# Boosting Safety Protocol Compliance with Eye-Tracking in Chemical Plants
## 2 Materials and Methods
### Empirical Support for Performance Metrics Selection  
The selection of reaction time, operational accuracy, attention focus, error count, and corrective response time as performance indicators in XR-based safety training is grounded in empirical research highlighting their predictive reliability and relevance in high-risk industrial environments. Reaction time has been shown to improve significantly when trainees are exposed to immersive training environments, with eye-tracking feedback further accelerating response times by ensuring continuous visual engagement with critical safety indicators [20]. Faster reaction times in XR training have been attributed to reduced cognitive load, enhanced situational awareness, and immediate feedback on gaze deviations, all of which contribute to improved decision-making efficiency [21]. The role of operational accuracy as a performance metric is reinforced by research demonstrating that eye-tracking technology enhances procedural adherence in safety training by directing visual attention toward essential operational elements [22]. Studies confirm that trainees who receive real-time gaze feedback show significantly higher accuracy in executing complex industrial tasks, particularly those requiring strict compliance with safety protocols and hazard mitigation strategies [23]. These findings suggest that gaze-controlled interactions improve visual attention distribution, leading to reduced task execution errors and enhanced procedural compliance in XR-based simulations. Attention focus, quantified through fixation duration and gaze stability, has been validated as a key predictor of hazard recognition and decision-making precision. Research has demonstrated that participants with stable fixation patterns on safety-critical elements exhibit higher success rates in identifying and mitigating potential risks [24]. Extended reality environments further enhance user engagement by optimizing visual field utilization,  
Figure 2: Experiment environment and materials. ensuring that trainees allocate appropriate attention resources to high-risk areas within the training scenario. Error count is widely recognized as an essential metric for evaluating training effectiveness, with studies confirming that trainees in XR-based safety simulations make fewer errors when guided by real-time visual feedback. Eye-tracking technology enables precise analysis of error-prone behaviors by detecting gaze drift away from critical operational zones, thereby facilitating proactive corrective interventions [25]. These findings highlight the predictive value of eye-tracking data in identifying error-prone areas in safety training and optimizing instructional design to reduce cognitive overload and procedural mistakes [26]. Corrective response time has been validated through studies examining the impact of real-time gaze correction on user performance, with results indicating that eye-tracking-enabled feedback mechanisms significantly enhance reaction efficiency [27]. Research confirms that trainees receiving automated gaze-based guidance demonstrate faster adaptation to hazardous events, leading to quicker corrective actions and reduced risk exposure [28]. This aligns with findings that suggest visual attention cues play a crucial role in minimizing response delays in emergency scenarios, reinforcing the importance of corrective response time as a performance metric [29]. The integration of reaction time, operational accuracy, attention focus, error count, and corrective response time as core performance indicators in XR-based training is supported by longitudinal studies demonstrating the stability and predictive reliability of gaze-tracking methodologies [30]. Empirical evidence confirms that eye-tracking feedback enhances training effectiveness by reinforcing attention distribution, improving decision accuracy, and reducing operational errors in high-risk industrial environments [31].