Flow is a mental state characterized by deep absorption during challenging activities, which was first studied by Mihaly Csikszentmihalyi. One of the defining characteristics of this state is the loss of the sense of time. Despite the widespread scientific interest in flow, there are few quantitative studies specifically on the aspect of time perception. The present study focuses on the relation between time perception and flow states in the context of video game play. Participants (n = 100) played the rhythm game Thumper for 25 minutes in one of two conditions: in virtual reality (VR) or on a computer screen (2D). Participants who played the game in VR performed better and had a stronger feeling of presence than those who played in 2D. Thumper was flow-inducing regardless of condition and the more flow participants experienced the less they thought about time and the faster time passed subjectively. The total score obtained by players as an objective measure of player performance was positively correlated with flow states, indicating that the more flow participants experienced, the better they played.

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Objective: The study explores associations of visually induced motion sickness (VIMS) with emergency braking reaction times (RTs) in driving simulator studies. It examines the effects over the progression of multiple simulated drives. Background: Driving simulator usage has many advantages for RT studies; however, if it induces VIMS, the observed driving behavior might deviate from real-world driving, potentially masking or skewing results. Possible effects of VIMS on RT have long been entertained, but the progression of VIMS across simulated drives has so far not been sufficiently considered. Method: Twenty-eight adults completed six drives on 2 days in a fixed-base driving simulator. At five points during each drive, pedestrians entered the road, necessitating emergency braking maneuvers. VIMS severity was assessed every minute using the 20-point Fast Motion Sickness Scale. The progression of VIMS was considered in mixed model analyses. Results: RT predictions were improved by considering VIMS development over time. Here, the relationship of VIMS and RT differed across days and drives. Increases in VIMS symptom severity predicted more prolonged RT after repeated drives on a given day and earlier within each drive. Conclusion: The assessment of VIMS in RT studies can be beneficial. In this context, VIMS measurements in close temporal proximity to the behaviors under study are promising and offer insights into VIMS and its consequences, which are not readily obtainable through questionnaires. Application: Driving simulator–based RT studies should consider cumulative effects of VIMS on performance. Measurement and analysis strategies that consider the time-varying nature of VIMS are recommended.