The use of heart rate variability in esports: A systematic review

Conceptualization and validation of the TILT questionnaire: relationship with IGD and life satisfaction

Currently, the study of esports is growing within the field of psychology. Among the different variables attracting interest - including stress or psychological factors associated with performance - an emerging concept known as tilt is gaining prominence in the literature. However, this construct has yet to be operationalized or defined. Thus, the present study aims to address this gap by defining and conceptualizing TILT while devising and validating a questionnaire to measure the construct in esports players. The initial phase of the study comprised 27 interviews conducted with professional players (n = 6), semi-professionals (n = 8), amateurs (n = 8), and coaches (n = 5) to characterize the concept of tilt. Following these interviews, a definition of tilt was formulated, and a panel of five experts in sports psychology and esports proposed a comprehensive set of 53 items. A total of 488 participants (278 males, 210 females), aged 18-50 (mean age = 26.9 years, SD = 7.57), completed the survey, including the 53 tilt items, a questionnaire measuring toxic behavior, and the Internet Gaming Disorder Scale-Short Form (IGDS9-SF). The tilt construct is primarily characterized as a state of frustration escalating into anger, resulting in diminished performance, attention, and recurring negative thoughts about errors. Its onset typically coincides with stressful situations, persisting for approximately 30 min. Through an Exploratory Factor Analysis (EFA), 18 items were retained and categorized into two factors: Causes (7 Items) and Consequences (11 Items) of tilt. The entire questionnaire yielded a Cronbach's α of 0.922, with the first and second factors showing values of 0.854 and 0.890, respectively. Confirmatory factor analysis (CFA) revealed an acceptable fit for the 2-factor solution. Correlations with related constructs, such as Toxic Behavior and IGD, provided preliminary evidence of external validity. Empirical evidence for the validity and internal consistency of the Tilt Scale is robust, indicating its potential utility in future research on the psychological experiences of esports players.

How Much Energy Do E'Athletes Use during Gameplay? Quantifying Energy Expenditure and Heart Rate Variability Within E'Athletes

BACKGROUND

Research into esports suggests that e'athletes experience physiological stressors and demands during competition and training. The physiological demands of esports are poorly understood and need to be investigated further to inform future training guidelines, optimise performance outcomes, and manage e'athlete wellbeing. This research aimed to quantify the metabolic rate of esports gameplay and compare this outcome with heart rate variability within expert e'athletes.

RESULTS

Thirteen healthy male participants ranked within the top 10% of their respective esports title participated in the study (age = 20.7 ± 2.69 years; BMI = 24.6 ± 5.89 kg·m- 2). Expired gas analysis indirect calorimetry measured gas exchange during rest and gaming. Compared to resting conditions, competitive esports gameplay significantly increased median energy expenditure (1.28 (IQR 1.16-1.49) kcal·min- 1 vs. 1.45 (IQR 1.20-1.77) kcal·min- 1, p = .02), oxygen consumption (0.27 (IQR 0.24-0.30) L·min- 1 vs. 0.29 (IQR 0.24-0.35) L·min- 1, p = .02) and carbon dioxide production (0.20 (IQR 0.19-0.27) L·min- 1vs. 0.27 (IQR 0.24-0.33) L·min- 1, p = .01). Competitive gameplay also resulted in a significant increase in heart rate (84.5 (IQR 74.1-96.1) bpm vs. 87.1 (IQR 80.3-104) bpm, p = .01) and decrease in R-R interval's (710 (IQR 624-810) ms vs. 689 (IQR 579-747) ms, p = .02) when compared to rest. However, there were no significant differences in time or frequency measures of heart rate variability.

CONCLUSIONS

The data reveal increased physiological responses to metabolic rate, energy expenditure and cardiovascular function to esports game play within expert e'athletes. Further physiological research into the physical demands on e'athletes, the influence of different training programs to esport performance, and the added multivariate determinants to elite level esport performance are warranted.

The impact of videogames on the mood of amateur youth players during consecutive games

Introduction

Esports have experienced tremendous growth in recent years. In the scientific field, previous research has shown the determining role of psychology in competitive performance, but little is known about the factors that may be more determinant. In addition, in the amateur field, where fun and enjoyment are the most important factors, it has been observed that players can see their psychological state altered due to different factors, but it is not known if the outcome of the game (win or lose) can be influential. For this reason, the aim of the present investigation was to analyze changes in players' mood between three consecutive games as a function of the outcome of each game.

Methods

A total of 14 amateur players participated in the research, all of them with previous experience and being regular League of Legends players. The participants completed the POMS questionnaire before the start of each game and the outcome of each game was recorded at the end.

Results

The results showed that no significant pre-game differences were found in any of the games, regardless of winning or losing. Significant differences were found in the pre-game mood between the first and second game, according to the outcome of the first game, and between the second and third game, according to the outcome of the second game. Between the first and second games, there was a significant increase in depression (p = 0.038) and anger (p = 0.003) when the first game was lost; and between the second and third games, there was a decrease in tension (p = 0.003) and anger (p = 0.022) when the second game was won. In addition, it should be noted that fatigue increased significantly after each game, regardless of the outcome, and with respect to the change in mood, this was more noticeable when the first game was lost and the second was won, as significant changes were observed in tension (p = 0.028), depression (p = 0.030) and anger (p = 0.006).

Conclusion

Pre-match mood does not influence post-match performance, but mood changes do occur between successive matches depending on the outcome of the match.