The number of video game and eSports players is steadily rising. Since little is known about their health behavior to date, the present study examines the demographics and health behavior of video game and eSports players. In this cross-sectional study, data on demographics, health status, physical activity, nutrition, sleep, and video game usage were assessed via a web-based survey of n = 1066 players (91.9% male; 22.9 ± 5.9 years; body mass index (BMI): 24.6 ± 4.8 kg/m²) in Germany in 2018. The majority of respondents (95%) reported a good to excellent health status. Two thirds (66.9%) engaged in moderate to vigorous physical activity for more than 2.5 h/week. The average duration of sitting and sleep time was 7.7 ± 3.6 h/day and 7.1 ± 1.3 h/day, respectively. Mean fruit and vegetable consumption was 2.7 ± 1.8 portions/day. Video games were played for 24.4 ± 15.9 h/week on average. Partial Spearman correlations revealed poor positive associations of video game play time to sedentary behavior (rho = 0.15; p < 0.01) and BMI (rho = 0.11; p < 0.01), as well as a poor negative association to self-reported health status (rho = −0.14; p < 0.01). These results indicate the good subjective health of this target group. Nevertheless, the high amount of video game play time and its poor negative association to health status indicate a need for specific health promotion strategies for this target group.

Quick reactions are considered important in both, traditional and electronic sports and research findings suggest that reaction time can be optimized by both sports activity and playing action video games. In this study, reaction and motor times of 18 professional and 21 non-professional eSports players from different genres and 36 non-professional traditional sportsmen were compared using the Vienna Test System. No differences between the groups were found in simple visual, acoustic, and choice reaction times. Differentiated by game genre, players from sports simulations had significantly shorter reaction times than MOBA players in the acoustic and choice reaction test. The results of this study suggest that traditional sports and eSports may improve reaction times to a similar amount. Furthermore, various game genres require different reaction times or may affect related abilities in different ways.

Studies show that high health literacy (HL) can support the promotion and maintenance of healthy behavior such as physical activity (PA). However, most studies rely on subjective data. The aim of the present study is to investigate the relationship between HL and PA, not only with subjectively but also with objectively measured PA data. The present study is a pooled analysis of baseline data from the research association TRISEARCH (2015–2018), which focused on the HL of working adults. HL was measured by Lenartz’ questionnaire, and PA by the Global Physical Activity Questionnaire (GPAQ; n = 1056). A subsample (n = 124) also received accelerometers (Actigraph GT3X+) to provide more objective PA data. Partial correlations and regression models were used to investigate the relationship between HL and questionnaire- and accelerometer-derived PA. Very low and medium partial correlations could be found for HL subscales and daily PA by questionnaire (r = −0.06, p < 0.05) and accelerometer (r = 0.26, p < 0.01). No subscale of HL made a significant contribution to the amount of daily PA (all p > 0.05). Not all subscales of HL seem to have an influence on the occurrence of healthy behavior, such as PA. This should be considered when HL-based interventions are designed. Further investigation of the relationship between HL and PA is needed. Objective assessments of both HL and PA can provide additional information for this task.

Background: The Global Physical Activity Questionnaire (GPAQ) is applied internationally as a tool to assess the level of physical activity. The GPAQ was designed as an interview, including the use of show cards, which visualise activities of moderate and intensive physical activity and support the distinction between these intensities. The self-administered version of the GPAQ is used in the application-oriented research for reasons of economy and practicality. However, the use of show cards often remains unknown. The aim of the present study was to examine differences in validity between two self-administered versions of the GPAQ with and without show cards. Methods: In this crossover study, two groups (n = 54; 57.4% female; 28.3 ± 12.2 years) received the GPAQ with or without show cards after 7 days and the respective other version after additional 7 days. For validation, all participants wore an accelerometer (ActiGraph GT3X+) on all 14 days. Differences between GPAQ versions and accelerometer data were compared by Wilcoxon signed rank test. Additionally, Spearman analyses and Bland-Altman plots were calculated. Results: No statistically significant difference between the GPAQ versions could be found in regard to the accuracy of physical activity assessment (p > 0.05). Both GPAQ versions show similar correlation coefficients for vigorous physical activity (rho = 0.31–0.42) and sedentary behaviour (rho = 0.29–0.32). No statistically significant correlation was found for physical activity of moderate intensity. The Bland-Altman plots support these results, as both GPAQ versions have the same trends in terms of overestimation and underestimation of physical activity. Conclusion: The use of show cards had no significant impact on questionnaire validity. Therefore, both GPAQ versions can be applied interchangeably. Nevertheless the exact description of application of the GPAQ is desirable in terms of reproducibility and transparent scientific research.

Summary: Young adults have a high societal relevance but are still an under-represented target group in health promotion. Health literacy is widely acknowledged as one of the strongest predictors and key determinant of health, so its influence on work ability is of great interest. The purpose of the study was to examine the associations between health-related skills and work ability within the structural model of health literacy of Lenartz, Soellner and colleagues, which explains health behaviour and health through the indirect and direct influence of six ‘advanced skills’ (‘self-perception’, ‘proactive approach to health’, ‘dealing with health information’, ‘self-control’, ‘self-regulation’ and ‘communication and cooperation’). The cross-sectional study was based on baseline data of a health literacy promotion intervention (495 vocational school students, 59.0% female, age span 18–25 years). Structural equation modelling with partial least squares was used to examine the associations between the six constructs of the model and the Work Ability Index (WAI). Mean WAI score was 39.7 ± 4.5 (51.1% categorized ‘moderate’/‘poor’). Five out of six constructs of the model showed a statistically significant indirect or direct effect, respectively, on work ability. The model explained 24.8% of the WAI score variance. Our findings show associations between the health literacy model and the work ability among young employees. In view of demographic change, it is crucial to develop and analyse target group-specific health literacy interventions. The model offers new facets in the modelling of health literacy.

In traditional sports like soccer or tennis, experts benefit from better anticipation abilities compared to novices through a more efficient gaze behavior. For electronic sports (eSports), this area is rather unexplored, although quick decision making, which is linked to gaze behavior, is considered fundamental in eSports. In this study, the gaze behavior of professional and non-professional eSports players (n=21, 23.4 ± 3.3 years) was recorded via eye-tracking in the sports simulation FIFA 19. Number, duration, and location of fixations were compared over an entire match and in offensive play situations. Except for fixation location, no significant differences were found. The players mainly fixated the same objectives regarding fixation number and duration, but professionals had significantly more fixations using the in-game radar and fixated off-ball teammates significantly shorter. Due to the limited results, gaze behavior does not seem to be a decisive factor for excellent performance in FIFA 19.