Applications, Shortcomings, and New Advances of Job Safety Analysis (JSA): Findings from a Systematic Review.

Background: Job safety analysis (JSA) is a popular technique for hazard identification and risk assessment in workplaces that has been applied across a wide range of industries. This systematic review was conducted to answer four main questions regarding JSA: (1) which sectors and areas have used JSA? (2) What has been the aim of employing JSA? (3) What are the shortcomings of JSA? (4) What are the new advances in the field of JSA? Methods: Three main international databases were searched: SCOPUS, Web of Science, and PubMed. After screening and eligibility assessment, 49 articles were included. Results: Construction industries have used JSA the most, followed by process industries and healthcare settings. Hazard identification is the main aim of JSA, but it has been used for other purposes as well. Being time-consuming, the lack of an initial list of hazards, the lack of a universal risk assessment method, ignoring hazards from the surrounding activities, ambiguities regarding the team implementing JSA, and ignorance of the hierarchy of controls were the main shortcomings of JSA based on previous studies. Conclusion: In recent years, there have been interesting advances in JSA making attempts to solve shortcomings of the technique. A seven-step JSA was recommended to cover most shortcomings reported by studies.

Failure mode and Effect Analysis of personal fall arrest system under the intuitionistic fuzzy environment.

Background and aims: Intuitionistic fuzzy sets (IFS) theory is more powerful than classic fuzzy sets theory in handling uncertainty. A new approach for Failure Mode and Effect Analysis (FMEA) was developed based on IFS and group decision-making (known as IF-FMEA) for investigating Personal Fall Arrest System (PFAS). Method: FMEA parameters, including occurrence, consequence, and detection, were re-defined based on a seven-point linguistic scale. Each linguistic term was associated with an intuitionistic triangular fuzzy set. Opinions on the parameters were gathered from a panel of experts, integrated using the similarity aggregation method, and defuzzified utilizing the center of gravity approach. Results: Nine failure modes were identified and analyzed using both FMEA and IF-FMEA. The risk priority numbers (RPNs) and prioritization obtained from the two approaches were different, highlighting the importance of using IFS. The highest RPN was associated with the lanyard web failure, while the failure of the anchor D-ring had the least RPN. Detection score was higher for metal parts of the PFAS, suggesting that failures in these parts are harder to detect. Conclusion: In addition to being economical in terms of calculations, the proposed method was efficient in handling uncertainty. Different parts of a PFAS create different levels of risk.

Protective gloves, hand grip strength, and dexterity tests: A comprehensive study.

Protective gloves can affect hand performance indicators (HPIs) like manual dexterity and hand grip. The present study was conducted to comprehensively and comparatively investigate several types of protective gloves and HPI assessment tools. Seventeen healthy men participated in this study. Four types of protective gloves, two structural firefighting and two general protective gloves, were investigated using four different dexterity tests and the bulb dynamometer. Structural firefighting gloves were significantly different in terms of dexterity, while there was no significant difference between general protective gloves. In contrast, firefighting gloves were not significantly different in terms of hand grip strength, while general protective gloves were significantly different in this regard. Among the four investigated tests, the hand tool dexterity test had the highest discrimination power. The negative effects of structural firefighting gloves on HPIs were higher than those of general protective gloves. A trade-off between safety requirements and hand performance is needed.

A comparative study of electronic and pen-paper safety inspections: A mixed method study design for assessing ergonomic parameters.

BACKGROUND: Workplace inspections are applied to facilitate the adherence to the occupational health and safety regulations. The Iranian Ministry of Health introduced a new software system for tablets to inspect workplaces. OBJECTIVES: The aim of this study was to take measurements of the usability, mental workload, and mood of inspectors. METHODS: Inspectors used both pen-and-paper and tablet methods to inspect the automotive industry in a mixed-method procedure. The NASA-TLX score, QUIS score, I-PANAS (SF) situation, inspection time, and number of errors were collected throughout the procedure. The differences were investigated using a paired sample and the Wilcoxon signed ranks test. RESULTS: In terms of efficacy, using the tablet resulted in lower error rates, but it took longer to complete the inspection task (P < 0.001). Participants perceived a lower workload when inspecting with a tablet rather than the traditional method. (Mental Demand: p < 0.002, Performance: p < 0.009, Effort: p < 0.012, TLX: p < 0.002 based on various subcomponents of NASA-TLX). The newly introduced system's usability was insufficient. CONCLUSION: Although the use of tablets has improved safety inspections, ergonomic redesign of the system and consideration of a user-centered approach, as well as inspector training, can make the system more likely to succeed.

Determining performance shaping factors to assess human error in the emergency response team in chemical process industries: a case study.

Objectives. Human error (HE) plays a crucial role in the occurrence of accidents in chemical process industries (CPIs). Emergency response team (ERT) members are predisposed to HEs due to the nature of their work. The HE potential is influenced by the performance shaping factors (PSFs). Managing PSFs can diminish the human error probability (HEP) and consequently increase the emergency response success chance. This article aimed to determine the PSFs for ERT members in CPIs. Methods. First, an initial list of PSFs was searched and classified within human reliability analysis methods and studies. Then, an expert panel of the emergency management system was utilized to identify, classify and weight the initial PSFs. The fuzzy Delphi method and content analysis technique were applied to summarize and categorize the PSFs. Results. The results of the study showed that 11 PSFs had greater impacts on the ERT members' error potential. Findings revealed that stress and physiological stressors, competency, and team and organization were the three most important PSFs. Conclusion. The most important and relevant PSFs can be effectively used in accurate HE assessment of ERT members in CPIs.

Problematic internet use and safety behavior: The moderating role of safety climate.

Problematic internet use (PIU) can cause mental and physical harm to individuals and may be an emerging factor contributing to unsafe work behavior. In this study, the relationship between PIU and safety behavior was investigated. Moreover, it was hypothesized that safety climate can moderate the relationship between PIU and safety behavior. Participants were employees from a mining industry in Iran. Three validated questionnaires were distributed to gather the required data regarding PIU, safety climate, and safety behavior. Hierarchical regression analysis was used to assess the moderating effect of safety climate on the relationship between PIU and safety behavior. The size of moderation effect was assessed using f2 index. Four hundred eighty-five employees participated in this study. The results demonstrated a negative relationship between PIU and safety behavior. The moderating effect of safety climate on the relationship between PIU and safety behavior was supported. The f2 index was 0.027 which demonstrates a small moderation effect. In conclusion, PIU has a significant negative effect on the safety behavior of employees. Providing a strong safety climate can be a long-term solution for reducing the negative effect of PIU on safety behavior.

Risk assessment of the work-related musculoskeletal disorders based on individual characteristics using path analysis models.

BACKGROUND: This study aimed to assess the risk of work-related musculoskeletal disorders (WMSDs) using the path analysis models. METHODS: This study was carried out on 350 office employees with good general health. All variables were collected using a questionnaire. Personality traits and mental workload of employees were evaluated using the NEO Personality Inventory and the NASA-task load index software, respectively. The individual and personality traits were used as predictor variables, and mental workload (MWL) and body posture scores as mediating variables of the musculoskeletal discomforts. The role of predictor and mediating variables on discomforts was explained based on the path analysis models. RESULTS: The impact coefficient of MWL and posture on WMSDs was significant. The coefficient of the direct effect of body mass index (BMI) and gender on musculoskeletal disorders was significant and positive and the women have reported a higher rate of discomforts. The strongest positive impact of personality traits on MWL and posture was conscientiousness, followed by neuroticism and agreeableness. In return, the strongest negative impact was extroversion, followed by openness. The strongest positive impact of individual factors on MWL and posture was BMI, followed by work experience. CONCLUSION: Gender, BMI, neuroticism, extraversion, and conscientiousness can be strong predictors for musculoskeletal discomforts which can mediate the impact of body posture and mental workload (mediating factors) on musculoskeletal discomfort. Therefore, personality and individual traits can be strong alarming and indicators for risk identification and preventing musculoskeletal disorders when choosing people for a job or task.

Insights into the relationship between usability and willingness to use a robot in the future workplaces: Studying the mediating role of trust and the moderating roles of age and STARA.

BACKGROUND AND AIM: Human-robot collaboration is the key component of the fourth industrial revolution concept. Workers' willingness to collaborate with industrial robots is a basic requirement for an efficient and effective interaction. The roles of human-robot trust and technology affinity as mediators in the relationship between robot usability and worker willingness were analyzed in this study. As other critical variables, the mediator roles of Age and STARA were also calculated. MATERIALS AND METHODS: This study included 400 workers from a car company who interacted with industrial robots in their daily work activities. After examining the questionnaires' validity and reliability, the main variables were determined to be willingness to use robots and robot usability. AMOS software also considered human-robot trust and worker technology affinity as mediators. The bootstrapping method was used to evaluate indirect relationships. A set of goodness-of-fit indices were presented to determine the adequacy of the goodness of fit between the proposed model and the data. RESULTS: Based on model fit indices, an overall satisfactory model fit was obtained for the direct/indirect relationship between robot usability and worker willingness to use it (with mediating role of human-robot trust). Workers' age and fear of Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA) were identified as moderators in the relationship between usability and willingness. CONCLUSION: Attention to the robot usability and the role of workers' trust in robots appears to be required to ensure workers' willingness to use robots and the success of human-robot collaboration in future workplaces. As the workers age and their fear of robots grows, usability can play a larger role in increasing their willingness to put robots to work.

A comprehensive method for the quantification of medication error probability based on fuzzy SLIM.

Medication errors can endanger the health and safety of patients and need to be managed appropriately. This study aimed at developing a new and comprehensive method for estimating the probability of medication errors in hospitals. An extensive literature review was conducted to identify factors affecting medication errors. Success Likelihood Index Methodology was employed for calculating the probability of medication errors. For weighting and rating of factors, the Fuzzy multiple attributive group decision making methodology and Fuzzy analytical hierarchical process were used, respectively. A case study in an emergency department was conducted using the framework. A total number of 17 factors affecting medication error were identified. Workload, patient safety climate, and fatigue were the most important ones. The case study showed that subtasks requiring nurses to read the handwritten of other nurses and physicians are more prone to human error. As there is no specific method for assessing the risk of medication errors, the framework developed in this study can be very useful in this regard. The developed technique was very easy to administer.

Analysis of occupational accidents among nurses working in hospitals based on safety climate and safety performance: a Bayesian network analysis.

Purpose. This study aimed to analyze causal relationships among safety climate dimensions, safety performance dimensions and occupational accidents for nurses working in hospitals. Methods. Data were gathered from questionnaires filled in by nurses from three public hospitals. To analyze interactions among variables, a Bayesian network (BN) analysis was conducted. Using the function of BN 'belief updating', variables with the highest influences on occupational accidents were determined. Results. A total of 211 nurses participated in this study. They were mainly female and married. The results showed that 39.3% of nurses experienced occupational accidents during the last 12 months before the study. Less than half of the nurses had an acceptable safety performance. Safety participation had the highest influence on occupational accidents, followed by safety compliance. Reporting of errors had the highest score among the safety climate dimensions. Training of nurses was necessary for improving both safety compliance and safety participation, and thereby reducing occupational accidents. Conclusion. The effect of safety participation on occupational accidents among nurses was higher than that of safety compliance. Among the safety climate dimensions, supervisors' attitude to safety and safety training had the highest effects on both nurses' safety performance and occupational accidents.

Fatigue profile among petrochemical firefighters and its relationship with safety behavior: the moderating and mediating roles of perceived safety climate.

The present study aimed to investigate fatigue among firefighters and its relationship with their safety behavior. The moderation and mediation effects of perceived safety climate on this relationship were also investigated. Firefighters from 10 petrochemical companies in Iran were investigated. Moderation analysis was performed based on hierarchical regression analyses and mediation effects were studied using structural equation modeling. A total number of 261 firefighters participated in this study. The mean scores of general fatigue, physical fatigue, reduced activity, reduced motivation and mental fatigue were 10.5, 9.0, 8.2, 7.6 and 8.7, respectively. Fatigue had a negative significant effect on firefighters' safety behavior. Perceived safety climate had a mediation but not moderation effect on the relationship between fatigue and safety behavior of firefighters. Generally, the fatigue level among firefighters was fairly low, but had a significant negative effect on firefighter's safety behavior. Perceived safety climate can mediate such a negative effect.

Prediction of human error probability during the hydrocarbon road tanker loading operation using a hybrid technique of fuzzy sets, Bayesian network and CREAM.

Objectives. The hydrocarbon road tanker loading operation is vulnerable to human error. The present study aimed to develop a methodology for predicting human error probabilities (HEPs) in various subtasks of this operation. Methods. First, task analysis was performed using hierarchal task analysis. Then, HEP was calculated using a hybrid technique of fuzzy set theory (FST), Bayesian network (BN) and cognitive reliability and error analysis method (CREAM). FST was used for handling uncertainties regarding common performance conditions (CPCs) and the BN was employed for modeling the interrelationships among CPCs and HEPs. The weighted sum algorithm was used for quantifying conditional probability tables in the network. Results. Twenty-six subtasks were required for completing the road tanker loading operation. Investigating the internal parts of the tanker before the loading operation and attaching the ground rode clamp were the subtasks with highest HEPs. Working conditions and crew collaboration were the CPCs with the highest contribution to these errors. HEP was most sensitive to crew collaboration. Conclusion. Improving collaboration among the driver, site operators and control room operators, as well as increasing the knowledge of the road tanker driver regarding the hazards of incompatible chemicals, are the best practices for reducing HEPs in this operation.

Ergonomics 4.0: A bibliometric review of Human Factors research in Industrial Revolution 4.0 (IR 4.0).

BACKGROUND: The scientometric study is a visualization method used to collect big data from databases, to explore the relationships between citing and co-cited documents and then visualize the results. Unlike the new term Ergonomics 4.0, bibliometric analysis has been studied in various related fields of Ergonomics. OBJECTIVE: The aim of this study was to create a bibliometric analysis in related field of Ergonomics and Fourth Industrial Revolution. This analysis can shed light on the new developed research field in both sides of the present study, occupational ergonomics and industry 4.0. METHODS: After selecting related keywords, Advance search was done in Scopus and Web of Science. Bibliometric results were presented by these databases' analyzer and by exported data to VOS viewer software. No time or language restriction was applied. RESULTS: Retrieved Articles were 104 and 285 for Web of Science and Scopus respectively. The frequent co-occurrences for keywords were seen between "industry 4.0" and "Human Factors". The USA and Germany were also the most productive countries in this field. Well-known Ergonomics journals had low participation in the Evolution of Ergonomics and Fourth Industrial Revolution topics. CONCLUSION: Due to more participation of industry 4.0-related researchers in this topic, it is recommended that ergonomists from around the world, and especially Eastern countries, attempt to conduct research in this field. Furthermore, devoting some forth-coming special issues in this field is recommended to top ergonomics journals.

Prevalence and severity of carpal tunnel syndrome symptoms among Iranian butchers and their association with occupational risk factors: Implications for ergonomic interventions.

BACKGROUND: Carpal tunnel syndrome (CTS) is a common disorder among occupations where upper extremities are actively involved in. Many occupational and non-occupational risk factors may contribute to this disorder. Knowledge regarding occupational risk factors can guide us to implement interventional programs. OBJECTIVE: The aim of the present study was to assess the prevalence and severity of CTS symptoms among butchers and their association with several occupational and non-occupational risk factors. METHODS: In this study, 152 butchers in Hamadan, Iran, were examined. The Boston Carpal Tunnel Syndrome Questionnaire (BCTQ) was used to investigate the severity of CTS symptoms among the individuals. Several risk factors such as body mass index (BMI), wrist ratio, active working hours per day, working experience, and the ergonomic quality of hand tools used by butchers were also investigated. Statistical tests such as the crude and robust regression were used to analyze the data. RESULTS: The prevalence of moderate and mild symptoms of CTS were 7% and 54%, respectively. Moreover, 39% of the butchers were free of CTS symptoms. Crude regression analyses showed that the severity of CTS symptoms had a significant relationship with age, work experience, active working hours per day, working hours per week, and ergonomic quality of the hand tools (p value <0.05). There was no significant relationship between the severity of CTS symptoms and wrist ratio and BMI. Results of the robust regression analysis showed a significant relationship between the severity of CTS symptoms with experience, active working hours, and quality of the hand tools. CONCLUSION: Occupational risk factors such as working experience, active working hours per day, and the ergonomic quality of hand tools are significant risk factors of CTS symptoms among butchers. Slippery handle is the main non-ergonomic feature of knives and cleavers used by butchers. There was no association between BMI and wrist ratio with CTS symptoms.

Musculoskeletal Consequences in Cyber-Addicted Students - Is It Really A Matter of Health? A ROC Curve Analysis for Prioritizing Risk Factors.

BACKGROUND: The high prevalence and also multiple consequences of addiction to various online content, including online games and social networks, have become a major challenge. The ability to predict musculoskeletal disorders from this addiction can help reveal in students' health status in the near future. The aim of this study was to determine the prevalence of this addiction and the ability to predict neck pain from this matter in students. STUDY DESIGN: A cross sectional study. METHODS: This study was carried out among 665 students. Data collection was performed through three questionnaires on problematic use of online games, social networking addiction, and Nordic musculoskeletal disorders. Data were compared with Chi-square and independent T-test, and the logistic regression model was then presented at a significant level of 0.05. Finally, the area under the receiver operating characteristic (ROC) curve and Discriminant analysis were conducted to clarify associations. RESULTS: The prevalence of Internet-related content addiction was 32.8%. The results showed that addiction to social networks and online games can increase the risk of neck disorder. Also 0.58 area under ROC curve depicted the ability to predict neck pain from this addiction. CONCLUSION: In students with internet - related content addiction, neck disorder can be predicted. Given the high prevalence of internet addiction in students, it is essential to take immediate and appropriate interventions to avoid the associated adverse effects such as neck problems.

Explanation and prediction of accidents using the path analysis approach in industrial units: The effect of safety performance and climate.

BACKGROUND: The safety climate in an organization depends on people's understanding of the safety policies and procedures, as well as the value, importance, and priority of safety in the workplace. OBJECTIVE: This study aimed to describe and predict accidents using the path analysis model (PAM) in industrial units though the analysis of the effect of safety performance and climate. METHODS: This cross-sectional study was conducted on 294 workers in industrial units in Hamadan, a province in the western part of Iran. The data on safety performance and climate was collected using a questionnaire. The first part of the questionnaire was a short version inventory (with 25 items on safety climate) that was used to assess five variables of management commitment, supportive environment, training, personal safety prioritization, and perceived work pressure. Moreover, the safety performance was measured using 10 items on safety rules and participation. The PAM was used to describe the effects of safety climate and performance on accidents. RESULTS: The results showed that the safety climate had the strongest negative impact on work pressure and safety compliance toward accident, followed by safety participation, and quality of training. Moreover, the negative influence of safety climate on accident was mainly mediated by two variables: work pressure and safety participation toward accident. The work pressure had the strongest indirect and total influence on accidents. However, none of the variables had a direct effect on accidents. Training was the most important direct cause of promoting personal safety priority. The safety compliance was more effective than safety participation in reducing accidents rates. CONCLUSIONS: Therefore, it seems that perceived work pressure has an indirect effect on accidents which is mediated by other variables, mainly personal safety priority and safety performance.

Risk assessment in academic laboratories in the west of Iran: compare the CHRA and the RSLs methods.

In the laboratories staffs, there is potential for adverse health effects in exposure to chemicals. Therefore, risk assessment is one of the main issues to prevent these effects. The purpose of this study was to assess the health risk of laboratory staffs and compare the two methods, including 'Chemical Health Risk Assessment' (CHRA) and 'Regional Screening Levels' (RSLs), that developed by the Department of Occupational Safety and Health of Malaysia and the Environmental Protection Agency respectively. Using these two methods, the places with the highest risk were identified. Comparisons showed that RSLs is a precise method without personal judgment. The CHRA is a simple method for wider chemicals that categorize risk. But CHRA includes fewer parameters compared to RSLs, as well as personal judgment. The results of the present study showed that two methods did not compatible. According to the characteristics of these two methods, it is recommended to use them as a compliment each other to obtain accurate results.

Predicting needlestick and sharps injuries and determining preventive strategies using a Bayesian network approach in Tehran, Iran.

OBJECTIVES: Recent studies have shown that the rate of needlestick and sharps injuries (NSIs) is unacceptably high in Iranian hospitals. The aim of the present study was to use a systematic approach to predict and reduce these injuries. METHODS: This cross-sectional study was conducted in 5 hospitals in Tehran, Iran. Eleven variables thought to affect NSIs were categorized based on the Human Factors Analysis and Classification System (HFACS) framework and modeled using a Bayesian network. A self-administered validated questionnaire was used to collect the required data. In total, 343 cases were used to train the model and 50 cases were used to test the model. Model performance was assessed using various indices. Finally, using predictive reasoning, several intervention strategies for reducing NSIs were recommended. RESULTS: The Bayesian network HFACS model was able to predict 86% of new cases correctly. The analyses showed that safety motivation and fatigue were the most important contributors to NSIs. Supervisors' attitude toward safety and working hours per week were the most important factors in the unsafe supervision category. Management commitment and staffing were the most important organizational-level factors affecting NSIs. Finally, promising intervention strategies for reducing NSIs were identified and discussed. CONCLUSIONS: To reduce NSIs, both management commitment and sufficient staffing are necessary. Supervisors should encourage nurses to engage in safe behavior. Excessive working hours result in fatigue and increase the risk of NSIs.

A path analysis model for explaining unsafe behavior in workplaces: the effect of perceived work pressure.

BACKGROUND: Unsafe behavior is closely related to occupational accidents. Work pressure is one the main factors affecting employees' behavior. The aim of the present study was to provide a path analysis model for explaining how work pressure affects safety behavior. METHODS: Using a self-administered questionnaire, six variables supposed to affect safety employees' behavior were measured. The path analysis model was constructed based on several hypotheses. The goodness of fit of the model was assessed using both absolute and comparative fit indices. RESULTS: Work pressure was determined not to influence safety behavior directly. However, it negatively influenced other variables. Group attitude and personal attitude toward safety were the main factors mediating the effect of work pressure on safety behavior. Among the variables investigated in the present study, group attitude, personal attitude and work pressure had the strongest effects on safety behavior. CONCLUSION: Managers should consider that in order to improve employees' safety behavior, work pressure should be reduced to a reasonable level, and concurrently a supportive environment, which ensures a positive group attitude toward safety, should be provided. Replication of the study is recommended.