• 한국노년학
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• v.41 no.2
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• pp.197-215
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• 2021

This study aims to evaluate Person Centered Care practice and characteristics of care services in Korean long-term care facilities using Dementia Care Mapping as a tool. DCM, systematic observational evaluation tool for measuring dementia patients' QOL, was transformed into self-report rating scale. The process of transforming DCM into a scale of 34 items involves operationalization of DCM concepts and it's adaptation into Korean long-term care practices. Review by research team of Bradford university was added to maintain DCM concept and meaning in this scale. The scale with Cronbach alpha of .88 was surveyed on 343 care workers. Survey result shows PCC value practiced by them is 3.77(of 5 likert scale) and values on each categories of PCC reveal the characteristics of care in Korean facilities; attachment(4.02), comfort(3.95), inclusion(3.89), identity(3.67) and occupation(3.41). Dementia care in Korean facilities focuses on recipients'safety, comfort but lacks individualistic care and the meaningful and fulfilling occupation for patients. Looking at the organizational and individual factors influencing DCM values, the small facilities showed higher PCC values and there are no significant difference in PCC values between public and private facilities. Managers and care workers with career of 1~2 years showed higher PCC values compared to other career ranks and lengthes. This study suggests care practice should be centered on personhood of patients in long-term care facilities, for which introduction of unit care and education of PCC for service providers including support personnel are needed. DCM and Korean DCM scale developed in this study are suggested for the PCC-based assessment on care quality.

• Journal of Korean Elementary Science Education
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• v.41 no.2
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• pp.283-294
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• 2022

Although the concept of light is important in the elementary school curriculum, substantial research suggests that students and teachers have difficulties in understanding it. Therefore, it is necessary to analyze the reasons for these difficulties-whether it is due to the content or due to the presentation method of contents, structure, and expression. The national curriculum and textbooks of Korea, the US, China, and Japan were comparatively analyzed from the following perspectives: 1) key concepts of light, 2) structure of light units in the textbook, 3) materials, light sources, and optics used in light units. Consequently, there were differences between countries in their inclusion of the concept of light in the curriculum. In particular, the Korean curriculum studies the concept of refraction by a convex lens, whereas the concept of light, light source, and vision is not introduced. Furthermore, countries also differed in their structuring of units. The Korean curriculum was presented segmentally by concept rather than structured according to core ideas or perspectives, and the connection between concepts was unclear. In addition, there were differences between the countries in materials, light sources, and optical instruments to explain key concepts. On using light, the US curriculum provides a purpose and uses light to achieve it, and China and Korea understand the concept. It was divided into the method of using the material to deepen. Based on the results of this analysis, the implications for the elementary science curriculum in Korea were derived as follows. First, it is necessary to introduce concepts sequentially and organize them so that the connection between concepts is well expressed. Second, it is necessary to introduce light and light sources as the predominant concepts. Third, it is necessary to include the principle of seeing objects. Fourth, it is necessary to adjust the material and content level of the refraction concept included in the light and lens unit. Fifth, an integrated approach is required because light has a deep connection with various concepts included in the elementary science curriculum.

• Journal of Food Hygiene and Safety
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• v.37 no.4
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• pp.260-270
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• 2022

In this study, we tested for pesticide residues in 114 samples representing 20 different types of fruit circulating in Gyeonggido. A total of 341 pesticides were identified via a multi-residue method using GC-NPD, GC-ECD, GC-MSMS, and LC-MSMS. In whole fruit, pesticides were detected in 48 cases, with a concentration range of 0.0025-0.1663 mg/kg. In the peels, pesticides were detected in 85 cases, with a concentration range of 0.0026-4.7185 mg/kg and a higher average concentration than was found in whole fruit. In the pulp, pesticides were detected in 8 cases, with a concentration range of 0.0021-0.0993 mg/kg. In most of the peels, pesticides were detected below MRL. In the kiwi peel, deltamethrin (with an MRL of 0.05 mg/kg) was detected at 0.1020 mg/kg. Since MRLs are applied to whole fruit, these levels are not unsuitable for ingestion. However, washing is recommended before ingestion to promote healthier and safer inclusion of the peel in the diet. Continuous monitoring of the peel and pulp is indicated.

• Korean Journal of Health Education and Promotion
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• v.2 no.1
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• pp.31-61
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• 2000

Introduction. Despite the fact that half of premature deaths are caused by unhealthy lifestyles such as smoking tobacco, sedentary lifestyle, alcohol and drug abuse and poor nutrition, there are no theoretical models which accurately explain these health promotion related behaviors. This study tests a new model of health behavior called the Model of Health Promotion Behavior. This model draws on elements and frameworks suggested by the Health Belief Model, Social Cognitive Theory, the Theory of Planned Action and the Health Promotion Model. This model is intended as a general model of behavior but this first test of the model uses amount of exercise as the outcome behavior. Design. This study utilized a cross sectional mail-out, mail-back survey design to determine the elements within the model that best explained intentions to exercise and those that best explained amount of exercise. A follow-up questionnaire was mailed to all respondents to the first questionnaire about 10 months after the initial survey. A pretest was conducted to refine the questionnaire and a pilot study to test the protocols and assumptions used to calculate the required sample size. Sample. The sample was drawn from 2000 eligible participants at two blue collar (utility company and part of a hospital) and two white collar (bank and pharmaceutical) companies located in Southeastern Michigan. Both white collar site had employee fitness centers and all four sites offered health promotion programs. In the first survey, 982 responses were received (49.1％) after two mailings to non-respondents and one additional mailing to secure answers to missing data, with 845 usable cases for the analyzing current intentions and 918 usable cases for the explaining of amount of current exercise analysis. In the follow-up survey, questionnaires were mailed to the 982 employees who responded to the initial survey. After one follow-up mailing to non-respondents, and one mailing to secure answers to missing data, 697 (71.0％) responses were received, with 627 (63.8％) usable cases to predict intentions and 673 (68.5％) usable cases to predict amount of exercise. Measures. The questionnaire in the initial survey had 15 scales and 134 items; these scales measured each of the variables in the model. Thirteen of the scales were drawn from the literature, all had Cronbach's alpha scores above .74 and all but three had scores above .80. The questionnaire in the second mailing had only 10 items, and measured only outcome variables. Analysis. The analysis included calculation of scale scores, Cronbach's alpha, zero order correlations, and factor analysis, ordinary least square analysis, hierarchical tests of interaction terms and path analysis, and comparisons of results based on a random split of the data and splits based on gender and employer site. The power of the regression analysis was .99 at the .01 significance level for the model as a whole. Results. Self efficacy and Non-Health Benefits emerged as the most powerful predictors of Intentions to exercise, together explaining approximately 19％ of the variance in future Intentions. Intentions, and the interaction of Intentions with Barriers, with Support of Friends, and with Self Efficacy were the most consistent predictors of amount of future exercise, together explaining 38％ of the variance. With the inclusion of Prior Exercise History the model explained 52％ of the variance in amount of exercise 10 months later. There were very few differences in the variables that emerged as important predictors of intentions or exercise in the different employer sites or between males and females. Discussion. This new model is viable in predicting intentions to exercise and amount of exercise, both in absolute terms and when compared to existing models.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.1
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• pp.59-73
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• 2023

Objective : To examine changes in participation patterns of children with Autism Spectrum Disorder (ASD) in play activities during COVID-19 by reviewing relevant literature. Methods : This scoping review was conducted via five steps. we created a research question and searched for relevant literature published in English through CINAHL, PubMed, ERIC, MEDLINE, Google Scholar and Google search engine. After selecting the literature based on inclusion criteria, data were charted based on 10 items (i.e., author name, journal name, publication year, nation, authors' majors, research method, participant' age and gender as well as quantitative and qualitative results of study). The results were analyzed using descriptive numerical and thematic analyses. Results : After reviewing 437 articles and 152 websites, six articles were included. Theses articles were conducted by experts from various fields and countries. Five themes were highlighted in selected articles: COVID-19 resulted in (1) decreased time of outdoor play, (2) increased play time on screen, (3) increased time spent with family, (4) increased sensory difficulties, and (5) recommendations for services for children with disabilities and during COVID-19. Conclusion : This study suggests telerehabilitation programs about parental behavior strategies in order to solve difficulties in which children with ASD may experience when participating in play activities during disasters. Study results can be used as fundamental evidence to emphasize importance of play activities and to systematize role of occupational therapists and service guidelines for supporting play activities of children with disabilities in disasters.

• Korean Journal of School Psychology
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• v.15 no.3
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• pp.399-431
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• 2018

The purpose of this study was to summarize the empirical literature on implementation of positive behavior support (PBS) within a multi-tiered system of supports in American and Korean schools and to compare its key features and outcomes in an attempt to suggest future directions for development of a Korean school-wide PBS model and implementation manuals as well as directions for future research. Twenty-four American articles and 11 Korean articles (total 35 articles) that reported the outcomes of implementation of PBS at a tier 1 and/or tier 2, or tier 3 level and that met established inclusion criteria were analyzed using systematic procedures. Comparisons were made in the areas of key features and outcomes of PBS in addition to general methodology (e.g., participants, design, implementation duration, dependent measures) at each tier of PBS. The results indicated that positive outcomes for student behavior and other areas were reported across tiers in all American and Korean studies. At the tier 1 level, teaching expectations and rules were the primary focus of PBS in American and Korean schools. However, Korean schools focused on modifying the school and classroom environments and teaching social skills whereas American schools focused on teacher training on standardized interventions or curricular by experts and teacher support during implementation of PBS. At the tier 2 level, more American studies reported implementation of tier 2 interventions within school-wide PBS, and Check/In Check/Out (CICO) was found to be the most commonly used tier 2 intervention. The results also indicated that in comparison to Korean schools, American schools were more likely to use systematic screening tools or procedures to identify students who need tier 2 interventions and more likely to promote parental involvement with implementing interventions. At the tier 3 level, more Korean studies reported the outcomes of individualized interventions, but more American studies reported that designing individualized intervention plans based on comprehensive functional behavior assessment results and establishment of systematic screening systems were focused when implementing individualized interventions. Furthermore, few Korean studies reported the assessment of procedural integrity, social validity, and contextual fit in implementing PBS across tiers, indicating the need for development of valid instruments that could be used in assessing these areas. Based on these results, limitations of the study and suggestions for future research are discussed.

• Journal of Korean Elementary Science Education
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• v.42 no.4
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• pp.523-537
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• 2023

This study encompassed the responses of 284 elementary school teachers, focusing on their teaching experiences, readiness, and needs for science education concerning the risk posed by science and technology. The key findings are summarized as follows. First, a significant portion of teachers lacked prior experience in addressing risks associated with science and technology within their science education practices. Second, a greater number of teachers were aware of the inclusion of risk-related content in the 2022 revised science curriculum's achievement standards than those who were not. Third, in terms of teachers' understanding of risk perception, risk assessment, and risk management, they demonstrated a relatively high level of understanding of risk perception but a lower level of understanding of risk assessment. Fourth, most teachers had not undergone any formal education or training related to risk. Fifth, among the 10 objectives of risk education, teachers displayed the highest competence in teaching "information use" and "action skills," while their lowest competence was observed in "interpreting probabilities" and "evaluating risk assessment." Sixth, a majority of teachers believe that it is important to teach about the risks posed by science and technology in school science classes, with "action skills," "information use," and "decision-making skills" being considered the most important and "action skills," "information use," and "influence of mass media" being regarded as the most urgent. However, teachers anticipated difficulties in addressing risk in school science classes, including a lack of relevant educational materials, a lack of understanding of teaching theories related to risk education, and the relationship between science curriculum content and achievement standards. Seventh, as a result of calculating the educational needs for each of the 10 goals of risk education, "influence of risk perception," "decision-making skills," "action skills," and "evaluate risk assessment" were the priority needs of elementary school teachers.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Medicine and Life Science
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• v.21 no.2
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• pp.40-48
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• 2024

Understanding the effectiveness of statin treatment is essential for developing tailored stroke prevention strategies. We aimed to evaluate the efficacy of statin treatment in preventing recurrent stroke among patients with various ischemic stroke subtypes. Using data from the Clinical Research Collaboration for Stroke-Korea-National Institute for Health (CRCS-K-NIH) registry, we included patients with acute ischemic stroke admitted between January 2011 and July 2020. To evaluate the differential effects of statin treatment based on the ischemic stroke subtype, we analyzed patients with large artery atherosclerosis (LAA), cardio-embolism (CE), and small vessel occlusion (SVO). The primary outcomes were recurrent ischemic stroke and recurrent stroke events. The hazard ratio for outcomes between statin users and nonusers was compared using a Cox proportional hazards model adjusted for covariates. A total of 46,630 patients who met the inclusion criteria were analyzed. Statins were prescribed to 92%, 93%, and 78% of patients with LAA, SVO, and CE subtypes, respectively. The hazards of recurrent ischemic stroke and recurrent stroke in statin users were reduced to 0.79 (95% confidence interval [CI], 0.63-0.99) and 0.77 (95% CI, 0.62-0.95) in the LAA subtype and 0.63 (95% CI, 0.52-0.76) and 0.63 (95% CI, 0.53-0.75) in CE subtype compared to nonusers. However, the hazards of these outcomes did not significantly decrease in the SVO subtype. The effectiveness of statin treatment in reducing the risk of recurrent stroke in patients with LAA and CE subtypes has been suggested. Nonetheless, no significant effect was observed in the SVO subtype, suggesting a differential effect of statins on different stroke subtypes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.129-152
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• 2024

In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.