Impact of Safety Attitude on the Safety Behavior of Coal Miners in China

Experimental Study on Emergency Psychophysiological and Behavioral Reactions to Coal Mining Accidents

Effective emergency responses are crucial for preventing coal mine accidents and mitigating injuries. This paper aims to investigate the characteristics of emergency psychophysiological reactions to coal mine accidents and to explore the potential of key indicators for identifying emergency behavioral patterns. Initially, virtual reality technology facilitated a simulation experiment for emergency escape during coal mine accidents. Subsequently, the characteristics of emergency reactions were analyzed through correlation analysis, hypothesis testing, and analysis of variance. The significant changes in physiological indicators were then taken as input features and fed into the three classifiers of machine learning algorithms. These classifications ultimately led to the identification of behavioral patterns, including agility, defensiveness, panic, and rigidity, that individuals may exhibit during a coal mine accident emergency. The study results revealed an intricate relationship between the mental activities induced by accident stimuli and the resulting physiological changes and behavioral performances. During the virtual reality simulation of a coal mine accident, subjects were observed to experience significant physiological changes in electrodermal activity, heart rate variability, electromyogram, respiration, and skin temperature. The random forest classification model, based on SCR + RANGE + IBI + SDNN + LF/HF, outperformed all other models, achieving accuracies of up to 92%. These findings hold promising implications for early warning systems targeting abnormal psychophysiological and behavioral reactions to emergency accidents, potentially serving as a life-saving measure in perilous situations and fostering the sustainable growth of the coal mining industry.

Validation of the Spanish version of the Neal, Griffin and Hart safety behavior scale

Objectives. The safety behavior scale (SBS), developed by Neal, Griffin and Hart, is one of the most widely used conceptualizations in the field of occupational safety. Previous studies have evaluated the psychometric properties of this scale in different populations. However, few validation studies have been conducted in the Latin American context. To fill these gaps in the literature, this study aimed to assess the validity, reliability and measurement invariance of this instrument in the context of the Latin American mining industry. Methods. Data were collected from 398 workers from Ecuadorian mining companies. The questionnaire was translated into Spanish following a back-translation process. The latent factorial structure of the SBS was explored by estimating a series of confirmatory factor analysis (CFA) and exploratory equation modeling (ESEM) models. Results. The analyses showed that the two correlated first-order factor CFA representation was the most appropriate model for the data. Measurement invariance by age, type of contract and firm size was also confirmed. Conclusions. The SBS is a valid and reliable measure of safety behavior. In addition, this study determined the applicability of this instrument in the Latin American context, which enhances opportunities for future research in the region.

Behavior-based safety program for process industries

Objectives. This article describes the reduction of unsafe behaviors observed at a fertilizer complex by implementation of a behavior-based safety (BBS) program via a behavior observation form developed by a multidisciplinary team. Methods. Six observation categories, i.e., position of people, reaction of people, personal protective equipment (PPE), tools used, operating procedures and housekeeping, are used to monitor safe and unsafe behaviors for a period of 18 months. Results. Safe behaviors increased from 57 to 70% and unsafe behaviors reduced from 40 to 26%. Behaviors of employees working in various sections of fertilizer complex such as ammonia, urea, utility, bagging/shipping and workshop were also observed. Non-compliance with PPE, housekeeping and standard operating procedures was also monitored in individual sections. Non-operational areas including the administration block, housing colony, maintenance workshop, warehouse, fire station and electrical substation were also observed. Among these, the maximum unsafe behaviors are for the housing colony and minimum for the electrical substation. Conclusion. It has been concluded that working on the housing colony, administration block and fire station areas will address 74% unsafe behaviors of non-operational areas. For practical applications, worldwide industries can implement this BBS program to enhance BBS, thus reducing unsafe behaviors and increasing employee morale.

Game analysis of enterprise safety investment and employee safety behavior strategy evolution in high-risk industries

This paper aims to explore the influential relationship between the decision-making of investment of enterprise safety and employee safety behavior strategy selection, thus improve the effectiveness of decision-making. Based on traditional game theory, this paper establishes an evolutionary game model of enterprise safety investment and employee safety behavior strategy selection, and conducts numerical simulation analysis. The result shows:when the security investment cost is greater than the security investment benefit, the employee's security behavior strategy choice is significant for the enterprise security investment strategy decision; when the security investment benefit is greater than the security investment cost, the enterprise security investment decision is not affected by the employee safety behavior strategy; the choice of employee safety behavior strategy is not affected by the choice of enterprise safety investment strategy. The conclusion can provide a reference basis for enterprise safety production decision-making, which has certain theoretical and practical significance.

The Predictors of Unsafe Behaviors among Nuclear Power Plant Workers: An Investigation Integrating Personality, Cognitive and Attitudinal Factors

Unsafe behaviors, such as violations and human errors, have long been recognized as the main causes of accidents in nuclear power plants (NPPs). However, personal factors that influence unsafe behaviors among NPP workers have not been well examined, especially in an integrated model. This study proposes an integrated contextual mediated model to examine personality, cognitive and attitudinal predictors of unsafe behaviors among commissioning workers at NPPs. The model was verified using structural equation modeling technique with survey data from 177 commissioning workers in two Chinese NPPs. Results show that personality traits (i.e., conscientiousness, neuroticism, openness and agreeableness), executive function and safety attitudes exerted significant effects on unsafe behaviors. In addition, the effects of agreeableness and executive function were partly mediated by safety attitudes. Both conscientiousness and neuroticism indirectly influenced unsafe behaviors through the mediating role of executive function. The findings shed light on the design of evidence-based interventions for safety performance in NPPs.

The Mediation Role of Safety Attitude in the Impact of Resilience on the Safety Behavior of Coal Miners in China

Resilience can improve the adaptability of coal miners to high-hazard and high-stress environments. After facing setbacks or adversities, resilience can enable coal miners to recover from bad mental states and have an optimistic safety attitude and positive safety behaviors. However, how resilience affects safety behavior and the role of safety attitude in the relationship have not been clear. This study systematically reviewed previous research on resilience, safety attitude, and safety behavior. By recovering 639 valid questionnaires, the validity and reliability of the resilience scale, safety attitude scale, and safety behavior scale for coal miners were verified. Hierarchical regression analysis explored the relationships between resilience, safety attitude, and safety behavior. Studies have shown that resilience positively affects safety attitude and safe behavior. Safety attitude positively affects safety behaviors and plays a role as a partial mediator in the impact of resilience on safe behavior. The theoretical contribution is that the resilience of miners has a positive impact on safety behavior. Moreover, resilience can also act on safety behaviors through the partial intermediation of safety attitude. The practical contribution is that managers of coal mining companies can promote the resilience and safety attitude of coal miners to improve safety behaviors and prevent accidents.

Exploring Occupational Health and Safety Standards Compliance in the South African Mining Industry, Limpopo Province, Using Principal Component Analysis

The health and safety of the miners in the South African mining industry are guided by the regulations and standards applied to promote a healthy work environment. The miners must comply with these regulations/standards to protect themselves from potential occupational health and safety risks, accidents, and fatalities. The status of compliance to safety regulations and standards in the mining industry of Limpopo Province has received little attention from scholars. This study explores the practices related to occupational health and safety standards compliance in the mining industry. A total of 277 miners were randomly selected from 1300 respondents in the mining industry. Data were collected using a 31-item survey questionnaire, administered to miners to explore occupational health and safety standards compliance from December 2019 to May 2020. Principal Component Analysis (PCA) extracted key attributes of occupational health and safety standards compliance in the mining industry and uncovered relationships between different dimensions. The study revealed that seven factors could measure occupational health and safety standards practices. It was observed that Factor 1 (occupational health practice related to regulations) is correlated with Factor 2 (measures to reduce risk of injuries/accidents). Additionally, Factor 2 (measures to minimise the risk of injuries/accidents) is correlated with Factor 4 (impact of the environment and production). There is a correlation between non-compliance with the safety regulations and the occurrence of injuries and accidents.

Risk Factors Identification of Unsafe Acts in Deep Coal Mine Workers Based on Grounded Theory and HFACS

The risk factors affecting workers' unsafe acts were comprehensively identified by Human Factors Analysis and Classification System (HFACS) and grounded theory based on interview data and accident reports from deep coal mines. Firstly, we collected accident case and field interview data from deep coal mines issued by authoritative institutions. Then, the data were coded according to grounded theory to obtain relevant concepts and types. The HFACS model was used to classify the concepts and categories. Finally, the relationship between core and secondary categories was sorted out by applying a story plot. The results show that risk factors of unsafe acts of deep coal mine workers include environmental factors, organizational influence, unsafe supervision and unsafe state of miners, and the main manifestations of unsafe acts are errors and violations. Among them, the unsafe state of miners is the intermediate variable, and other factors indirectly affect risky actions of coal miners through unsafe sates. Resource management, organizational processes and failure to correct problems are the top three risk factors that occur more frequently in unsafe acts. The three most common types of unsafe act are unreasonable labor organization, failure to enforce rules, and inadequate technical specifications. By combining grounded theory and the HFACS framework to analyze data, risk factors for deep coal miners can be quickly identified, and more precise and comprehensive conceptual models of risk factors in unsafe acts of deep coal miners can be obtained.

Influencing Factors, Formation Mechanism, and Pre-control Methods of Coal Miners′ Unsafe Behavior: A Systematic Literature Review

Coal mine accidents are mainly caused by the unsafe behavior of workers. Studying workers' unsafe behaviors can help in regulating such behaviors and reducing the incidence of accidents. However, there is a dearth of systematic literature review in this area, which has hindered mine managers from fully understanding the unsafe behavior of workers. This study aims to address this research gap based on the literature retrieved from the Web of Science. First, a descriptive statistical analysis is conducted on the year, quantity, publications, and keywords of the literature. Second, the influencing factors, formation mechanism, and pre-control methods of coal miners' unsafe behavior are determined and discussed, and the research framework and future research directions of this study are proposed. The study results will help mine safety managers fully understand the influencing factors, formation mechanism, and pre-control methods of workers' unsafe behavior, and lay a theoretical foundation for the future research direction in this field.

Mining Employees Safety and the Application of Information Technology in Coal Mining: Review

Background: Though the introduction of modern safer underground coal mining methods and automation, mine accidents still cause loss of lives, time, and money. This paper aims to analyze in detail the causes of safety and environmental issues in the coal mining industry, as well as the impact of IoT on coal mining. Method: A systematic review was conducted. A comprehensive search involving Web of Science, Google Scholar, Scopus, and Science direct databases was conducted using a combination of the following keywords: mining accidents, coal mining injuries, human error in mining, intelligent mining, etc. The inclusion criteria: (1) the study was published between January 2000 and June 2020; (2) the participants were coal mining employees/coal mining accidents and accidents were work-related; (3) the study focused on identifying causes of coal mining safety issues or accidents, factors that influence unsafe behaviors and accidents in coal mining, coal mining rescue management, coal mining rescue plan, coal mining environmental impact, mining information technology, intelligent mining; (4) the study was published in a refereed journal; (5) the study was written in English. In this paper, articles were retained if they were original studies. Results: A total of 59 papers were reviewed in detail. Safety issues in coal mining and the impact of IoT were identified and categorized into three main factors: general safety issues, environmental factors, and mining information technology. Recently, the coal mines had become mechanized and automated leading to improved safety, productivity, and cost. However, Human factors such as lack of appropriate skill, lack of experience, perceptual error, and unsafe behaviors, as well as lack of detailed emergency rescue plan were the leading causes of coal mining injuries. Furthermore, abandoned mining sites' carbon emission is greater than active sites. Conclusion: The study recommends further research to be conducted using different psychological models to understand human factors and design effective safety management systems. And the environmental impact of abandoned mining sites should be given due attention.

Upward Voice: Participative Decision Making, Trust in Leadership and Safety Climate Matter

A supportive upward voice environment is critical in nuclear power plants in order to provide energy in a sustainable manner. In high–reliability organizations, front–line employees’ suggestions and concerns enable the early identification of potential problems that might have catastrophic consequences (e.g., a nuclear accident). Despite this, previous research has mostly focused on person–centered antecedents of upward voice and, to a lesser extent, the influence of the supervisor–subordinate relationship, while neglecting the importance of the organizational context. This study responds to the aforementioned research lacuna. It examined the relationship between participative decision making and upward voice, and the mediating role of trust in leadership in this relationship. Moreover, it further extends previous research by examining the role of safety climate, which is expected to moderate both the direct and the indirect effect of participative decision making on upward voice. The sample was composed of 495 workers from two nuclear power plants from the same organization. Findings supported the hypothesized moderated mediation model: the indirect effect of participative decision making (PDM) on upward voice via trust in leadership was contingent upon the level of the safety climate. The indirect effect became weaker as the safety climate increased. These findings support the relevance of the organizational context.