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Sensory processing sensitivity predicts pilot decision time via indecisiveness: evidence from flight simulation and
Kun Zhou1, Yifan Zhang2, Yulu Lei2
1College of Safety Science and Engineering, Civil Aviation University of China, Tianjin, 300300, People's Republic of China. zhouk_psy@sina.com.
High sensory processing sensitivity (SPS) in pilots correlates with longer decision times and poorer flight performance, especially under stress. Indecisiveness and dorsolateral prefrontal cortex (DLPFC) activation amplify these effects, impacting aviation safety.
Area of Science:
- Aviation psychology
- Neuroscience
- Human factors in flight safety
Background:
- Timely decision-making is crucial for aviation safety during emergencies.
- Individual differences in stress response and decision-making abilities exist among pilots.
- Understanding neural mechanisms of decision delay is key for risk mitigation and training.
Purpose of the Study:
- To investigate the impact of sensory processing sensitivity (SPS) on pilot decision-making under stress.
- To explore the roles of indecisiveness and dorsolateral prefrontal cortex (DLPFC) activation in decision delay.
- To integrate trait, behavioral, and neural factors into a model of aviation decision performance.
Main Methods:
- Fifty-one male cadet pilots were categorized into high- and low-SPS groups.
- Participants completed simulated landing tasks in high- and low-risk scenarios.
- Decision time, flight performance, and DLPFC activation (using fNIRS) were measured.
Main Results:
- High-SPS pilots exhibited significantly longer decision times compared to low-SPS pilots.
- Flight performance was significantly lower in high-SPS pilots under high-risk conditions.
- Indecisiveness mediated the relationship between SPS and decision time; DLPFC activation moderated indecisiveness and decision delay.
Conclusions:
- SPS and indecisiveness jointly impair decision-making and flight performance under stress.
- DLPFC engagement exacerbates decision delays in pilots.
- The study provides a unified model of aviation decision performance integrating individual traits and neural correlates.
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