• Healthcare Informatics Research
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• v.24 no.4
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• pp.359-370
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• 2018

Objectives: We assessed the public acceptance of a health information exchange (HIE) and examined factors that influenced the acceptance and associations among constructs of the Technology Acceptance Model (TAM). Methods: We collected data from a survey of 1,000 individuals in Korea, which was administered through a structured questionnaire. We assessed the validity and reliability of the survey instrument with exploratory factor analysis and Cronbach's alpha coefficients. We computed descriptive statistics to assess the acceptance and performed regression analyses with a structural equation model to estimate the magnitude and significance of influences among constructs of TAM. Results: Eighty-seven percent of the respondents were willing to use the technology, and the average level of agreement with the need for the technology was 4.16 on a 5-point Likert scale. The perception of ease of use of the technology significantly influenced perceptions of usefulness and attitudes about the need for HIE. Perceptions of usefulness influenced attitude and behavioral intention to use HIE, and attitude influenced intention. Age showed a wide range of influences throughout the model, and experience with offline-based information exchange and health status also showed noteworthy influences. Conclusions: The public acceptance of HIE was high, and influences posited by TAM were mostly confirmed by the study results. The study findings indicated a need for an education and communication strategy tailored by population age, health status, and prior experience with offline-based exchange to gain public buy-in for a successful introduction of the technology.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.117-125
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• 2019

This study aims to evaluate of validity and reliability of the job performance tool already developed for the elementary school health teachers. 305 health teachers responded to the questionnaire composed of 50 items. The validity and reliability of the tool were verified by confirmatory factor analysis. That were composed of 8 sub-categories and had 4 factors. The importance, frequency, and difficulty of the four factors were classified according to the questionnaire criteria, but the importance of health promotion is classified as one new item factor. The statistical significance of the fit of the model was 3.664 (df = 246, p<0.001), RMSEA=0.09, NFI=0.85 and CFI=0.88. The internal consistency of the subscales was Cronbach's ${\alpha}$ of 0.88 to 0.96. The internal consistency of the subscales, Cronbach's ${\alpha}$ was 0.88~0.96. This study shows that the analysis tool for primary school health teacher is valid and reliable as a measurement tool.

• Quality Improvement in Health Care
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• v.24 no.2
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• pp.41-61
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• 2018

Purpose: Falls are one of the most frequent health events in medical institutions, however, they can be predicted and prevented. The Quality Improvement Nurse Society clinical practice guideline Steering Committee developed the Clinical Practice Guideline for the assessment and prevention of falls in adult people. The purpose of this study was to assess the risk factors for falls in adults aged 19 years and older, to present an evidence for preventing falls, formulate a recommendations, and indicators for applying the recommendations. Methods: This clinical practice guideline was developed using a 23-step adaptation method according to the Handbook for clinical practice guideline developer (version 1.0) by National Evidence-based Healthcare Collaborating Agency. Evidence levels and recommendation ratings were established in accordance to SIGN 2011 (The Scottish Intercollegiate Guidelines Network). Results: The final 15 recommendations from four domains were derived from experts' advice; 1) assessment of risk factor for falls in adult 2) preventing falls and reducing the risks of falls or falls-related injury 3) management and reassessment after a person falls 4) leadership and culture. Conclusion: This clinical practice guideline can be used as a basis for evaluation and prevention of fall risk factors for adults, to formulate recommendations for fall risk assessment and fall prevention, and to present monitoring indicators for applying the recommendations.

• Research in Community and Public Health Nursing
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• v.31 no.spc
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• pp.525-533
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• 2020

Purpose: Workers in special employment relationship (WSERs) are workers in nonstandard employment arrangements who lack worker protection accorded in standard employment arrangements. This study aimed to describe self-rated health (SRH) and depressive symptoms (DS) among Korean WSERs in comparison to regular wage workers (RWW) and identify associations between working conditions and those outcomes. Methods: In this study, secondary data analysis using the 5th Korean Working Conditions Survey was used. The sample totaled 29,120, including 1,538 WSERs and 27,564 RWWs. Sociodemographic and work-related characteristics were employed as explanatory variables and SRH and DS as dependent variables. Using multiple logistic regression, the determinants of fair/poor SRH and DS were identified. Results: The prevalence rates for fair/poor SRH and DS in WSERs were 25.2% and 28.3%, respectively, and 20.7% and 25.0% in RWWs, respectively. Compared to RWWs, WSERs had 31% (aOR=1.31, 95% CI=1.14~1.49) and 20% (aOR=1.20, 95% CI=1.06~1.36) higher odds of SRH and DS, respectively. Some factors, such as a lack of rest guarantee and sickness presenteeism, had a larger influence in the WSER than in the RWW group. Conclusion: Compared to RWWs, WSERs reported having poorer working conditions and were more likely to report poor general and mental health. Therefore, in Korea, public health policymakers should consider measures to protect the working conditions and health of WSERs, a growing segment of the working population. The study produced new epidemiological evidence regarding the relationships between employment arrangements and health.

• Fisheries and Aquatic Sciences
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• v.25 no.6
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• pp.327-334
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• 2022

Marine resources have various biological activities and their constituents are more novel than those of land organisms. Several biologically active constituents have been found in marine organisms. Recently, many studies have reported that marine animals (MAs) can be used as functional ingredients in functional foods or nutraceutical due to their health benefits. However, no studies have extensively investigated the cosmeceutical activities of MAs extracts. Here, 70% ethanol extracts of 38 MAs were investigated for their activities of whitening and anti-aging properties for use as materials in novel cosmeceuticals. Anti-aging activities were determined by skin aging-related enzyme activities (anti-collagenase, anti-elastase, anti-hyaluronidase) and whitening activities (anti-tyrosinase, anti-3,4-dihydroxyl-L-phenylalanine [DOPA] oxidation) evaluated by colorimetric method. Among the 38 MAs, we found that Urechis unicinctus and Petrosia corticata extracts showed the strongest inhibitory effects against tyrosinase and DOPA oxidation, respectively. Our results additionally showed that Protankyra bidentata extract might provide a major source of anti-hyaluronidase and anti-elastase; meanwhile, anti-collagenase effects were similar in most MAs. Overall, these results suggest that extracts of marine animals have potential as a tyrosinase, collagenase, elastase, and hyaluronidase inhibitors. Taken together, MA resources could be considered as a novel cosmeceutical agent to be applied in cosmetic industry.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.303-311
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• 2022

The tremendous growth of the Internet of things is unbelievable. Many IoT devices have emerged on the market over the last decade. This has made our everyday life easier inside our homes. The technology used at home has changed significantly over the past several decades, leading to what is known today as the smart home. However, this growth has also brought new challenges to our home security and privacy. With the smart home becoming more mainstream, cybersecurity issues have become a fundamental concern. The smart home is an environment where heterogeneous devices and appliances are interconnected through the Internet of Things (IoT) to provide smart services to residents. These services include home climate control, energy management, video on demand, music on-demand, remote healthcare, remote control, and other similar services in a ubiquitous manner. Smart home devices can be controlled via the Internet using smartphones. However, connecting smart home appliances to wireless networks and the Internet makes individuals vulnerable to malicious attacks. Remote access within the same environment or over the Internet requires an effective access control mechanism. This paper intends to shed light on how smart home devices are working as well as the type of security and privacy threats of the smart home. It also illustrated the types of authentication methods that can be used with smart home devices. In addition, a comparison of Smart home IoT-based security protocols was presented along with a security countermeasure that can be used in a smart home environment. Finally, a few open problems were mentioned as future research directions for researchers.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Korean Journal of Community Nutrition
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• v.28 no.2
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• pp.95-103
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• 2023

Objectives: The budget gap in the health sector of local governments affects the supply of health services, which can cause the health gap. This study classified local governments according to their financial characteristics, such as local financial independence and health budget level. It analyzed the health behaviors and disease prevalence of local residents to examine the effect of local government financial investment on the health of local residents. Methods: To classify types according to the financial characteristics of local governments, financial independence and the health budget data for 17 local governments were collected from the local fiscal yearbook of the Ministry of Public Administration and Security. The prevalence of chronic diseases and healthy behavior was compared using the 16,333 data of adults between the ages of 30 and 65 years among the original data of the National Health and Nutrition Examination Survey (2016-2020). Results: Cluster analysis was used to classify local governments into five clusters according to the health financial capacity type. A comparison of the prevalence of local residents by cluster revealed a similar prevalence of hypertension, diabetes, and hypercholesterolemia. On the other hand, the obesity rate (P < 0.01), high-risk drinking rate (P < 0.01), aerobic physical activity rate (P < 0.001), and healthy eating practice rate (P < 0.001) were significantly different. In addition, an analysis of the odds ratio based on the Seoul area revealed a higher risk of health behavior of non-Seoul residents. Conclusions: It is necessary to review the universal health promotion project budget considering the degree of regional financial vulnerability from the viewpoint of health equity to narrow the health gap among regions.

• Korea Journal of Hospital Management
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• v.28 no.2
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• pp.32-43
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• 2023

Purposes: This research is conducted to identify main features and trends of mission, vision and core values in Korean tertiary general hospitals by using text-mining. Methodology: For the study, 45 mission, 112 vision and 190 core values are collected from 45 tertiary general hospitals' homepages in 2022 and use word frequency analysis and Leyword co-occurrence analysis. Findings: In the tertiary general hospitals' mission, there are high frequency words such as 'health', 'humanity', 'medical treatment', 'education', 'research', 'happiness', 'love', 'best', 'spirit', and mission mainly includes the content of contributing humanity's health and happiness with these words. In case of vision, high frequency words are 'hospital', 'medical treatment', 'research', 'lead', 'trust', 'centered', 'patient', 'best', 'future'. By using these words in vision, it represents the definition and characteristics of vision such as ideal organizations in the future, goals and targets. As a result of the Leyword co-occurrence analysis, vision includes the content of 'high-tech medical treatment', 'special care for patients', 'leading education and research', 'the highest trust with customer', 'creative talents training'. -astly, the high frequency word-pairs in core values are 'social distribution', 'innovation pursuit', 'cooperation and harmony', and it defines standards of behavior for organizations. Practical Implication: To correct the problems of vision, mission and core values from findings, firstly, it needs for Korean tertiary general hospitals to use the words that can explain organization's identity and differentiate others in their mission. Secondly, considering strengthening the role of hospitals in their community and the importance of members in organizations, it is necessary to establish vision with considering community and members to activate vision effectively. Thirdly, because there are no specific guidelines of establishing mission, vision and core values for healthcare organizations, this research concepts and results could be utilized when other organizations establish mission, vision and core values.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2073-2081
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• 2021

Deep learning-based applications have great potential to enhance the quality of medical services. The power of deep learning depends on open databases and innovation. Radiologists can act as important mediators between deep learning and medicine by simultaneously playing pioneering and gatekeeping roles. The application of deep learning technology in medicine is sometimes restricted by ethical or legal issues, including patient privacy and confidentiality, data ownership, and limitations in patient agreement. In this paper, we present an open platform, MI2RLNet, for sharing source code and various pre-trained weights for models to use in downstream tasks, including education, application, and transfer learning, to encourage deep learning research in radiology. In addition, we describe how to use this open platform in the GitHub environment. Our source code and models may contribute to further deep learning research in radiology, which may facilitate applications in medicine and healthcare, especially in medical imaging, in the near future. All code is available at https://github.com/mi2rl/MI2RLNet.