(2017) Comparison of the ROSA and RULA methods in risk assessment of catching to musculoskeletal disorders and the relationship with mental health on computer users. Iran Occupational Health. pp. 130-139. ISSN 17355133 (ISSN)
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Abstract
Background and aims: Musculoskeletal disorders and lack of mental health are two very important problems among employed people. The present study was conducted to compare the ROSA and RULA methods in risk assessment of catching to musculoskeletal disorders and to find the relationship with mental health on computer users. Methods: Present study was a descriptive - analytic cross-sectional study. 71 employees were selected from Isfahan University of Medical Sciences. Data collection was carried out in five stages as follows: 1) demographical data investigation 2) Prevalence investigation of musculoskeletal disorders with Nordic questionnaire, assessment of ergonomic factors risk in among employees using 3) ROSA method 4) RULA method 5) Evaluation of mental health. The collected data were analyzed by SPSS 20 software. Results: Assessment of staff body posture during work with two methods of ROSA and RULA had a direct and significant relationship (R=0.808 and p<0.001). Also, the final score of ROSA had a direct and significant relationship (R= 0.555 and p<0.001) with mental health of the staff. Conclusion: Given that two methods of ROSA and RULA have a direct and desirable correlation with each other, each of these two methods can be used interchangeably with great confidence. In addition, the increase risk of musculoskeletal disorders was associated with mental health reduction in the staff. © 2018 Tehran University of Medical Sciences and Health Services. All rights reserved.
Item Type: | Article |
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Keywords: | Mental health Musculoskeletal disorders Rapid office strain assessment Rapid upper limb assessment Risk factors |
Divisions: | Faculty of Health > Department of Occupational Health |
Page Range: | pp. 130-139 |
Journal or Publication Title: | Iran Occupational Health |
Journal Index: | Scopus |
Volume: | 14 |
Number: | 5 |
ISSN: | 17355133 (ISSN) |
Depositing User: | مهندس مهدی شریفی |
URI: | http://eprints.mui.ac.ir/id/eprint/1746 |
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