Gaming Disorder: The role of a gamers flow profile.

Digital games are widely popular and integral to contemporary entertainment. Nevertheless, a proportion of users present with disordered/excessive gaming behaviours, provisionally classified as Internet Gaming Disorder (IGD). Previous literature suggests examining the contribution of an individual's profile of immersive engagement with their gaming activity, known as online flow, for disordered gaming behaviours. Therefore, the main goals of this study were (1) to categorise gamers into distinct profiles based on their online flow experiences and (2) to investigate the differences in disordered gaming among these different flow profiles. A sample of 565 gamers (12-68 years, Mage = 29.3 years) was assessed twice over six months with the Online Flow Questionnaire (OFQ), the Internet Gaming Disorder Scale-Short-Form (IGDS9-SF), and the Gaming Disorder Test (GDT). Latent profile analysis (LPA) identified five distinct profiles encompassing 'High-Flow with High Loss of Control' (HF-HLOC; 14.0 %), 'Low Flow with Low Enjoyment' (LF-LE; 11.9 %), 'Average Flow with Low Enjoyment' (AF-LE; 17.5 %), 'Low Flow with High Enjoyment' (LF-HE; 20.2 %), and 'High Loss of Sense of Time with Low Loss of Control' groups (HLOT-LLOC; 36.5 %). As hypothesised, individuals across varying profiles evidenced differences in their concurrent and longitudinal disordered gaming behaviours. Overall, findings suggest that 'loss of sense of time' may be the most pivotal factor in differentiating flow states and profiles during gaming, advocating its consideration in disordered gaming assessment and treatment.

Examining how gamers connect with their avatars to assess their anxiety: A novel artificial intelligence approach.

Research has supported that a gamer's attachment to their avatar can offer significant insights about their mental health, including anxiety. To assess this hypothesis, longitudinal data from 565 adult and adolescent participants (Mage = 29.3 years, SD = 10.6) was analyzed at two points, six months apart. Respondents were assessed using the User-Avatar Bond (UAB) scale and the Depression Anxiety Stress Scale (DASS) to measure their connection with their avatar and their risk for anxiety. The records were processed using both untuned and tuned artificial intelligence [AI] classifiers to evaluate present and future anxiety. The findings indicated that AI models are capable of accurately and autonomously discerning cases of anxiety risk based on the gamers' self-reported UAB, age, and duration of gaming, both at present and after six months. Notably, random forest algorithms surpassed other AI models in effectiveness, with avatar compensation emerging as the most significant factor in model training for prospective anxiety. The implications for assessment, prevention, and clinical practice are discussed.

Physical Activity and Self-Determination towards Exercise among Esports Athletes.

BACKGROUND: Esports is competitive video gaming, performed within teams or individually, across multiple genres. Players are required to be sedentary for extended periods and require a high-level of cognitive skills for successful competitive performance. There are conflicting findings within the physical activity research in the esports industry. The aim of this research is to explore self-reported physical activity through accelerometer-assessed physical activity, to gain a better insight into the physical activity behaviours of international e'athletes. METHOD: Participants (n = 796) across multiple popular esports games, holding any in-game rank, competing at any level, were recruited. The survey consisted of demographic details, esports experience, the International Physical Activity Questionnaire-Long Form (IPAQ-LF), and Behavioural Regulations towards Exercise Questionnaire (BREQ-3). Within a convenience sample, local intervarsity e'athletes (n = 18) were recruited to wear a wrist-worn accelerometer to measure physical activity for 7-days and then complete the survey. Results from the accelerometers were compared to the survey results to explore physical activity reporting within this population. RESULTS: When comparing IPAQ-LF to accelerometer data, players significantly over-report moderate-to-vigorous physical activity and weekly MET-min- 1 (p = .018, r = .63 and p ≤ .001, r = .92). The BREQ-3 showed that e'athletes categorised as high physical activity displayed significantly higher levels of intrinsic motivation, when compared to players categorised as low and moderate physical activity. CONCLUSIONS: E'athletes significantly over report physical activity time when measured through the IPAQ-LF, suggesting previous surveys may overestimate physical activity and further research is needed. Given the exponential growth of the industry and the level of physical inactivity, esports may contribute to global physical inactivity levels.

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 influence of an esports-adapted coping effectiveness training (E-CET) on resilience, mental health, and subjective performance among elite league of Legends players: A pilot study.

OBJECTIVE: This study aimed to develop, and pilot esports-adapted coping effectiveness training (E-CET) and measure its influence on coping effectiveness (global and specific), subjective performance, mental health (psychological distress and wellbeing), and resilience. DESIGN: Five elite male League of Legends players competing in the League of Legends Circuit Oceania participated in a mixed methods research design. The effects of E-CET were measured using a within-subjects quasi-experimental design (i.e., pre-to-post, no control group). To measure the effects of E-CET on specific stressors, a longitudinal diary design was used. METHOD: Players participated in a 2-h session of E-CET and a 45-min follow-up workshop. The 2-h workshop delivered content on two conceptual areas: (1) developing awareness of the stress and coping process; and (2) how to cope with stress. Players completed pre-intervention, post-intervention, and follow-up measures and twice-weekly stress journals. RESULTS: E-CET led to increases in players' perceived coping effectiveness and subjective performance, but there were no changes in psychological distress, psychological wellbeing, and resilience. However, the results indicate some positive signs for future coping interventions with League of Legends players and iterations of E-CET. CONCLUSION: The E-CET program appears to provide an opportunity to improve performance and mental health for esports players.

A qualitative analysis of the perceived determinants of success in elite esports athletes.

The current study aimed to qualitatively investigate the perceived determinants of success in professional esports athletes. Guided by the bioecological model (Bronfenbrenner & Morris, 2006), thematic analysis was used to explore elite esports athletes' perceptions of success determinants. Semi-structured interviews were conducted with seven elite esports athletes. The interviews were used to investigate players' psychology when playing well, training in elite esports, and working in esports teams. Deductive and inductive analyses were conducted to capture the core themes of success in esports within the bioecological model. When playing well, elite esports athletes experienced high levels of confidence, uninterrupted focus, and flow states. Elite esport athletes use mental strategies to help regulate their emotions and remain mindful in the presence of "tilt". Furthermore, breathing techniques and tactical breaks were used when players felt nervous or when trying to "reset" from a stressful situation. When working in elite esport teams, players reported using strategies to improve team cohesion and that the biggest challenge was interpersonal disagreements. The results contribute to the growing body of literature highlighting the psychological similarities between elite esports and traditional sports athletes and serve as an index for future research into high-performance in esports.

Social Support, Self-Regulation, and Psychological Skill Use in E-Athletes.

The aims of the present study were twofold. First, to investigate self-reported social support, self-regulation, and psychological skill use in esports athletes (e-athletes) compared to traditional athletes. Second, to determine if self-reported social support, self-regulation, and psychological skill use influenced e-athlete in-game rank. An online survey was used to collect data from an international sample of e-athletes (n = 1,444). The e-athletes reported less social support, self-regulation, and psychological skill use than reported by traditional athletes in previous studies. E-athletes with higher scores in social support, self-regulation, and psychological skill use was associated with higher in-game rank. The lack of an organisational structure in esports may be a contributing factor as to why e-athletes score lower than traditional athletes on social support, self-regulation, and psychological skill use. Future research is warranted to explore the development of esports programs aiming to promote athletes' social support, self-regulation, and use of psychological skills to enhance in-game performance and well-being.

Examining the Impact of School Esports Program Participation on Student Health and Psychological Development.

This study examined the influence of 7 high school esports developmental programs on student self-regulation, growth mindset, positive youth development (PYD), perceived general health and physical activity (PA), and sport behaviour. A total of 188 students (male n = 120; female n = 68) originally participated (89 enrolled in an esports program in their school and 99 acted as aged-matched controls), with 58 participants (n = 19 esports group; n = 39 controls) completing both pre- and post-program information. At baseline, no significant differences were found between youth e-athletes and their aged-matched controls. The analysis for the observation period showed a significant interaction effect for the PYD confidence scale, with post-hoc comparisons showing a significant decrease in the control group from pre- to post assessment whereas the esports group remained the same. Time main effects showed a decrease in the self-regulation motivation factor, PYD connection factor and PA for all participants. Overall, this study showed that students enrolled in their respective school esports program did not differ from those who did not in self-regulation, growth mindset, PYD, perceived health and PA, and sport behaviour. It was likely that all participants showed a decrease in motivation, connection, and PA due to COVID19 lockdown during the study period. This study is the first to investigate the longitudinal impact of student involvement in high school esports and showed that esports participation did not have a negative impact on any health or psychological factors.

The Association between Esports Participation, Health and Physical Activity Behaviour.

We investigated the association between obesity, self-reported physical activity, cigarette smoking, alcohol consumption, and perceived health in esports players, and the influence of player in-game rank. Data was collected with an online survey with an international participant sample of esports players representing five esports and all skill levels (n = 1772). Esports players were more likely to be categorized as normal weight, or obesity class 2 and 3 and as non-smokers (92%) and non-drinkers (65.1%) compared to international reference data. Esports players met international physical activity guidelines less than global general population. Esports players ranked in the top 10% were more physically active compared to the remaining esports players. As esports player in-game rank increased, so did the amount of time spent playing esports. Although esports players appear generally healthy, a small group was significantly obese and most esports players did not meet physical activity guidelines, indicating potential future health risks.

Stress and Coping in Esports and the Influence of Mental Toughness.

This study explored stress and coping in electronic sports (esports) athletes and the influence of mental toughness (MT), as defined by two prominent conceptualizations: the 4/6Cs and Mental Toughness Index (MTI) frameworks. Participants were 316 esports athletes, ranked in the top 40% of one of five major esports: Defense of the Ancients 2, League of Legends (LoL), Counter Strike: Global Offensive, Overwatch and Rainbow Six: Siege. Participants completed the MTI, Mental Toughness Questionnaire 6 (MTQ6), Stress Appraisal Measure, and Brief COPE inventory. Results showed that MT (via both MT frameworks) was associated with perceived control, and MTQ6 subscales were associated with stress intensity. Mental toughness (both frameworks) was associated with the selection of more problem-focused and emotion-focused coping strategies and less avoidance coping strategies. The results indicate there is some overlap between the MT and stress-coping process in high-performing traditional sports and competitive esports athletes. These results suggest that esports athletes could benefit from sports psychology interventions designed for traditional sports athletes. Finally, the MTQ6 and MTI had low shared variance (20%), suggesting that the two questionnaires appear to measure different aspects of MT.