A Study on Relationship between Physical Elements and Tennis/Golf Elbow
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- Journal of the Ergonomics Society of Korea
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- v.36 no.3
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- pp.183-196
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- 2017
Objective: The purpose of this research was to assess the agreement between job physical risk factor analysis by ergonomists using ergonomic methods and physical examinations made by occupational physicians on the presence of musculoskeletal disorders of the upper extremities. Background: Ergonomics is the systematic application of principles concerned with the design of devices and working conditions for enhancing human capabilities and optimizing working and living conditions. Proper ergonomic design is necessary to prevent injuries and physical and emotional stress. The major types of ergonomic injuries and incidents are cumulative trauma disorders (CTDs), acute strains, sprains, and system failures. Minimization of use of excessive force and awkward postures can help to prevent such injuries Method: Initial data were collected as part of a larger study by the University of Utah Ergonomics and Safety program field data collection teams and medical data collection teams from the Rocky Mountain Center for Occupational and Environmental Health (RMCOEH). Subjects included 173 male and female workers, 83 at Beehive Clothing (a clothing plant), 74 at Autoliv (a plant making air bags for vehicles), and 16 at Deseret Meat (a meat-processing plant). Posture and effort levels were analyzed using a software program developed at the University of Utah (Utah Ergonomic Analysis Tool). The Ergonomic Epicondylitis Model (EEM) was developed to assess the risk of epicondylitis from observable job physical factors. The model considers five job risk factors: (1) intensity of exertion, (2) forearm rotation, (3) wrist posture, (4) elbow compression, and (5) speed of work. Qualitative ratings of these physical factors were determined during video analysis. Personal variables were also investigated to study their relationship with epicondylitis. Logistic regression models were used to determine the association between risk factors and symptoms of epicondyle pain. Results: Results of this study indicate that gender, smoking status, and BMI do have an effect on the risk of epicondylitis but there is not a statistically significant relationship between EEM and epicondylitis. Conclusion: This research studied the relationship between an Ergonomic Epicondylitis Model (EEM) and the occurrence of epicondylitis. The model was not predictive for epicondylitis. However, it is clear that epicondylitis was associated with some individual risk factors such as smoking status, gender, and BMI. Based on the results, future research may discover risk factors that seem to increase the risk of epicondylitis. Application: Although this research used a combination of questionnaire, ergonomic job analysis, and medical job analysis to specifically verify risk factors related to epicondylitis, there are limitations. This research did not have a very large sample size because only 173 subjects were available for this study. Also, it was conducted in only 3 facilities, a plant making air bags for vehicles, a meat-processing plant, and a clothing plant in Utah. If working conditions in other kinds of facilities are considered, results may improve. Therefore, future research should perform analysis with additional subjects in different kinds of facilities. Repetition and duration of a task were not considered as risk factors in this research. These two factors could be associated with epicondylitis so it could be important to include these factors in future research. Psychosocial data and workplace conditions (e.g., low temperature) were also noted during data collection, and could be used to further study the prevalence of epicondylitis. Univariate analysis methods could be used for each variable of EEM. This research was performed using multivariate analysis. Therefore, it was difficult to recognize the different effect of each variable. Basically, the difference between univariate and multivariate analysis is that univariate analysis deals with one predictor variable at a time, whereas multivariate analysis deals with multiple predictor variables combined in a predetermined manner. The univariate analysis could show how each variable is associated with epicondyle pain. This may allow more appropriate weighting factors to be determined and therefore improve the performance of the EEM.
School nurses, in service of 102 special schools in Korea, were urveyed by mail questionnaires from February to March, 1991 and 77 of hem responded. Collected data were analyzed to establish the direction of health management in special school and to provide basic reference data for improving the quality of the management of school-nurses' services. The major findings are as follows: Out of special schools surveyed, 67.5% is private school and 83.2% is located in city. The average number of classes, students, and educational personnels per special school is 17.2, 194, and 28 respectively. The average age of school-nurses surveyed is 32.7. The proportion of graduates from the junior college and upward was 97.4%, the proportion of the married was 71.4%. Out of respondents, 71.4% has religion : 79.2% has past career in the fields of clinics or public health: 62.3% accompanishes independent services: 77.9% belongs to primary school. About 69% of nursing room in special schools surveyed is located at the first floor. Out of special school surveyed, 90.9% has no organization for school health programms: Only 18.2% entrusted everyone of school doctor, school dentist, and school pharmacists with school health. 46.8% of respondents didn't know about the annual budget for school health programmes. The average annual expenditure for school health programme per special school was 317,000F26. won and the purchase cost for medical supplies accounted for the larger part of them. The monthly average number of students utilizing school nursing room was 71 per school, annual utilization times of school nursing room was 4.4 per student and utilization due to injury was prevalent by 26.6% and there is some differences in using the school nursing room according to disabled area. Rate of referral to medical facilities was 1.4%. The leading reason of referral to medical facilities was high fever among those who have visual handicaps, fracture among those who have emotional disturbance, injury by trauma among others. Nine hundred fifty six students of students in special school surveyed have sufferd from epilepsy and prevalence rate of epilepsy was 6.4%. Only 22.6% of respondents replied that they had physical examination more than 2 times per year. Out of respnodents, 98.7% answered that they had health education and 67.1% of them ansered that they educated in a classroom, 98.7% of respondents emphasized need of sex education. Respondents put the most emphasis on the personal hygiene when they performed health education and they used broadcasting education in the area of visual handicaps, OHP or VTR in hearing handicaps, home correspondence or OHP VTR in other area importantly. About 47% of repondents answered that health education was the most difficult and they emphasized that definite guide on health management was requested. Respondents had self-confidence and high perfomance rate in most of school-nurses' services completely, but so they was not in area of evaluation of school health programmes, an examination of physical strength, evaluation of health education, management of school purification area, suture of wounds. In consideration of above findings, we may conclude that special education for school-nurse in special schools as well as improvement of definite guiding principles are requested to establish direction for health management in special schools and to improve the degree of quality for school-nurses' sevices in special schools.