Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers
Background: This study aimed to examine the effect of perception, attention, and sleep levels on the number of occupational accidents and near-misses in the mining and metal sectors. Methods: The data were collected from 53 employees in the mining (n = 30) and metal (n = 23) sectors in 2021 from a mining and metal company. The study collected the following data from the sample: demographic information forms, previous accident and previous near-miss histories, Pittsburgh Sleep Quality (PSQI) scale, pulse, sleep levels, and attention tests. Results: Having an education at primary school and below (B = 0.235; p < 0.05), and having an education at the high school level (B = 0.710; p < 0.01), being single (B = −0.291; p < 0.01), time working in the department (B = 0.027; p < 0.05), time working in the company (B = −0.034; p < 0.05), and the number of near-misses (B = 0.354; p < 0.01), had a significant impact on accidents. Having an education in primary school or below (B = −1.532; p < 0.01), not having had an accident (B = −3.654; p < 0.01), age (B = 0.074; p < 0.01), correct score (B = 0.014; p < 0.01), incorrect time (B = 0.228; p < 0.01) and unanswered score averages (B = −0.029; p < 0.01) had a significant impact on near-misses. Conclusion: Education, the working year, and working time had significant effects on workplace accidents.
A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers
Background: This study aimed to examine the effect of perception, attention, and sleep levels on the number of occupational accidents and near-misses in the mining and metal sectors. Methods: The data were collected from 53 employees in the mining (n = 30) and metal (n = 23) sectors in 2021 from a mining and metal company. The study collected the following data from the sample: demographic information forms, previous accident and previous near-miss histories, Pittsburgh Sleep Quality (PSQI) scale, pulse, sleep levels, and attention tests. Results: Having an education at primary school and below (B = 0.235; p < 0.05), and having an education at the high school level (B = 0.710; p < 0.01), being single (B = −0.291; p < 0.01), time working in the department (B = 0.027; p < 0.05), time working in the company (B = −0.034; p < 0.05), and the number of near-misses (B = 0.354; p < 0.01), had a significant impact on accidents. Having an education in primary school or below (B = −1.532; p < 0.01), not having had an accident (B = −3.654; p < 0.01), age (B = 0.074; p < 0.01), correct score (B = 0.014; p < 0.01), incorrect time (B = 0.228; p < 0.01) and unanswered score averages (B = −0.029; p < 0.01) had a significant impact on near-misses. Conclusion: Education, the working year, and working time had significant effects on workplace accidents.
A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers
Ahmet Tasdelen (Autor:in) / Alper M. Özpinar (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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