eitan & Gazit, 2023 ; Steinberger & Kim, 2023 ). The findings of the present study also support the positive association between FoMO and social comparison. The study also revealed that FoMO, social comparison, and depression scores varied across several demographic variables. Three groups were particularly prominent: young adults (18–29), single individuals, and students. In terms of age, the 18–29 group had significantly higher FoMO and depression scores compared to the 40–49 age group. Upward social comparison was also most prevalent among young adults. This finding is consistent with the literature, which frequently employs young adult samples in social media and FoMO research and emphasizes that this age group represents the heaviest users of social media (Przybylski et al., 2013 ; Varchetta et al., 2023 ). The intensive use of social media by young adults in the processes of identity formation, seeking social approval, and navigating peer relationships appears to create a more vulnerable context for FoMO and social comparison. In terms of marital status, the finding that single participants had significantly higher FoMO, upward social comparison, and depression scores compared to married individuals is noteworthy. This result may suggest that single individuals maintain their social connections more intensively through online platforms and rely on Instagram more frequently as a reference point for social comparison. Although the literature on marital status is relatively limited, previous studies highlight that FoMO and problematic social media use are closely linked to loneliness, the need for belonging, and the pursuit of social approval (Alt, 2018 ; Oberst et al., 2017 ; Kelly et al., 2018 ). From this perspective, the co-occurrence of high FoMO and depression among single individuals suggests a meaningful area of risk From the perspective of occupation groups, the finding that students have higher FoMO scores than individuals in the educator and small business owner/businessperson groups is also an expected outcome. Numerous studies have shown that university students are heavy social media users and tend to exhibit higher levels of FoMO and social comparison (Hoşgör et al., 2017 ; Parveiz et al., 2023 ). In this study, although students also had higher depression scores than other occupation groups, the difference was statistically marginal; nevertheless, students can still be considered an important risk group in terms of FoMO and depression. With regard to income level, the finding that participants with an income of 100,000 TL or more had significantly lower depression scores than all other groups suggests that economic resources may serve as a protective factor for psychological well-being. Overall, the findings point to the following risk pattern associated with Instagram use: longer usage duration, more intense upward social comparison, and higher FoMO levels collectively form a profile linked to depressive symptoms. This pattern suggests that visual self-presentation and social comparison processes on social media may exert a substantial influence on users’ subjective well-being (Chae, 2017 ; Saiphoo & Vahedi, 2019 ; Lin & Utz, 2015 ; Hodkinson & Poropat, 2014 ). Particularly on visually oriented platforms such as Instagram, representations of ‘success, happiness, beauty, and the ideal life’ are prominently displayed, which may make users more susceptible to feeling inadequate, insufficient, or left behind (Tandoc et al., 2015 ; Asıcı, 2022 ). Conclusion This study examined the relationships between Instagram usage characteristics, FoMO, social comparison, and depression in a Turkish sample. The findings showed that increased time spent on Instagram significantly elevated FoMO and depression scores, with FoMO and depressive symptoms rising markedly among individuals who used Instagram for six hours or more per day. While upward social comparison was positively associated with both FoMO and depression, downward social comparison appeared to have a protective effect against depressive symptoms. Overall, these results highlight that social comparison processes in visually driven, self-presentation–oriented social media environments constitute a critical risk factor for psychosocial well-being. The demographic findings indicate that young adults (18–29), single individuals, and students constitute more vulnerable groups in terms of FoMO and depression. Additionally, higher depression scores among lower-income participants suggest that economic resources may serve as a protective factor for psychological well-being. Overall, when longer usage duration, intensive upward social comparison, and high FoMO levels are considered together, a risk pattern emerges that is associated with depressive symptoms. In line with these findings, psychoeducational programs targeting young adults and university students may benefit from incorporating themes such as FoMO, social comparison, and digital well-being. Schools, universities, and mental health professionals can systematically assess not only depressive symptoms but also social media usage duration, usage purposes, and tendencies toward social comparison in their work with students or clients. Moreover, digital literacy and social media awareness programs may emphasize the critical discussion of ‘ideal life’ portrayals on platforms such as Instagram, helping users develop more realistic expectations and question the FoMO cycle. Future research could investigate the potential mediating and moderating roles of FoMO and social comparison on depression through longitudinal or experimental designs focusing on Instagram use. Qualitative studies may also provide deeper insights into young adults’ Instagram experiences, their self-presentation strategies, and their coping mechanisms related to FoMO. Additionally, the development of psychoeducational programs, digital awareness workshops, and social media literacy interventions may inform preventive initiatives, particularly for young, single, and student populations. Declarations Ethics approval and consent to participate This study was conducted in accordance with institutional and international ethical standards. Ethical approval for the research was obtained from the Republic of Türkiye Hitit University Non-Interventional Research Ethics Committee (Approval No: 2025-09; Meeting Date: April 30, 2025). All participants were informed about the purpose and procedures of the study, and electronic informed consent was obtained prior to participation. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Authors’ information Not applicable. Funding This research received no external funding. Author Contribution A.K. conceptualized the study, designed the methodology, collected the data, performed the analyses, and drafted the manuscript. F.A. contributed to data analysis and critically revised the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Al-Menayes J. (2016). The fear of missing out scale: validation of the Arabic version and correlation with social media addiction. Int. J. Appl. Psychol. 6, 41–46. https://doi.org10.5923/j.ijap.20160602.04. Alt D. Students’ wellbeing, fear of missing out, and social media engagement for leisure. Curr Psychol. 2018;37(1):128–38. https://doi.org/10.1007/s12144-016-9496-1 . Appel H, Gerlach AL, Crusius J. The interplay between Facebook use, social comparison, envy, and depression. 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Motivational, emotional, and behavioral correlates of fear of missing out. Comput Hum Behav. 2013;29(4):1841–8. https://doi.org/10.1016/j.chb.2013.02.014 . 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 Soc. 2019. https://doi.org/10.1177/1461444818823719 . Saiphoo AN, Vahedi Z. A meta-analytic review of the relationship between social networking sites use and body image disturbance. Comput Hum Behav. 2019;101:259–75. https://doi.org/10.1016/j.chb.2019.07.028 . Sepetçi P, Özdemir S, Sever M. Canım Sıkılıyor! Can sıkıntısı, Sosyotelizm ve Gelişmeleri Kaçırma Korkusu. Mersin Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 2021;5(1):26–36. https://doi.org/10.55044/meusbd.962572 . Sezgin M, Güler Ş. The Role of Digital Feedback on the Self-Esteem of Digital Natives. Türkiye İletişim Araştırmaları Derneği. 2020;35:46–62. Shannon H, Bush K, Villeneuve PJ, Hellemans KG, Guimond S. Problematic Social Media Use in Adolescents and Young Adults: Systematic Review and Meta-analysis. JMIR Ment Health. 2022;9(4):e33450. https://doi.org/10.2196/33450 . Stead H, Bibby PA. Personality, fear of missing out and problematic internet use and smartphone use. Comput Hum Behav. 2017;76:534–40. https://doi.org/10.1016/j.chb.2017.08.016 . Steinberger P, Kim H. Social comparison of ability and fear of missing out mediate the relationship between subjective well-being and social network site addiction. Front Psychol. 2023;14:1157489. https://doi.org/10.3389/fpsyg.2023.1157489 . Tandoc EC Jr., Ferrucci P, Duffy M. Facebook use, envy, and depression among college students: Is facebooking depressing? Comput Hum Behav. 2015;43:139–46. https://doi.org/10.1016/j.chb.2014.10.053 . Tosun P, Kaşdarma E. Passive Facebook Use and Depression. J Media Psychol. 2019;32:165–75. https://doi.org/10.1027/1864-1105/a000269 . We Are Social. (2024). Digital media usage statistics in Turkey. https://www.guvenliweb.org.tr/dosya/3degJ.pdf Varchetta M, González-Sala F, Mari E, Quaglieri A, Fraschetti A, Cricenti C, Giannini AM, Martí-Vilar M. Psychosocial risk factors of technological addictions in a sample of Spanish university students: The influence of emotional (dys)regulation, personality traits and fear of missing out on internet addiction. Psychiatry Res. 2023;329:1–9. https://doi.org/10.1016/j.psychres.2023.115518 . Verduyn P, Lee DS, Park J, Shablack H, Orvell A, Bayer J, Kross E. Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence. J Exp Psychol Gen. 2015;144(2):480–8. https://doi.org/10.1037/xge0000057 . Walther JB. Selective self-presentation in computer-mediated communication: Hyperpersonal dimensions of technology, language, and cognition. Comput Hum Behav. 2007;23(5):2538–57. https://doi.org/10.1016/j.chb.2006.05.002 . Wills TA. Downward comparison principles in social psychology. Psychol Bull. 1981;90(2):245–71. https://doi.org/10.1037/0033-2909.90.2.245 . Wood JV. Theory and research concerning social comparisons of personal attributes. Psychol Bull. 1989;106(2):231–48. https://doi.org/10.1037/0033- 2909.106.2.231 . Yin L, Wang P, Nie J, Guo J, Feng J, Lei L. Social networking sites addiction and FoMO: the mediating role of envy and the moderating role of need to belong. Curr Psychol. 2021;40:3879–87. https://doi.org/10.1007/s12144-019-00344-4 . Yıldız İ, Yürekli E. Dijital yaşamda gelişmeleri kaçırma korkusu (FoMO) ve sosyal medya: Üniversite öğrencileri üzerine bir araştırma. Selçuk Üniversitesi Sosyal Bilimler Meslek Yüksekokulu Dergisi. 2024;27:709–25. https://doi.org/10.29249/selcuksbmyd.1529186 . Yılmaz B. Üniversite öğrencilerinde instagram bağımlılığının sıkılma algısı ile ilişkisinde öz-kontrolün aracılık rolü. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi. 2025;27(2):739–55. Young A, Quan-Haase A. (2009). Information revelation and internet privacy concerns on social network sites: a case study of Facebook. Proceedings of the Fourth International Conference on Communities and Technologies , 265–274. Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx 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-8722751","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":602550167,"identity":"8ff35bec-9cdb-418f-92ca-5b9904abd664","order_by":0,"name":"Abdulkadir KARABULUT","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYBACCQYGgwMMB8AsRiBlk8DGwNgA5DITpQVIJaQlsLExNjaAtbDh1sKApOVwAgPEGtxaJNsPbzxcccYun392j8Fh3h/n8/jkm9sfMFRYJzbI9z7ApkWaJ63g4JkbyZYz7pwxOMyTcLsY4rAz6YkNbOwG2LTIMeQYHGz4wGzAcCMHrCWxDaSFse0wUAt2l8nxvwFpqTeQh2g5B9XyD7cWaQmQLTcOGxhAtByAamnArUVyxrOCgw1njhsY3jlWcHBOWjJQS2LjjIRj6cZtbGlYtUicT978seFYtYHc7eaND97Y2CXObz7+4MOHGmvZfuZjWLXgAAkMOKNlFIyCUTAKRgERAACsDWlu5ZyQKAAAAABJRU5ErkJggg==","orcid":"","institution":"Hitit University","correspondingAuthor":true,"prefix":"","firstName":"Abdulkadir","middleName":"","lastName":"KARABULUT","suffix":""},{"id":602550168,"identity":"a034dd45-bbe3-4c0a-a40a-1016768dbb5e","order_by":1,"name":"Furkan ARI","email":"","orcid":"","institution":"Sivas Cumhuriyet University","correspondingAuthor":false,"prefix":"","firstName":"Furkan","middleName":"","lastName":"ARI","suffix":""}],"badges":[],"createdAt":"2026-01-28 15:38:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8722751/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8722751/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106093033,"identity":"511cf699-0346-4613-97d1-0b7bd559f473","added_by":"auto","created_at":"2026-04-03 11:32:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":681773,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8722751/v1/412d99cf-817e-4fc4-9dd9-be192c40ae3f.pdf"},{"id":104375098,"identity":"36f7ce9f-6818-41d7-a368-6f933ea5b8c8","added_by":"auto","created_at":"2026-03-11 06:12:44","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46863,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-8722751/v1/e70f25f8b35d9e2a38e52b08.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Relationship Between FoMO, Social Comparison, and Depression in the Context of Instagram Use","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eIn recent years, the use of social media platforms has increased significantly worldwide. These platforms have become an indispensable part of people's daily routines. Users communicate and interact with others on social media, while also keeping up with current events and accessing the latest content (Parveiz et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A similar picture emerges in Turkey. Current data shows that there are 57.5\u0026nbsp;million active social media users and that social media penetration is quite high. Of all the social media platforms, Instagram stands out as one of the most popular in Turkey. Its monthly usage time is 32 hours and 41 minutes, and 91.8% of people in Turkey are Instagram users (We Are Social, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePeople tend to show others the most beautiful and special aspects of their lives, as if displaying them in a showcase. One of the social media platforms that most clearly fulfills this showcase function is Instagram. On Instagram, people present themselves and seek emotional satisfaction by viewing others' posts (Goffman, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Young \u0026amp; Quan-Haase, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Walther, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In Turkey, people also tend to use Instagram primarily to express themselves and follow others (Sezgin \u0026amp; G\u0026uuml;ler, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInstagram's visually-heavy structure allows individuals to share their identities and create continuously updatable profiles. Along with its Stories and Reels formats, this leads users to feel caught up in a fast-paced flow, afraid of missing out on what is being shared on social media (Yılmaz, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nowadays, people feel the need to check the Instagram posts of the accounts they follow frequently, so as not to miss anything (Hoşg\u0026ouml;r et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This desire to check is often explained in the literature by the concept of FoMO (fear of missing out).vFoMO is defined as the desire not to fall behind other social media users, and the anxiety individuals feel when they think that the people they follow may be having a better time than them when they are not using social media (Przybylski et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Sharing successes, happiness and positive aspects of one's life on Instagram can accelerate FOMO among other users, thereby reducing their life satisfaction and potentially undermining their well-being (Al-Menayes, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Stead \u0026amp; Bibby, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yin et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe tendency to make social comparisons with others is also triggered by FoMO behaviour on Instagram (Eitan \u0026amp; Gazit, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e: 2; Reer et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Steinberger \u0026amp; Kim, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Social comparison is defined as the process by which individuals evaluate themselves by comparing themselves with others (Festinger, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1954\u003c/span\u003e), and it often occurs unconsciously (Asıcı, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Social comparisons made through social media are based on variables such as users' happiness (Chou \u0026amp; Edge, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), physical appearance, career and status (Haferkamp \u0026amp; Kr\u0026auml;mer, 2010).\u003c/p\u003e \u003cp\u003eThere are two main types of social comparison (Wood,1989). Individuals on Instagram who believe that the users they follow are better off than themselves make upward social comparisons (Collins, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), while those who feel that others are worse off make downward social comparisons (Wills, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1981\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs people on Instagram mostly share the best versions of themselves, followers tend to engage in upward social comparison when viewing these profiles (Chou \u0026amp; Edge, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Studies have shown that passive Instagram use involving upward social comparisons can reduce self-esteem and pose a threat to mental health. (Aubry et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Tosun \u0026amp; Kaşdarma, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Verduyn et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. OBJECTIVES","content":"\u003cp\u003eIt is important to examine the relationship between Instagram usage characteristics (e.g. usage duration and purpose) and FoMO (fear of missing out), types of social comparison (e.g. upward and downward) and depression, in order to understand the effects of digitalised social relationships on psychosocial well-being.\u003c/p\u003e \u003cp\u003eThe primary objective of this study is to examine the relationship between the duration and purposes of Instagram usage and FoMO, social comparison and depression, and to reveal the patterns formed by FoMO and social comparison tendencies in relation to depression. Based on the relevant literature, the following hypotheses have been developed:\u003c/p\u003e \u003cp\u003eH1: An increase in time spent using Instagram leads to an increase in individuals' FoMO levels.\u003c/p\u003e \u003cp\u003eH2: The more time individuals spend on Instagram, the more they engage in upward social comparison.\u003c/p\u003e \u003cp\u003eH3: As FoMO levels increase, so do depression levels.\u003c/p\u003e \u003cp\u003eH4: Depression levels increase with upward social comparison and decrease with downward social comparison.\u003c/p\u003e \u003cp\u003eH5: There is a positive correlation between increased Instagram usage and increased depression levels.\u003c/p\u003e"},{"header":"3. METHODS","content":"\u003cp\u003eThis quantitative study aims to examine the relationship between social media usage habits and indicators of psychological well-being. The study was designed using both a correlational survey model and a cross-sectional approach. The study did not involve any interventions, such as training or workshops. Relationships between variables were measured using scales and questionnaires over the same time period.\u003c/p\u003e \u003cp\u003eThe study focuses on adults aged 18 and over who live in Turkey. As a sampling strategy, convenience sampling was adopted, which allows data to be collected from participants who are easy to reach. Participants were recruited via Google Forms, an online survey platform, and social media channels (Instagram, Twitter and Facebook). The inclusion criteria for the study are: being aged 18 or over; and agreeing to participate voluntarily. Those who did not meet these criteria were excluded from the study. A minimum of 300 participants was targeted to ensure the power of the statistical analyses, and a total of 449 individuals participated. To ensure a balanced demographic distribution among participants, attention was paid to factors such as age, gender, education level and geographic region.\u003c/p\u003e \u003cp\u003eData collection took place between 10 May and 10 June 2025. Ethical approval for the study was obtained from the Hitit University Non-Interventional Research Ethics Committee on 30 April 2025 (decision number 2025-09). All participants were informed about the purpose of the study before starting the survey, and electronic voluntary consent was obtained.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.1. Measures\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eResearchers collected the data using three different scales and a personal information form, which were applied in a single stage.\u003c/p\u003e \u003cp\u003eDemographics characteristics: It consists of questions covering participants' demographic characteristics, such as age, gender and educational status, as well as their social media usage habits, such as daily usage time, the most frequently used platforms and the purpose of using Instagram.\u003c/p\u003e \u003cp\u003eFear of Missing Out Scale (FoMOS): To measure individuals' levels of fear of missing out (FOMO), the 10-item scale developed by Przybylski et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and adapted into Turkish by \u0026Ccedil;elik \u0026amp; \u0026Ouml;zkara (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) was used.\u003c/p\u003e \u003cp\u003eSocial Comparison Scale on Instagram: The eight-item scale developed by Asıcı (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) based on the Frequency of Social Comparisons Scale on Facebook (Kaşdarma, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was used. The scale includes sub-dimensions of both upward and downward social comparisons.\u003c/p\u003e \u003cp\u003eBeck Depression Inventory (BDI): The severity of depressive symptoms among participants was measured using a 21-item form developed by Beck et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1961\u003c/span\u003e) and validated in Turkish by Hisli (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3\u003cb\u003e.2. Data analysis\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe collected data were analysed using IBM SPSS Statistics version 25. The statistical significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The analyses were performed in the following order:\u003c/p\u003e \u003cp\u003eDescriptive statistics (frequency, percentage, mean and standard deviation).\u003c/p\u003e \u003cp\u003eSkewness and kurtosis coefficients to examine the distribution of variables;\u003c/p\u003e \u003cp\u003eCronbach's alpha reliability coefficients were used to assess the internal consistency of the scales.\u003c/p\u003e \u003cp\u003eT-tests and one-way analysis of variance (ANOVA) were used for group comparisons based on demographic variables.\u003c/p\u003e \u003cp\u003eMultiple linear regression analysis was employed to identify the predictors of depression and FoMO levels. The multicollinearity problem in regression analyses was examined by evaluating the tolerance, VIF and CI values.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. RESULTS","content":"\u003cp\u003eA total of 449 individuals took part in the study. Their socio-demographic characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. According to this table:\u003c/p\u003e \u003cp\u003eThe vast majority of participants are women (78.0%) aged between 18 and 29 (also 78.0%).\u003c/p\u003e \u003cp\u003eIn terms of educational attainment, around half of the participants have an associate degree (49.9%).\u003c/p\u003e \u003cp\u003eIn terms of marital status, 81.1% of participants are single and the highest proportion of students are found among occupational groups (67.7%).\u003c/p\u003e \u003cp\u003eThe highest income bracket is 22,105\u0026ndash;30,000 TL (28.5%).\u003c/p\u003e \u003cp\u003eIn terms of place of residence, a significant proportion of participants live in districts (32.7%) or metropolitan cities (27.2%).\u003c/p\u003e \u003cp\u003eInstagram use is most prevalent among those who use it for 1\u0026ndash;2 hours (38.1%) or 3\u0026ndash;5 hours (35.0) per day. The most frequent reason for using Instagram is to relieve boredom (38.3%) (see Table\u0026nbsp;\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\u003eParticipants' socio-demographic characteristics (N\u0026thinsp;=\u0026thinsp;449)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\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\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducational attainment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssociate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGraduate degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCivil servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eIncome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026ndash;22.104 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.105\u0026ndash;30.000 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.001\u0026ndash;50.000 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.001\u0026ndash;100.000 TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100.000\u0026thinsp;+\u0026thinsp;TL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVillage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistrict\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMetropolitan city\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eInstagram usage duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 1 hour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;2 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026ndash;5 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u0026ndash;8 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than 8 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePurpose of Instagram use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFollowing current events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBoredom relief\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsuming video/music content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePosting content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.0\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\u003eNormality of the study variables was assessed using skewness and kurtosis values. Following the guidelines of George and Mallery (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), values within the range of \u0026plusmn;\u0026thinsp;2 were considered indicative of normal distribution. All study variables met this criterion; therefore, parametric statistical analyses were conducted. Descriptive statistics and reliability coefficients for the study variables are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The mean FoMO score was 17.62 (SD\u0026thinsp;=\u0026thinsp;10.62). The mean scores for upward and downward social comparison were 6.75 (SD\u0026thinsp;=\u0026thinsp;2.79) and 6.76 (SD\u0026thinsp;=\u0026thinsp;2.71), respectively. The mean Beck Depression Inventory score was 14.40 (SD\u0026thinsp;=\u0026thinsp;9.58). All scales demonstrated high internal consistency, with Cronbach\u0026rsquo;s alpha coefficients ranging from .849 to .951.\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\u003eDescriptive statistics and reliability of study variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCronbach\u0026rsquo;s α\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFoMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpward social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDownward social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.849\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression (BDI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.891\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\u003eThe mean FoMO score was 17.62 (SD\u0026thinsp;=\u0026thinsp;10.62). The mean scores for upward and downward social comparison were 6.75 (SD\u0026thinsp;=\u0026thinsp;2.79) and 6.76 (SD\u0026thinsp;=\u0026thinsp;2.71), respectively. The mean Beck Depression Inventory score was 14.40 (SD\u0026thinsp;=\u0026thinsp;9.58). All scales demonstrated high internal consistency, with Cronbach\u0026rsquo;s alpha coefficients ranging from .849 to .951.\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\u003eThe Effects of Depression, Social Media Usage Duration, Purpose of Social Media Use, and Social Comparison Levels on FoMO\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\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\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,005\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\u003e1,396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media usage duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurpose of social media use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0,375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0,037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0,847\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpward social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDownward social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0,523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,008\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\u003eR = .451, R\u0026sup2; = .203, Adjusted R\u0026sup2; = .194, F(5, 443)\u0026thinsp;=\u0026thinsp;22.615, p \u0026lt; .001.\u003c/p\u003e \u003cp\u003eThe regression model predicting total FoMO scores was found to be significant (R = .451, R\u0026sup2; = .203, adjusted R\u0026sup2; = .194, F(5, 443)\u0026thinsp;=\u0026thinsp;22.615, p \u0026lt; .001). Accordingly:\u003c/p\u003e \u003cp\u003eSocial media usage duration (B\u0026thinsp;=\u0026thinsp;2.527, p \u0026lt; .001), upward social comparison (B\u0026thinsp;=\u0026thinsp;1.039, p \u0026lt; .001), and depression scores (B\u0026thinsp;=\u0026thinsp;0.135, p = .008).\u003c/p\u003e \u003cp\u003eSignificantly and positively predicted FoMO levels. In contrast, purpose of social media use and downward social comparison did not have a significant effect on FoMO (p \u0026gt; .05).\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\u003eThe Effects of FoMO, Social Media Usage Duration, Purpose of Social Media Use, and Social Comparison Levels on Depression\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\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\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,826\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\u003e4,361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial media usage duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePurpose of social media use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0,311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0,034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0,756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpward social comparison.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDownward social comparison\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0,799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0,226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4,459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal FoMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0,044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0,129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0,008\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\u003eR = .396, R\u0026sup2; = .157, adjusted R\u0026sup2; = .147, F(5, 443)\u0026thinsp;=\u0026thinsp;16.452, p \u0026lt; .001.\u003c/p\u003e \u003cp\u003eThe regression model predicting depression scores was found to be significant.Upward social comparison (B\u0026thinsp;=\u0026thinsp;1.182, p \u0026lt; .001) and total FoMO (B\u0026thinsp;=\u0026thinsp;0.116, p = .008) were identified as positive predictors that increased depression scores.In contrast, downward social comparison had a negative and significant effect on depression (B = \u0026minus;\u0026thinsp;0.799, p \u0026lt; .001). Social media usage duration also significantly increased depression scores (B\u0026thinsp;=\u0026thinsp;1.103, p = .018). However, purpose of social media use did not have a significant effect on depression (p = .450).\u003c/p\u003e \u003cp\u003eThe regression model predicting depression scores was also significant (R = .396, R\u0026sup2; = .157, adjusted R\u0026sup2; = .147, F(5, 443)\u0026thinsp;=\u0026thinsp;16.452, p \u0026lt; .001). Accordingly:\u003c/p\u003e \u003cp\u003eUpward social comparison (B\u0026thinsp;=\u0026thinsp;1.182, p \u0026lt; .001), total FoMO score (B\u0026thinsp;=\u0026thinsp;0.116, p = .008), and social media usage duration (B\u0026thinsp;=\u0026thinsp;1.103, p = .018) positively predicted depression.In contrast, downward social comparison had a negative and significant effect on depression (B = \u0026minus;\u0026thinsp;0.799, p \u0026lt; .001). Purpose of social media use did not have a significant effect on depression (p \u0026gt; .05).These findings indicate that longer usage duration, higher FoMO, and more intensive upward social comparison constitute a risk pattern associated with depression. Conversely, downward social comparison appears to play a protective role against depressive symptoms.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, the relationships between Instagram usage characteristics, FoMO, social comparison, and depression were examined. Additional group comparisons based on demographic variables are provided in the Supplementary Materials. These results are briefly discussed here to contextualize the main findings. Overall, the findings align with the existing literature demonstrating the adverse effects of social media use, FoMO, and social comparison on psychosocial well-being (Przybylski et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Reer et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Steinberger \u0026amp; Kim, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Parveiz et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). At the same time, the findings provide important insights into the distinct roles of upward and downward social comparison within the context of Instagram, as well as the heightened vulnerability observed in certain demographic groups.\u003c/p\u003e \u003cp\u003eOne of the key findings of the study is that the amount of time spent on Instagram is significantly and positively associated with both FoMO and depression. In the regression analyses, social media usage duration significantly predicted both FoMO and depression. The ANOVA results support this pattern as well. The group that used Instagram for more than 8 hours per day had significantly higher FoMO and depression scores than all other groups. This finding is consistent with studies showing that FoMO levels increase as social media usage duration rises (Blackwell et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Franchina et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yıldız \u0026amp; Y\u0026uuml;rekli, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Considering that FoMO is defined as the desire to remain constantly online to monitor what others are doing and the anxiety of missing out on experiences (Przybylski et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the fast-paced and repeatedly checkable structure of Instagram provides a fertile ground that reinforces this cycle (Sepet\u0026ccedil;i et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).Similarly, numerous studies have demonstrated that problematic social media use is associated with adverse psychological symptoms such as depression and anxiety (Huang, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Shannon et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, the significantly elevated depression scores observed particularly among heavy users (\u0026ge;\u0026thinsp;6\u0026ndash;8 hours) further support this body of literature.\u003c/p\u003e \u003cp\u003eFrom the perspective of usage purpose, participants who used Instagram for posting had higher FoMO and upward social comparison scores compared to those who used it for information-seeking. This finding aligns with studies emphasizing that Instagram functions as an ideal \u0026lsquo;showcase\u0026rsquo; for self-presentation and the pursuit of social approval (Goffman, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Walther, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sezgin \u0026amp; G\u0026uuml;ler, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Individuals who frequently share their own content may experience a stronger need to monitor others\u0026rsquo; posts and to track reactions to their own posts in real time; this may function as a mechanism that reinforces the FoMO cycle (Stead \u0026amp; Bibby, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yin et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother important finding of the study is that the relationships between FoMO, social comparison, and depression exhibit a bidirectional pattern. In the first regression model, upward social comparison and depression significantly increased FoMO; whereas in the second model, FoMO and upward social comparison positively predicted depression, while downward social comparison negatively predicted it. This pattern is consistent with the literature indicating that, within social media environments, upward social comparison\u0026mdash;believing that others lead happier, more successful, or more attractive lives\u0026mdash;undermines self-esteem and is associated with depressive symptoms (Chou \u0026amp; Edge, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Haferkamp \u0026amp; Kr\u0026auml;mer, 2011; Appel et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Aubry et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The results of the study indicate that higher levels of upward social comparison are associated with increases in both FoMO and depression scores. This suggests that social comparison processes may constitute a shared cognitive mechanism underlying both FoMO and depression (Burnell et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Reer et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn contrast, downward social comparison (perceiving others as being worse off than oneself) appears to have a protective effect against depression. The findings show that higher levels of downward social comparison are associated with lower depression scores. The literature has noted that downward comparison can, at times, enhance subjective well-being and contribute to a greater sense of personal adequacy (Kim \u0026amp; Kim, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). From this perspective, the present finding aligns with previous research. However, it should also be noted that, in the long term, reliance on downward comparison may carry the risk of fostering insensitivity toward others or promoting generalized negative attitudes.\u003c/p\u003e \u003cp\u003eThe relationship between FoMO and social comparison is another noteworthy aspect of the findings. When the regression results and descriptive analyses are considered together, it becomes evident that higher FoMO levels are associated with a greater tendency toward upward social comparison. The literature suggests that FoMO drives individuals to seek validation and approval through online platforms, thereby triggering social comparison behaviors in the process (Eitan \u0026amp; Gazit, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Steinberger \u0026amp; Kim, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The findings of the present study also support the positive association between FoMO and social comparison.\u003c/p\u003e \u003cp\u003eThe study also revealed that FoMO, social comparison, and depression scores varied across several demographic variables. Three groups were particularly prominent: young adults (18\u0026ndash;29), single individuals, and students. In terms of age, the 18\u0026ndash;29 group had significantly higher FoMO and depression scores compared to the 40\u0026ndash;49 age group. Upward social comparison was also most prevalent among young adults. This finding is consistent with the literature, which frequently employs young adult samples in social media and FoMO research and emphasizes that this age group represents the heaviest users of social media (Przybylski et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Varchetta et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The intensive use of social media by young adults in the processes of identity formation, seeking social approval, and navigating peer relationships appears to create a more vulnerable context for FoMO and social comparison.\u003c/p\u003e \u003cp\u003eIn terms of marital status, the finding that single participants had significantly higher FoMO, upward social comparison, and depression scores compared to married individuals is noteworthy. This result may suggest that single individuals maintain their social connections more intensively through online platforms and rely on Instagram more frequently as a reference point for social comparison. Although the literature on marital status is relatively limited, previous studies highlight that FoMO and problematic social media use are closely linked to loneliness, the need for belonging, and the pursuit of social approval (Alt, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Oberst et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Kelly et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). From this perspective, the co-occurrence of high FoMO and depression among single individuals suggests a meaningful area of risk\u003c/p\u003e \u003cp\u003eFrom the perspective of occupation groups, the finding that students have higher FoMO scores than individuals in the educator and small business owner/businessperson groups is also an expected outcome. Numerous studies have shown that university students are heavy social media users and tend to exhibit higher levels of FoMO and social comparison (Hoşg\u0026ouml;r et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Parveiz et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this study, although students also had higher depression scores than other occupation groups, the difference was statistically marginal; nevertheless, students can still be considered an important risk group in terms of FoMO and depression. With regard to income level, the finding that participants with an income of 100,000 TL or more had significantly lower depression scores than all other groups suggests that economic resources may serve as a protective factor for psychological well-being.\u003c/p\u003e \u003cp\u003eOverall, the findings point to the following risk pattern associated with Instagram use: longer usage duration, more intense upward social comparison, and higher FoMO levels collectively form a profile linked to depressive symptoms. This pattern suggests that visual self-presentation and social comparison processes on social media may exert a substantial influence on users\u0026rsquo; subjective well-being (Chae, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Saiphoo \u0026amp; Vahedi, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lin \u0026amp; Utz, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hodkinson \u0026amp; Poropat, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Particularly on visually oriented platforms such as Instagram, representations of \u0026lsquo;success, happiness, beauty, and the ideal life\u0026rsquo; are prominently displayed, which may make users more susceptible to feeling inadequate, insufficient, or left behind (Tandoc et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Asıcı, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examined the relationships between Instagram usage characteristics, FoMO, social comparison, and depression in a Turkish sample. The findings showed that increased time spent on Instagram significantly elevated FoMO and depression scores, with FoMO and depressive symptoms rising markedly among individuals who used Instagram for six hours or more per day. While upward social comparison was positively associated with both FoMO and depression, downward social comparison appeared to have a protective effect against depressive symptoms. Overall, these results highlight that social comparison processes in visually driven, self-presentation\u0026ndash;oriented social media environments constitute a critical risk factor for psychosocial well-being.\u003c/p\u003e \u003cp\u003eThe demographic findings indicate that young adults (18\u0026ndash;29), single individuals, and students constitute more vulnerable groups in terms of FoMO and depression. Additionally, higher depression scores among lower-income participants suggest that economic resources may serve as a protective factor for psychological well-being. Overall, when longer usage duration, intensive upward social comparison, and high FoMO levels are considered together, a risk pattern emerges that is associated with depressive symptoms.\u003c/p\u003e \u003cp\u003eIn line with these findings, psychoeducational programs targeting young adults and university students may benefit from incorporating themes such as FoMO, social comparison, and digital well-being. Schools, universities, and mental health professionals can systematically assess not only depressive symptoms but also social media usage duration, usage purposes, and tendencies toward social comparison in their work with students or clients. Moreover, digital literacy and social media awareness programs may emphasize the critical discussion of \u0026lsquo;ideal life\u0026rsquo; portrayals on platforms such as Instagram, helping users develop more realistic expectations and question the FoMO cycle.\u003c/p\u003e \u003cp\u003eFuture research could investigate the potential mediating and moderating roles of FoMO and social comparison on depression through longitudinal or experimental designs focusing on Instagram use. Qualitative studies may also provide deeper insights into young adults\u0026rsquo; Instagram experiences, their self-presentation strategies, and their coping mechanisms related to FoMO. Additionally, the development of psychoeducational programs, digital awareness workshops, and social media literacy interventions may inform preventive initiatives, particularly for young, single, and student populations.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e This study was conducted in accordance with institutional and international ethical standards. Ethical approval for the research was obtained from the Republic of T\u0026uuml;rkiye Hitit University Non-Interventional Research Ethics Committee (Approval No: 2025-09; Meeting Date: April 30, 2025). All participants were informed about the purpose and procedures of the study, and electronic informed consent was obtained prior to participation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAuthors\u0026rsquo; information\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eA.K. conceptualized the study, designed the methodology, collected the data, performed the analyses, and drafted the manuscript. F.A. contributed to data analysis and critically revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAl-Menayes J. (2016). The fear of missing out scale: validation of the Arabic version and correlation with social media addiction. \u003cem\u003eInt. J. Appl. Psychol.\u003c/em\u003e 6, 41\u0026ndash;46. https://doi.org10.5923/j.ijap.20160602.04.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlt D. Students\u0026rsquo; wellbeing, fear of missing out, and social media engagement for leisure. 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Curr Psychol. 2021;40:3879\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12144-019-00344-4\u003c/span\u003e\u003cspan address=\"10.1007/s12144-019-00344-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYıldız İ, Y\u0026uuml;rekli E. Dijital yaşamda gelişmeleri ka\u0026ccedil;ırma korkusu (FoMO) ve sosyal medya: \u0026Uuml;niversite \u0026ouml;ğrencileri \u0026uuml;zerine bir araştırma. Sel\u0026ccedil;uk \u0026Uuml;niversitesi Sosyal Bilimler Meslek Y\u0026uuml;ksekokulu Dergisi. 2024;27:709\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.29249/selcuksbmyd.1529186\u003c/span\u003e\u003cspan address=\"10.29249/selcuksbmyd.1529186\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYılmaz B. \u0026Uuml;niversite \u0026ouml;ğrencilerinde instagram bağımlılığının sıkılma algısı ile ilişkisinde \u0026ouml;z-kontrol\u0026uuml;n aracılık rol\u0026uuml;. Afyon Kocatepe \u0026Uuml;niversitesi Sosyal Bilimler Dergisi. 2025;27(2):739\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoung A, Quan-Haase A. (2009). Information revelation and internet privacy concerns on social network sites: a case study of Facebook. \u003cem\u003eProceedings of the Fourth International Conference on Communities and Technologies\u003c/em\u003e, 265\u0026ndash;274.\u003c/span\u003e\u003c/li\u003e\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":false,"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-8722751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8722751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction: \u003c/strong\u003eFrequent Instagram use is linked to increased FoMO and social comparison, both of which may contribute to depression. This study explores how usage patterns relate to FoMO, comparison types, and depressive symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods.\u003c/strong\u003e Cross-sectional data were collected from 449 adults living in Turkey using a personal information form and the FoMO, social comparison and Beck Depression scales. The predictive relationships between the variables were then tested using descriptive statistics, reliability analyses, group comparisons and multiple regression models.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eSpending more time on Instagram significantly increases feelings of FOMO, social comparison and depression, particularly among those who use the platform intensively. Analyses showed that upward social comparison and FoMO significantly predicted higher depression scores, whereas downward social comparison had a protective effect. Additionally, although young adults, singles and students are more vulnerable groups, a focus on sharing reinforces feelings of FOMO and social comparison.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion: \u003c/strong\u003eThis study shows that social comparison in digital environments creates intense cognitive cycles that weaken young users' self-perception. It is understood that FOMO perpetuates this cycle, pressuring users to stay online constantly and increasing their psychological burden. In general, it is seen that Instagram's showcase-like structure transforms social media use from a superficial activity into a decisive psychosocial factor on subjective well-being.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion : \u003c/strong\u003eBased on the research findings, programmes focusing on psycho-education, digital awareness and social media literacy should be developed. These programmes should focus on themes such as FoMO, social comparison and digital well-being. Protective interventions should also be created for at-risk user groups.\u003c/p\u003e","manuscriptTitle":"The Relationship Between FoMO, Social Comparison, and Depression in the Context of Instagram Use","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-11 06:12:39","doi":"10.21203/rs.3.rs-8722751/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":"e97bcc30-ba6e-4197-88b8-0d9541824e6f","owner":[],"postedDate":"March 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-31T05:25:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-11 06:12:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8722751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8722751","identity":"rs-8722751","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}