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      Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

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      International Journal of Environmental Research and Public Health
      MDPI AG

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          Abstract

          The unsafe behavior of miners seriously affects the safety of deep mining. A comprehensive evaluation of miners’ unsafe behavior in deep coal mines can prevent coal mine accidents. This study combines HFACS-CM, SEM, and SD models to evaluate miners’ unsafe behaviors in deep coal mining. First, the HFACS-CM model identifies the risk factors affecting miners’ unsafe behavior in deep coal mines. Second, SEM was used to analyze the interaction between risk factors and miners’ unsafe behavior. Finally, the SD model was used to simulate the sensitivity of each risk factor to miners’ unsafe behavior to explore the best prevention and control strategies for unsafe behavior. The results showed that (1) environmental factors, organizational influence, unsafe supervision, and unsafe state of miners are the four main risk factors affecting the unsafe behavior of miners in deep coal mines. Among them, the unsafe state of miners is the most critical risk factor. (2) Environmental factors, organizational influence, unsafe supervision, and the unsafe state of miners have both direct and indirect impacts on unsafe behaviors, and their immediate effects are far more significant than their indirect influence. (3) Environmental factors, organizational influence, and unsafe supervision positively impact miners’ unsafe behavior through the mediating effect of miners’ unsafe states. (4) Mental state, physiological state, business abilities, resource management, and organizational climate were the top five risk factors affecting miners’ unsafe behaviors. Taking measures to improve the adverse environmental factors, strengthening the organization’s supervision and management, and improving the unsafe state of miners can effectively reduce the risk of miners’ unsafe behavior in deep coal mines. This study provides a new idea and method for preventing and controlling the unsafe behavior of miners in deep coal mines.

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          Most cited references68

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          Predicting safety behavior in the construction industry: Development and test of an integrative model

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            Calculating workplace WBGT from meteorological data: a tool for climate change assessment.

            The WBGT heat stress index has been well tested under a variety of climatic conditions and quantitative links have been established between WBGT and the work-rest cycles needed to prevent heat stress effects at the workplace. While there are more specific methods based on individual physiological measurements to determine heat strain in an individual worker, the WBGT index is used in international and national standards to specify workplace heat stress risks. In order to assess time trends of occupational heat exposure at population level, weather station records or climate modelling are the most widely available data sources. The prescribed method to measure WBGT requires special equipment which is not used at weather stations. We compared published methods to calculate outdoor and indoor WBGT from standard climate data, such as air temperature, dew point temperature, wind speed and solar radiation. Specific criteria for recommending a method were developed and original measurements were used to evaluate the different methods. We recommend the method of Liljegren et al. (2008) for calculating outdoor WBGT and the method by Bernard et al. (1999) for indoor WBGT when estimating climate change impacts on occupational heat stress at a population level.
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              Industrial Dynamics

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                Author and article information

                Contributors
                Journal
                IJERGQ
                International Journal of Environmental Research and Public Health
                IJERPH
                MDPI AG
                1660-4601
                September 2022
                August 29 2022
                : 19
                : 17
                : 10762
                Article
                10.3390/ijerph191710762
                4c569ddc-b968-4686-b001-ebef4907d6b9
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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