A Comparative Risk Assessment of Human Error in Firefighting Using SLIM and Fuzzy SLIM Method

Raheleh  Pourhosein; Saeed  Musavi; Yahya  Rasoulzadeh

doi:10.18502/jhsw.v14i1.17129

Raheleh Pourhosein Department of Occupational Health Engineering, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran.
Saeed Musavi Department of Biostatistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
Yahya Rasoulzadeh Department of Occupational Health Engineering, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran

DOI: https://doi.org/10.18502/jhsw.v14i1.17129

Keywords: Human error, Risk assessment, Emergency situations, Fuzzy logic, Fuzzy SLIM, SLIM

Abstract

Introduction: The accurate evaluation of error probability and risk is important. Accordingly, this Comparative study was conducted to evaluate the risk of human error in emergency situations using SLIM and Fuzzy SLIM techniques in fierfighting tasks.

Material and Methods: This cross-sectional and descriptive-analytical study was conducted among 12, using Fuzzy SLIM and SLIM techniques. 39 sub-tasks were studied in 4 phases (Awareness, Evaluation, Egress and Recovery). Considering the advantages of the Fuzzy SLIM method, fuzzy logic was used in weighting of performance shaping factors (PSF). Excel software was used to calculate the probability of error. Also, correlation and kappa statistical tests were used for data analysis in SPSS software.

Results: The mean and standard deviation of human error probability in different sub-tasks of firefighting in SLIM and Fuzzy SLIM methods were 0.095357 ± 0.026193 and 0.06490 ± 0.051748, respectivly. In 48.7 percent of the sub-tasks, the probability category of human error and the assessed risk were the same; however, in 89.7 percent of the sub-tasks, the estimated level of risk was the same in both methods. Correlation test showed that the correlation coefficient of error probability values between the two methods was 0.32, which indicated a moderate correlation in this regard. Additionally, the results of kappa statistical test for the estimated level of risk showed that there is a high agreement between Fuzzy SLIM and SLIM (P value <0.05).

Conclusion: The results of the study indicated meaningful agreement and a moderate correlation between Fuzzy SLIM and SLIM. Therefore, due to the relatively high accuracy of Fuzzy logic methods, and also the long steps of implementing the SLIM method, the Fuzzy SLIM method can be a good alternative to this method.