The use of head-mounted displays (HMD) for virtual reality (VR) application-based purposes including therapy, rehabilitation, and training is increasing. Despite advancements in VR technologies, many users still experience sickness symptoms. VR sickness may be influenced by technological differences within HMDs such as resolution and refresh rate, however, VR content also plays a significant role. The primary objective of this systematic review and meta-analysis was to examine the literature on HMDs that report Simulator Sickness Questionnaire (SSQ) scores to determine the impact of content. User factors associated with VR sickness were also examined. A systematic search was conducted according to PRISMA guidelines. Fifty-five articles met inclusion criteria, representing 3,016 participants (mean age range 19.5–80; 41% female). Findings show gaming content recorded the highest total SSQ mean 34.26 (95%CI 29.57–38.95). VR sickness profiles were also influenced by visual stimulation, locomotion and exposure times. Older samples (mean age ≥35 years) scored significantly lower total SSQ means than younger samples, however, these findings are based on a small evidence base as a limited number of studies included older users. No sex differences were found. Across all types of content, the pooled total SSQ mean was relatively high 28.00 (95%CI 24.66–31.35) compared with recommended SSQ cut-off scores. These findings are of relevance for informing future research and the application of VR in different contexts.

Besides allowing us to perceive our surroundings, eye movements are also a window into our mind and a rich source of information on who we are, how we feel, and what we do. Here we show that eye movements during an everyday task predict aspects of our personality. We tracked eye movements of 42 participants while they ran an errand on a university campus and subsequently assessed their personality traits using well-established questionnaires. Using a state-of-the-art machine learning method and a rich set of features encoding different eye movement characteristics, we were able to reliably predict four of the Big Five personality traits (neuroticism, extraversion, agreeableness, conscientiousness) as well as perceptual curiosity only from eye movements. Further analysis revealed new relations between previously neglected eye movement characteristics and personality. Our findings demonstrate a considerable influence of personality on everyday eye movement control, thereby complementing earlier studies in laboratory settings. Improving automatic recognition and interpretation of human social signals is an important endeavor, enabling innovative design of human–computer systems capable of sensing spontaneous natural user behavior to facilitate efficient interaction and personalization.

The present study investigates skill transfer from Virtual Reality (VR) sports training to the real world, using the fast-paced sport of table tennis. A key assumption of VR training is that the learned skills and experiences transfer to the real world. Yet, in certain application areas, such as VR sports training, the research testing this assumption is sparse. Real-world table tennis performance was assessed using a mixed-model analysis of variance. The analysis comprised a between-subjects (VR training group vs control group) and a within-subjects (pre- and post-training) factor. Fifty-seven participants (23 females) were either assigned to a VR training group (n = 29) or no-training control group (n = 28). During VR training, participants were immersed in competitive table tennis matches against an artificial intelligence opponent. An expert table tennis coach evaluated participants on real-world table tennis playing before and after the training phase. Blinded regarding participant's group assignment, the expert assessed participants’ backhand, forehand and serving on quantitative aspects (e.g. count of rallies without errors) and quality of skill aspects (e.g. technique and consistency). VR training significantly improved participants’ real-world table tennis performance compared to a no-training control group in both quantitative (p < .001, Cohen’s d = 1.08) and quality of skill assessments (p < .001, Cohen’s d = 1.10). This study adds to a sparse yet expanding literature, demonstrating real-world skill transfer from Virtual Reality in an athletic task.