농작업 자세 평가도구의 개발과 타당성 검증 연구

Abstract

Objective: The purposes of this study were to validate the accuracy of AWBA (Agricultural Whole Body Assessment) by comparing with expert's evaluation and to suggest the improvements of AWBA based on the results of this study. Background: In the agriculture field, many tasks could have awkward postures such as back, neck, and knee flexion according to the crops and growing processes. Many risk assessment tools such as RULA (Rapid Upper Limb Assessment), REBA (Rapid Entire Body Assessment), OWAS (Ovako Working posture Analysis System) have been used to quantify these awkward working postures. However, existing posture assessment tools were developed focused on the manufacturing industry, not on the agricultural tasks which require different types of working postures with the industry sites. Thus there are many limitations for applying these assessment tools to evaluate agricultural working postures. To overcome these limitations, AWBA has been developed with focusing on the agricultural tasks. Method: The validation study of AWBA was conducted based on comparison with the expert's evaluation results. For validation study, a total of 80 working postures were selected from pepper and bean crops. At least one representative working posture was obtained from each unit work for each crop, and the experts were asked to evaluate subjective risk levels for all 80 working postures with 4 risk levels. To compare the agreements between AWBA analyses and experts' evaluations vs. between other existing assessment tools' analyses and experts' evaluations, percent of agreement and weighted kappa analysis were applied. Based on these results, improvements of AWBA were also suggested in this study. Results: The largest percent of agreement (44.4%) was obtained from AWBA and it is significantly larger than the percent of agreement of existing assessment tools [RULA (28.3%), REBA (37.6%), OWAS (28.6%)]. Kappa values of AWBA and REBA were 0.44 and 0.47, which means 'moderate consistency' also significantly larger than results of RULA and OWAS. Results also showed that there are some difference between AWBA and expert's evaluation at the back flexion posture (at 90°) and standing posture. Based on this, ABWA was revised and thus a revised Kappa value has been changed to 0.62 which means 'substantial to almost perfect'. Conclusion: The agreement between AWBA and expert's results was significantly higher than existing assessment tools. However some revisions were needed to improve the accuracy of AWBA. Thus, AWBA was revised based on the results of this study and the revised AWBA which was improved has been suggested. Application: The results of this study could be applied for evaluation of agricultural working postures and may lead to improve the accuracy of risk evaluation in agricultural field. Eventually, it could improve the work environment and reduce work-related musculoskeletal disorders.