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Volume 2, Issue 3 (12-2012)
Abstract
Introduction: Occupational injuries are among factors that cause death and disability of thousands individuals in the workplace. Thus, identifying the influential factors of occupational injuries is of paramount importance. Previous researches have indicated that transformational leadership style has an essential role in occupational injuries. Consequently, the aim of the current study is to investigate the role of transformational leadership style in predicting occupational injuries among Esfahan Steel’s employees.
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Material and Method: The current descriptive-correlation study was conducted among 189 Esfahan Steel’s employees in 2012. They were randomly selected through Stratified sampling. Data were collected using transformational leadership style questionnaire (Bass and Avolio, 1990), safety consciousness inventory (Barling, et al., 2002) and safety-related events and occupational injuries questionnaire (Barling, et al., 2002). The obtained data were analyzed thorough descriptive Statistics methods, Pearson product-moment correlation coefficients, and regression analysis by SPSS 18.
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Result: The findings of the study showed that transformational leadership style had a significant correlation with safety consciousness and safety-related events (P< 0.05). The Results of regression analysis showed that transformational leadership style reduced the occupational injuries through increasing safety consciousness and reducing safety-related events.
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Conclusion: The present study emphasizes the importance of transformational leadership style and its instruction to mangers and supervisor. The consequences as well as the suggestion for the further study are discussed in this article.
T. Rahimi Pordanjani, A. Mohammadzade Ebrahimi,
Volume 4, Issue 4 (1-2015)
Abstract
Introduction: The present study aimed to test a model of the relationship between management commitment to safety and consciousness with unsafe performance,considering the mediating role of safety self-efficacy.
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Material and Method: Research design was the correlation throughStructural Equation Modeling (SEM) and the sampleconsisted of 265 employees of an industrialcompany who were selected by stratifiedrandom sampling method. Participants of this study completedsafety climatescale, short form of NEO personality questionnaire,safety self-efficacy scale, and unsafe performance questionnaire.Reliability and validity of the questionnaires were reported as acceptable. Evaluation of the proposed model was done by SEM through AMOS-21and SPSS-19 software packages. In addition, Preacher and Hayes’ SPSS Macro program was used for testing the mediating role.
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Result: The results showed that the proposedmodel fit the data properly.Management commitment to safety and consciousness had direct effect on unsafe performance and safety self-efficacy.Moreover, the mediating effect of safety self-efficacy in the relationship between management commitment to safety and consciousness with unsafe performancewas confirmed.
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Conclusion: Overall, organizations canreduce unsafe performance and consequently occupational accidentsby increasing the management commitment to safety and employees’ consciousness and also training of employees and supervisors to reinforce their safety self-efficacy.
Naser Nik Afshar, Mostafa Kamali, Elham Aklaghi Pirposhteh, Hesamedin Askai Majabadi, Nasir Amanat, Mohsen Poursadeqiyan,
Volume 13, Issue 1 (3-2023)
Abstract
Introduction: In recent years, driver’s drowsiness has been one of the leading causes of road accidents, which can lead to physical injuries, death, and significant economic losses. Statistics show that an efficient system is needed to detect the driver’s drowsiness, that gives the necessary warning before an unfortunate event occurs. Therefore, this review study was conducted to investigate the studies on driver’s drowsiness sensors and to present a combination of diagnostic methods and an efficient model design.
Material and Methods: This narrative review study was conducted through a systematic search using “driver” and “drowsiness detection” as search keywords in indexing databases including Scopus, PubMed, and Web of Sciences. The search encompassed the latest related research conducted in this field from 2010 to September 2020. The reference lists were also reviewed to find further studies.
Results: In general, researchers evaluate driver’s drowsiness using three methods including vehicle-based measurement, behavioural measurement, and physiological measurement. The details and how these measurements are made make a big difference to the existing systems. In this study, which is a narrative review, the three mentioned measurements were examined using sensors and also the advantages and limitations of each were discussed. Real and simulated driving conditions were also compared. In addition, different ways to detect drowsiness in the laboratory were examined. Finally, after an analytical comparison of the methods of diagnosing drowsiness, a diagram was presented based on which an efficient and combined model was developed.
Conclusion: Taking into account the limitations of each of the methods, we need a combination of behavioural, performance, and other measures to have an efficient drowsiness diagnosing model. Such model must be tested using simulations and in real world situations.
