Assessment of musculoskeletal disorders in a manufacturing company using QEC and LUBAmethods and comparison of results

Background and aims   Musculoskeletal disorders (MSDs) are the most important causes of workers disabilities, increasing compensations and reducing productivity in developed and developing countries. This study was aimed to determine prevalence of musculoskeletal disorders and assessment of them by using QEC and LUBA methods and comparison of results in a manufacturing company in Iran.     Methods   This descriptive-analytical study was performed on 115 operators in 15 working stations by using QEC and LUBA methods. The prevalence of MSDs was obtained by using Nordic Musculoskeletal Questionnaire (NMQ). The data were analyzed by Spearman correlation coefficients.     Results   According to findings of NMQ, 81.4 percent of operators at least in one of nine parts of musculoskeletal system have pain since 12 months ago. Assessment with QEC and LUBA  revealed that 71.3 and 24.35 percent of operators respectively are in action level four.     Conclusion   According to the analysis, correlation between findings of NMQ and action levels in QEC is higher than LUBA action levels. Whereas LUBA just assess working postures, this method is not a suitable tool for evaluation of working stations that require repetitive carrying of loads, static posture and long time to do.

Evaluation of relationship between the rate of unsafe behaviors and personality trait Case study: construction project in a car manufacturing company

Introduction: According to the previous studies, about 90% of accidents in the workplace are due to the unsafe behaviors. In this study, the impact of personality traits, as a predictive factor on the unsafe acts was surveyed in a construction project of a car manufacturing company. .Material and Method: In this study, personality traits and unsafe behavior rates were determined using NEO-Five Factor Inventory (NEO-FFI) and safety behavior sampling (SBS) technique. The Spearman correlation coefficient was used. To analyze the acquired results, the total population of the project was 243 people. .Result: The results showed that 31.7% of workers’ behaviors were unsafe behaviors. The correlation between unsafe behaviors and the neuroticism and extroversion were direct and significant (p<0.001). . Conclusion: Assessment of the personality traits could be used as a predictive tool to identify employees with higher rates of unsafe behaviors and helps planning to reduce the accident rates