• Asian Oncology Nursing
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• v.6 no.1
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• pp.15-26
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• 2006

Purpose: This study was to assess relationships among the uncertainty, medical staff's support, and anxiety perceived by family members with cancer patients while the family members were waiting for their patients undergoing surgery. Method: The data were collected from the family members of cancer patients who were undergoing surgery in D University Hospital at B city from February 1 to April 12, 2005. The used instruments were the State Anxiety Scale of Spielberger's(1975) STAI, Mishel's Uncertainty in Illness Scale (MUIS)(1981), and Relationship Questionnaires (Lee, 1978). The collected data was analyzed by using t-test, ANOVA, Pearson's coefficients, and stepwise multiple regression. Results: As the result, the most influential variable explaining anxiety of family members was uncertainty $({\ss}=0.37)$, followed by perceived illness state $({\ss}=-0.27)$. These two variables simultaneously explained 29.3% of the variance in anxiety. Conclusion: We suggest to develop a nursing intervention program to reduce the uncertainty through the medical staff's support and o test its effects.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.6
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• pp.39-46
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• 2019

In the 21st century, medical facility projects are required to operate appropriate digital technologies as the development of technology and the interests of various participants become more complex. In order for architects to successfully lead negotiations among various stakeholder groups, it is necessary to plan for effective communication through appropriate design reflecting their opinions and coordination of conflicts. For this purpose, building information modeling (BIM), which is a method of designing based on knowledge information related to medical facilities in the building database, can respond to change of order promptly and minimizes the occurrence of design errors can do. Recently, BIM technology and cloud computing technology in ICT have been combined and research on cloud BIM has been actively carried out. The use of cloud computing technology in BIM-based healthcare facility projects can effectively support decision making among project participants and has the advantage of sharing and collaborating on various forms of information generated during the design process, regardless of location and time. Therefore, the purpose of this study is to build of system that can support the design of medical facility using cloud computing technology in BIM.

• Anxiety and mood
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• v.16 no.2
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• pp.98-105
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• 2020

Objective : The purpose of this study was to investigate the prevalence of social anxiety disorder (SAD) and its association with psychosocial factors including self-esteem, ego-resiliency, and social support in a sample of medical students. Methods : A total of 405 medical students were included in this study. Subjects were asked to complete a self-reported questionnaire, measures of the Social Phobia Inventory (SPIN), the Rosenberg's Self-Esteem Scale (RSES), the Ego-Resiliency Scale (ERS), and the Duke-UNC Functional Social Support Questionnaire (DUFSS). The SAD and non-SAD group were defined using the SPIN score of 25 as a cut-off. The multiple regression analyses were performed to examine the association of self-esteem, ego-resiliency, and social support with SAD symptoms. Results : A total of 79 subjects (19.5%) were identified with SAD. The total RSES score, ERS score, and DUFSS score were significantly lower in the SAD group than the non-SAD group. The total SPIN score negatively correlated with the total RSES score (r=-0.481, p<0.001), the ERS score (r=-0.417, p<0.001), and the DUFSS score (r=-0.406, p<0.001). In the multiple regression, SAD symptoms were associated with self-esteem (β=-0.549, p<0.001), ego-resiliency (β=-0.395, p<0.001), and social support (β=-0.346, p<0.001). Conclusion : This study revealed the prevalence of SAD and its negative association with self-esteem, ego-resiliency, and social support among medical students. Our findings indicate that improving self-esteem and ego-resiliency as well as perceived social support may contribute to the management of SAD symptoms among medical students.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.37-45
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• 2013

In this paper proposes the latest network-assisted online telemedicine service to coincide with the point being discussed for health care providers to match patients, patients with personalized medical service support system. In order to design the system, to understand the requirements of the patient personalized medical support service system, the data were normalized and were designed architecture client server structure. Further, in order to implement the system that was designed to define the structure of server and client, ontology repository, we implement the system. In this paper, as a result of the test by creating a scenario and prerequisites for testing patient personalized medical service support system that is design and implementation, selecting a patient's condition, department of symptoms by the selected but it was confirmed that the inference is, inference medical institutions that fits department inferred one following upon the items medical patient has the required.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.35-40
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• 2022

In this paper, we propose a method of constructing clinical knowledge with clinical concept relations and predicting diseases based on a deep learning model to support clinical decision-making. Clinical terms in UMLS(Unified Medical Language System) and cancer-related medical knowledge are classified into five categories. Medical related documents in Wikipedia are extracted using the classified clinical terms. Clinical concept relations are established by matching the extracted medical related documents with the extracted clinical terms. After deep learning using clinical knowledge, a disease is predicted based on medical terms expressed in a query. Thereafter, medical terms related to the predicted disease are selected as an extended query for clinical document retrieval. To validate our method, we have experimented on TREC Clinical Decision Support (CDS) and TREC Precision Medicine (PM) test collections.

• Korean Journal of Adult Nursing
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• v.12 no.4
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• pp.533-545
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• 2000

The purpose of this study was to identify the effect of social support revealed in the time duration of sick role behavior compliance on the patients with hypertension using Quasiexperimental research design. Data collection was made through the interview survey technique from the hypertensive patients who received social support intervention (experimental group, n=41) and from those who were not exposed to the intervention(control group, n= 34). The subjects were registered in the cardiovascular outpatient clinic at the Chonnam National University Hospital from June 3, 1996 to November 30, 1997. $\chi^2$-test or t- test, Repeated measures ANOVA were utilized in the data analysis. The results were as follows: 1. The effect of social support intervention on sick role behavior compliance was significant in 1 month(F=69.17, p=.000), 6 months (F=11.51, p=.001), and 12 months(F=.07, p=.789) and between two groups(1 month; F=153.70, p=.000, 6 months; F=13.94, p=.000, 12 months; F=6.72, p= .011). 2. The effect of social support intervention on blood pressure was not significant through all the periods of time (F=1.21, p=.274) between the two groups(F=.12, p=.732). In conclusion, it was showed that social support had an effect on sick role behavior compliance and the effect of social support continued for twelve months(F= 10.03, p=.002) However, the score of compliance tends to decrease after 6 months of intervention. Therefore, this study indicated that social support re-intervention would be needed between six and twelve months.

• Health Policy and Management
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• v.33 no.2
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• pp.166-172
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• 2023

Background: To improve the support low-income individuals' medical expenses, it is necessary to think about ways to enhance the Catastrophic Health Expenditure Support Program. This study proposes expanding support criteria and changing the income standard. Methods: This study conducted simulations using national data from the National Health Insurance Service. Simulations performed for people who have used health services (n=172,764) in 2022 to confirm the Catastrophic Health Expenditure Support Program's size based on changes to the subject selection criteria. Results: As a result of the simulation with expanded criteria, the expected budget was estimated to increase between Korean won (KRW) 13.2 (11.5%) and 138.6 billion (37.4%), and the number of recipients increased between 41,979 (48.9%) and 150,317 (76.1%). The results of the simulation for the change in income criteria (applied to health insurance levels below the 50th percentile) estimated the expected budget to increase between KRW -8.9 (-7.8%) and 55.6 billion (15.0%) and the number of recipients to increase between -8,704 (-10.1%) and 41,693 (21.1%) compared to the current standard. Conclusion: The 2023 Catastrophic Health Expenditure Support Program's criteria were expanded as per the 20th Presidential Office's national agenda to alleviate the burden of medical expenses on the low-income class. In addition, The Catastrophic Health Expenditure Support Program needs to be integrated with other medical expense support policies in the mid- to long-term, and a foundation must be prepared to ensure the consistency of each system.

• The Journal of Korean Physical Therapy
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• v.29 no.2
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• pp.62-68
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• 2017

Purpose: This study was conducted to identify the impacts of stroke patients' general and disease-related properties on depression and family support. Methods: Subjects consisted of 79 persons who were diagnosed with cerebral hemorrhage and cerebral infarction and met the criteria for selection. The Korean version of Beck depression inventory (BDI) and a revision of the family support developed by Cobb were used. Frequency analysis of the subjects' general and medical history properties was conducted, and one way ANOVA was utilized to evaluate the degree of depression and family support with respect to the properties. Pearson's correlation coefficient was conducted to investigate the degree of depression and family support. Results: Participants showed no significant difference in depression based on the subjects' general and disease-related properties (p>0.05), although there were significant differences in family support based on marital status, hobbies and the medical expenses payers (p<0.05). The correlation between family support and depression was r=-0.491 (p<0.01). Conclusion: Through the results of this study, it was found that general and disease-related properties would not have any impact on depression while they would affect family support.

• Korean Journal of Artificial Intelligence
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• v.10 no.2
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• pp.13-18
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• 2022

The role of artificial medical intelligence through medical big data has been focused on data-based medical device business and medical service technology development in the field of diagnostic examination of the patient's current condition, clinical decision support, and patient monitoring and management. Recently, with the 4th Industrial Revolution, the medical field changed the medical treatment paradigm from the method of treatment based on the knowledge and experience of doctors in the past to the form of receiving the help of high-precision medical intelligence based on medical data. In addition, due to the spread of non-face-to-face treatment due to the COVID-19 pandemic, it is expected that the era of telemedicine, in which patients will be treated by doctors at home rather than hospitals, will soon come. It can be said that artificial medical intelligence plays a big role at the center of this paradigm shift in prevention-centered treatment rather than treatment. Based on big data, this paper analyzes the current status of artificial intelligence technology for chronic disease patients, market trends, and domestic and foreign company trends to predict the expected effect and future development direction of artificial intelligence technology for chronic disease patients. In addition, it is intended to present the necessity of developing digital therapeutics that can provide various medical services to chronically ill patients and serve as medical support to clinicians.

• Environmental Analysis Health and Toxicology
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• v.31
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• pp.19.1-19.7
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• 2016

A large portion of the Korean population has been exposed to toxic humidifier disinfectants (HDs), and considering that the majority of the victims are infants, the magnitude of the damage is expected to be considerably larger than what has currently been revealed. The current victims are voicing problems caused by various diseases, including but not limited to lung, upper respiratory tract, cardiovascular, kidney, musculoskeletal, eye, and skin diseases, etc. However, there has been difficulty in gaining validation for these health problems and identifying causal relationships due to lack of evidence proving that toxic HD is the specific causes of extrapulmonary diseases such as allergic rhinitis. Furthermore, the victims and bereaved families of the HD case have not received any support for psychological distress such as post-traumatic stress disorder, depression, feelings of injustice, and anger caused by the trauma. In addition, because the underlying mechanisms of the toxic materials within the HDs such as polyhexamethylene guanidine phosphate, poly(oxyalkylene guanidine) hydrochloride, chloromethylisothiazolinone /methylisothiazolinone have yet to be determined, the demand for information regarding the HD issue is growing. The victims of the HD cases require support that goes beyond financial aid for medical costs and living expenses. There is a desperate need for government-led integrated support centers that provide individualized support through health screenings; in other words, we need an integrated facility that provides the appropriate social support to allow the victims to recover their physical and mental health, so as to well prepare them to return to a normal life. The implementation of such a plan requires not only the close cooperation between those departments already directly involved such as the Ministry of Environment and the Ministry of Health and Welfare, but also active support on a national scale from pan-governmental consultative bodies.