Word recognition during movement under simulated weather conditions

Processing linguistic materials while driving is essential for ensuring road safety; however, adverse weather conditions can compromise our ability to read at ease. Here we rely on Virtual Reality (VR) to recreate real-world perceptual disfluency, allowing us to investigate the effects of differing weather scenarios-such as sunny and rainy-on word recognition while in movement. Participants navigated a realistic VR driving environment and performed a word identification and naming task, with linguistic materials displayed on road signs encountered along the route. Results showed that high-frequency words were recognized better than low-frequency counterparts, reaffirming the strength of the frequency effect, even under dynamic situations. Additionally, reaction times were slower in rainy compared to sunny conditions, indicating that adverse weather impairs processing speed but not overall recognition accuracy. The negative effect of rain also increased progressively over time, suggesting a potential accumulation of perceptual fatigue or diminished visual adaptation. The lack of a significant interaction between the weather conditions and word frequency suggests that these effects were independent, with no significant interaction between frequency and weather condition. These findings demonstrate the utility of VR as an ecologically valid framework to investigate the complex interplay between environmental context and reading comprehension. In conclusion, the current study provides insights into how varying environmental conditions affect word recognition during movement.