Few research studies have examined the predictors of mental ill health in esports. This study addresses that gap by investigating stressors, sleep, burnout, social phobia anxiety and mental ill health in esport athletes. An online survey was disseminated to competitive student esport athletes (n = 313) residing in the UK. The survey included measures of stressors resulting from competing in esports, sleep quality, burnout, and social phobia, as well as outcome measures of mental ill health. Hierarchical regression analyses examined these relationships. All the hypotheses were supported, with stressors significantly predicting sleep quality, burnout, and social phobia anxiety, and stressors, sleep quality, burnout, and social phobia anxiety were all significant positive predictors of mental ill health. The strength of these predictions varied, for example, the daytime dysfunction subscale of sleep was a strong predictor of all outcome variables; two subscales of burnout, reduced sense of accomplishment and exhaustion significantly predicted each of the three mental ill health outcome variables, and two subscales of social phobia anxiety, fear and avoidance, significantly predicted mental ill health. Our study has important implications for player health in esports, highlighting interventions that could target specific aspects of stress, sleep, burnout, and social phobia anxiety to improve the mental health of those who compete in esports.

The assessment of an athlete’s performance can play a key role in determining their current state, their readiness to compete, the impact of an experimental manipulation, and/or the influence of an intervention. At present, there is limited empirical evidence stating the indicators that encapsulate individual performance within any esport. To identify the variables that are historically associated with indicating Counter-Strike: Global Offensive performance, a literature review was conducted. Identified variables were accumulated and presented to three technical expert panels composed of world-class esport athletes, researchers, and practitioners. We utilized a modified Delphi method to provide direction concerning the examination of performance in esports. The expert panelists presented numerous opinions on what encapsulates performance, considerations for best practices, and concerns associated with the semantics of performance. This study presents the opinions of various domain-specific experts and encourages the use of more explicit terminology when discussing performance measurement. It was the intention of the project to generate an open discussion rather than draw a unified conclusion on best practices.

Heart rate variability (HRV) is a psychophysiological measure of particular interest in esports due to its potential to monitor player self-regulation. This study aimed to systematically review the utilisation of HRV in esports. Consideration was given to the methodological and theoretical underpinnings of previous works to provide recommendations for future research. The protocol was made available on the Open Science Framework. Inclusion criteria were empirical studies, examining HRV in esports, using esports players, published in English. Exclusion criteria were non-peer-reviewed studies, populations with pre-existing clinical illness other than Internet Gaming Disorder (IGD), opinion pieces or review papers. In November 2022 a search of Web of Science, PubMed, and EBSCOHost identified seven studies using HRV in esports. Risk of bias was assessed using the Mixed Methods Appraisal Tool. Narrative review identified two primary uses of HRV in esports; stress response and IGD. A lack of theoretical and methodological underpinning was identified as a major limitation of current literature. Further investigation is necessary before making recommendations regarding the use of HRV in esports. Future research should employ sound theoretical underpinning such as the use of vagally mediated HRV and the robust application of supporting methodological guidelines when investigating HRV in esports.

While scientific interest in electronic sports (esports) is steadily growing, there remains an absence of research evidence concerning training practices in specific esports such as League of Legends. Anecdotal evidence suggests that current approaches to training may be suboptimal in terms of performance and, concerningly, linked to negative consequences for player health and well-being. In order to address the lack of literature and aid understanding of the (in)effectiveness of current training practices in esports, our study sought to qualitatively examine the experiences and perceptions of training in a sample of professional and semiprofessional League of Legends players. Through interviews with 10 players who ranked in the top 0.24% of the playing population, three core themes were identified: (a) the state of training, (b) training experiences, and (c) motivational change. This study provides important insights into current training practices in esports and players’ perceptions of the (in)effectiveness of these practices. The paper concludes with practical recommendations for coaches and support staff working in esports.

The present study provides a unique contribution to the literature by offering the first study to examine the prevalence of mental ill health and mental well-being of professional Counter-Strike athletes. The sample consisted of 51 current Counter-Strike professionals (M_age = 23.22, SD = 4.7 years; male = 48, female = 3) representing 17.1% of all registered Counter-Strike professionals. An online questionnaire was administered via Qualtrics. We found that one quarter of our sample reported moderately severe (15.7%) and severe (9.8%) symptoms of depression using the Patient Health Questionnaire-9, over three quarters (82.4%) reported symptoms of anxiety/depression using the General Health Questionnaire—short form-12, over half (54.9%) reported psychological distress using the distress screener, and nearly three quarters (72.5%) reported low mental well-being using the Short Warwick–Edinburgh Mental Well-Being Scale. Our findings suggest that greater importance should be placed on screening and intervention support by both performance and clinical practitioners to facilitate mental health within the esports ecosystem.

The think aloud (TA) protocol is used to capture conscious cognition for wide ranging applications. However, the methods used to train the TA technique have been inconsistent, involving a mixture of both traditional guidelines and task-specific examples. This study aimed to examine how best to train the TA process. We recruited 20 competitive golfers as research participants, and we randomly assigned them to equal sized groups of traditional TA training as described by Ericsson and Simon and task-specific training in which participants were familiarized with TA via task-specific examples. Following training, all participants performed a golf task and were asked to TA. We transcribed audiotapes of their verbatim TA content and analyzed them using a deductive framework. We also collected various social validation self-report measures to assess participant perceptions of TA training. Overall, we found no significant differences in the frequency or type of TA verbalizations when comparing traditional and task-specific TA training groups. However, participants in the task-specific training group reported more favorable perceptions of training and found training significantly clearer than did participants in the traditional training group. We suggest that these findings support traditional TA training following Ericsson and Simon’s training guidelines, but adding task-specific examples seems to increase the familiarity of TA use and facilitate more reliable and accurate cognition data for research use.