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Showing 3 results for Cmdq
Evaluation of WMSDs in VDT users with Rapid office strain assessment (ROSA) method
Farhad Ferasati, M.sadegh Sohrabi, Mohsen Jalilian,
Volume 1, Issue 3 (3-2014)
Abstract

Introduction: Regarding the increasing growth in jobs dealing with computers and the development of musculoskeletal disorders (MSDs) among VDT users, the assessment and identification of ergonomic risk factors are of greater importance. This study aimed to evaluate MSDs among office VDT users.

Materials and Methods: This cross-sectional study was conducted on 71 participants (37 females and 34 males) selected randomly among administrative staff of Isfahan Art University. CMD questionnaire was used to assess the prevalence of MSDs and for measuring ergonomic risk factors ROSA method was employed in VDT stations.

Results: According to ROSA risk levels, 21% (15 participants) were at low risk (score of less than 3), 48% (34 participants) were in the notification area (score 3 to 5) and 31% (22 participants) were in the need area for ergonomic intervention (score of more than 5). Sex, body mass index, educational level and work experience had significant impacts on ROSA final score (p<0.001). There was a positive significant correlation between ROSA final score and MSDs in the participants (p<0.001, r=0.828).

Conclusion: With regard to the purpose of ROSA method for evaluating risk factors of working with computer in administrative and office settings and the finding of this study, it can be employed as a useful tool in identifying and ranking ergonomic risks in today office environments. Normal 0 false false false EN-US X-NONE AR-SA
Investigating the Prevalence of Musculoskeletal Disorders in Melli Bank Staff and Determining Its Relationship with Office Tension in North Khorasan Province in 2019
Seyed Taghi Mirmohammadi, Osman Gook, Seyed Nouroddin Mousavinasab, Hadi Mahmoodi Sharafe,
Volume 7, Issue 4 (2-2020)
Abstract

Background and Objectives: Bank staff do much of their work using computers, Their equipment and layout may put the body in an inappropriate position and lead to musculoskeletal disorders (MSDs), so this study aimed to determine the prevalence of MSDs in bank staff and its relationship with office tensions.
Methods: This descriptive cross-sectional study was performed on 173 employees of Melli Bank of North Khorasan Province. The prevalence of MSDs was estimated through CMDQ, Risk factors were estimated through ROSA and data were entered into SPSS 20. Then their relationship with each other and with the equipment layout was determined by Spearman test.
Results: The mean ROSA scores were 4.73±0.793 and 63.6% of the postures were in the intervention group. The mean CMDQ scores were 103.63±181.004. Spearman test showed a good correlation between ROSA and CMDQ results (P=0.021, R= 0.175). There was a significant relationship between work experience and prevalence of MSDs (P=0.037, R=0.159). Kruskal-Wallis test showed a significant relationship between education level and CMDQ scores (P=0.38). The most common disorders in the organs were neck (53.8%) and lower back (49.7%).
Conclusion: Given the correlation between the ROSA results and the CMDQ, they can be used together. The change should be considered immediately for persons who are in intervention group. The chair and monitor played a more important role in raising the ROSA score. Improvements should be made by providing an ergonomic chair as well as a proper layout of other equipment such as a monitor.


Prediction of Musculoskeletal Disorders Based on People's Demographic Information Using Artificial Intelligence Methods and the Cornell Musculoskeletal Discomfort Questionnaire
Mousa Nazari, Arezoo Sammak Amani, Mohammad Amin Mououdi, Mohammad Mahdi Alyan Nezhadi,
Volume 11, Issue 4 (1-2024)
Abstract
Objectives: Work-related musculoskeletal Disorders (WMSDs) are the most significant challenges in both developing and developed countries, affecting the majority of individuals throughout their lives. Considering the detrimental effects of musculoskeletal disorders on the productivity and general health of employees, this research utilizes the Cornell Musculoskeletal Disorder Questionnaire (CMDQ) to develop an intelligent model for assessing and predicting the levels of musculoskeletal disorders.
Methods: In this descriptive-analytical study, 810 employees from five organizations (in four occupational categories, including administrative, technical, production, and services) completed the CMDQ voluntarily. After collecting the questionnaire and performing relevant statistical analyses, data normalization and clustering based on the K-Means method were used to determine levels of musculoskeletal disorders. Finally, the multilayer perceptron artificial neural network was trained to predict the levels of musculoskeletal disorders; moreover,  the criteria of precision, accuracy, recall, and F1-score were used to evaluate the proposed model.
Results: The performance of the proposed model in predicting the levels of musculoskeletal disorders is presented in two scenarios (use and non-use of the Synthetic Minority Oversampling Technique (SMOTE) method) based on the evaluation criteria provided. The accuracy, precision, recall, and F1-score values were 0.724, 0.709, 0.756, and 0.720, respectively. The appropriate accuracy and precision in the proposed model indicate its capability to identify the levels of musculoskeletal disorders in individuals and help healthcare professionals take necessary measures to prevent and predict them.
Conclusion: This study employs the CMDQ questionnaire and artificial intelligence to analyze musculoskeletal disorders in the workplace. The proposed model demonstrates significant accuracy and precision compared to similar studies. The results indicate that this model can be utilized to identify and predict musculoskeletal disorders in organizational employees, offering the potential to expedite the identification process and reduce costs.

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