The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience
The construction industry is one of the most dangerous industries with grave situation owing to high accident rate and mortality rate, which accompanied with a series of security management issues that need to be tackled urgently. The unsafe behavior of construction workers is a critical reason for...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Psychology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.895929/full |
| _version_ | 1817970251214618624 |
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| author | Dan Chong Anni Yu Hao Su Yue Zhou |
| author_facet | Dan Chong Anni Yu Hao Su Yue Zhou |
| author_sort | Dan Chong |
| collection | DOAJ |
| description | The construction industry is one of the most dangerous industries with grave situation owing to high accident rate and mortality rate, which accompanied with a series of security management issues that need to be tackled urgently. The unsafe behavior of construction workers is a critical reason for the high incidence of safety accidents. Affective Events Theory suggests that individual emotional states interfere with individual decisions and behaviors, which means the individual emotional states can significantly influence construction workers’ unsafe behaviors. As the complexity of the construction site environment and the lack of attention to construction workers’ emotions by managers, serious potential emotional problems were planted, resulting in the inability of construction workers to effectively recognize safety hazards, thus leading to safety accidents. Consequently, the study designs a behavioral experiment with E-prime software based on social cognitive neuroscience theories. Forty construction workers’ galvanic skin response signals were collected by a wearable device (HKR-11C+), and the galvanic skin response data were classified into different emotional states with support vector machine (SVM) algorithm. Variance analysis, correlation analysis and regression analysis were used to analyze the influence of emotional states on construction workers’ recognition ability of safety hazards. The research findings indicate that the SVM algorithm could effectively classify galvanic skin response data. The construct ion workers’ the reaction time to safety hazards and emotional valence were negatively correlated, while the accuracy of safety hazards recognition and the perception level of safety hazard separately had an inverted “U” type relationship with emotional valence. For construction workers with more than 20 years of working experience, work experience could effectively reduce the influence of emotional fluctuations on the accuracy of safety hazards identification. This study contributes to the application of physiological measurement techniques in construction safety management and shed a light on improving the theoretical system of safety management. |
| first_indexed | 2024-04-13T20:31:27Z |
| format | Article |
| id | doaj.art-b5ea3afea46f4bee9caa5e0cc8ce1175 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-13T20:31:27Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-b5ea3afea46f4bee9caa5e0cc8ce11752022-12-22T02:31:10ZengFrontiers Media S.A.Frontiers in Psychology1664-10782022-06-011310.3389/fpsyg.2022.895929895929The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive NeuroscienceDan Chong0Anni Yu1Hao Su2Yue Zhou3Department of Management Science and Engineering, Shanghai University, Shanghai, ChinaDepartment of Management Science and Engineering, Shanghai University, Shanghai, ChinaDepartment of Management Science and Engineering, Shanghai University, Shanghai, ChinaShanghai Urban Construction Road Engineering Co., Ltd, Shanghai Road & Bridge (Group) Co., Ltd, Shanghai, ChinaThe construction industry is one of the most dangerous industries with grave situation owing to high accident rate and mortality rate, which accompanied with a series of security management issues that need to be tackled urgently. The unsafe behavior of construction workers is a critical reason for the high incidence of safety accidents. Affective Events Theory suggests that individual emotional states interfere with individual decisions and behaviors, which means the individual emotional states can significantly influence construction workers’ unsafe behaviors. As the complexity of the construction site environment and the lack of attention to construction workers’ emotions by managers, serious potential emotional problems were planted, resulting in the inability of construction workers to effectively recognize safety hazards, thus leading to safety accidents. Consequently, the study designs a behavioral experiment with E-prime software based on social cognitive neuroscience theories. Forty construction workers’ galvanic skin response signals were collected by a wearable device (HKR-11C+), and the galvanic skin response data were classified into different emotional states with support vector machine (SVM) algorithm. Variance analysis, correlation analysis and regression analysis were used to analyze the influence of emotional states on construction workers’ recognition ability of safety hazards. The research findings indicate that the SVM algorithm could effectively classify galvanic skin response data. The construct ion workers’ the reaction time to safety hazards and emotional valence were negatively correlated, while the accuracy of safety hazards recognition and the perception level of safety hazard separately had an inverted “U” type relationship with emotional valence. For construction workers with more than 20 years of working experience, work experience could effectively reduce the influence of emotional fluctuations on the accuracy of safety hazards identification. This study contributes to the application of physiological measurement techniques in construction safety management and shed a light on improving the theoretical system of safety management.https://www.frontiersin.org/articles/10.3389/fpsyg.2022.895929/fullsafety managementconstruction workersemotional statessafety hazardsgalvanic skin response |
| spellingShingle | Dan Chong Anni Yu Hao Su Yue Zhou The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience Frontiers in Psychology safety management construction workers emotional states safety hazards galvanic skin response |
| title | The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience |
| title_full | The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience |
| title_fullStr | The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience |
| title_full_unstemmed | The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience |
| title_short | The Impact of Emotional States on Construction Workers’ Recognition Ability of Safety Hazards Based on Social Cognitive Neuroscience |
| title_sort | impact of emotional states on construction workers recognition ability of safety hazards based on social cognitive neuroscience |
| topic | safety management construction workers emotional states safety hazards galvanic skin response |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.895929/full |
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