Maziyar Arassi, Heidar Mohammadi, Majid Motamedzade, Mojtaba Kamalinia, Davoud Mardani, Misagh Mohammadi Beiragani, Mehdi Shekari, Mehdi Akbarzadeh,
Volume 2, Issue 1 (6-2014)
Abstract
Background: Psychosocial factors are present in most workplaces that could affect various aspects of workers’ health. Accordingly, psychosocial risks may lead to work related musculoskeletal disorders, increased risk of cardiovascular disease, effect on quality of working life, sickness absence, depression work injuries and accidents and various health problems. The aim of the present study was to assess work psychosocial problems and their association with non-fatal occupational accidents among Aghmary workers of Iranian drilling rigs.
Methods: A cross-sectional study using the short version of the Copenhagen Psychosocial Questionnaire (COPSOQ) was carried out on a total sample of 270 employees working on Aghmary system in drilling rigs. History of non-fatal occupational accidents was assessed by self-report during one year prior to the study. Statistical analyses were done using SPSS 16.0.
Results: The results showed that high work pace (OR=1.55), high emotional demands (OR=1.62), high influence at work (OR=1.5), low quality of leadership (OR=1.8), low social support (OR=1.87), high burnout (OR=1.72) and high threat of violence (OR=6.2) were significantly related to non-fatal occupational accident.
Conclusions: This study revealed the significant association between occupational accident and some psychosocial dimensions and recommended the incorporation of psychosocial factors in preventive measures.
Amin Amiri Ebrahimabadi, Ahmad Soltanzadeh, Samira Ghiyasi,
Volume 8, Issue 1 (5-2020)
Abstract
Background and Aim: Occupational accidents are recognized as one of the major concerns in the mining industry. The purpose of this study was to analyze the incidence of occupational accidents in a mine for 10 years using Human Factor Analysis and Classification System (HFACS).
Method: This cross-sectional study was carried out on 664 mining accidents during 2009-2018. The tools used in this study included accident reporting checklists, human factors analysis and classification system (HFACS), and a team approach to analyze these accidents. Data analysis was performed using IBM SPSS AMOS v. 23.0.
Results: The accident frequency rate (AFR) was 15.10±3.34. The results of 10-years accident analysis in this mine based on HFACS model showed that the highest contribution of each parameter to the four layers including unsafe acts, preconditions for unsafe acts, unsafe supervision and organizational influences were respectively devoted to perceptual error (64.4%), Physical environment (29.5%), inadequate supervision (59.6%), and organizational process (65.6%). The results of structural equation modeling showed that the AFR is directly and indirectly affected by the layers of the HFACS model (P<0.05). The most significant impact on the AFR was related to the unsafe acts layer.
Conclusion: The findings of this study indicated that all four causal layers of human factors were effective in mine accidents, in addition the HFACS model is highly effective for unsafe acts-based accidents analysis, so it can be used for future planning to reduce accidents in the mining sector.
