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Postural Loading Assessment in Assembly Workers of an Iranian Telecommunication Manufacturing Company

Kamalinia M., Saraji G. N., Kee D., Hosseini M., Choobineh A

International Journal of Occupational Safety and Ergonomics

2013

Vol. 19, No. 2

311--319

Background. Changes in industries and work practices have coincided with work-related musculoskeletal disorders(MSDs). This study was conducted to determine the prevalence of MSDs and to assess postural loading in assembly workers of an Iranian telecommunication manufacturing company. Methods. Data were collected from 193 randomly selected workers in 4 units of the company. The Nordic musculoskeletal disorders questionnaire and the UBC ergonomic checklist were used as data collection tools. Loading on the upper body assessment(LUBA) was used to assess postural loading. Results. Lower back symptoms were the most prevalent problems among the workers (67.9%). LUBA showed that most assembly workers (94.3%) had experienced considerable and high postural loading (postural load index, PLI > 5). Regression analyses revealed that lighting, rotation, contact stress, repetition, gender and age were factors associated with symptoms. Conclusion. Work-related MSDs occurred at a high rate among workers. Postural loading requires consideration. Any ergonomic intervention should focus on eliminating ergonomic factors associated with symptoms.

Cognitive Failures, Driving Errors and Driving Accidents

Allahyari T., Saraji G. N., Adl J., Hosseini M., Iravani M., Younesian M., Kass S. J.

International Journal of Occupational Safety and Ergonomics

2008

Vol. 14, No. 2

149--158

Introduction. The impact of a driver’s cognitive capability on traffic safety has not been adequately studied. This study examined the relationship between cognitive failures, driving errors and accident data. Method. Professional drivers from Iran (160 males, ages 18–65) participated in this study. The cognitive failures questionnaire (CFQ) and the driver error questionnaire were administered. The participants were also asked other questions about personal driving information. A principal component analysis with varimax rotation was performed to determine the factor structure of the CFQ. Poisson regression models were developed to predict driving errors and accidents from total CFQ scores and the extracted factors. Results. Total CFQ scores were associated with driving error rates, but not with accidents. However, the 2 extracted factors suggested an increased effect on accidents and were strongly associated with driving errors. Discussion. Although the CFQ was not able to predict driving accidents, it could be used to identify drivers susceptible to driving errors. Further development of a driving-oriented cognitive failure scale is recommended to help identify error prone drivers. Such a scale may be beneficial to licensing authorities or for developing driver selection and training procedures for organizations.