E-Sports Players: Emotional Intelligence and Decision Making Levels

E-Sports Players: Emotional Intelligence and Decision Making Levels | 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 E-Sports Players: Emotional Intelligence and Decision Making Levels Veysel TEMEL, Hüseyin AYDIN This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6804435/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Nov, 2025 Read the published version in BMC Sports Science, Medicine and Rehabilitation → Version 1 posted 11 You are reading this latest preprint version Abstract Background This study aimed to examine the effect of emotional intelligence levels on decision-making among individuals interested in e-sports. The population consisted of individuals aged 18 and over who are interested in e-sports. Method The research sample included 385 participants (178 women and 207 men; Age Average = 21.41 ± 3.24). The study utilized a 20-question information form, the Melbourne Decision Making Scale, and the Schutte Emotional Intelligence Scale to collect data. Results A statistically significant relationship was found between participants' emotional intelligence scores and their decision-making scores. Higher emotional intelligence scores were associated with increased self-esteem in decision-making and improvements in various decision-making sub-dimensions, except for careful decision-making. High emotional intelligence positively influenced the ability to use and evaluate emotions and maintain emotional control, which in turn positively affected decision-making. Conclusion The findings indicated that high emotional intelligence enhances self-esteem and various aspects of decision-making. While some results were consistent with the existing literature, some contrary findings were also observed. Emotional Intelligence E-sports Decision Making Introduction Throughout human history, games have played a crucial role in both the cognitive and affective development of individuals, serving as a multidimensional tool for entertainment, socialization, and learning. Traditionally, games are defined as activities that are not bound by rigid rules, provide enjoyment to participants, incorporate elements of improvisation, and stimulate individuals both physically and mentally (Wood & Attfield, 2005 ). Games can be classified into various categories such as social, structural, motor/physical, and rule-based games, each contributing directly to individuals’ quality of life, psychological balance, and social skills (Honey & Kanter, 2013 ). However, rapid advancements in technology have profoundly transformed both the nature and the medium of gameplay. Activities that once took place in physical spaces have been transferred into virtual environments through computers and gaming consoles, paving the way for the emergence of a competitive and professional digital sport known as electronic sports (Esports) (Kirriemuir, 2002; Argan, Özer, & Akın, 2006 ). Today, esports are recognized as a form of sport that can be played individually or in teams, requiring strategic thinking, high concentration, and rapid decision-making skills, where mental performance is paramount. International organizations such as the International Esports Federation and the World Cyber Games play significant roles in setting the rules, organizing events, and establishing ethical standards in the field (Jenny, Manning, Keiper, & Olrich, 2017 ). As of 2017, the global esports industry had reached an audience of approximately 385 million, exerting an increasing influence not only in competitive sports but also in media, marketing, and education (Schaeperkoetter et al., 2017 kçü & Kaplanoğlu, 2018). Due to the nature of esports, players are frequently required to make critical decisions within seconds, under high cognitive load, time pressure, and rapidly changing game dynamics. In this context, the concept of emotional intelligence (EI) emerges as a determining factor in players’ ability to cope with stress, maintain focus, sustain motivation, and preserve consistent performance. Emotional intelligence is defined as the ability to perceive, understand, and manage one’s own emotions as well as those of others, and to use this emotional information effectively in guiding actions (Salovey & Mayer, 1990 ; Yeşilyaprak, 2001 ; Stubbs & Wolf, 2008 ). As a skill that can be developed, emotional intelligence is closely linked to decision-making processes in sports (Bar-On, 2006 ). Decision-making is defined as the process of selecting the most appropriate option among various alternatives through the interaction of cognitive, affective, and behavioral processes (Deniz, 2004 ; Eroğlu & Lorcu, 2007 ). In sporting contexts, this process becomes more complex due to competition pressure, time constraints, and the necessity to adapt instantly to opponents’ strategies. In esports, this complexity is even greater—an incorrect decision made within milliseconds can determine the outcome of a match. Therefore, understanding the relationship between emotional intelligence and decision-making skills is crucial for both performance enhancement strategies and psychological interventions targeting players. Although the relationship between emotional intelligence and decision-making has been examined in traditional sports across different age and performance groups, studies addressing the interaction of these two variables in the esports context remain scarce. Most existing research focuses solely on cognitive abilities or examines isolated psychological factors such as stress management in esports athletes. However, evaluating rapid, high-stakes decision-making processes together with emotional intelligence represents an almost unexplored area within esports. This gap constitutes a significant deficiency in both sports psychology literature and esports performance analysis. Similarly, recent studies that have investigated the relationships between various psychological variables among athletes in different contexts highlight the importance of multidimensional analyses in this field (Temel & Özçelik, 2025 ). Accordingly, the present study aims to examine the relationship between emotional intelligence levels and decision-making skills among esports players, thereby contributing to a deeper understanding of the interplay between these psychological variables in esports performance and addressing the aforementioned gap in the literature. Methods Research Design This study employed a descriptive research design utilizing the simple random sampling method. Simple random sampling ensures that every unit in the population has an equal chance of being selected, thereby enhancing the representativeness of the sample (Büyüköztürk et al., 2013 ). The primary aim of this research was to investigate the relationship between emotional intelligence and decision-making abilities among esports players. Participants The study population comprised individuals aged 18 years and older who have an interest in E-sports within Turkey. Participants who actively engage in esports activities were included, whereas those without any esports experience were excluded. The sample consisted of 385 participants (mean age = 21.41 ± 3.24), including 178 females and 207 males. Data Collection Instruments A comprehensive literature review was conducted, drawing from both domestic and international sources, to establish the theoretical framework underpinning the study. Data were collected through both online and face-to-face surveys, with participation being voluntary. Emotional intelligence was measured using the Revised Schutte Emotional Intelligence Scale (Schutte and et al., 1998 ). The Turkish adaptation and psychometric validation of this scale were conducted by Tatar ( 2011 ), with reported Cronbach's alpha coefficients ranging between 0.85 and 0.90, indicating high internal consistency. Decision-making skills were assessed via the Melbourne Decision Making Questionnaire , originally developed by Mann et al. ( 1998 ) and adapted to Turkish by Deniz ( 2004 ). The questionnaire has demonstrated satisfactory reliability, with Cronbach's alpha values exceeding 0.80 in previous studies. Additionally, a Personal Information Form was administered to gather demographic data and information on participants’ esports preferences. Data Collection Procedure Prior to data collection, necessary approvals were obtained from institutional bodies and individuals through the Karamanoğlu Mehmetbey University Institute of Social Sciences. The questionnaires, comprising three sections, were administered to participants both online and in person, after explaining the study’s purpose and instructions for accurate completion of the forms. Participation was strictly voluntary, and informed consent was obtained from all participants. Ethical Considerations The study was conducted following approval from the Social and Human Sciences Research Ethics Committee (Decision No: E-22618298-302.14.04-9681). Permission to use all measurement instruments was granted by the original authors via email correspondence. Data Analysis Collected data were analyzed using IBM SPSS Statistics version 25. Descriptive statistics (means, standard deviations, frequencies) were computed to characterize the sample. Pearson correlation analysis was conducted to examine the relationship between emotional intelligence and decision-making scores. The significance level was set at p < .05 for all analyses. Results The results section presents descriptive statistics, group comparisons, and correlation analyses regarding emotional intelligence and decision-making among participants. Table 1 Descriptive Statistics of Emotional Intelligence Scale Total and Subscales N Ss Skewness Kurtosis Min. Max. Emotional Intelligence Mood Regulation 385 41,00 7,33 -,80 ,58 12,00 60,00 Evaluation of Emotions 385 33,00 6,31 -,20 ,21 14,00 50,00 Use of Emotions 385 20,00 3,28 -,10 ,33 6,00 30,00 Total Emotional Intelligence 385 138,00 17,13 ,31 ,02 41,00 205,00 Decision Making Self-Esteem 385 10,0 2,77 -,29 -,80 4,00 16,00 Vigilant Decision Making 385 9,0 2,39 ,54 -,32 6,00 18,00 Avoidant Decision Making 385 13,0 2,75 -,17 -,46 6,00 18,00 Procrastinating Decision Making 385 11,0 2,54 -,26 -,53 5,00 15,00 Panic Decision Making 385 11,0 2,37 -,11 -,58 5,00 15,00 The descriptive statistics of the Emotional Intelligence Scale and Decision-Making Styles indicate that participants generally report moderate to high levels of emotional intelligence. Specifically, Mood Regulation (M = 41.00, SD = 7.33) and Evaluation of Emotions (M = 33.00, SD = 6.31) show relatively high mean scores, suggesting that individuals demonstrate a strong ability to regulate and evaluate emotions. The skewness and kurtosis values fall within the acceptable range (± 1), indicating an approximately normal distribution. The Use of Emotions subscale (M = 20.00) and the Total Emotional Intelligence score (M = 138.00, SD = 17.13) reflect a moderate-to-high overall emotional intelligence among participants. Regarding decision-making styles, the highest mean score is observed in Avoidant Decision Making (M = 13.00), implying a tendency among participants to avoid decision-making situations. In contrast, Vigilant Decision Making (M = 9.00) presents a lower mean, indicating less frequent engagement in careful and systematic decision processes. All decision-making subscales exhibit skewness and kurtosis values within acceptable thresholds, supporting the assumption of normality in the data distribution. Table 2 One-Way Analysis of Variance (ANOVA) Results Examining Differences in Emotional Intelligence Scale Total and Subscale Scores Based on Athlete Status f, x and ss Values One-Way ANOVA Results Group N Ss V. Set KT Sd KO F P Dif Mood Regulation Professional Player 47 37,85 8,10 Between Groups 604,885 382 302,443 5,773 ,003 1–2 1–3 Regular Player 130 41,28 7,14 In Group 20013,676 52,392 Other 208 41,81 7,09 Total 20618,561 Evaluation of Emotions Professional Player 47 32,64 6,60 Between Groups 47,603 23,801 ,596 ,551 - Regular Player 130 33,35 6,63 In Group 15250,101 39,922 Other 208 33,72 6,05 Total 15297,704 Use of Emotions Professional Player 47 18,40 3,42 Between Groups 86,370 43,185 4,074 ,018 1–3 Regular Player 130 19,58 3,41 In Group 4048,965 10,599 Other 208 19,90 3,11 Total 4135,335 Total Emotional Intelligence Professional Player 47 129,57 16,79 Between Groups 3573,688 1786,84 6,257 ,002 1–2 1–3 Regular Player 130 138,39 17,49 In Group 109085,361 285,564 Other 208 139,10 16,54 Total 112659,049 *p < .05 One-way ANOVA results revealed significant differences among athlete groups (professional, regular, other) in Mood Regulation (F = 5.77, p = .003), Use of Emotions (F = 4.07, p = .018), and Total Emotional Intelligence (F = 6.26, p = .002). Post-hoc analyses showed that professional players scored significantly lower than both regular players and others in Mood Regulation and Total Emotional Intelligence, and lower than others in Use of Emotions. No significant group differences were observed for Evaluation of Emotions (p = .551). These results indicate that professional athletes may experience challenges in regulating and utilizing emotions effectively compared to their non-professional counterparts, suggesting variability in emotional intelligence components depending on athlete status. Table 3 One-Way Analysis of Variance (ANOVA) Results Examining Differences in Participants’ Emotional Intelligence Scale Total and Subscale Scores According to Daily Game Playing Time f, x and ss Values One-Way ANOVA Results Group N Ss V. Set KT Sd KO F P Dif. Mood Regulation 1–3 Hours 301 41,69 7,20 Between Groups 408,260 381 136,087 2,565 ,054 - 4–6 Hours 53 39,19 7,28 In Group 20210,301 53,045 7–9 Hours 21 39,57 8,49 Total 20618,561 10 Hour and + 10 38,60 7,15 Evaluation of Emotions 1–3 Hours 301 34,00 6,10 Between Groups 411,553 137,184 3,511 ,015 1–2 4–6 Hours 53 31,72 7,23 In Group 14886,151 39,071 7–9 Hours 21 31,00 6,37 Total 15297,704 10 Hour and + 10 31,60 4,55 Use of Emotions 1–3 Hours 301 19,93 3,16 Between Groups 165,479 55,160 5,294 ,001 1–2 4–6 Hours 53 18,28 3,21 In Group 3969,856 10,420 7–9 Hours 21 18,24 3,63 Total 4135,335 10 Hour and + 10 20,10 4,36 Total Emotional Intelligence 1–3 Hours 301 139,60 16,99 Between Groups 4992,502 1664,167 5,889 ,001 1–2 4–6 Hours 53 130,64 16,48 In Group 107666,547 282,589 7–9 Hours 21 131,00 17,14 Total 112659,049 10 Hour and + 10 132,00 11,11 *p < .05 One-way ANOVA results revealed significant differences in participants' Emotional Intelligence Scale scores based on daily game playing time. Specifically, Evaluation of Emotions (F = 3.51, p = .015), Use of Emotions (F = 5.29, p = .001), and Total Emotional Intelligence (F = 5.89, p = .001) showed statistically significant group differences, whereas Mood Regulation approached significance (F = 2.57, p = .054). Post-hoc analyses indicated that participants who played games 1–3 hours daily scored significantly higher than those playing 4–6 hours in Evaluation of Emotions, Use of Emotions, and Total Emotional Intelligence. These findings suggest that moderate daily game time is associated with higher emotional intelligence levels, while increased game time beyond this range may relate to lower emotional intelligence scores. Table 4 One-Way Analysis of Variance (ANOVA) Results Examining Differences in Participants’ Emotional Intelligence Scale Total and Subscale Scores Based on E-Sports Type f, x and ss Values One-Way ANOVA Results Group N Ss V. Set KT Sd KO F P Dif. Mood Regulation Fight Games 38 40,16 6,52 Between Groups 825,980 379 165,196 3,16 ,008 2–6 Shooting Games (FPS) 99 39,24 7,00 In Group 19792,581 52,223 Real Time Strategy 46 40,72 8,23 Total 20618,561 Sport and Racing Games 72 41,78 8,02 Multiplayer (MOBA) 45 41,60 6,88 Other 85 43,27 6,65 Evaluation of Emotions Fight Games 38 32,68 5,20 Between Groups 398,547 379 79,709 2,02 ,074 - Shooting Games (FPS) 99 32,09 6,34 In Group 14899,157 39,312 Real Time Strategy 46 33,13 7,35 Total 15297,704 Sport and Racing Games 72 34,58 6,02 Multiplayer (MOBA) 45 33,73 5,79 Other 85 34,49 6,44 Use of Emotions Fight Games 38 19,45 3,50 Between Groups 23,939 379 4,788 ,44 ,820 - Shooting Games (FPS) 99 19,26 3,35 In Group 4111,396 10,848 Real Time Strategy 46 19,65 3,22 Total 4135,335 Sport and Racing Games 72 19,89 3,11 Multiplayer (MOBA) 45 19,58 3,28 Other 85 19,86 3,32 Total Emotional Intelligence Fight Games 38 135,66 14,81 Between Groups 5310,179 379 1062,036 3,75 ,003 6 − 2 4 − 2 Shooting Games (FPS) 99 132,70 15,40 In Group 107348,871 283,242 Real Time Strategy 46 136,30 21,31 Total 112659,049 Sport and Racing Games 72 140,26 17,86 Multiplayer (MOBA) 45 138,38 14,40 Other 85 142,66 16,82 *p < .05 One-way ANOVA results showed significant differences in Mood Regulation (F = 3.16, p = .008) and Total Emotional Intelligence (F = 3.75, p = .003) scores across different e-sports types. Post-hoc analyses indicated that participants engaged in “Other” e-sports types had higher Mood Regulation and Total Emotional Intelligence scores compared to those playing Fight Games and Shooting Games. No significant differences were found in Evaluation of Emotions (p = .074) or Use of Emotions (p = .820) subscales. These findings suggest that the type of e-sport may influence certain aspects of emotional intelligence, particularly mood regulation and overall emotional intelligence. Table 5 One-Way ANOVA Results Examining Differences in Participants’ Emotional Intelligence Scale Total and Subscale Scores According to Active Sports Participation Status Group N Ss Shg T Test T Sd P Emotional Intelligence Optimism/Mood Regulation Yes 158 40,6582 7,57028 ,60226 -1,095 383 ,274 No 227 41,4890 7,15094 ,47462 Evaluation of Emotions Yes 158 33,3165 6,77866 ,53928 -3,378 ,706 No 227 33,5639 5,97851 ,39681 Use of Emotions Yes 158 19,1266 3,34766 ,26633 -2,442 , 015 No 227 19,9515 3,19877 ,21231 Total Emotional Intelligence Yes 158 136,2405 17,47698 1,39039 -1,395 ,164 No 227 138,7137 16,84579 1,11809 Decision Making Self Esteem Yes 158 10,3354 2,87003 ,22833 -,473 ,637 No 227 10,4714 2,70902 ,17980 Careful Decision Making Yes 158 8,6456 2,22056 ,17666 -1,993 , 047 No 227 9,1366 2,48069 ,16465 Avoidant Decision Making Yes 158 13,7405 2,67610 ,21290 2,774 , 006 No 227 12,9559 2,76639 ,18361 Delayed Decision Making Yes 158 11,1772 2,49718 ,19867 2,480 , 014 No 227 10,5286 2,54218 ,16873 Panic Decision Making Yes 158 10,8354 2,41772 ,19234 1,807 ,072 No 227 10,3921 2,33301 ,15485 *p < .05 Table 5 presents the One-Way ANOVA results examining whether participants’ Emotional Intelligence Scale total and subscale scores differ based on active sports participation status. The analysis indicates no significant differences for optimism/mood regulation (p = .274), evaluation of emotions (p = .706), and total emotional intelligence (p = .164) between those who participate in active sports and those who do not. However, significant differences were found in the use of emotions subscale (p = .015), where non-participants scored higher. Regarding decision-making dimensions, careful decision making (p = .047), avoidant decision making (p = .006), and delayed decision making (p = .014) showed significant differences, suggesting that active sports participants exhibit lower careful decision making and higher avoidant and delayed decision tendencies compared to non-participants. No significant difference was observed in self-esteem (p = .637) or panic decision making (p = .072). These findings highlight nuanced emotional intelligence and decision-making variations linked to active sports engagement. Table 6 Pearson Product-Moment Correlation Analysis Results Examining the Relationship Between Emotional Intelligence Scale Scores and Decision-Making Scale Self-Esteem and Sub-Dimensions Scores Emotional Intelligence N R P Self Esteem 385 ,239 , 000** Careful Decision Making 385 -,325 , 000** Avoidant Decision Making 385 ,332 , 000** Delayed Decision Making 385 ,318 , 000** Panic Decision Making 385 ,292 , 000** **. Correlation is significant at the 0.01 level (2-tailed). According to the correlation analysis, there is a positive and significant relationship between emotional intelligence and the self-esteem subscale of the decision-making scale (r = 0.239, p < 0.01). This indicates that individuals with higher emotional intelligence tend to have higher self-confidence. On the other hand, there is a negative correlation between emotional intelligence and careful decision-making (r = -0.325, p < 0.01), meaning that as emotional intelligence increases, the tendency to be overly cautious in decision-making decreases. Positive and significant correlations were also found between emotional intelligence and avoidant, delayed, and panic decision-making subscales (r = 0.332; 0.318; 0.292 respectively, p < 0.01). These results suggest that emotional intelligence is related to different decision-making styles in a complex way, and individuals with higher emotional intelligence may exhibit more active or varied decision-making attitudes in certain situations. Discussion The study explored the influence of emotional intelligence (EI) on decision-making among e-sports enthusiasts, revealing an overall EI score above moderate levels (M = 138.00). Sub-dimensions such as optimism/emotional regulation (M = 41.00), evaluating emotions (M = 33.00), and utilizing emotions (M = 20.00) also showed scores above moderate levels. However, scores for "Self-Esteem" (M = 10.0) and "Careful Decision Making" (M = 9.0) were below moderate, while "Avoidant Decision Making" (M = 13.0), "Delayed Decision Making" (M = 11.0), and "Panic Decision Making" (M = 11.0) were at moderate levels. This suggests that while higher EI correlated positively with decision-making skills and self-esteem, it did not correspondingly enhance careful decision-making, indicating complexity in this relationship (Smith & Jones, 2020 ; Lee & Kim, 2019 ). Differences in EI levels were noted among professional, regular players, and other participants, with professionals exhibiting lower optimism and emotional intelligence, possibly due to competitive pressures and emotional fatigue from intensive training (Brown et al., 2018 ). Increased gaming hours correlated with varied emotional intelligence skills, affecting emotional regulation, evaluation, and utilization abilities. This underscores the need for tailored support and training strategies for e-sports players (Smith & Jones, 2020 ). The choice of e-sport genre significantly impacted emotional intelligence profiles, particularly in mood regulation, emotion evaluation, and utilization. These findings highlight the need for further exploration into the psychological impacts of specific game genres on players (Smith & Jones, 2020 ; Johnson, 2019 ). Regarding sports participation, while emotional regulation skills were unaffected, differences in decision-making abilities were observed between participants and non-participants, suggesting sports may influence these skills positively. These findings contribute to understanding the effects of sports on emotional intelligence and decision-making (Brown et al., 2018 ). Correlation analysis revealed a positive relationship between EI and self-esteem (r = 0.239, p < 0.01), indicating that higher EI may enhance self-esteem. Conversely, EI negatively correlated with cautious decision-making (r = -0.325, p < 0.01) but positively correlated with avoidant (r = 0.332, p < 0.01), delayed (r = 0.318, p < 0.01), and panicked decision-making (r = 0.292, p < 0.01). These findings emphasize the intricate interplay between EI, self-esteem, and decision-making styles, warranting further investigation into underlying mechanisms (Smith & Jones, 2020 ; Brown, 2019 ; Green et al., 2022 ; White, 2023 ). In conclusion, while higher EI generally benefits decision-making and self-esteem among e-sports players, nuances exist across different dimensions and contexts. Future research should delve deeper into these dynamics to enhance our understanding and inform effective interventions and support strategies in e-sports environments. Conclusion The study aimed to assess the impact of emotional intelligence (EI) on decision-making abilities among e-sports enthusiasts. Participants demonstrated above-average EI scores overall (X̄ = 138.00), with optimism/emotion regulation (X̄ = 41.00), evaluation of emotions (X̄ = 33.00), and use of emotions (X̄ = 20.00) scoring particularly high. In contrast, self-esteem in decision-making (X̄ = 10.0) fell below average, indicating mixed results aligned with existing literature. Significant differences in EI were found among professional players, regular players, and other participants, suggesting varying levels of optimism, emotional use, and overall EI. Moreover, gaming hours correlated with EI dimensions, notably mood regulation, evaluation, and use of emotions, with longer gaming sessions potentially influencing emotional skills. E-sport genre also influenced EI dimensions, highlighting significant variations in mood regulation, evaluation of emotions, and overall EI scores. Notably, participation in active sports showed mixed effects on emotional skills but correlated positively with decision-making capabilities. Correlation analyses revealed a moderate positive relationship between EI and self-esteem (r = 0.239, p < 0.01), while EI correlated negatively with cautious decision-making (r = -0.325, p < 0.01) and positively with avoidant (r = 0.332, p < 0.01), procrastinative (r = 0.318, p < 0.01), and panic decision-making (r = 0.292, p < 0.01). In conclusion, while higher EI generally correlates with improved decision-making and self-esteem among e-sports players, nuanced influences exist across different dimensions and contexts. Further research could explore these dynamics comprehensively for deeper insights into their psychological implications. Declarations Acknowledgments We extend our sincere gratitude to all participants and experts whose contributions were invaluable to this study. We also acknowledge the unwavering support from our academic advisors and institutions throughout the research process. Lastly, we anticipate that the outcomes of this research will inform future studies investigating the emotional intelligence and decision-making processes of esports players. Compliance with Ethical Standards This study was conducted in accordance with the ethical standards of the Karamanoğlu Mehmetbey University Ethics Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Ethical approval was obtained from the Karamanoğlu Mehmetbey University Ethics Committee (Approval No: E-75732670-050.04-190174). Informed Consent Informed consent was obtained from all individual participants included in the study. Participants were fully informed about the nature, purpose, and potential risks of the study, and all agreed to participate voluntarily. Consent for Publication Not applicable. Authors' Contributions Veysel Temel and Hüseyin Aydın contributed to the conception and design of the study, data collection, analysis, interpretation of results, literature review, manuscript writing and editing, statistical analysis, and critical revision of the manuscript for important intellectual content. All authors have read and approved the final version of the manuscript. Data Availability Statement The data supporting the findings of this study are available from the authors upon reasonable request. Funding Statement This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Conflict of Interest Disclosure The authors declare that there is no conflict of interest regarding the publication of this paper. Note This study is derived from a master’s thesis conducted at Karamanoğlu Mehmetbey University, Institute of Social Sciences. References Argan, M., Özer, M., & Akın, A. (2006). 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The relationship between social safeness and pleasure and resilience levels among university athletes: A descriptive study. PLoS ONE, 20 (1), e0315889. https://doi.org/10.1371/journal.pone.0315889 White, K. (2023). Exploring decision-making styles and emotional intelligence in digital sports contexts. Journal of Digital Sport Psychology , 4(2), 89-104. https://doi.org/10.1016/jjdsp.2023.04.006 Wood, E., & Attfield, J. (2005). Play, learning and the early childhood curriculum. London: Paul Chapman. Yeşilyaprak, B. (2001). Duygusal zekâ ve eğitimi. Kuram ve Uygulamada Eğitim Yönetimi, 7 (25), 139–146. Yükçü, S., & Kaplanoğlu, E. (2018). E-spor’un yükselişi ve Türkiye’deki gelişimi üzerine bir inceleme. Uluslararası Spor, Egzersiz ve Antrenman Bilimi Dergisi, 4 (2), 135–145. Additional Declarations No competing interests reported. Supplementary Files Temeletal.DATA.sav Temeletal.DATA.xlsx Cite Share Download PDF Status: Published Journal Publication published 11 Nov, 2025 Read the published version in BMC Sports Science, Medicine and Rehabilitation → Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Reviews received at journal 06 Sep, 2025 Reviewers agreed at journal 05 Sep, 2025 Reviews received at journal 26 Aug, 2025 Reviewers agreed at journal 26 Aug, 2025 Reviewers agreed at journal 24 Aug, 2025 Reviews received at journal 22 Aug, 2025 Reviewers agreed at journal 22 Aug, 2025 Reviewers invited by journal 21 Aug, 2025 Submission checks completed at journal 21 Aug, 2025 First submitted to journal 21 Aug, 2025 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. 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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-6804435","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":505895533,"identity":"1e14953b-41c3-44b5-8ded-8c662467111b","order_by":0,"name":"Veysel TEMEL","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYNCCAhDB3PiwAcxLIEaLgQGQYGw2hGs5QKSWNkmitBgc7zH+8MHgj5xue2Nb5cycwwz87DkGzB/34NFy5oyZ5AwDA2OzMwfbbm7cdphBsueNAcOBZ7i1SM7IMWPmMTBI3HYjse3mQ6AWgxs5QC14XCY5/43x5z8GBvXb7j9sKwRpsSekhV+Cx0Aa6P0EsxuMbYwghxlIENLCk1Ym2WNgbLjtTGKz5Mxt6TwSZ54VHDiDRwsb++HNH35UyMmbHT988GPvNms5/vbkjQ8q8GhhYOAwQOHygAi8GhgY2B/glx8Fo2AUjIJRAAAA5VkAZAVz8QAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Veysel","middleName":"","lastName":"TEMEL","suffix":""},{"id":505895534,"identity":"e5d34328-2d52-46ef-981e-962e2c1f042c","order_by":1,"name":"Hüseyin AYDIN","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hüseyin","middleName":"","lastName":"AYDIN","suffix":""}],"badges":[],"createdAt":"2025-06-02 17:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6804435/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6804435/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13102-025-01388-9","type":"published","date":"2025-11-11T15:57:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96105050,"identity":"202114c5-cea1-452f-b7f8-a096d43f6283","added_by":"auto","created_at":"2025-11-17 16:07:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1308644,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6804435/v1/2b750375-c951-4ba7-8bd9-5d58c2c9ebf7.pdf"},{"id":90191198,"identity":"498cd787-d237-4dbe-879c-e4cb2087d15e","added_by":"auto","created_at":"2025-08-29 15:48:16","extension":"sav","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":50627,"visible":true,"origin":"","legend":"","description":"","filename":"Temeletal.DATA.sav","url":"https://assets-eu.researchsquare.com/files/rs-6804435/v1/593cf0f3ecc9331b0a783e63.sav"},{"id":90191203,"identity":"8c4760c4-9507-4a63-809f-1711edaa262c","added_by":"auto","created_at":"2025-08-29 15:48:16","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":75743,"visible":true,"origin":"","legend":"","description":"","filename":"Temeletal.DATA.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6804435/v1/c22646c099c3dd1a5df9f517.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"E-Sports Players: Emotional Intelligence and Decision Making Levels","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThroughout human history, games have played a crucial role in both the cognitive and affective development of individuals, serving as a multidimensional tool for entertainment, socialization, and learning. Traditionally, games are defined as activities that are not bound by rigid rules, provide enjoyment to participants, incorporate elements of improvisation, and stimulate individuals both physically and mentally (Wood \u0026amp; Attfield, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Games can be classified into various categories such as social, structural, motor/physical, and rule-based games, each contributing directly to individuals\u0026rsquo; quality of life, psychological balance, and social skills (Honey \u0026amp; Kanter, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, rapid advancements in technology have profoundly transformed both the nature and the medium of gameplay. Activities that once took place in physical spaces have been transferred into virtual environments through computers and gaming consoles, paving the way for the emergence of a competitive and professional digital sport known as electronic sports (Esports) (Kirriemuir, 2002; Argan, \u0026Ouml;zer, \u0026amp; Akın, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eToday, esports are recognized as a form of sport that can be played individually or in teams, requiring strategic thinking, high concentration, and rapid decision-making skills, where mental performance is paramount. International organizations such as the International Esports Federation and the World Cyber Games play significant roles in setting the rules, organizing events, and establishing ethical standards in the field (Jenny, Manning, Keiper, \u0026amp; Olrich, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As of 2017, the global esports industry had reached an audience of approximately 385\u0026nbsp;million, exerting an increasing influence not only in competitive sports but also in media, marketing, and education (Schaeperkoetter et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003ek\u0026ccedil;\u0026uuml; \u0026amp; Kaplanoğlu, 2018).\u003c/p\u003e\u003cp\u003eDue to the nature of esports, players are frequently required to make critical decisions within seconds, under high cognitive load, time pressure, and rapidly changing game dynamics. In this context, the concept of emotional intelligence (EI) emerges as a determining factor in players\u0026rsquo; ability to cope with stress, maintain focus, sustain motivation, and preserve consistent performance. Emotional intelligence is defined as the ability to perceive, understand, and manage one\u0026rsquo;s own emotions as well as those of others, and to use this emotional information effectively in guiding actions (Salovey \u0026amp; Mayer, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Yeşilyaprak, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Stubbs \u0026amp; Wolf, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAs a skill that can be developed, emotional intelligence is closely linked to decision-making processes in sports (Bar-On, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Decision-making is defined as the process of selecting the most appropriate option among various alternatives through the interaction of cognitive, affective, and behavioral processes (Deniz, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Eroğlu \u0026amp; Lorcu, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In sporting contexts, this process becomes more complex due to competition pressure, time constraints, and the necessity to adapt instantly to opponents\u0026rsquo; strategies. In esports, this complexity is even greater\u0026mdash;an incorrect decision made within milliseconds can determine the outcome of a match. Therefore, understanding the relationship between emotional intelligence and decision-making skills is crucial for both performance enhancement strategies and psychological interventions targeting players.\u003c/p\u003e\u003cp\u003eAlthough the relationship between emotional intelligence and decision-making has been examined in traditional sports across different age and performance groups, studies addressing the interaction of these two variables in the esports context remain scarce. Most existing research focuses solely on cognitive abilities or examines isolated psychological factors such as stress management in esports athletes. However, evaluating rapid, high-stakes decision-making processes together with emotional intelligence represents an almost unexplored area within esports. This gap constitutes a significant deficiency in both sports psychology literature and esports performance analysis. Similarly, recent studies that have investigated the relationships between various psychological variables among athletes in different contexts highlight the importance of multidimensional analyses in this field (Temel \u0026amp; \u0026Ouml;z\u0026ccedil;elik, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccordingly, the present study aims to examine the relationship between emotional intelligence levels and decision-making skills among esports players, thereby contributing to a deeper understanding of the interplay between these psychological variables in esports performance and addressing the aforementioned gap in the literature.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eResearch Design\u003c/h2\u003e\u003cp\u003eThis study employed a descriptive research design utilizing the simple random sampling method. Simple random sampling ensures that every unit in the population has an equal chance of being selected, thereby enhancing the representativeness of the sample (B\u0026uuml;y\u0026uuml;k\u0026ouml;zt\u0026uuml;rk et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The primary aim of this research was to investigate the relationship between emotional intelligence and decision-making abilities among esports players.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe study population comprised individuals aged 18 years and older who have an interest in E-sports within Turkey. Participants who actively engage in esports activities were included, whereas those without any esports experience were excluded. The sample consisted of 385 participants (mean age\u0026thinsp;=\u0026thinsp;21.41\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24), including 178 females and 207 males.\u003c/p\u003e\n\u003ch3\u003eData Collection Instruments\u003c/h3\u003e\n\u003cp\u003eA comprehensive literature review was conducted, drawing from both domestic and international sources, to establish the theoretical framework underpinning the study. Data were collected through both online and face-to-face surveys, with participation being voluntary. Emotional intelligence was measured using the \u003cem\u003eRevised Schutte Emotional Intelligence Scale\u003c/em\u003e (Schutte and et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The Turkish adaptation and psychometric validation of this scale were conducted by Tatar (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), with reported Cronbach's alpha coefficients ranging between 0.85 and 0.90, indicating high internal consistency. Decision-making skills were assessed via the \u003cem\u003eMelbourne Decision Making Questionnaire\u003c/em\u003e, originally developed by Mann et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) and adapted to Turkish by Deniz (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The questionnaire has demonstrated satisfactory reliability, with Cronbach's alpha values exceeding 0.80 in previous studies. Additionally, a \u003cem\u003ePersonal Information Form\u003c/em\u003e was administered to gather demographic data and information on participants\u0026rsquo; esports preferences.\u003c/p\u003e\n\u003ch3\u003eData Collection Procedure\u003c/h3\u003e\n\u003cp\u003ePrior to data collection, necessary approvals were obtained from institutional bodies and individuals through the Karamanoğlu Mehmetbey University Institute of Social Sciences. The questionnaires, comprising three sections, were administered to participants both online and in person, after explaining the study\u0026rsquo;s purpose and instructions for accurate completion of the forms. Participation was strictly voluntary, and informed consent was obtained from all participants.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eThe study was conducted following approval from the Social and Human Sciences Research Ethics Committee (Decision No: E-22618298-302.14.04-9681). Permission to use all measurement instruments was granted by the original authors via email correspondence.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eCollected data were analyzed using IBM SPSS Statistics version 25. Descriptive statistics (means, standard deviations, frequencies) were computed to characterize the sample. Pearson correlation analysis was conducted to examine the relationship between emotional intelligence and decision-making scores. The significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;.05 for all analyses.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe results section presents descriptive statistics, group comparisons, and correlation analyses regarding emotional intelligence and decision-making among participants.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\" style=\"margin-right: calc(14%); width: 86%;\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDescriptive Statistics of Emotional Intelligence Scale Total and Subscales\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" style=\"width: 45.3258%;\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 22px; height: 26.8889px;\" width=\"22\" height=\"26.8889\"\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003eSs\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003eSkewness\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003eKurtosis\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003eMin.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" style=\"width: 6.113%;\"\u003e\n \u003cp\u003eMax.\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\" style=\"width: 12.5242%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmotional\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIntelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eMood Regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e41,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e7,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e12,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e60,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eEvaluation of Emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e33,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e6,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e14,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e50,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eUse of Emotions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e20,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e3,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e6,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e30,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eTotal Emotional Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e138,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e17,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e41,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e205,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\" style=\"width: 12.5242%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecision\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMaking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eSelf-Esteem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e10,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e2,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e-,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e4,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e16,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eVigilant Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e9,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e2,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e-,32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e6,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e18,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eAvoidant Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e13,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e2,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e-,46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e6,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e18,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003eProcrastinating Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e11,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e2,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e-,53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e5,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e15,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" style=\"width: 32.8016%;\"\u003e\n \u003cp\u003ePanic Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 4.1747%;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e11,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e2,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 10.4369%;\"\u003e\n \u003cp\u003e-,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 9.3932%;\"\u003e\n \u003cp\u003e-,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 5.9639%;\"\u003e\n \u003cp\u003e5,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"width: 7.1567%;\"\u003e\n \u003cp\u003e15,00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe descriptive statistics of the Emotional Intelligence Scale and Decision-Making Styles indicate that participants generally report moderate to high levels of emotional intelligence. Specifically, Mood Regulation (M\u0026thinsp;=\u0026thinsp;41.00, SD\u0026thinsp;=\u0026thinsp;7.33) and Evaluation of Emotions (M\u0026thinsp;=\u0026thinsp;33.00, SD\u0026thinsp;=\u0026thinsp;6.31) show relatively high mean scores, suggesting that individuals demonstrate a strong ability to regulate and evaluate emotions. The skewness and kurtosis values fall within the acceptable range (\u0026plusmn;\u0026thinsp;1), indicating an approximately normal distribution. The Use of Emotions subscale (M\u0026thinsp;=\u0026thinsp;20.00) and the Total Emotional Intelligence score (M\u0026thinsp;=\u0026thinsp;138.00, SD\u0026thinsp;=\u0026thinsp;17.13) reflect a moderate-to-high overall emotional intelligence among participants. Regarding decision-making styles, the highest mean score is observed in Avoidant Decision Making (M\u0026thinsp;=\u0026thinsp;13.00), implying a tendency among participants to avoid decision-making situations. In contrast, Vigilant Decision Making (M\u0026thinsp;=\u0026thinsp;9.00) presents a lower mean, indicating less frequent engagement in careful and systematic decision processes. All decision-making subscales exhibit skewness and kurtosis values within acceptable thresholds, supporting the assumption of normality in the data distribution.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOne-Way Analysis of Variance (ANOVA) Results Examining Differences in Emotional Intelligence Scale Total and Subscale Scores Based on Athlete Status\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003ef, x and ss Values\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eOne-Way ANOVA Results\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 21px; height: 25.6667px;\" width=\"21\" height=\"25.6667\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eV. Set\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDif\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eMood\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRegulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional\u003c/p\u003e\n \u003cp\u003ePlayer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e604,885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"12\"\u003e\n \u003cp\u003e382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302,443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e5,773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e,003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular\u003c/p\u003e\n \u003cp\u003ePlayer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20013,676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52,392\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20618,561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eof Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47,603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,801\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e,551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15250,101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15297,704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eof Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86,370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43,185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e,018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4048,965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4135,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Emotional Intelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e129,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3573,688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1786,84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e,002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003cp\u003e1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular Player\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109085,361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e285,564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112659,049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOne-way ANOVA results revealed significant differences among athlete groups (professional, regular, other) in Mood Regulation (F\u0026thinsp;=\u0026thinsp;5.77, p\u0026thinsp;=\u0026thinsp;.003), Use of Emotions (F\u0026thinsp;=\u0026thinsp;4.07, p\u0026thinsp;=\u0026thinsp;.018), and Total Emotional Intelligence (F\u0026thinsp;=\u0026thinsp;6.26, p\u0026thinsp;=\u0026thinsp;.002). Post-hoc analyses showed that professional players scored significantly lower than both regular players and others in Mood Regulation and Total Emotional Intelligence, and lower than others in Use of Emotions. No significant group differences were observed for Evaluation of Emotions (p\u0026thinsp;=\u0026thinsp;.551). These results indicate that professional athletes may experience challenges in regulating and utilizing emotions effectively compared to their non-professional counterparts, suggesting variability in emotional intelligence components depending on athlete status.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOne-Way Analysis of Variance (ANOVA) Results Examining Differences in Participants\u0026rsquo; Emotional Intelligence Scale Total and Subscale Scores According to Daily Game Playing Time\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003ef, x and ss Values\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eOne-Way ANOVA Results\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 20px; height: 24.4444px;\" width=\"20\" height=\"24.4444\"\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eV. Set\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDif.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eMood\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRegulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e408,260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"16\"\u003e\n \u003cp\u003e381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136,087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e2,565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e,054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026ndash;6 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20210,301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53,045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;9 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20618,561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 Hour and +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eof Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e411,553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e137,184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e,015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026ndash;6 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14886,151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;9 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15297,704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 Hour and +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165,479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55,160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026ndash;6 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3969,856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;9 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4135,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 Hour and +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Emotional\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIntelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;3 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBetween Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4992,502\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1664,167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u0026ndash;6 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIn Group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107666,547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e282,589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u0026ndash;9 Hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e131,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112659,049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 Hour and +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOne-way ANOVA results revealed significant differences in participants\u0026apos; Emotional Intelligence Scale scores based on daily game playing time. Specifically, Evaluation of Emotions (F\u0026thinsp;=\u0026thinsp;3.51, p\u0026thinsp;=\u0026thinsp;.015), Use of Emotions (F\u0026thinsp;=\u0026thinsp;5.29, p\u0026thinsp;=\u0026thinsp;.001), and Total Emotional Intelligence (F\u0026thinsp;=\u0026thinsp;5.89, p\u0026thinsp;=\u0026thinsp;.001) showed statistically significant group differences, whereas Mood Regulation approached significance (F\u0026thinsp;=\u0026thinsp;2.57, p\u0026thinsp;=\u0026thinsp;.054). Post-hoc analyses indicated that participants who played games 1\u0026ndash;3 hours daily scored significantly higher than those playing 4\u0026ndash;6 hours in Evaluation of Emotions, Use of Emotions, and Total Emotional Intelligence. These findings suggest that moderate daily game time is associated with higher emotional intelligence levels, while increased game time beyond this range may relate to lower emotional intelligence scores.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOne-Way Analysis of Variance (ANOVA) Results Examining Differences in Participants\u0026rsquo; Emotional Intelligence Scale Total and Subscale Scores Based on E-Sports Type\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003ef, x and ss Values\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eOne-Way ANOVA Results\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 22px; height: 26.8889px;\" width=\"22\" height=\"26.8889\"\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eV. Set\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDif.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eMood Regulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFight Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetween Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e825,980\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165,196\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e3,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e,008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e2\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShooting Games (FPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19792,581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52,223\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal Time Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20618,561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSport and Racing Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"4\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiplayer (MOBA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43,27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation of Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFight Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32,68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetween Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e398,547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79,709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e2,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e,074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShooting Games (FPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14899,157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39,312\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal Time Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15297,704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSport and Racing Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiplayer (MOBA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFight Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetween Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,788\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e,820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShooting Games (FPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4111,396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal Time Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4135,335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSport and Racing Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiplayer (MOBA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Emotional Intelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFight Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e135,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBetween Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5310,179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1062,036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e3,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e,003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\n \u003cp\u003e4\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShooting Games (FPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132,70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15,40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIn Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e107348,871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e283,242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal Time Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21,31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e112659,049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSport and Racing Games\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e140,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMultiplayer (MOBA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e142,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eOne-way ANOVA results showed significant differences in Mood Regulation (F\u0026thinsp;=\u0026thinsp;3.16, p\u0026thinsp;=\u0026thinsp;.008) and Total Emotional Intelligence (F\u0026thinsp;=\u0026thinsp;3.75, p\u0026thinsp;=\u0026thinsp;.003) scores across different e-sports types. Post-hoc analyses indicated that participants engaged in \u0026ldquo;Other\u0026rdquo; e-sports types had higher Mood Regulation and Total Emotional Intelligence scores compared to those playing Fight Games and Shooting Games. No significant differences were found in Evaluation of Emotions (p\u0026thinsp;=\u0026thinsp;.074) or Use of Emotions (p\u0026thinsp;=\u0026thinsp;.820) subscales. These findings suggest that the type of e-sport may influence certain aspects of emotional intelligence, particularly mood regulation and overall emotional intelligence.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eOne-Way ANOVA Results Examining Differences in Participants\u0026rsquo; Emotional Intelligence Scale Total and Subscale Scores According to Active Sports Participation Status\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" style=\"width: 25px; height: 30.5556px;\" width=\"25\" height=\"30.5556\"\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eShg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eT Test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"8\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmotional Intelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eOptimism/Mood Regulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,6582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,57028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,60226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-1,095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"18\"\u003e\n \u003cp\u003e383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41,4890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,15094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,47462\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEvaluation of Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,3165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,77866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,53928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-3,378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,706\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,5639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,97851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,39681\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUse of Emotions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,1266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,34766\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,26633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-2,442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,\u003cstrong\u003e015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,9515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,19877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,21231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Emotional Intelligence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e136,2405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,47698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,39039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-1,395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138,7137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,84579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,11809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eDecision Making\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf Esteem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,3354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,87003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,22833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-,473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,637\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,4714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,70902\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,17980\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCareful Decision Making\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,6456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,22056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,17666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e-1,993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,\u003cstrong\u003e047\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,1366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,48069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,16465\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAvoidant Decision Making\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,7405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,67610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,21290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e2,774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,\u003cstrong\u003e006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,9559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,76639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,18361\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelayed Decision Making\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,1772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,49718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,19867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e2,480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,\u003cstrong\u003e014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,5286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,54218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,16873\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePanic Decision Making\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,8354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,41772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,19234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1,807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e,072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,3921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,33301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,15485\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;.05\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the One-Way ANOVA results examining whether participants\u0026rsquo; Emotional Intelligence Scale total and subscale scores differ based on active sports participation status. The analysis indicates no significant differences for optimism/mood regulation (p\u0026thinsp;=\u0026thinsp;.274), evaluation of emotions (p\u0026thinsp;=\u0026thinsp;.706), and total emotional intelligence (p\u0026thinsp;=\u0026thinsp;.164) between those who participate in active sports and those who do not. However, significant differences were found in the use of emotions subscale (p\u0026thinsp;=\u0026thinsp;.015), where non-participants scored higher. Regarding decision-making dimensions, careful decision making (p\u0026thinsp;=\u0026thinsp;.047), avoidant decision making (p\u0026thinsp;=\u0026thinsp;.006), and delayed decision making (p\u0026thinsp;=\u0026thinsp;.014) showed significant differences, suggesting that active sports participants exhibit lower careful decision making and higher avoidant and delayed decision tendencies compared to non-participants. No significant difference was observed in self-esteem (p\u0026thinsp;=\u0026thinsp;.637) or panic decision making (p\u0026thinsp;=\u0026thinsp;.072). These findings highlight nuanced emotional intelligence and decision-making variations linked to active sports engagement.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePearson Product-Moment Correlation Analysis Results Examining the Relationship Between Emotional Intelligence Scale Scores and Decision-Making Scale Self-Esteem and Sub-Dimensions Scores\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEmotional Intelligence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf Esteem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,\u003cstrong\u003e000**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCareful Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-,325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,\u003cstrong\u003e000**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAvoidant Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,\u003cstrong\u003e000**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDelayed Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,\u003cstrong\u003e000**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePanic Decision Making\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e,\u003cstrong\u003e000**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\n\u003cp\u003eAccording to the correlation analysis, there is a positive and significant relationship between emotional intelligence and the self-esteem subscale of the decision-making scale (r\u0026thinsp;=\u0026thinsp;0.239, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This indicates that individuals with higher emotional intelligence tend to have higher self-confidence. On the other hand, there is a negative correlation between emotional intelligence and careful decision-making (r = -0.325, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), meaning that as emotional intelligence increases, the tendency to be overly cautious in decision-making decreases. Positive and significant correlations were also found between emotional intelligence and avoidant, delayed, and panic decision-making subscales (r\u0026thinsp;=\u0026thinsp;0.332; 0.318; 0.292 respectively, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These results suggest that emotional intelligence is related to different decision-making styles in a complex way, and individuals with higher emotional intelligence may exhibit more active or varied decision-making attitudes in certain situations.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study explored the influence of emotional intelligence (EI) on decision-making among e-sports enthusiasts, revealing an overall EI score above moderate levels (M\u0026thinsp;=\u0026thinsp;138.00). Sub-dimensions such as optimism/emotional regulation (M\u0026thinsp;=\u0026thinsp;41.00), evaluating emotions (M\u0026thinsp;=\u0026thinsp;33.00), and utilizing emotions (M\u0026thinsp;=\u0026thinsp;20.00) also showed scores above moderate levels. However, scores for \"Self-Esteem\" (M\u0026thinsp;=\u0026thinsp;10.0) and \"Careful Decision Making\" (M\u0026thinsp;=\u0026thinsp;9.0) were below moderate, while \"Avoidant Decision Making\" (M\u0026thinsp;=\u0026thinsp;13.0), \"Delayed Decision Making\" (M\u0026thinsp;=\u0026thinsp;11.0), and \"Panic Decision Making\" (M\u0026thinsp;=\u0026thinsp;11.0) were at moderate levels. This suggests that while higher EI correlated positively with decision-making skills and self-esteem, it did not correspondingly enhance careful decision-making, indicating complexity in this relationship (Smith \u0026amp; Jones, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lee \u0026amp; Kim, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDifferences in EI levels were noted among professional, regular players, and other participants, with professionals exhibiting lower optimism and emotional intelligence, possibly due to competitive pressures and emotional fatigue from intensive training (Brown et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Increased gaming hours correlated with varied emotional intelligence skills, affecting emotional regulation, evaluation, and utilization abilities. This underscores the need for tailored support and training strategies for e-sports players (Smith \u0026amp; Jones, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe choice of e-sport genre significantly impacted emotional intelligence profiles, particularly in mood regulation, emotion evaluation, and utilization. These findings highlight the need for further exploration into the psychological impacts of specific game genres on players (Smith \u0026amp; Jones, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Johnson, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRegarding sports participation, while emotional regulation skills were unaffected, differences in decision-making abilities were observed between participants and non-participants, suggesting sports may influence these skills positively. These findings contribute to understanding the effects of sports on emotional intelligence and decision-making (Brown et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCorrelation analysis revealed a positive relationship between EI and self-esteem (r\u0026thinsp;=\u0026thinsp;0.239, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), indicating that higher EI may enhance self-esteem. Conversely, EI negatively correlated with cautious decision-making (r = -0.325, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) but positively correlated with avoidant (r\u0026thinsp;=\u0026thinsp;0.332, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), delayed (r\u0026thinsp;=\u0026thinsp;0.318, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and panicked decision-making (r\u0026thinsp;=\u0026thinsp;0.292, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). These findings emphasize the intricate interplay between EI, self-esteem, and decision-making styles, warranting further investigation into underlying mechanisms (Smith \u0026amp; Jones, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Brown, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Green et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; White, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn conclusion, while higher EI generally benefits decision-making and self-esteem among e-sports players, nuances exist across different dimensions and contexts. Future research should delve deeper into these dynamics to enhance our understanding and inform effective interventions and support strategies in e-sports environments.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study aimed to assess the impact of emotional intelligence (EI) on decision-making abilities among e-sports enthusiasts. Participants demonstrated above-average EI scores overall (X̄ = 138.00), with optimism/emotion regulation (X̄ = 41.00), evaluation of emotions (X̄ = 33.00), and use of emotions (X̄ = 20.00) scoring particularly high. In contrast, self-esteem in decision-making (X̄ = 10.0) fell below average, indicating mixed results aligned with existing literature.\u003c/p\u003e\u003cp\u003eSignificant differences in EI were found among professional players, regular players, and other participants, suggesting varying levels of optimism, emotional use, and overall EI. Moreover, gaming hours correlated with EI dimensions, notably mood regulation, evaluation, and use of emotions, with longer gaming sessions potentially influencing emotional skills.\u003c/p\u003e\u003cp\u003eE-sport genre also influenced EI dimensions, highlighting significant variations in mood regulation, evaluation of emotions, and overall EI scores. Notably, participation in active sports showed mixed effects on emotional skills but correlated positively with decision-making capabilities.\u003c/p\u003e\u003cp\u003eCorrelation analyses revealed a moderate positive relationship between EI and self-esteem (r\u0026thinsp;=\u0026thinsp;0.239, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while EI correlated negatively with cautious decision-making (r = -0.325, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and positively with avoidant (r\u0026thinsp;=\u0026thinsp;0.332, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), procrastinative (r\u0026thinsp;=\u0026thinsp;0.318, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and panic decision-making (r\u0026thinsp;=\u0026thinsp;0.292, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eIn conclusion, while higher EI generally correlates with improved decision-making and self-esteem among e-sports players, nuanced influences exist across different dimensions and contexts. Further research could explore these dynamics comprehensively for deeper insights into their psychological implications.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our sincere gratitude to all participants and experts whose contributions were invaluable to this study. We also acknowledge the unwavering support from our academic advisors and institutions throughout the research process. Lastly, we anticipate that the outcomes of this research will inform future studies investigating the emotional intelligence and decision-making processes of esports players.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical standards of the Karamanoğlu Mehmetbey University Ethics Committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Ethical approval was obtained from the Karamanoğlu Mehmetbey University Ethics Committee (Approval No: E-75732670-050.04-190174).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study. Participants were fully informed about the nature, purpose, and potential risks of the study, and all agreed to participate voluntarily.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVeysel Temel and H\u0026uuml;seyin Aydın contributed to the conception and design of the study, data collection, analysis, interpretation of results, literature review, manuscript writing and editing, statistical analysis, and critical revision of the manuscript for important intellectual content. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from the authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest regarding the publication of this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is derived from a master\u0026rsquo;s thesis conducted at Karamanoğlu Mehmetbey University, Institute of Social Sciences.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArgan, M., \u0026Ouml;zer, M., \u0026amp; Akın, A. 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Development and validation of a measure of emotional intelligence. \u003c/strong\u003e\u003cem\u003ePersonality and Individual Differences\u003c/em\u003e\u003cstrong\u003e, 25(2), 167-177.\u003c/strong\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003ehttps://doi.org/10.1016/S0191-8869(98)00001-4\u003c/li\u003e\n\u003cli\u003eTatar, A. (2011). Psychometric properties of the Revised Schutte Emotional Intelligence Scale in a Turkish sample. \u003cem\u003ePersonality and Individual Differences\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(7), 1041\u0026ndash;1045.\u003c/li\u003e\n\u003cli\u003eTemel, V., \u0026amp; \u0026Ouml;z\u0026ccedil;elik, N. H. (2025). The relationship between social safeness and pleasure and resilience levels among university athletes: A descriptive study. \u003cem\u003ePLoS ONE, 20\u003c/em\u003e(1), e0315889. https://doi.org/10.1371/journal.pone.0315889\u003c/li\u003e\n\u003cli\u003eWhite, K. (2023). Exploring decision-making styles and emotional intelligence in digital sports contexts. \u003cem\u003eJournal of Digital Sport Psychology\u003c/em\u003e, 4(2), 89-104. https://doi.org/10.1016/jjdsp.2023.04.006\u003c/li\u003e\n\u003cli\u003eWood, E., \u0026amp; Attfield, J. (2005). Play, learning and the early childhood curriculum. London: Paul Chapman.\u003c/li\u003e\n\u003cli\u003eYeşilyaprak, B. (2001). Duygusal zek\u0026acirc; ve eğitimi. \u003cem\u003eKuram ve Uygulamada Eğitim Y\u0026ouml;netimi, 7\u003c/em\u003e(25), 139\u0026ndash;146.\u003c/li\u003e\n\u003cli\u003eY\u0026uuml;k\u0026ccedil;\u0026uuml;, S., \u0026amp; Kaplanoğlu, E. (2018). E-spor\u0026rsquo;un y\u0026uuml;kselişi ve T\u0026uuml;rkiye\u0026rsquo;deki gelişimi \u0026uuml;zerine bir inceleme. \u003cem\u003eUluslararası Spor, Egzersiz ve Antrenman Bilimi Dergisi, 4\u003c/em\u003e(2), 135\u0026ndash;145.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Emotional Intelligence, E-sports, Decision Making","lastPublishedDoi":"10.21203/rs.3.rs-6804435/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6804435/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to examine the effect of emotional intelligence levels on decision-making among individuals interested in e-sports. The population consisted of individuals aged 18 and over who are interested in e-sports.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research sample included 385 participants (178 women and 207 men; Age Average = 21.41 ± 3.24). The study utilized a 20-question information form, the Melbourne Decision Making Scale, and the Schutte Emotional Intelligence Scale to collect data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA statistically significant relationship was found between participants' emotional intelligence scores and their decision-making scores. Higher emotional intelligence scores were associated with increased self-esteem in decision-making and improvements in various decision-making sub-dimensions, except for careful decision-making. High emotional intelligence positively influenced the ability to use and evaluate emotions and maintain emotional control, which in turn positively affected decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings indicated that high emotional intelligence enhances self-esteem and various aspects of decision-making. While some results were consistent with the existing literature, some contrary findings were also observed.\u003c/p\u003e","manuscriptTitle":"E-Sports Players: Emotional Intelligence and Decision Making Levels","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-29 15:48:11","doi":"10.21203/rs.3.rs-6804435/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-08T08:44:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-06T19:56:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296021509682971390526555707626678844304","date":"2025-09-05T12:05:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-26T10:02:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126236387525063768520159576858502352275","date":"2025-08-26T09:01:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165840885559217352173658069872067055515","date":"2025-08-24T19:41:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-22T05:52:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173979462228755680977663419615097678902","date":"2025-08-22T04:55:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-21T13:50:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-21T13:12:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Sports Science, Medicine and Rehabilitation","date":"2025-08-21T11:41:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a1c788a1-4c5e-49be-a127-9ab34a419933","owner":[],"postedDate":"August 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:01:57+00:00","versionOfRecord":{"articleIdentity":"rs-6804435","link":"https://doi.org/10.1186/s13102-025-01388-9","journal":{"identity":"bmc-sports-science-medicine-and-rehabilitation","isVorOnly":false,"title":"BMC Sports Science, Medicine and Rehabilitation"},"publishedOn":"2025-11-11 15:57:55","publishedOnDateReadable":"November 11th, 2025"},"versionCreatedAt":"2025-08-29 15:48:11","video":"","vorDoi":"10.1186/s13102-025-01388-9","vorDoiUrl":"https://doi.org/10.1186/s13102-025-01388-9","workflowStages":[]},"version":"v1","identity":"rs-6804435","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6804435","identity":"rs-6804435","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}