• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5593-5596
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• 2014

Background: The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. Materials and Methods: The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Results: Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Conclusions: Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

• Safety and Health at Work
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• v.1 no.1
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• pp.37-42
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• 2010

Over years it has been increasingly concerned with how upper extremity musculoskeletal disorders (UEMSDs) are attributed to psychosocial job stressors. A review study was conducted to examine associations between UEMSDs and psychosocial work factors, and to recommend what to consider for the associations. For studies in which the job demand-control-support (DCS) model or its variables were specifically employed, published papers were selected and reviewed. A number of studies have reported relationships between UEMSDs symptoms and psychosocial exposure variables. For example, the findings are: higher numbness in the upper extremity was significantly attributed to by less decision latitude at work; work demands were significantly associated with neck and shoulder symptoms while control over time was associated with neck symptoms; and the combination of high psychosocial demands and low decision latitude was a significant predictor for shoulder and neck pain in a female working population. Sources of bias, such as interaction or study design, were discussed. UEMSDs were shown to be associated with psychosocial work factors in various studies where the job DCS model was addressed. Nonetheless, this review suggests that further studies should be conducted to much more clarify the association between UEMSDs and psychosocial factors.

• Health Policy and Management
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• v.30 no.3
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• pp.286-300
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• 2020

In 2019, the Seoul metropolitan government established its own 'Seoul-type paid sick leave project'. Although the central government had to introduce such a system, which is also called sickness benefits, it was not implemented. In order to understand the process by which the Seoul government has implemented such a policy, this study used Kingdon's multiple streams framework. As a result, in the problem stream, it was found that the economic burden of sickness has been considered only in terms of medical expenses in the past of Korea. Then Songpa's three women and Middle East respiratory syndrome incidents raised awareness of the necessity of the sickness benefit system in 2014 and 2015. In the political stream, several social affairs such as national health insurance huge surpluses and the 2017 presidential election opened policy window. At that time, Seoul Mayor actively promoted sickness benefits as a policy entrepreneur. In the policy stream, the sickness benefit system has gained new attention through political events. To summary, these three streams flowed separately and then they assembled around huge political affairs. As a result, it was confirmed that Kingdon's model is the most effective theory than any other models in analyzing the health care policy decision process in Korea.

• The Korean Journal of Applied Statistics
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• v.27 no.5
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• pp.667-679
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• 2014

National Health Insurance Service(NHIS) provide care-plans for beneficiaries in the long-term care insurance(LTCI) systems that help them use LTC services appropriately. The care-plan includes recommendations for the most adequate type of care (gold standard) for beneficiaries. This study develops a decision-support system to determine the appropriate type of care plan. To develop a model, we used a data set that well-trained assessors in the NHIS investigated as a gold standard for beneficiaries: nursing home care, home-visit care, home-visit bathing, home-visit nursing, or day and night care. The decision-support system was established through a decision-tree model, because it may be easy to explain the algorithm of a decision-support system to working groups and policy makers. Our results might be useful in evidence-based care planning in an LTCI system and contribute to the efficient use of LTC services.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.23-32
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• 2011

U-health services have been progressed as treatment and management for specific diseases and prevention services for providing the behavior management to customers according to the increase in chronic patients. The conventional U-health services provide required services and bio-information monitoring only through remote diagnoses and counsels and that represent limitations in preventing and managing metabolic syndrome patients like chronic patients. Thus, in this study a multi platform based U-health service model for managing the health of chronic patients is proposed. The multi-platform based U-health service model can provide continuous health information, diet, and exercise services regardless of the location of customers through PCs and smart phones. In addition, it is able to provide prescription services to doctors and nurses using a CDS (Clinical Decision Support) module based on clinical information. Doctors can identify the life pattern of patients through a behavior modification program and provide customized services to patients. The U-health service model provides effective services in multi-platform environments to customers and that will improve the health of chronic patients.

• Environmental Engineering Research
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• v.23 no.4
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• pp.430-441
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• 2018

The adverse health impact of air pollution is becoming more serious. The purpose of this study is twofold: One is to analyze the effect of air pollution and temperatures on human health by analyzing the number of deaths from cardiovascular disease in Seoul, Korea; the other is to determine what impact the location of a monitoring site has on the results of a health study. For this latter purpose, air pollution and temperature monitors are sited at three locations termed green, public, and residential. Then, a decision tree model is used to analyze factors linked with deaths occurring at each monitoring site. The results show that the environmental temperatures before death and the $PM_{2.5}$ concentrations on the day of death are highly linked with the number of deaths regardless of the monitoring location. However, results are most accurate with residential data. The results of this study can be used as base data for a similar analysis and ultimately, as a guide to minimize the health impact of air pollution.

• Journal of Environmental Impact Assessment
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• v.6 no.1
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• pp.93-103
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• 1997

LHR(Landfill Site Hazard Ranking Model) was developed for ranking the relative hazard of landfill sites by using the method of value-structured approach. LHR consists of combining a multiattribute decision-making method with a Qualitative risk assessment approach. A pairwise com parisian method was applied to determine weights of landfill site factors related. To determine the hazard of landfill site, hydrogeological factors, waste characteristics factors and receptors factors were evaluated by LHR. LHR can help decision-makers prioritization of remediation of landfill sites through the relatively convenient and concise evaluation method of landfill site features related. LHR focuses mainly on pathways of groundwater and surfacewater for evaluating landfill hazard to receptors including humans. To validiate the applicability of LHR, Nanjido Landfill site, Metropolitan Landfill site, and Hwasung Landfill site were evaluated.

• Journal of Korean Biological Nursing Science
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• v.26 no.1
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• pp.26-40
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• 2024

Purpose: The aim of this study was to predict the subgroups vulnerable to poorer health-related quality of life (HRQoL) according to gender in older adults. Methods: Data from 5,553 Koreans aged 65 or older were extracted from the Korea National Health and Nutrition Examination Survey. HRQoL was assessed using the EQ-5D tool. Complex sample analysis and decision-tree analysis were conducted using SPSS for Windows version 27.0. Results: The mean scores of the EQ-5D index were 0.93 ± 0.00 in men and 0.88 ± 0.00 in women. In men, poorer HRQoL groups were identified with seven different pathways, which were categorized based on participants' characteristics, such as restriction of activity, perceived health status, muscle exercise, age, relative hand grip strength, suicidal ideation, the number of chronic diseases, body mass index, and income status. Restriction of activity was the most significant predictor of poorer HRQoL in elderly men. In women, the poorer HRQoL groups were identified with nine different pathways, which were categorized based on participants' characteristics, such as perceived health status, restriction of activity, age, education, unmet medical service needs, anemia, body mass index, relative hand grip, and aerobic exercise. Perceived health status was the most significant predictor of poorer HRQoL in elderly women. Conclusion: This study presents a predictive model of HRQoL in older adults according to gender and can be used to detect individuals at risk of poorer HRQoL.

• Journal of Korean Biological Nursing Science
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• v.20 no.2
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• pp.103-113
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• 2018

Purpose: This study was performed to assess problems associated with sleep (short and long sleep duration) and to identify risky subgroups with sleep problems among adult cancer survivors. The study is based on the Korea National Health and Nutrition Examination Survey (KNHANES VI and VII) from 2013 to 2016. Methods: The sociodemographic and clinical data of 504 Korean cancer survivors aged 20-64 years was extracted from the KNHANES VI and VII database. Descriptive statistics for complex samples was used, and decision-tree analyses were performed using the SPSS WIN 24.0 program. Results: The mean age for survivors was approximately 51 years. The mean sleep duration was 6.97 hours; 36.2% of participants had short (< 7 hours) and 9.9% had long (> 8 hours) sleep duration. From the decision-trees analyses, the characteristics of the adult cancer survivors related to sleep problems were presented with six different pathways. Sleep problems were analyzed according to the survivors' sociodemographic information (age, education, living status, and occupation), clinical characteristics (body mass index, hypercholesterolemia, and anemia) and health-related quality of life (HRQoL). The HRQoL (${\leq}0.5$ or > 0.5 cutoff point) was a significant predictor of the participants' sleep problems because all six pathways were started from this predictor in the model. Conclusion: Health care professionals could use the decision-tree model for screening adult cancer survivors with sleep problems in clinical or community settings. Nursing interventions considering these specific individual characteristics and HRQoL level should be developed to have adequate sleep duration for Korean adult cancer survivors.

• Health Policy and Management
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• v.16 no.1
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• pp.54-72
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• 2006

This study was conducted as the primary work to develop a customer relationship management (CRM) system to improve the performance of health screening programs. The specific aims of the study was to identify and classify the characteristics of the people who did not receive their health screening using decision trees and to propose management strategies according to their characteristics identified. The data on a total of 5,102,761 subjects of health screening provided by the National Health Insurance Program in the year of 2002 were used. The target variable was whether they underwent their health screening. The input variables included a total of 27. The SAS 9.1 version was used for data preprocessing and statistical analyses. SAS Enterprise Miner was used to develop the decision trees model. The decision trees identified the factors greatly affecting the health screening. In the non-disease group, the highest rate of non-examinees was characterized by: no experience of receiving a health screen, household's age, non-insured episode for the last one year, and patients' age. In the disease group, the one showing the highest rate of non-examinees was characterized by: no experience of receiving a health screening, no experience of going to public health center or midwife clinic for the last one year, and examinees' age. Developing CRM systems for health screening management taking into account the individual characteristics would be considerably helpful to increase the rate of receiving health screening.