Validity and reliability of a questionnaire to investigate people prone to accidents in different industries.

Objectives. In recent years, workplace accidents have imposed a considerable cost on industries. Accident proneness is one of the most influential factors known to cause unsafe behaviors and occupational accidents. Therefore, the present study investigated the validity and reliability of the accident proneness questionnaire in industries. Methods. The questionnaire was developed to measure accident proneness in industries - the developed instrument was distributed in East Azarbaijan industries (1100 questionaries). Content validity, confirmatory factor analysis and exploratory factor analysis were used to examine the construct validity, and Cronbach's α and the test-retest method were used to examine the reliability and reproducibility of the instrument. Results. In the face validity section, the impact score of all items was determined to be >1.5. In the content validity section, the content validity index (CVI) and the content validity ratio (CVR) were higher than the standard value of 0.42. The Cronbach's α coefficient for all dimensions was 0.914. Conclusion. The findings of the study show that the accident proneness questionnaire in industries has acceptable validity and reliability, and can be used as a comprehensive, practical, robust and reliable instrument to investigate the accident proneness of different industries.

Prediction of time in industrial chemical accidents: A survival analysis.

BACKGROUND: Chemical accidents have imposed casualties and high economic and social consequences to Iranian industries and society. OBJECTIVE: This study investigated the effect of risk factors involved in occurrences of the chemical accidents and predicted the time of occurrences in Iranian chemical factories. METHODS: A cross-sectional study was implemented in 574 chemical facilities with more than 25 employees from 2018 to 2020. Collecting data instruments were 2 checklists with 15 and 25 three-point Likert scale questions, respectively. Chi square and Monte Carlo tests assessed the relationships between independent risk factors and dependent hazardous chemical accidents. Cox semi-parametric and log-normal parametric models were used to predict the upcoming time of chemical accidents based on the impacts of risk factors understudy. Data analyses were performed using Stata and R software. RESULTS: The results showed that safety data sheets, labeling, fire extinguishing system, safe chemicals storage, separation, loading, transportation and training were statistically significant with occurrences of the chemical accidents (P-value < 0.05). Loading and transportation were mostly related to chemical incidents and reduced significantly the expected time of chemical events (P-value = 0.028). CONCLUSION: Establishing a comprehensive chemical accidents dataset and strict governmental supervision on chemical safety regulations are suggested to decrease the chemical accidents at regional and local levels in chemical plants.

Risk assessment of physical unit operations of wastewater treatment plant using fuzzy FMEA method: a case study in the northwest of Iran.

Failure Mode and Effects Analysis (FMEA) is one of the most used methods in risk assessment and prioritization. This study was conducted to identify, evaluate, prioritize, and analyze risks associated with the physical processes of Sahand municipal wastewater plant using traditional and fuzzy FMEA methods. The present research was a cross-sectional analytical study that was conducted to prioritize the risks of unit operations of screening and grit removal in Sahand municipal wastewater treatment plant for 6 months. First, a team of five experts was formed and the traditional FMEA worksheet was completed. Then, the fuzzy membership functions were determined according to experts' opinions and using the MATLAB program, and the severity, occurrence, detection, and risk priority number (RPN) became fuzzy and risks were prioritized according to the fuzzy logic outputs. A total of 53 failure modes were identified for screening (26 failures) and grit removal units (27 failures) using the traditional FMEA risk assessment technique. The results of the traditional FMEA method showed that among the 53 identified failure modes, in physical treatment equipment of Sahand municipal wastewater, 51 failures (96.2%) were in the low-risk levels and two failures (3.8%) were in the medium-risk levels. According to the results of the fuzzy FMEA, 5 failures (9.4%) were in the low-risk levels, 43 failures (81.2%) were in the medium-risk levels, and 5 failures (9.4%) were in the high-risk levels. Based on the traditional FMEA, the highest and lowest level of risk belonged to manual screening clogging and conveyor cutting of mechanical screening with RPN of 540 and 12, respectively, whereas in the fuzzy FMEA, the highest and lowest level of risk were related to manual screening clogging and fracture of pump pipes with RPN of 894 and 105, respectively. The finding showed that risk assessment using fuzzy FMEA provides more accurate and better results than traditional FMEA. In the fuzzy FMEA, the involvement of the experts' opinions in risk assessment and fuzzy models leads to more realistic results, as well as corrective action prioritization is better performed.

Development and psychometric assessment an instrument for investigating Women's attitude toward home safety.

BACKGROUND: Approximately half of the Iranian population are women, and they play a vital role in the home. The women's attitude can play a critical role in the safety of homes. Best of our knowledge, there is not a valid and reliable instrument to measure their attitude toward home safety. So, the present study aimed to design a psychometrics tool to assess women's attitudes toward home safety. METHODS: The researchers designed an instrument based on the home safety concept as the first instrument to measure housewives' attitudes toward home safety. The developed instrument distributed among 686 women in Tabriz health centers. Content validity, confirmatory, and exploratory factor analysis were used to examine the construct validity, and Cronbach's alpha and test-retest were employed to examine the reliability and reproducibility of the instrument. RESULTS: In the face validity section, the impact score of all items was determined to be above 1.5. In the content validity section, 4 items were excluded from the 39 questionnaire items due to low Content Validity Ratio (CVR). The mean CVR of all items was 0.842. By conducting exploratory factor analysis, it was found that the questionnaire has six dimensions. Three questions were removed from the study due to lack of connection with other items. Also, Cronbach's alpha coefficient of the questionnaire is equal to 0.924, which indicates the appropriate reliability of the instrument. CONCLUSIONS: This study aimed to develop a questionnaire to assess the safety attitudes of housewives toward home safety. It was found that the prepared tool has acceptable validity and reliability.

Likely behaviours of people under emergency circumstances in hospitals: A cross-sectional study.

Hospitals, which play an important role in reducing injuries and casualties, must be prepared for a crowd of people in emergencies. The present study aimed to survey and collect data on the likely behaviours of people under emergency circumstances in hospitals in order to improve emergency response plans in these places. The target population was all individuals present in three hospitals from Tabriz (including patients, companions and treatment staff), and the sample size was 1145. A questionnaire was administered to this population in order to collect the data. The comparison of different groups was performed based on participants' gender and their role. Results showed that, in general, everyone in the surveyed hospitals is more likely to choose a reactive strategy rather than a preventive strategy as well as a cooperative strategy rather than a competitive strategy, and less willing to use lifts during emergencies. Comparing different strategies utilized by different people resulting from ordered logit models revealed that there are significant differences in evacuation strategies between men and women as well as between treatment staff and all respondents. Men were more likely to select a proactive strategy rather than a reactive strategy compared to women. Also, the treatment staff group were more likely to employ a cooperative strategy and less likely to use a competitive strategy compared to other people. In view of the role of hospitals, the results of this study can play a major role in policy-making to predict the behaviour of different individuals in healthcare settings and perform needs assessment to consider the necessary facilities or raining required for different people in various countries.

Prioritizing the indicators influencing permit to work system efficiency based on an analytic network process.

A permit to work (PTW) system is a formal procedure designed to control non-routine and hazardous works. However, this system by itself does not prevent incidents, and various factors contribute to its efficiency. This study aims to prioritize the indicators influencing system efficiency. To do this, indicators of the system were identified and scored by 15 safety experts. Next, priority weights of the indicators were analyzed by an analytic network process and Super Decisions version windows 2.10. Accordingly, the nine main indicators and 43 sub-indicators influencing the PTW system were ranked. The main indicators from high to low were preventive actions, training, safe procedures, emergency system, control and corrective measures, coordination, monitoring, details of the permit form and documentation, respectively. The present work helps identify the involved indicators in PTW system efficiency. Thereby, the experts can prioritize and perform measures to prevent failures in the system and decrease accidents.

Investigating the status of accident precursor management in East Azarbaijan Province Gas Company.

Purpose. The accident precursor reporting system is a key point in preventing accidents and proper functioning of this system is critical. In the present study, the accident precursor reporting system in the Iranian East Azarbaijan Province Gas Company was investigated. Methods. This quantitative-qualitative study used field survey and document review methods to determine how the company was reporting. Qualitative content analysis approaches were used to analyze the reporting system over a 3-year period. From 1209 accident precursor reports, 2271 codes were extracted. Finally, these codes were reduced to three clusters: 996 (43.86%), 447 (19.68%) and 828 (36.46%) codes related to near misses, unsafe conditions and unsafe acts, respectively. A χ2 test was used to investigate the reporting process. Results. Reporting rates varied by time (e.g., people reported more accident precursors in the first 6 solar months), by area (some areas had higher reporting rates than others) and by type of job (operational jobs had the highest reporting rate [73.16%] compared to non-operational jobs [26.84%]). Conclusion. It was suggested that policy-makers should improve the accident precursor reporting system. Changes to the current reporting system are essential to help in the prevention of future unpleasant accidents.

Dimensions analysis of the Hospital Survey on Patient Safety Culture questionnaire in Iran: Psychometric properties.

AIM: The present study aimed to investigate the possible alternative factorial structure of the patient safety culture model in Iran. METHODS: This study was performed based on data collected by Hospital Survey on Patient Safety Culture (HSOPSC) questionnaire from 420 staff in four hospitals. Internal consistency reliability and construct validity were evaluated by Cronbach's alpha and correlation analysis. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to investigate the possible alternative factorial structure, examine and confirm the obtained structure, alternatively. Kaiser-Meyer-Olkin measure and Bartlett test were calculated to determine the factor ability of sample and fit of the factor analysis, alternatively. SPSS and AMOS version 25 were used. RESULTS: EFA identified 12 dimensions which one dimension has been also created from a new question. Distribution of items in all dimensions differed from the original HSOPSC questionnaire except two dimensions. The obtained structure was a proportional model. The calculation of Cronbach's alpha (∝ = .8) showed that, the internal consistency reliability was appropriate for all items in the questionnaire. Also, construct validity was acceptable for all factors. CONCLUSIONS: The structure of the dimensions obtained in this study was not consistent with the structure of the original HSOPSC model. HIGHLIGHTS: Provide a model for assessing patient safety culture with relative stability with respect to the native culture of the region. Good content and construct validity. Differences in the distribution of items in dimensions. Formation of new dimensions. Performing a psychometric analysis of the instrument using EFA, CFA and SEM to examine the disagreement on the validity, reliability and dimensions of patient safety culture in previous studies in Iran. Numerous discrepancies in item wording comply with the approach advocated by the translation guideline for AHRQ survey on patient safety.

The priority setting of factors affecting a crash severity using the Analytic Network Process.

BACKGROUND: The original step in reducing crash severity is recognition of the involved factors. The aim of this paper is to prioritize the factors affecting crashes severity. The current study was carried out in 2018 in Iran. METHODS: The present cross-sectional study focuses on factors affecting the crash severity. Due to the complicated nature of traffic accidents, Multi-Criteria Decision-Making methods can be considered as an effective approach. In this work, the factors affecting a crash severity were identified and then attained factors were scored by ten traffic safety experts. To prioritize and weigh these factors, the Analytic Network Process method and Super Decisions program were used. RESULTS: The results showed four main factors and 60 sub-factors in which the main factors in the order of priority were the safety (the most important sub-factor: speed over the upper limit), the other factors (the most important sub-factor: road user type), the health (the most important sub-factor: drowsiness), and the environment (the most important sub-factor: slipping the road). CONCLUSIONS: In order to control the crash severity, the presented factors in this study could help traffic safety experts to prioritize and perform controlling actions.

Assessment of accident severity in the construction industry using the Bayesian theorem.

AIM: Construction is a major source of employment in many countries. In construction, workers perform a great diversity of activities, each one with a specific associated risk. The aim of this paper is to identify workers who are at risk of accidents with severe consequences and classify these workers to determine appropriate control measures. METHODS: We defined 48 groups of workers and used the Bayesian theorem to estimate posterior probabilities about the severity of accidents at the level of individuals in construction sector. First, the posterior probabilities of injuries based on four variables were provided. Then the probabilities of injury for 48 groups of workers were determined. RESULTS: With regard to marginal frequency of injury, slight injury (0.856), fatal injury (0.086) and severe injury (0.058) had the highest probability of occurrence. It was observed that workers with <1 year's work experience (0.168) had the highest probability of injury occurrence. The first group of workers, who were extensively exposed to risk of severe and fatal accidents, involved workers ≥ 50 years old, married, with 1-5 years' work experience, who had no past accident experience. CONCLUSION: The findings provide a direction for more effective safety strategies and occupational accident prevention and emergency programmes.

Analysis of Occupational Accident Fatalities and Injuries Among Male Group in Iran Between 2008 and 2012.

BACKGROUND: Because of occupational accidents, permanent disabilities and deaths occur and economic and workday losses emerge. OBJECTIVES: The purpose of the present study was to investigate the factors responsible for occupational accidents occurred in Iran. PATIENTS AND METHODS: The current study analyzed 1464 occupational accidents recorded by the Ministry of Labor and Social Affairs' offices in Iran during 2008 - 2012. At first, general understanding of accidents was obtained using descriptive statistics. Afterwards, the chi-square test and Cramer's V statistic (Vc) were used to determine the association between factors influencing the type of injury as occupational accident outcomes. RESULTS: There was no significant association between marital status and time of day with the type of injury. However, activity sector, cause of accident, victim's education, age of victim and victim's experience were significantly associated with the type of injury. CONCLUSIONS: Successful accident prevention relies largely on knowledge about the causes of accidents. In any accident control activity, particularly in occupational accidents, correctly identifying high-risk groups and factors influencing accidents is the key to successful interventions. Results of this study can cause to increase accident awareness and enable workplace's management to select and prioritize problem areas and safety system weakness in workplaces.

Building a model using bayesian network for assessment of posterior probabilities of falling from height at workplaces.

BACKGROUND: Falls from height are one of the main causes of fatal occupational injuries. The objective of this study was to present a model for estimating occurrence probability of falling from height. METHODS: In order to make a list of factors affecting falls, we used four expert group's judgment, literature review and an available database. Then the validity and reliability of designed questionnaire were determined and Bayesian networks were built. The built network, nodes and curves were quantified. For network sensitivity analysis, four types of analysis carried out. RESULTS: A Bayesian network for assessment of posterior probabilities of falling from height proposed. The presented Bayesian network model shows the interrelationships among 37 causes affecting the falling from height and can calculate its posterior probabilities. The most important factors affecting falling were Non-compliance with safety instructions for work at height (0.127), Lack of safety equipment for work at height (0.094) and Lack of safety instructions for work at height (0.071) respectively. CONCLUSION: The proposed Bayesian network used to determine how different causes could affect the falling from height at work. The findings of this study can be used to decide on the falling accident prevention programs.