دورية أكاديمية

Research on psychophysiological characteristics of construction workers during consciously unsafe behaviors

التفاصيل البيبلوغرافية
العنوان: Research on psychophysiological characteristics of construction workers during consciously unsafe behaviors
المؤلفون: Xiangchun Li, Yuzhen Long, Chunli Yang, Qin Li, Weidong Lu, Jiaxing Gao
المصدر: Heliyon, Vol 9, Iss 10, Pp e20484- (2023)
بيانات النشر: Elsevier, 2023.
سنة النشر: 2023
المجموعة: LCC:Science (General)
LCC:Social sciences (General)
مصطلحات موضوعية: Risky psychology, Physiological characteristic, Multiple linear regression, Decision tree regressor, Unsafe behavior prediction, Science (General), Q1-390, Social sciences (General), H1-99
الوصف: Workers' unsafe behavior is a primary cause leading to falling accidents on construction sites. This study aimed to explore how to utilize psychophysiological characteristics to predict consciously unsafe behaviors of construction workers. In this paper, a psychological questionnaire was compiled to measure risky psychology, and wireless wearable physiological recorders were employed to real-timely measure the physiological signals of subjects. The psychological and physiological characteristics were identified by correlation analysis and significance test, which were then utilized to develop unsafe behavior prediction models based on multiple linear regression and decision tree regressor. It was revealed that unsafe behavior performance was negatively correlated with task-related risk perception, while positively correlated with hazardous attitude. Subjects experienced remarkable increases in skin conductivity, while notable decreases in the inter-beat interval and skin temperature during consciously unsafe behavior. Both models developed for predicting unsafe behavior were reliably and well-fitted with coefficients of determination higher than 0.8. Whereas, each model exhibited its unique advantages in terms of prediction accuracy and interpretability. Not only could study results contribute to the body of knowledge on intrinsic mechanisms of unsafe behavior, but also provide a theoretical basis for the automatic identification of workers’ unsafe behavior.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2405-8440
العلاقة: http://www.sciencedirect.com/science/article/pii/S2405844023076922Test; https://doaj.org/toc/2405-8440Test
DOI: 10.1016/j.heliyon.2023.e20484
الوصول الحر: https://doaj.org/article/7589466f5dec44adaae2d8462545a0a2Test
رقم الانضمام: edsdoj.7589466f5dec44adaae2d8462545a0a2
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24058440
DOI:10.1016/j.heliyon.2023.e20484