• Journal of Oral Medicine and Pain
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• v.34 no.4
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• pp.397-407
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• 2009

The aim of the study was to evaluate psychosocial impact of non-dental chronic orofacial pain (OFP) on daily living using the graded chronic pain (GCP) scale. It is also investigated the clinical profile such as demographics, event related to initiation of OFP and prior treatments for patients. During previous 6 months since September 2008, 572 patients (M:F=1:1.5, mean age=34.7 years) with non-dental OFP attended university-based specialist orofacial pain clinic (Dankook University Dental Hospital, Cheonan) to seek care although 63% of them already experienced related treatment for their OFP problem. They visited the most frequently general dental practitioner and orthopedic doctors due to their pain problem and medication was the most commonly employed modality. Most of the patients (89.2%) had TMD and the most common related event to initiation of their pain was trauma, followed by dental treatment. Almost half of the patients (46%) suffered from chronic pain(${\geq}6\;M$) and 40% of them exhibited relatively high disability due to chronic OFP. GCP pain intensity and disability days were significantly different for age and diagnosis (p<0.05) but not for gender and duration. GCP grades were affected by all the factors including gender, age, pain duration and diagnosis.(p=0.000) Female gender, elders, and long lasting pain were closely related to high disability. The patients with neuropathic Pain and mixed OFP rather than TMD were graded as being highly disabled. Conclusively, a considerable percentage of chronic OFP patients reports high pain-related disability in their daily, social and work activity, which suggest a need for psychosocial support and importance of earlier referral for appropriate diagnosis and tailored management.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.117-126
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• 2018

The purpose of this study was to examine the relationship between the working posture and symptoms of musculoskeletal disorders of dental hygienists during scaling. The subjects in this study were 264 selected dental hygienists. A convergence study was implemented using questionnaire that was prepared to cover general characteristics, health care, the work of scaling, working posture and subjective musculoskeletal symptoms. As for data analysis, R 2.15.1 was employed. As a result of analyzing the collected data, the rate of good working posture during scaling stood at 29.9 percent; roughly good posture, at 37.5 percent; incorrect posture, at 32.6 percent. Regarding the area of the body in which they complained of musculoskeletal symptoms, the shoulders were 3.32-fold more mentioned than any other area(OR,3.32;95%CI, 1.58~6.98); the foot, 2.97-fold more(OR,2.97;95%CI, 1.18~7.48); the hands, 2.84-fold more(OR,2.84:95%CI, 1.35~5.98); the neck, 2.82-fold more(OR, 2.82;95%CI, 1.35~5.91); the back, 2.41-fold more(OR,2.41;95%CI, 1.02~5.68). The findings of the study that demonstrate the importance of good working posture are expected to make a contribution to the improvement of work environments, the development of efficient preventive programs and the preparation of sustained educational plans, and it's necessary in the future to make a research study by including psychosocial factors.

• Sleep Medicine and Psychophysiology
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• v.26 no.2
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• pp.111-124
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• 2019

Objectives: Healthy sleep is important and can have a positive effect on resilience. The aim of the present study was to compare the differences in resilience between two group nurses in rotating shift and daytime fixed work schedules and to investigate stress perception, coping factors, social and psychological health, and sleep factors that may affect resilience. Methods: A total of 400 female nurses having rotating shift and daytime fixed work schedules at two hospitals was surveyed from June 12, 2017 to June 12, 2018. All participants completed perceived stress scale (PSS), stress coping short form (Brief COPE), psycho-social wellbeing Index short form (PWI-SF) or general health questionnaire-18 (GHQ-18), center for epidemiologic studies depression scale (CES-D), STAI-X-1 in state-trait anxiety inventory (STAI), Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), insomnia severity index (ISI), Conner Davidson resilience scale (CD-RISC). Independent t-test, paired t-test, Pearson correlation analysis, and multiple regression analysis were applied to the results of the final 373 questionnaires of 400 nurses in two general hospitals. Results: Comparing the variable statistics between the two groups of rotating shift and daytime fixed work nurses, showed statistically significant differences in all variables except perceived stress, sleep quality, and daytime sleepiness. Factors that had a significant correlation with resilience were stress coping strategies, depression, and insomnia severity (p < 0.001). In multiple regression analysis, larger positive reframing1 (β = 0.206, p < 0.001), severe less depression (β = -3.45, p < 0.001), and higher psychosocial health (β = 0.193, p < 0.001). As acceptance coping2 increased (β = 0.129, p < 0.05), as daytime sleepiness decreased (β = -1.17, p < 0.05), and as active coping2 increased (β = 0.118, p < 0.05), as the positive reframing2 increases (β = 0.110, p < 0.05), the resilience increased. Conclusion: This study, it was found that resilience was higher in daytime fixed workers than in shift workers. In addition, specific stress coping strategies, psycho-social health, sleep, and depression factors were associated with resilience.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.21 no.3
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• pp.146-155
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• 2011

Objectives: This study was conducted to investigate the association between job stress and mental health among male and female workers in a large electric manufacture company. Methods: A cross-sectional study was carried out on 3,228 employees who participated in annual medical check-up working in a large electric manufacture company in Gyeonggi Province. Medical check-up and self-administrated questionnaire were performed at the same time. Korean Occupational Stress Scale Short Form (KOSS-SF) and Psychosocial Wellbeing Index Short Form (PWI-SF) were applied to assess occupational stress and mental health. Hierarchical multiple linear regression and multiple logistic regression were performed to estimate the association between job stress and mental health. Results: The proportion of high risk of mental health was 17.1% in male, and 46.9% in women. Job stress had a greater effect on mental health than other general and work characteristics. All subscales of job stress were revealed to affect mental health. Bad occupational climate and lack of reward are the strongest risk factors in mental health of male and female respectively. Conclusions: Our results suggest that job stress could affect mental health among large electronic manufacture workers.

• Journal of Korean Medicine Rehabilitation
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• v.23 no.2
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• pp.95-104
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• 2013

Objectives : The purpose of this study is to analyze internal research trends of work-related musculoskeletal disorders(WMSDs) and provide problems of researches forward. Methods : 6 Korean databases were searched for articles of WMSDs published from 2000 to 2012, and 264 research were systematic reviewed. An analytical method was used descriptive statistics, an actual number and percentage. Results : The results of distribution by year were reported more than 20 articles after 2004, and 45 articles in 2009. Industrial classification distribution of research subjects the manufacturing industry was many most at the 84. Research contents in most description were 147 whether it was risk factor and relation. Research design type of articles was most description survey research 226. In the research field 89 articles were reported to the journal related to technologies. Conclusions : It is considered to be necessary that ergonomic approach would cooperate with other approaches such as integrated health management system as well as industrial medicine considering psychosocial factors.

• 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.