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Accidents are frequent in the construction industry, where managerial negligence and inadequate safety supervision are significant factors that contribute to these safety incidents. However, existing research tended to concentrate on the outcomes resulting from inadequate safety supervision but neglected the decision-making process behind insufficient supervision, which fails to fundamentally address the issue of accidents caused by insufficient supervision. To address these gaps, this study examines the key cost–benefit factors influencing safety supervision decisions among employers, contractors, supervisors, and construction workers in the Chinese construction industry. Using semistructured interviews with 49 participants and questionnaire surveys with 203 respondents, the effects of various factors on safety supervision were identified. An evolutionary game model was then employed for simulation based on the identified key factors to provide recommendations. The findings reveal 58 pivotal cost–benefit factors that influence safety-related decisions, encompassing four explicit benefits, eight implicit benefits, 35 explicit costs, and 11 implicit costs. The results indicate that implicit costs and benefits are significant factors driving safety supervision. Explicit costs are primarily driven by company or project standards, whereas implicit costs are influenced by company or employee attitudes and perceptions. Additionally, recommendations were proposed: increasing awareness of the implicit benefits of safety supervision, reducing noncritical expenditures, improving hazard awareness, and strengthening government and employer supervision. This research contributes to enriching the cost–benefit framework in construction safety supervision, shedding light on the root causes of insufficient safety supervision through a cost–benefit analysis, and implementing measures to promote safety supervision and onsite safety performance. [ABSTRACT FROM AUTHOR]

Objectives. Although some studies have shown role stressors can lead to unsafe behaviors, it is unclear how role stressors induce delivery riders' unsafe behaviors. We found that delivery riders suffered from tremendous role stressors during the delivery process and had to conduct frequent smartphone interactions. This study aimed to explore the effects of role stressors and smartphone interactions on delivery riders' unsafe behaviors. Methods. First, a questionnaire survey (N = 326) was used to collect data, and correlation and regression analyses were conducted to explore the relationship between role stressors, smartphone interaction frequency and delivery riders' unsafe behaviors. Second, a scenario survey (N = 35) was conducted, and comparative analysis was used to further explore how smartphone interactions affect delivery riders' unsafe behaviors. Results. The questionnaire survey revealed that role stressors, smartphone interaction frequency and delivery riders' unsafe behaviors were positively correlated. In addition, the role stressors forced delivery riders to conduct necessary and unnecessary smartphone interactions. The scenario survey found that smartphone interactions reduced delivery riders' motion speed and motion ability, and increased their psychology, so they had a risk-taking mentality, which led to an increase in unsafe behaviors. [ABSTRACT FROM AUTHOR]

Effective safety management is vital for ensuring construction safety. Traditional safety inspections in construction heavily rely on manual labor, which is both time-consuming and labor-intensive. Extensive research has been conducted integrating computer-vision technologies to facilitate intelligent surveillance and improve safety measures. However, existing research predominantly focuses on singular tasks, while construction environments necessitate comprehensive analysis. This study introduces a multi-task computer vision technology approach for the enhanced monitoring of construction safety. The process begins with the collection and processing of multi-source video surveillance data. Subsequently, YOLOv8, a deep learning-based computer vision model, is adapted to meet specific task requirements by modifying the head component of the framework. This adaptation enables efficient detection and segmentation of construction elements, as well as the estimation of person and machine poses. Moreover, a tracking algorithm integrates these capabilities to continuously monitor detected elements, thereby facilitating the proactive identification of unsafe practices on construction sites. This paper also presents a novel Integrated Excavator Pose (IEP) dataset designed to address the common challenges associated with different single datasets, thereby ensuring accurate detection and robust application in practical scenarios. [ABSTRACT FROM AUTHOR]

The construction industry’s poor safety is a global issue, with construction workers’ unsafe behaviors (CWUBs) identified as a major cause of accidents. Based on social cognitive theory (SCT) and using multiple regression analysis, this study categorizes accident experience (AE) into direct and indirect types, examining how each affects CWUBs and the roles of risk perception (RP), safety attitude (SA), and safety competence (SC) in these relationships. Utilizing a structured questionnaire completed by 334 valid respondents and analyzed through structural equation modeling (SEM), the study found that indirect experience (IE) significantly reduced CWUBs, with a standardized path coefficient of −0.364, while direct experience (DE) has a smaller impact, with a standardized path coefficient of −0.154, but a significant p. Furthermore, IE positively influenced RP, SA, and SC, explaining 66.8% of its total effect. This study offers a new framework for understanding how AE influences CWUBs, providing actionable insights for managers to implement effective strategies that reduce CWUBs on construction sites.

Effective safety management is vital for ensuring construction safety. Traditional safety inspections in construction heavily rely on manual labor, which is both time-consuming and labor-intensive. Extensive research has been conducted integrating computer-vision technologies to facilitate intelligent surveillance and improve safety measures. However, existing research predominantly focuses on singular tasks, while construction environments necessitate comprehensive analysis. This study introduces a multi-task computer vision technology approach for the enhanced monitoring of construction safety. The process begins with the collection and processing of multi-source video surveillance data. Subsequently, YOLOv8, a deep learning-based computer vision model, is adapted to meet specific task requirements by modifying the head component of the framework. This adaptation enables efficient detection and segmentation of construction elements, as well as the estimation of person and machine poses. Moreover, a tracking algorithm integrates these capabilities to continuously monitor detected elements, thereby facilitating the proactive identification of unsafe practices on construction sites. This paper also presents a novel Integrated Excavator Pose (IEP) dataset designed to address the common challenges associated with different single datasets, thereby ensuring accurate detection and robust application in practical scenarios.

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. [ABSTRACT FROM AUTHOR]

Identifying and modeling the factors affecting unsafe behaviors (UBs) have been conducted by various methods such as qualitative studies, game theory, and modeling using dynamic system. Therefore, the present study aimed to provide a study protocol in the field of modeling the factors affecting UBs by conducting a case study in Iranian workers. This protocol consists of four phases including identifying the factors affecting UBs using grounded theory, weighting the factors extracted by fuzzy best–worst and mapping relationships with fuzzy cognitive map, modeling effective factors with system dynamic, and examining possible scenarios to reduce UBs; all its stages are described in detail and finally the results of a case study is reported. Since the implementation of policies and adoption of the best method to reduce UBs is based on trial and error and always requires a lot of time, cost, and equipment, using modeling study can help reduce the cost of choosing an intervention method. Also, by using the protocol present in each industry, the best scenarios and models can be identified in accordance with the specified factors and specific to the same industry; we can also select and implement the most appropriate strategy to reduce UBs appropriate for preventing unsafe behavior and reduce industrial accidents. [ABSTRACT FROM AUTHOR]

Introduction: Nurses are under the influence of stressful factors and high work pressure, which increases nursing errors. One factor affecting nurses’ behavior and performance is the mental workload and cognitive failures. This research has investigated the mental workload and cognitive failures in two groups of nurses with and without unsafe behaviors during the outbreak of Covid-19. Material and Methods: This case-control study was conducted on 312 nurses during the severe period of the Covid-19 outbreak through the public hospitals in Guilan province. Sampling was performed by selecting 104 nurses in the case group (with unsafe behavior) and 208 nurses in the control group (with safe behavior) using the full count method. The data collection tool is a three-part questionnaire including demographic information, the mental workload (NASA-TLX) questionnaire, and the occupational cognitive failures questionnaire. The incidence of needle stick as a consequence of unsafe behavior was used as a criterion. Results: The results have shown that the workload in this research was 63.96±18.26, and the total score of cognitive failures was 59.1±13.9. There was no statistically significant difference between the two groups of nurses with and without unsafe behaviors (P>0.05). Still, there was a significant correlation between the total mental workload score in all areas and the total score of cognitive failures in the group of nurses with and without unsafe behaviors (p=0.001, r=0.225). Conclusion: According to the results, the perceived mental workload is high for the nursing job. Despite of positive correlation between mental workload and cognitive failures, it can be mentioned that there are two-way interactions through their dimensions. Therefore, the nursing job requires adopting optimal engineering and management strategies to reduce the workload.

Work stress has a significant impact on unsafe behaviors. However, there has been limited exploration of the relationship between work stress and unsafe behaviors. The aim of this research was to examine the effect of work stress on unsafe behaviors, while incorporating the mediating effect of fatigue and the moderating role of safety climate. Data were collected from 1224 front-line oil workers in China. The findings showed that work stress had a significant effect on unsafe behaviors, and that fatigue and safety climate played partial mediating and moderating roles in the relationship respectively. In terms of their sub-dimensions, (1) job certainty and job control had positive influences on unsafe behaviors, while only social support was negatively associated with unsafe behaviors. (2) Five sub-dimensions of safety climate moderated the effect of work stress on unsafe behaviors. This research contributes to the study on the mechanism of unsafe behaviors by demonstrating differential effects of work stress, fatigue and safety climate and by considering their combined effects. Measures for reducing unsafe behaviors from the perspective of work stress and safety climate are discussed. [ABSTRACT FROM AUTHOR]

Background: Some researchers state that they are not yet able to provide a deep understanding of the underlying causes of unsafe behaviors (UBs). Therefore, the present study was conducted to investigate the attitudes and experiences of Iranian workers of UBs. Methods: This present study was conducted in 35 industries using a semistructured interview based on grounded theory. Forty participants were interviewed, including 13 industrial safety and health experts and 27 workers and supervisors. The analysis of the present study consisted of a three-step coding process including open, axial, and selective coding. Results: The results showed that the factors affecting UBs could be classified into three categories: organizational, individual, and socioeconomic factors. Organizational factors were divided into 6 parts: procedure and environmental conditions, communications, monitoring, organizational safety culture, resource allocation, and human resources. Socioeconomic factors had three subcategories: community safety culture, type of organizational ownership, and economic problems. Finally, the individual factors were classified into two categories of personality traits and individual competence. Conclusion: The results showed that organizational factors were the most categorized, and it is estimated that this factor has a more important role in the UBs. Of course, to better understand the close relationship between these factors and find the weight and importance of each factor, it needs to measure it with multicriteria decision systems.

In order to study the influence mechanism of emotional intelligence on miners’ unsafe behaviors, emotional labor strategy was introduced as an intermediary variable. Based on a questionnaire survey of 300 miners, the optimal structural equation model of the influence of emotional intelligence on miners’ unsafe behaviors was constructed by AMOS24.0 software. The results show that: all dimensions of emotional intelligence of miners have a significant negative impact on the surface acting, and a positive impact on the deep acting, and the ability of self-emotion perception, emotion regulation and emotional use ability have a significant negative impact on unsafe behavior. At the same time, surface acting and deep acting in emotional labor strategy mediate the relationship between emotional intelligence and unsafe behavior of miners.

Introduction: Accidents may occur in all occupations. However, firefighting is considered one of the most dangerous occupations considering firefighters' perception of security, work-related injury rate, safety behaviors, attitudes, and norms. Therefore, this study aims to investigate the correlation between the organizational safety climate and unsafe behaviors among firefighters. Methodology: This was a descriptive and survey research. The statistical population included all the managers and employees working in a fire department consisting of 16 fire stations in Tehran. A researcher-made checklist and an organizational safety climate questionnaire were used to assess the prevalence of unsafe behaviors and safety climate. The data were analyzed using SPSS 21.0 software. Results: The employees' mean age, body mass index (BMI), and work, rest, and exercise duration were 32.5±66.83 years old, 25.69±3.7, 9.2±14.1 h/d, 8.15±1.73 h/d, and 5.44±4.46 h/w, respectively. Also, 66% of the employees were overweight and 29% had normal weight. Among the safety climate dimensions, the highest mean was related to management commitment to safety issues (33.7±62.68) and the lowest mean was related to priority over products (6.1±03.63). Unsafe behaviors were mostly associated with lack of using the breathing apparatus in small fires (91.9%) as well as personal protective equipment (PPE) (77.4%) in accidents and not performing operations with inappropriate physical condition (38.7%). The t-test results revealed a significant correlation between the safety climate and prevalence of unsafe behaviors (P≤0.05). Moreover, a significant correlation was observed between the employees' knowledge, participation, attitudes, and environmental safety (P≤0.05). However, no significant correlation was found between emergency preparedness, safety priority, and ignoring risks. Conclusion: Organizational safety climate could affect and predict employees' behaviors. Therefore, it is recommended that fire department managers develop a plan to achieve the required safety climate and improve the safety climate level. [ABSTRACT FROM AUTHOR]

Background. In this study, we aimed to discover why workers engage in unsafe behaviors and reach a deep understanding of all causes influencing unsafe acts among workers in a mining industry. We also aimed to determine which causes play a more important role in the occurrence of unsafe acts. Methods. First, we determined the unsafe acts through observation and then investigated the factors affecting them based on semi-structured interviews. In order to identify the most important causes, we utilized centrality indicators including the degree and betweenness centrality of the social network analysis using UCINET version 6.0. Results. In total, 3058 unsafe acts were observed and 85 causes, classified into 14 factors, were found to influence the behavioral intention of workers. In this study, inadequate supervision, with the highest degree of centrality, proved to be of great influence on performing unsafe behaviors. In addition, inadequate training, with the highest betweenness centrality, was determined as the main intermediary in the mining industry under investigation. Discussion and conclusion. The findings indicate that workers' unsafe acts are affected by different causes, leading to significant implications for policy-makers seeking to reduce unsafe behaviors and to improve workplace safety in the mining environment. [ABSTRACT FROM AUTHOR]

Aim: Unsafe behaviors (UBs) are the most important cause of accidents, so there is a need to identify the factors effective on it. The purpose of this study was to identify the factors affecting the occurrence of UBs and also to build a strong theoretical model with fuzzy logic. Materials and Methods: This study was conducted among 270 participants in the steel industry in Iran. The factors, such as work-family conflict, job stress, and general health were investigated using relevant questionnaires, and the prevalence of UBs was investigated with the safety behavior sampling technique. Finally, the results were analyzed with SPSS 21.0 and MATLAB software. Findings: The results showed that out of 1310 samples of observed behavior, 531 UBs were observed (39.81%). There were 202 cases of nonuse or inappropriate use of personal protective equipment. General health, job stress in the supervisor, and colleagues' support were significantly associated with UBs (P < 0.05). In addition, general health, work-family conflict, job stress and were significantly correlated with each other (P < 0.001). Diffuse results using fuzzy logic predicted 56% of the behavioral conditions. Conclusions: This study showed that managing UBs is possible by controlling factors such as the support of supervisors and the way of management, as well as the reduction of social stresses such as work-family conflict, in addition to being able to increase people's health, also reducing accidents and UBs. Finally, using fuzzy logic, it is able to predict reality, and by knowing several behaviors, better models can be obtained. [ABSTRACT FROM AUTHOR]

A representativeness heuristic (RH) refers to a shortcut in decision making, one or two subdimensions of which have been found to impact construction workers' unsafe behaviors prominently. To reduce workers' reliance on representativeness heuristic effectively, two key questions should be clarified: (1) whether all subdimensions of the representativeness heuristic influence workers' decision making, and (2) whether such a heuristic is more or less prevalent in certain groups. However, both issues remain unresolved. To fill in these research gaps, the current study collected data using a questionnaire survey from 194 Chinese workers in eight construction projects. After a series of analyses, the results revealed that (1) all subdimensions of the representativeness heuristic had potential to impact construction workers' decision making; and (2) workers' reliance on the representativeness heuristic had an initial downtrend followed by an uptrend as age and education level increased, whereas seniority and type of work were not related to this heuristic. The research findings are helpful for safety organizations to manage their diverse workforces. Devoting prevention resources to workers of particular age and education background groups is recommended to reduce the representativeness heuristic and improve the safety performance of construction sites further. [ABSTRACT FROM AUTHOR]

Previous studies have indicated that work stress has a significant impact on unsafe behaviors. This study explored the impacts of work stress on unsafe behaviors quantitatively using experimental methodology by developing a representative operation task to simulate the actual work in coal mines. The participants' work stress and unsafe behaviors were measured by the salivary cortisol concentrations and error rates, respectively. The results indicated that the experimental scenarios could effectively induce work stress, and there was a critical point from where unsafe behaviors were considerably minimized. When the stress level was below the critical point, there was a linear relationship between unsafe behaviors and the stress level. When the stress level was above the critical point, there was a quadratic relationship between them. The stress level below and above the critical point indicated challenge stress and hindrance stress, respectively. The results illustrated the feasibility of the experimental design, providing new ideas to eliminate unsafe behaviors induced by work stress among miners. [ABSTRACT FROM AUTHOR]

In order to explore the interaction relations of factors of miners' unsafe behaviors;emergent property theory is employed to extract the individual, managing, organizational and environmental factors that influence miners' unsafe behaviors based on 144 serious coal mine safety accident reports from 2009 to 2018.The DEMATEL/ISM methods are used to screen out key factors.On this basis, a miners' unsafe behaviors emergency model based on CGP was established.Then, using Netlogo simulation platform, the impact of these factors on the emergence degree and trend of the unsafe behavior of coal miners were dynamically simulated, and the simulation results under standard mode and analysis mode were compared and analyzed.The results show that the unsafe behaviors of coal miners is a emergent phenomenon under the influence of many factors.The emergence of unsafe behaviors of coal miners are affected by their personal educational level, the safety values of managers, the level of organizational safety commitment and safety status of workplace.In coal mine safety management, targeted measures based on these findings can be taken to pre-control and manage unsafe behaviors of miners.

Background and Objective: Offshore oil and gas platforms have a high potential for major and critical events due to sensitive operating conditions, the existence of critical equipment, and significant volumes of hydrocarbon materials. This study aimed to investigate the effect of organizational leadership and safety climate on the occurrence of unsafe behaviors among employees of oil platforms. Materials and Methods: This cross-sectional study was conducted in 2018 on five oil platform located in the Persian Gulf, Iran. The sample size was obtained at 291 employees. Multifactor Leadership Questionnaire and standard occupational safety climate questionnaire were used to assess the organizational leadership and safety climate, respectively. Furthermore, the unsafe behaviors checklist was utilized to determine the occurrence of unsafe behaviors based on the risk factors of accidents that have occurred at the oil platforms during the past 10 years. Results: According to the results, there was a significant inverse relationship between leadership styles (i.e., transformational and transactional) and the occurrence of unsafe behaviors. Moreover, the study of the relationship between different dimensions of safety climate and the occurrence of unsafe behaviors showed that dimensions of safety at work correlated significantly with the probability of ignoring the error and the occurrence of unsafe behaviors. Conclusion: The results of the present study showed that leadership styles (i.e., transformational and transactional), safety at work, and probability of ignoring errors in oil platforms are important and influential factors in the occurrence of unsafe behaviors.

Background and Objective: Offshore oil and gas platforms have a high potential for major and critical events due to sensitive operating conditions, the existence of critical equipment, and significant volumes of hydrocarbon materials. This study aimed to investigate the effect of organizational leadership and safety climate on the occurrence of unsafe behaviors among employees of oil platforms. Materials and Methods: This cross-sectional study was conducted in 2018 on five oil platform located in the Persian Gulf, Iran. The sample size was obtained at 291 employees. Multifactor Leadership Questionnaire and standard occupational safety climate questionnaire were used to assess the organizational leadership and safety climate, respectively. Furthermore, the unsafe behaviors checklist was utilized to determine the occurrence of unsafe behaviors based on the risk factors of accidents that have occurred at the oil platforms during the past 10 years. Results: According to the results, there was a significant inverse relationship between leadership styles (i.e., transformational and transactional) and the occurrence of unsafe behaviors. Moreover, the study of the relationship between different dimensions of safety climate and the occurrence of unsafe behaviors showed that dimensions of safety at work correlated significantly with the probability of ignoring the error and the occurrence of unsafe behaviors. Conclusion: The results of the present study showed that leadership styles (i.e., transformational and transactional), safety at work, and probability of ignoring errors in oil platforms are important and influential factors in the occurrence of unsafe behaviors.

Introduction and purpose: One of the most effective strategies in Health, Safety, and Environment Management System (HSE-MS) is the importance of training in safety. Therefore, the present study aimed to investigate the effectiveness of safety training on reducing the rate of unsafe acts using a management system in Ekbatan profiling industry. Methods: This cross-sectional study was conducted based on a descriptive-analytical and interventional design. Safety behavior sampling was initially utilized to determine the rate of unsafe behaviors. Subsequently, the rate of individuals' unsafe behaviors was assessed using prepared checklists and random observation. The HSE-MS was used for the improvement of unsafe behaviors. The effectiveness of the intervention and the level of unsafe behaviors were analyzed before and after the intervention, after two years using Excel 2007 and SPSS software (version 16) through the paired t-test. Results: The mean rate of the individuals' unsafe behaviors was 34% before the intervention. Moreover, the highest and lowest rates of the unsafe acts were awkward posture (25.8%) and running (0.8%) at the workplace, respectively. The results obtained from the paired t-test showed the effect of the intervention and a decrease in the rate of unsafe behaviors by 20% (P=0.037). Conclusion: Training is the cornerstone of the MS leading to the improvement of the unsafe behaviors. Therefore, continuous and effective training in the safety management system will result in a reduction in the rate of accidents and the improvement of the safety status.

The rate of coal mine accidents in China is still high and most coal mine accidents are caused by human unsafe behavior, and the correction of the behavior is, therefore, paramount. In this article, a group dynamics field model and a hierarchical index system of the group dynamics factors of the unsafe behavior of coal miners are established. The internal and external dynamics of groups are analyzed and the importance of each factor is calculated and determined. On this basis, suggested correction measures are put forward. Then, in combination with a questionnaire, the corrective measures of unsafe behaviors are determined and simulated. The results show that, while the correction of unsafe behaviors both in progress and after implementation can achieve good results, the former is more effective than the latter. Via the present research, both unsafe behaviors and the occurrence of coal mine accidents can be effectively prevented, and the safety of coal mine production can be ensured. [ABSTRACT FROM AUTHOR]

Building and urban railway construction are two typical high-risk types of construction in which unsafe behaviors have a considerable impact on the occurrence of accidents. To explore the patterns of unsafe behaviors and promote accident prevention, a comparative analysis is conducted to analyze the behavioral risk chains of accidents for these two construction types in the Chinese construction industry using complex network (CN) theory. First, accident cases are collected from government websites, and unsafe behaviors are extracted and classified according to a summary list of several safety standards and operating procedures. Second, behavioral risk chain networks of accidents (BRCNAs) for the two construction types are established as directed networks. Pajek, a program for visualizing and analyzing large networks, is then used to construct network models. Finally, the topological parameters of the BRCNAs are calculated and compared. The results show that BRCNAs are both scale-free and small-world networks. The characteristics of the building construction BRCNA are related to individual workers, and the characteristics of the urban railway construction BRCNA are related to the working environment and supervisors. However, there are certain unsafe behaviors that play an important role in accidents in both construction types. These findings reveal the variations in interactions among unsafe behaviors that cause accidents in the two construction types to further understand the patterns of unsafe behaviors. This study is of theoretical and practical significance for improving accident causation models and supporting on-site safety management in the construction industry. [ABSTRACT FROM AUTHOR]

Background: Unsafe behaviors are the cause of 80% of accidents. However, there has also been no worldwide review and meta-analysis of the prevalence of workers’ unsafe behaviors. Therefore, the present study aimed to investigate and estimate the prevalence of unsafe behaviors among Iranian workers using a systematic review and meta-analysis study. Methods: This systematic review and meta-analysis were conducted from Nov to Dec 2018. The researchers searched Medline/PubMed, Scopus, Embase, Science Direct, and Google Scholar for international articles and four Iranian databases (Scientific Information Database, MagIran, IranMedex, and IranDoc) for Persian articles. The method of reporting this study was based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) checklist. Results: Overall, 235 articles from databases were imported to EndNote library. Final screening of the included studies produced a total of 38 studies. Based on the random-effect model, the prevalence of total unsafe behaviors, non-use or inappropriate use of personal protective equipment, and inappropriate work posture was 40.37% (CI 95% = 35.8-44.9), 27.79% (CI 95% = 21.2-34.3), and 14.87% (CI 95% = 10.7-18.9). There was no statistically significant relationship between unsafe behaviors and mean age, mean of work experiences, and year of study. Conclusion: The prevalence of unsafe behaviors among Iranian workers was relatively high and the most common behaviors were non-use or inappropriate use of PPE; one of the most important causes for this behavior is lack of training, inappropriate working conditions, and lack of positive attitude towards safety. Therefore, further studied are required to investigate the causes of these unsafe behaviors.

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers' violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased. [ABSTRACT FROM AUTHOR]

This research tests whether the stressor-detachment model can explain the mechanism between workplace ostracism and employees' unsafe behaviors. We used a self-report questionnaire to assess Chinese construction workers' workplace ostracism, psychological detachment, emotional exhaustion, and unsafe behaviors. In total, 349 valid questionnaires were collected. We used cross-sectional structural equation modeling to assess our conceptual model. The results indicate that workplace ostracism has a significant effect on psychological detachment and emotional exhaustion and thus affects employees' unsafe behaviors. In addition, workplace ostracism could influence employees' unsafe behaviors through the sequential combination of psychological detachment and emotional exhaustion. Moreover, psychological detachment mediates the relationship between workplace ostracism and emotional exhaustion. Taken together, our findings extend the application of the stressor-detachment model by revealing how workplace ostracism influences employees' unsafe behaviors. [ABSTRACT FROM AUTHOR]

Abstract: Background and aims: The present study tests a model of the relationship between safety management practices with unsafe behaviors and with of mediation of safety motivation. Methods: Research design was correlation through structural equation modeling (SEM) and the sample consisted of 265 employees of an industrial company who were selected by stratified random sampling method. Participants of this study completed safety management practices Scale, safety motivation scale and unsafe behaviors questionnaire. Reliability and validity all of questionnaires were accepted. Structural equation modeling (SEM) through AMOS-21 and SPSS-19 software packages was used for data analysis. In addition, Preacher and Hayes’ SPSS Macro program was used for testing mediation. Results: The results showed that the proposed model fit the data properly. Safety management practices have direct effect on unsafe behaviors and safety motivation (p

Nowadays, occupational related diseases and accidents are considered one of the main causes for mortality worldwide. However, Kiken Yochi Training (KYT) is one of the interventions to reduce the incidence of unsafe behaviors at workplace, yet there are few evidence-based studies on its effectiveness. This study was aimed to identify the unsafe behaviors among workers in the construction industry in Iran and determine the influence of Kiken Yochi Training intervention on their reduction. In this study, the unsafe behaviors of workers in Atieh Sazan construction Company, Tehran, Iran, were investigated. For this purpose, 452 workers were randomly selected and 11733 observations regarding unsafe behaviors were reported. In the second phase, Kiken Yochi Training was applied over three months, then observations were recorded once again. Socio-demographic questionnaire and Tarrant’s checklist were used. 25.69% of the recorded behaviors in the first phase and 18.57% after the intervention, were unsafe. Unsafe use of equipment and inappropriate ergonomic status were among the most common risky behaviors. The average percentages of unsafe behaviors before and after the intervention were reduced by about 36%. Kiken Yochi Training was effective in diminishing the unsafe behaviors among workers. There was a significant relationship between the number of unsafe behaviors, age, experience, type of occupation, educational status, and having a previous accident (P value

Nowadays, occupational related diseases and accidents are considered one of the main causes for mortality worldwide. However, Kiken Yochi Training (KYT) is one of the interventions to reduce the incidence of unsafe behaviors at workplace, yet there are few evidence-based studies on its effectiveness. This study was aimed to identify the unsafe behaviors among workers in the construction industry in Iran and determine the influence of Kiken Yochi Training intervention on their reduction. In this study, the unsafe behaviors of workers in Atieh Sazan construction Company, Tehran, Iran, were investigated. For this purpose, 452 workers were randomly selected and 11733 observations regarding unsafe behaviors were reported. In the second phase, Kiken Yochi Training was applied over three months, then observations were recorded once again. Socio-demographic questionnaire and Tarrant's checklist were used. 25.69% of the recorded behaviors in the first phase and 18.57% after the intervention, were unsafe. Unsafe use of equipment and inappropriate ergonomic status were among the most common risky behaviors. The average percentages of unsafe behaviors before and after the intervention were reduced by about 36%. Kiken Yochi Training was effective in diminishing the unsafe behaviors among workers. There was a significant relationship between the number of unsafe behaviors, age, experience, type of occupation, educational status, and having a previous accident (P value <0.01). In the present study, it was concluded that the occurrence of unsafe behaviors among construction industry workers could be reduced by promoting awareness and raising knowledge. Moreover, it was recommended to have continuous monitoring, training sessions based on behavioral safety principles establishment, a safety culture in addition to reliance on academic experiences development. [ABSTRACT FROM AUTHOR]

This study examined the relationship between authoritarian leadership and employees' unsafe behaviors, and the mediating roles of organizational cynicism and work alienation. Questionnaires were distributed to first-line production employees, and structural equation modeling was employed to test the hypotheses. The results showed that organizational cynicism mediated the relationship between authoritarian leadership and employees' unsafe behaviors. Furthermore, authoritarian leadership was related to employees' unsafe behaviors through organizational cynicism first and then work alienation. The theoretical implications of these findings for advancing the research and practical approaches to reduce employees' unsafe behaviors are discussed. [ABSTRACT FROM AUTHOR]

This article takes system theory, organization theory and safety management theory as the theoretical foundation, uses the DEMATEL method to calculate the center degree and reason degree of 13 major risk sources that affect the unsafe behaviors of construction workers, and distinguishes the cause set and the result set. The correction threshold is employed to remove the redundancy factors, so as to get the initial matrix M in the ISM method and finally establish an ISM model. Through the DEMATEL-ISM comprehensive modeling, all factors are divided into three categories. A few preventive measures of unsafe behaviors are proposed according to the internal relationship and the key factors of each type. These measures constrain the unsafe behaviors of construction workers by controlling the key influencing factors, which provides a reliable basis for improving the safety of building construction. [ABSTRACT FROM AUTHOR]

Coal mine safety is an important part of safety management for a risk society and the unsafe behaviors of coal miners are major sources of hidden dangers. A considerable number of studies on coal miners' unsafe behaviors have been done based on behavioral science. However, few studies have been conducted from the perspective of cognition. This study explored the cognitive mechanism of coal miners' unsafe behaviors and proposed corresponding intervention strategies. A conceptual model of coal miners' unsafe behaviors was constructed after the analysis on the cognitive failure mechanism of unsafe behaviors, and an empirical test was carried out in Zhaizhen coal mine of China. Results show the necessity of exploring the causes of coal miners' unsafe behaviors from the perspective of cognitive failure. Among all the identified causes, the combined influence of personal causes is the most profound and the degree of influence of environmental causes, organization management, and behavioral attributes are decreased in turn. Unsafe behaviors can be restrained by optimizing the employment mechanism, improving the level of mechanization of underground mining, arranging the job division and operation schedule reasonably, and improving safety training mechanism and safety culture. Moreover, the safety of coal miner' operation behaviors can be ensured by improving safety management capability of managers, strengthening site management and safety protection, and improving the safety management system and incentive mechanism. T his study provides significant reference for behavioral intervention to reduce coal miners' unsafe behaviors in an effort to avoid the unsafe factors in risk society. [ABSTRACT FROM AUTHOR]

To create a safe work atmosphere, it is essential to control the spread of unsafe behaviors among construction workers. Based on group behavior theory, the relationship between the influence factors and means of spreading unsafe behavior among construction workers is verified using a structural equation model (SEM) and multiround research data. According to the research, (1) spreading methods of unsafe behaviors consists of demonstration-imitation and infecting-conformity; (2) the influence of important figures, personal safety accomplishments, intensity of penalties for individual violations and benefit-to-risk ratios of unsafe behaviors are correlated significantly with the spread of unsafe demonstration-imitation behaviors and (3) the relational closeness of members, personal safety accomplishments, safety climate and benefit-to-risk ratio of unsafe behaviors are correlated significantly with the spread of unsafe infecting-conformity behaviors. [ABSTRACT FROM AUTHOR]

A cross-sectional observational study with descriptive and analytical approach that aims at determining unsafe behavior of bus drivers from a company of public transportation and its relation to traffic accidents was conducted in a probability sample of 127 drivers. The results showed that drivers performed an average of 86.86 unsafe driving behaviors for every two hours of travel time; the most frequent behavior was speeding, while not keeping a safe distance was the main cause of the company's bus accidents. The correlation between unsafe behavior and causes of accidents in the company was positive but non-significant. The information gathered will allow to modify behaviors from unsafe to safe, as a future strategy for the improvement of road safety. [ABSTRACT FROM AUTHOR]

Training interventions are regarded as essential managerial strategies in various organizations. The present study investigated managerial interventions in training based on Deming model and their effectiveness to decrease the rate of unsafe behaviors of workers. It was a case study, conducted in a rolling industry and a descriptive- analytic research, done periodically during three years (2012-2015). It was tried to implement training programs based on the Deming cycle. To study the effectiveness of training interventions, safety performance indicators and standardized questionnaires were used. A comparison was also drawn between the rate of unsafe behaviors before and a year after applying the interventions. Sampling safety behavior was used to determine the rate of unsafe behaviors and such behaviors were investigated through checklists and random observations. The mean score of unsafe behaviors was 46%. The most and the least frequently occurred unsafe behaviors were failure to use earmuffs (14.5%) and throwing tools (0.02%) respectively. The results showed that applying interventions were influential in decreasing unsafe behaviors (31%, P=0.006). After interventions, obtained results of safety performance indicators and the status of training came to a desirable level. Findings also proved that training is one of the major cornerstones of improved safe behaviors. Therefore, it is important to hold regular training courses and establish an efficient training system in the workplace to develop safety purposes and professional health.

Background and aims Today, the reduction of unsafe work behavior is an accepted principle. Unsafe behaviors at work are said to be the main cause of work accidents. Therefore, careful attention toward unsafe work behavior is one of the main factors for eliminating the causes of injuries and damages which has been taken into consideration in recent years.Also, due to the high rate of accidents in foundry industries; the present research has been conducted to reduce unsafe work behaviors through an appropriate method. Methods The present study is of analytical; interventional. The subject investigated in this study is one of foundry industries. Sample size was determined. In order to gather data, the methods of observation, interview and checklist were used. The five-year-accident record of the company was analyzed.Data analysis was done by means of spss10. Results In the present study, Pearson Correlation test indicates that there is no relationship between safety performance score before and after training and the age of workers. (r=0.6 Pvalue= 0.639) Pearson correlation test also demonstrated that there is a linear relationship between safety performance score and work experience. In other words, the more work experience, the more safety performance (r=0.25 P-value=0.03). Pearson correlation test indicates that there is no relationship between safety performance score and educational level. (r=0.12 P-value=0.29) Conclusion The present study indicated that with the reduction of unsafe work behavior accidents declined significantly. This research also resulted in the reduction of unsafe work behaviors, lost workdays as well as work accidents.

This paper focuses on construction workers' unsafe behaviors and develops a cognitive model of construction workers' unsafe behaviors (CM-CWUB). In the construction industry, many accident investigations reveal that workers' unsafe behaviors are the most frequent and direct causes of on-site accidents, and thus need to be addressed urgently. Based on cognitive and social psychology theories and existing accident causation models, this paper develops a CM-CWUB by adopting a five-stage form, specifically representing the construction workers' cognitive processes when confronted with potential hazards on construction sites. Using a cognitive perspective can reveal the mechanism of human error and thus can elucidate how unsafe behaviors are produced. The five stages include obtaining information, understanding information, perceiving responses, selecting response, and taking action, with obtaining information and selecting response as the two key stages. Obtaining information elaborates construction workers' observations and processing of hazard information on sites by themselves, and selecting response adopts the theory of planned behavior to reflect various factors of influence when workers select unsafe behavior. Based on the developed model, cognitive failures that would lead to construction workers' unsafe behaviors at different cognitive stages are then systematically analyzed. [ABSTRACT FROM AUTHOR]

Training interventions are regarded as essential managerial strategies in various organizations. The present study investigated managerial interventions in training based on Deming model and their effectiveness to decrease the rate of unsafe behaviors of workers. It was a case study, conducted in a rolling industry and a descriptive-analytic research, done periodically during three years (2012-2015). It was tried to implement training programs based on the Deming cycle. To study the effectiveness of training interventions, safety performance indicators and standardized questionnaires were used. A comparison was also drawn between the rate of unsafe behaviors before and a year after applying the interventions. Sampling safety behavior was used to determine the rate of unsafe behaviors and such behaviors were investigated through checklists and random observations. The mean score of unsafe behaviors was 46%. The most and the least frequently occurred unsafe behaviors were failure to use earmuffs (14.5%) and throwing tools (0.02%) respectively. The results showed that applying interventions were influential in decreasing unsafe behaviors (31%, P=0.006). After interventions, obtained results of safety performance indicators and the status of training came to a desirable level. Findings also proved that training is one of the major cornerstones of improved safe behaviors. Therefore, it is important to hold regular training courses and establish an efficient training system in the workplace to develop safety purposes and professional health. [ABSTRACT FROM AUTHOR]

Introduction: Inrecent years, with the aim of reducingaccidents, useofthe behavior-based safetytechniqueshas gained significance. Methods: In the present pre- and post-test design quasi-experimental study, the unsafe behaviors of the workers in a car- making factory were evaluated using observation and safety behavior samplingmethod. After description of the unsafe behavior and based on the result of a pilot study and sampling accuracy to %5, 115 workers were selected and a total number of 9200 unsafe behaviors were observed. A questionnaire was used to collect different related variables including personal characteristics. Inthe second phaseafter3 monthsofintervention, includingtrainingworkersandsupervisors, safetysignsand the useofpunishmentandencouragement, observationswere repeated. Results:The resultsindicatedthat workers inthe firstphase showed unsafebehavior up to13.9percent butinthe secondphasethe behaviordeclined to 9.04 percent. Amongthesebehaviors, poorergonomicconditionsandlackofprotective equipmenthad thehighestfrequency. The study detected the relation between the number of unsafe acts and level of education (p=0.04) as well as the history of accidents among the workers (P=0.001) as significant. The results showed the relation between the number of unsafe acts and age, duration of the employment and number of family as unsignificant. Conclusion:The resultsproved atendencyofbehavior-based safetyasthe mainstrategy forreducingthe unsafebehaviorand thuslowering theaccident rateinthe country. [ABSTRACT FROM AUTHOR]

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.

Unsafe or at-risk behaviors of employees are the root cause of almost all accidents and fatalities in organizations. Behavior Based Safety or BBS is a process of chaining people in safety behaviors. This article is a case of a large gas company in India on various processes and emerging outcomes of behavior based safety (BBS) implementation. A set of issues and apprehensions faced by the Lead Trainers/Observers as well as emerging outcomes of BBS implementation is reflected. Recommendations are made for consolidating BBS implementation. This article is intended to be useful for companies interested in implementing BBS as a significant step towards managing zero occupational injuries and accidents. [ABSTRACT FROM AUTHOR]