Investigation of ability to guess safety signs based on cognitive features in one of the petrochemical industries

• Main Authors: G. A. Shirali, T. Hosseinzadeh, D. Afshari, M. S. Moradi
• Format: Article
• Language: fas
• Published: Tehran University of Medical Sciences 2015-07-01
• Series: بهداشت و ایمنی کار
• Subjects: Ability to guess; Cognitive features; Ergonomics; Petrochemical industry; Safety signs
• Online Access: http://jhsw.tums.ac.ir/browse.php?a_code=A-10-25-130&slc_lang=en&sid=1

Introduction: Safety signs provide information,related to hazards or dangers in the industry,in form of instructions. These signs are effective as long as they are designed in accordance with principles of ergonomics and design cognitive features. The purpose of this present research was to study the relationship between cognitive features of signs and ability to guess, and to develop the relevant regression model. . Materials and methods: This descriptive cross-sectional study was carried out on 100 employees in a petrochemical industry complex. A three part questionnaire was used to collect required data while first part of the questionnaire dealt with demographic information, second part included cognitive features of signs designand the third part proceeded on testing the ability to guess. Then, a regression model was developed to determine the relationship between cognitive features, and the ability to guess. .Results: Mean and standard deviation obtained for the ability to guess the total study signs were 63.73 and 4.36, respectively. The feature of “familiarity” obtained the lowest possible score (49.15). The “semantic closeness” (β=0/390) and “meaningfulness” (β=0/369) had the highest correlation with the ability to guess safety signs. .Conclusion: According to results of this study, use of principles of ergonomic design of signs and training are necessary to promote the ability to guess the safety signs to the minimum available standards. Therefore, it is possible to balance cognitive features especially “familiarity”, with the lowest score, and “meaningfulness” and “semantic closeness”, with the highest influential relationship with the ability to guess of signs. The developed regression model for this industry can be used to predict the ability to guess of safety signs in future studies