• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.59-67
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• 2020

With the development of wearable devices, individuals' health status can be checked in real time and risks can be predicted. For example, an application has been developed to detect an emergency situation of a patient with heart disease and contact a guardian through analysis of health data such as heart rate and electrocardiogram. However, health data is seriously damaging when it is leaked as it relates to life. Therefore, a method to protect personal information is essential in collecting health data, and this study proposes a method of collecting data while protecting the personal information of the data owner through a LDP(Local Differential Privacy). The previous study introduced a technique of transmitting feature point data rather than all data to a data collector as an algorithm for searching for fixed k feature points. Next, this study will explain how to improve the performance by up to 75% using an algorithm that finds the optimal number of feature points k.

• Korean Journal of Health Education and Promotion
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• v.31 no.5
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• pp.1-11
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• 2014

Objectives: The purpose of this study was to examine health information seeking behavior of people with cancer in terms of information seeking or avoiding behavior and the differences of the two groups in demographic and disease variables. Methods: Data were collected from October 21 to December 5 in 2013 from out-patient clinics of a university affiliated hospital in Suwon, Korea. One hundred (100) patients with cancer were participated in this study. Health Information National Trends Survey Questionnaires (National Cancer Institute, 2007) was used. Results: Three quarters (n=77) of the participants were in health information seeking group while 23% were in health information avoiding group. Participants who were female, higher education were more likely to seek health information than their counter parts. Among participants, a considerable number of cancer patients intentionally avoided information due to either the lack of accessibility of information source or the lack of credibility of information from the sources. Conclusion: Significant differences in gender and educational level were found in the two groups. Different approaches for both groups were necessary to increase information seeking behavior. And barriers of the information avoiding group should be considered in designing interventions to fill the gap between seekers and avoiders.

• 한국노년학
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• v.29 no.2
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• pp.529-546
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• 2009

Depression in old age not only is prevalent but also causes a considerable amount of burden in physical, psychosocial, and economic terms. Intervention, however, is often delayed due to the understanding that considers depressive symptoms as a normal process of aging or signs of physical illnesses. Since the recognition of symptoms often initiate one's help seeking process, a correct identification of symptoms can contribute to early detection and intervention to depression in oneself as well as in others. This study interviewed 104 older adults living in an urban area, and explored their ability to correctly identify depressive symptoms and factors related to identification. The study results show that respondents who were able to correctly identify symptoms of depression were only 14%, and the rest defined the symptoms as social, economic, and other psychological issues. Of the factors in the logistic regression model, age being 75 and over and mass media as source of mental health information affected negatively their ability to correctly identify symptoms; mental health education programs affected positively their ability. Based on these results, it is suggested that such strategies as employing a face-to-face provision of concrete information and counseling can be more effective than delivering information via large-scale lectures. Additionally, a future research deems necessary to conduct an in-depth examination of mental health/illness-related contents on mass media.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.64-66
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• 2006

본 논문에서는 실내 거주자의 위치를 기반으로 분산객체그룹 프레임워크의 구성요소인 모바일 프락시(Mobile Proxy)를 이용하여 상황정보 지원 시스템 구축에 대해 기술하였다. 본 시스템은 가정 내 거주자의 이동을 고려하여 건강상태 및 상황정보를 제공하는 헬스케어 상황정보 서비스를 수행한다. 이를 위해 분산객체그룹 프레임워크의 그룹관리 서비스는 가정 내 위치 탐색 및 추적 센서와 서비스 수행객체 및 다양한 출력 장치들을 거실이나 침실과 같은 분할된 영역으로 그룹화하고, 모바일 프락시는 서비스를 요청하는 이동 사용자의 위치를 기반으로 헬스케어 서비스 수행의 연속성을 지원한다. 그리고 상황정보에 따라 헬스케어 맞춤형 정보 서비스가 지원되도록 했다. 상황정보 지원 시스템이 제공하는 서비스는 이동성을 고려한 멀티미디어 서비스와 시간 및 위치에 따라 처방 주의 정보 및 스케줄 알림 서비스로 구현했으며, 상황정보 지원 헬스케어 서비스의 수행 결과를 원격 데스크 탑과 상황정보 서비스 인터페이스를 통해 확인했다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.177-187
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• 2013

Association rule mining is a popular data mining technique with a wide range of application domains, and aims to extract the cause-and-effect relations between the discrete items included in transaction data. However, analysts sometimes have trouble in interpreting and using the plethora of association rules extracted from a large amount of data. To address this problem, this paper aims to propose a novel approach called HTM for extracting the interesting association rules from given transaction data. The HTM approach consists of three main steps, hierarchical clustering, table-view, and mosaic plot, and each step provides the analysts with appropriate visual representation. For illustration, we applied our approach for analyzing the mass health examination data, and the result of this experiment reveals that the HTM approach help the analysts to find the interesting association rules in more effective way.

• Korean Journal of Community Nutrition
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• v.19 no.5
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• pp.436-447
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• 2014

Objectives: The purpose of this study was to investigate the health food consumption patterns and their relationship to dietary behavior in middle-aged women (45-60 years). Methods: The exclusive face-to-face interviews by well-trained interviewers guaranteed a scientific data collection and the quality of survey data of 731 women. Subjects were divided into two groups according to the intake of the health foods, 'Intake' group (${\geq}3.2$, n = 488) and 'Non-intake' group (n = 243). Data were analyzed using the SPSS 20.0 program. Results: The average age of the subjects was 49.8 years and 66.8% of subjects were taking the health foods. Vitamins and minerals were consumed by the subjects. The major reason for intake of health foods was that they provide nutrient supplements may prevent diseases. More than 70% of the subjects reported checking nutrition information, ingredients, recommended daily intakes, instructions, when they bought the health foods. The average dietary life score of the intake group was significantly higher (p < 0.05) than that of the non-intake group. In analysis of exploratory factors of dietary life, the intake group showed significantly higher score (p < 0.001) in 'moderation of food intake' among the 4 exploratory factors. Conclusions: These results showed that women who took health foods had better dietary behavior than others suggesting a positive relation between the dietary behavior and the health food consumption. Therefore, we suggest that developing guidelines and then educating women about those guidelines could improve the ability of choosing health foods appropriately for their own benefit.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.3
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• pp.28-36
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• 1999

Environmental problems arise from the rapidly developing personal computers and are gradually becoming a significant part of problems. Computer industry are usually viewed as relatively clean. However, discarded personal computer and related equipment which are piling up at warehouse, or going to landfills has on the negative effects of hazardous substance on health and the ecosystem are growing problems which did not trouble society a few years ago. This paper will estimate the quantity of the obsolete personal computer in 1999 and suggest the alternatives of its disposition.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.31-48
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• 2021

The purpose of this study was to provide an understanding of the trajectories of multidimensional health among older adults, including depression, chronic diseases, and cognitive function. Data were drawn from the 1-6 waves of the Korean Longitudinal Study of Ageing(KLoSA), and a sample of 2,059 respondents aged 65 and older at baseline was used for the analyses. Latent growth curve models and growth mixture models were used to explore the changes in depression, chronic diseases, cognitive function, and heterogeneous trajectories among them. One-way ANOVAs with Scheffé post-hoc analysis and chi-square tests were used to find differences in sociodemographic characteristics, health behaviors, and life satisfaction across the latent trajectory classes. Latent growth curve models revealed that depressive symptoms and the number of chronic diseases increased over time, while cognitive function showed gradual decreases. Three heterogeneous patterns of multidimensional health trajectories were identified: normal aging, increase in chronic diseases, and chronic deterioration. Significant differences were observed in sociodemographic characteristics, health behaviors, and life satisfaction across the three latent classes. In particular, low educational attainment, household income, and life satisfaction were associated with the chronic deterioration class. Based on the findings, we discussed suggestions for health promotion education targeting older adults. This study also emphasizes the importance of home economics education in promoting health literacy across the life course.

• 한국노년학
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• v.40 no.4
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• pp.729-746
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• 2020

For the development and better use of information and communication technology(ICT) for promoting health and quality of life in older people, it is important to understand personal factors associated with ICT use. The aims of this study were to describe the pattern of ICT use according to health characteristics of elderly and to investigate significant factors related to ICT use among three age groups. The data of 2017 National Survey of Older Koreans was used for analysis and 10,058 of older adults aged 65 and over were included for study participants. As results, first, the young old(65~74) used more functions of ICT than the middle-old(75~84) and the old-old(85 and over). Second, ICT was more used among older people with good conditions in chronic disease, subjective health, cognition, depression, vision, hearing, walking and IADL. Third, higher prevalence of ICT use was significantly associated with age, education, household income, subjective health, depression, cognitive function, vision limitation and walking limitation. Fourth, factors influencing the use of ICT were a little different among three age groups. For the young-old(65~74), subjective health, depression, cognitive decline, walking limitation, and IADL disability were significant factors affecting on ICT use. For the middle-old(75-84), subjective health, depression, cognitive decline, vision, hearing, and walking limitation were related with their ICT use. For the old-old(85 and over), only cognitive function and depression were associated with their ICT use. Based on these results, this study suggested the need to consider multiple health conditions for developing and using ICT for older adults.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.1
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• pp.29-41
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• 2024

Objectives: This study used an efficient data mining algorithm to explore association rules between the lifestyle risk behaviors and multimorbidity (having more than one chronic disease) in Korean adults. Methods: We used data from the 8th Korean National Health and Nutrition Examination Survey(2019-2020) for 7,609 adults aged ≥19 years. This study was undertaken where 6 lifestyle risk behaviors and 11 morbidities were analyzed using R and Rstudio for the ARM. Results: Among 117 association rules, combinations of hypertension, dyslipidemia and diabetes, hypertension were important role in inadequate sleep, physical inactivity and inadequate weight. Conclusion: The findings of this study are significant because they demonstrate the importance of lifestyle risk factors and the role of multiple chronic diseases using big data analytics such as association rule mining. We recommend developing selective and focused health education programs, such as exercise programs to address physical inactivity, dietary interventions to address inadequate weight, and mental health education programs to address inadequate sleep.