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Sun-Young Kim,Seon-Ju Yi,Young Seob Eum,Hae-Jin Choi,Hyesop Shin,Hyoung Gon Ryou,Ho Kim 환경독성보건학회 2014 환경독성보건학회지 Vol.29 No.-
Objectives : Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to 10 μm in diameter (PM<SUB>10</SUB>) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods : We obtained hourly PM<SUB>10</SUB> data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average PM<SUB>10</SUB> concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared (R²) statistics were computed. Results : Mean annual average PM<SUB>10</SUB> concentrations in the seven major cities ranged between 45.5 and 66.0 μg/m³ (standard deviation=2.40 and 9.51 μg/m3, respectively). Cross-validated R² values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had R² values of zero. The national model produced a higher crossvalidated R² (0.36) than those for the city-specific models. Conclusions : In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate PM<SUB>10</SUB> source characteristics.
산림치유프로그램이 사회복지전담공무원과 정신보건종사자의직무스트레스와 기분상태에 미치는 영향
신창섭 ( Chang Seob Shin ),연평식 ( Poung Sik Yeoun ),김영규 ( Young Gyu Kim ),엄재옥 ( Jae Ouk Eum ),임영란 ( Young Ran Yim ),윤수복 ( Soo Bok Yoon ),박석희 ( Suk Hee Park ),김인옥 ( In Ok Kim ),이상희 ( Sang Hee Lee ) 한국산림과학회 2015 한국산림과학회지 Vol.104 No.2
This study was conducted to investigate the influence of a forest healing program on the level of job stress and the profile of mood states (POMS). 38 public servants who were in charge of social welfare in A city as well as 24 metal health care workers in C province participated in the forest healing programs. The data were collected by a pretest-posttest design. The data analysis showed that both job stress and POMS levels were significantly improved by the forest healing program. The therapeutic effects of forests are highly expected to be utilized for healing programs for job stress reduction and burnout prevention.
숲활동 중재가 암환자의 불안, 우울, 기분상태 및 희망에 미치는 영향
김영규(Kim, Young-Guy),이상희(Lee, Sang-Hee),김윤희(Kim, Youn-Hee),엄재옥(Eum, Jae-Ouk),임영란(Yim, Young-Ran),하태국(Ha, Tae-Guk),신창섭(Shin, Chang-Seob) 한국산림휴양복지학회 2015 한국산림휴양학회지 Vol.19 No.1
& & 본 연구는 숲활동 중재가 암환자의 불안과 우울, 기분상태 및 희망에 어떤 영향을 미치는지 알아보고자 수행하였다. 서울과 경기도에 위치한 암 전문 요양병원의 환자 53명을 대상으로 수행 되었으며, 연구 대상은 실험집단과 비교집단으로 구분하였고, 두 집단은 사전-사후 측정방법을 사용하여 연구를 진행하였다. 자료는 2014년 8월부터 11월까지 수집하였고 수집된 자료는 SPSS 18.0를 이용하여 t-검정 분석을 실시하였다. 분석 결과, 숲활동 중재를 받은 실험군이 숲활동 중재를 받지 않은 대조군보다 불안과 우울이 개선되었다. 기분상태의 경우 활기 요인을 제외하고 긴장, 우울, 분노, 피로, 혼돈의 5개 하위요소는 개선되었으며, 종합감정장애(TMD)도 개선된 것으로 나타났다. 희망은 통계적으로 유의하지 않았으나 실험후 평균값 비교 결과 숲활동 중재를 받은 실험군의 희망 평균이 대조군보다 높게 나타났다. 그러므로 암환자에게 적용한 숲활동 중재가 암환자의 불안과 우울, 기분상태 및 희망 개선에 효과적이라고 볼 수 있다. & & This study is a research into what effect the forest activity intervention can affect anxiety·depression, profile of mood states(POMS) and hope of cancer patients. The subject of the study was 53 cancer patients of the care hospital that treats cancer patients in Seoul and Gyeonggi-do. The subject was divided into two groups, or an experimenting group and a comparing group, and was performed by using the method of measuring the results before and after the researching process. The data were collected from august to november in 2014, and collected data were analyzed using SPSS 18.0 through independent t-test. After analyzing the research data, it was revealed that the anxiety and depression was improved the level(p<.05) which experimenting group who participate in the forest activity intervention was better than control group who didn’t, and that POMS was improved the level of tension, depression, anger, fatigue, confusion and total mood disturbance(TMD) except vigor factor. There were not statistically significant differences in hope, but the experimental group which received forest activity intervention was higher mean level of hope than the control group which not received. Therefore, it was revealed that forest activity intervention applying to cancer patients could be an effective method for improving anxiety, depression, POMS and hope of cancer patients.
Kim, Sun-Young,Yi, Seon-Ju,Eum, Young Seob,Choi, Hae-Jin,Shin, Hyesop,Ryou, Hyoung Gon,Kim, Ho The Korean Society of Environmental Toxicology 2014 환경독성보건학회지 Vol.29 No.-
Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to $10{\mu}m$ in diameter ($PM_{10}$) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly $PM_{10}$ data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average $PM_{10}$ concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared ($R^2$) statistics were computed. Results Mean annual average $PM_{10}$ concentrations in the seven major cities ranged between 45.5 and $66.0{\mu}g/m^3$ (standard deviation=2.40 and $9.51{\mu}g/m^3$, respectively). Cross-validated $R^2$ values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had $R^2$ values of zero. The national model produced a higher cross-validated $R^2$ (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate $PM_{10}$ source characteristics.