Dan Chong, Siyu Liao, Mingjie Xu, Yuting Chen, Anni Yu
{"title":"Understanding How Negative Emotions Affect Hazard Assessment Abilities in Construction: Insights from Wearable EEG and the Moderating Role of Psychological Capital.","authors":"Dan Chong, Siyu Liao, Mingjie Xu, Yuting Chen, Anni Yu","doi":"10.3390/brainsci15020190","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background</b>: The construction industry faces significant safety hazards, frequent accidents, and inadequate management. Studies identify unsafe worker behaviors as the primary cause of construction accidents. However, most research overlooks the psychological state, particularly emotions, of construction workers. <b>Methods</b>: This study designed a behavioral experiment integrating social cognitive neuroscience, collecting real-time EEG data to classify and recognize fear, anger, and neutral emotions. Variance analysis explored differences in safety hazard identification and risk assessment under these emotional states. A total of 22 male participants were involved, with data collection lasting three days. The role of psychological capital in mediating the effects of emotions on unsafe behaviors was also examined. <b>Results</b>: Emotional classification using EEG signals achieved 79% accuracy by combining frequency domain and nonlinear feature extraction. Fear significantly enhanced safety hazard identification accuracy compared to neutral and anger emotions (F = 0.027, <i>p</i> = 0.03). Risk assessment values under fear and anger were higher than under neutral emotion (F = 0.121, <i>p</i> = 0.023). Psychological capital interacted significantly with emotions in hazard identification accuracy (F = 0.68, <i>p</i> = 0.034), response time (F = 2.562, <i>p</i> = 0.003), and risk assessment response time (F = 1.415, <i>p</i> = 0.026). Safety hazard identification correlated with the number of safety trainings (<i>p</i> = 0.002) and safety knowledge lectures attended (<i>p</i> = 0.025). Risk assessment was significantly associated with smoking (<i>p</i> = 0.023), alcohol consumption (<i>p</i> = 0.004), sleep duration (<i>p</i> = 0.017), and safety training (<i>p</i> = 0.024). <b>Conclusions</b>: The findings provide insights into how emotions affect safety hazard identification and risk assessment, offering a foundation for improving emotional regulation, reducing accidents, and enhancing safety management in construction.</p>","PeriodicalId":9095,"journal":{"name":"Brain Sciences","volume":"15 2","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11852488/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Sciences","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/brainsci15020190","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Understanding How Negative Emotions Affect Hazard Assessment Abilities in Construction: Insights from Wearable EEG and the Moderating Role of Psychological Capital.
Background: The construction industry faces significant safety hazards, frequent accidents, and inadequate management. Studies identify unsafe worker behaviors as the primary cause of construction accidents. However, most research overlooks the psychological state, particularly emotions, of construction workers. Methods: This study designed a behavioral experiment integrating social cognitive neuroscience, collecting real-time EEG data to classify and recognize fear, anger, and neutral emotions. Variance analysis explored differences in safety hazard identification and risk assessment under these emotional states. A total of 22 male participants were involved, with data collection lasting three days. The role of psychological capital in mediating the effects of emotions on unsafe behaviors was also examined. Results: Emotional classification using EEG signals achieved 79% accuracy by combining frequency domain and nonlinear feature extraction. Fear significantly enhanced safety hazard identification accuracy compared to neutral and anger emotions (F = 0.027, p = 0.03). Risk assessment values under fear and anger were higher than under neutral emotion (F = 0.121, p = 0.023). Psychological capital interacted significantly with emotions in hazard identification accuracy (F = 0.68, p = 0.034), response time (F = 2.562, p = 0.003), and risk assessment response time (F = 1.415, p = 0.026). Safety hazard identification correlated with the number of safety trainings (p = 0.002) and safety knowledge lectures attended (p = 0.025). Risk assessment was significantly associated with smoking (p = 0.023), alcohol consumption (p = 0.004), sleep duration (p = 0.017), and safety training (p = 0.024). Conclusions: The findings provide insights into how emotions affect safety hazard identification and risk assessment, offering a foundation for improving emotional regulation, reducing accidents, and enhancing safety management in construction.
期刊介绍:
Brain Sciences (ISSN 2076-3425) is a peer-reviewed scientific journal that publishes original articles, critical reviews, research notes and short communications in the areas of cognitive neuroscience, developmental neuroscience, molecular and cellular neuroscience, neural engineering, neuroimaging, neurolinguistics, neuropathy, systems neuroscience, and theoretical and computational neuroscience. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.