The Journal of Korean Academic Society of Nursing Education
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v.29
no.3
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pp.247-262
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2023
Purpose: This study aimed to identify the types of perception toward non-face-to-face clinical practice and to characterize the types of students who experienced online clinical practice during the coronavirus disease 2019 (COVID-19) pandemic. Methods: Q-methodology was used in this study, and 270 Q populations were formed based on in-depth interviews with 10 nursing students who had experienced non-face-to-face clinical practice, as well as related literature. Interviews were performed from August 1 to 31, 2022. A total of 42 Q samples were extracted, and Q sorting was performed on 33 nursing students who had experienced non-face-to-face clinical practice. A Q factor analysis was performed using the PC-QUANL program. Results: The nursing students' perceptions of non-face-to-face clinical practice were classified into the following five types: "future professional competency-focused type," "realistic convenience priority type," "task burden awareness type," "negative critic type," and "limited experience dissatisfaction type." Conclusion: This study revealed non-face-to-face clinical practice's positive and negative aspects in nursing education. Moreover, it identified the aspects of clinical practice that cannot be replaced by non-face-to-face clinical practice and the elements of non-face-to-face practice that can complement clinical practice. These findings can be used as fundamental data to establish a stable and efficient system for improving the quality of clinical practice in the post-COVID-19 era and to implement effective non-face-to-face clinical practice according to student types.
Objectives: Measuring the quality of care is paramount to inform policies for healthcare services. Nevertheless, little is known about the quality of primary care and acute care provided in Korea. This study investigated trends in the quality of primary care and acute care. Methods: Case-fatality rates and avoidable hospitalization rates were used as performance indicators to assess the quality of primary care and acute care. Admission data for the period 2008 to 2020 were extracted from the National Health Insurance Claims Database. Case-fatality rates and avoidable hospitalization rates were standardized by age and sex to adjust for patients' characteristics over time, and significant changes in the rates were identified by joinpoint regression. Results: The average annual percent change in age-/sex-standardized case-fatality rates for acute myocardial infarction was -2.3% (95% confidence interval, -4.6 to 0.0). For hemorrhagic and ischemic stroke, the age-/sex-standardized case-fatality rates were 21.8% and 5.9%, respectively in 2020; these rates decreased since 2008 (27.1 and 8.7%, respectively). The average annual percent change in age-/sex-standardized avoidable hospitalization rates ranged from -9.4% to -3.0%, with statistically significant changes between 2008 and 2020. In 2020, the avoidable hospitalization rates decreased considerably compared with the 2019 rate because of the coronavirus disease 2019 pandemic. Conclusions: The avoidable hospitalization rates and case-fatality rates decreased overall during the past decade, but they were relatively high compared with other countries. Strengthening primary care is an essential requirement to improve patient health outcomes in the rapidly aging Korean population.
The purpose of this study is a method to discover problems and improve them by analyzing the status of software education of A primary school conducted by online class. The coronavirus infection-19(COVID-19) pandemic, which began in early 2020, has continued to delay the start of the new semester. Finally, on April 9, 2020, the first semester began with online class. While progressing non-face to face online class, most students said they had difficulties. Students solved difficulties in class with Internet searches or program hints, not teachers. In the post-class self-evaluation, most students answered that there was no increase in coding skills. To solve this problem, the school rents additional smart devices to student. schools should have real-time interactive classes. After covid 19, online class became a paradigm for classes. Therefore, software education will also require research and development of curriculum and teaching learning methods suitable for online classes.
Purpose: This scoping review investigated the content and quality of YouTube videos on women's health. Methods: A literature search of the Cochrane Library, PubMed, Embase, CINAHL, ERIC, and RISS databases was performed using the keywords "('youtube'/exp OR youtube OR 'social media'/exp OR 'social media' OR (('social'/exp OR social) AND ('media'/exp OR media))) AND ('female health care' OR (('female'/exp OR female) AND ('health'/exp OR health) AND ('care'/exp OR care)))" from February 21 to 27, 2023. Peer-reviewed analytic studies in English or Korean that focused on women's health using YouTube were included. Results: The review identified 21 articles that covered various themes related to women's health, such as breast cancer, urinary disease, sexual health, pelvic organ prolapse, the human papillomavirus vaccine, Papanikolaou smears, contraception, women's health information during the coronavirus disease 2019 pandemic, obstetric epidural anesthesia, and placenta accreta. However, the overall quality of the content was low, inaccurate, unreliable, and misleading. Conclusion: This scoping review demonstrated that YouTube videos on women's health covered diverse topics, but the quality of the content needed improvement. More reliable and high-quality videos produced by academic institutes and healthcare professionals specializing in women's health are needed for social media to be usable as a reliable source of women's health information. The high number of views and shares received by the videos underscores the importance of providing accurate and reliable information on women's health.
The Journal of Korean Academic Society of Nursing Education
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v.30
no.1
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pp.49-60
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2024
Purpose: The coronavirus disease 2019 (COVID-19) pandemic has had significant physical and psychological impacts on registered nurses (RNs). This study aimed to identify long COVID symptoms and their associated factors specifically among RNs. Methods: This descriptive correlational study's sample comprised 189 nurses (31.57±5.98 years, 93.7% female) in Korea. Self-reported long COVID symptoms were assessed using the COVID-19 Yorkshire Rehabilitation Scale. Data were collected from December 31, 2022, to January 13, 2023, using the online survey method and were analyzed using independent t-test, Wilcoxon signed-rank test, one-way ANOVA, Pearson's correlation, and a multiple linear regression analysis with the IBM SPSS Statistics 26.0 program. Results: A total of 179 participants (94.7%) experienced one or more long COVID symptoms. The most prevalent symptoms were weakness (77.8%), fatigue (68.3%), breathlessness (67.7%), cough/throat sensitivity/voice change (50.3%), and sleep problems (50.3%). The factors related to long COVID symptoms were marital status, type of institution, working time, acute COVID-19 symptoms, and vaccination status. The quarantine period (β=.26, p<.001) and the nursing workforce after COVID-19 (β=-.17, p=.018) were significantly associated with long COVID symptoms (Adjusted R2 =.33). Conclusion: Providing comprehensive recognition is necessary for the understanding of long COVID symptoms and their associated factors among nurses and could promote a long COVID symptom management education program targeted at nurses. Moreover, it could facilitate effective nursing care and education plans for long COVID patients.
Purpose: The significance of the healthcare industry has grown exponentially in recent years due to the impact of the fourth industrial revolution and the ongoing pandemic. Accordingly, this study aimed to examine domestic healthcare-related patents comprehensively. Big data analysis was used to present the trend and status of patents filed in nursing. Methods: The descriptive review was conducted based on Grant and Booth's descriptive review framework. Patents related to nursing was searched in the Korea Intellectual Property Rights Information Service between January 2016 to December 2020. Data analysis included descriptive statistics, phi-coefficient for correlations, and network analysis using the R program (version 4.2.2). Results: Among 37,824 patents initially searched, 1,574 were selected based on the inclusion criteria. Nursing-related patents did not specify subjects, and many patents (41.4%) were related to treatment in the healthcare delivery phase. Furthermore, most patents (56.1%) were designed to increase effectiveness. The words frequently used in the titles of nursing-related patents were, in order, "artificial intelligence," "health management," and "medical information," and the main terms with high connection centrality were "artificial intelligence" and "therapeutic system." Conclusion: The industrialization of nursing is the best solution for developing the healthcare industry and national health promotion. Collaborations in education, research, and policy will help the nursing industry become a healthcare industry of the future. This will prime the enhancement of the national economy and public health.
Multisystem inflammatory syndrome in children (MIS-C) is a rare complication of coronavirus disease 2019 (COVID-19), causing multi-organ damage affecting the heart, lungs, kidneys, digestive tract, and nervous system. As the cases of MIS-C have been increasing following the COVID-19 pandemic, the importance of appropriate management for MIS-C is becoming increasingly apparent. Immunomodulating agents such as anakinra, infliximab, and steroids are regarded as supplementary therapy to the first-line treatment with intravenous immunoglobulin. However, these immunomodulating therapies can potentially precipitate opportunistic infections, including those caused by cytomegalovirus (CMV), Epstein-Barr virus, and tuberculosis, or increase the risk of co-infections. Herein, we report a case of a 3-year-old boy who was treated with immunoglobulin, infliximab, and high-dose methylprednisolone for MIS-C, and subsequently developed a persistent fever lasting 32 days caused by a CMV infection.
Purpose: The objective of this study was to develop a predictive model for the sexual experiences of adolescents using the random forest method and to identify the "variable importance." Methods: The study utilized data from the 2019 to 2021 Korea Youth Risk Behavior Web-based Survey, which included 86,595 man and 80,504 woman participants. The number of independent variables stood at 44. SPSS was used to conduct Rao-Scott χ2 tests and complex sample t-tests. Modeling was performed using the random forest algorithm in Python. Performance evaluation of each model included assessments of precision, recall, F1-score, receiver operating characteristics curve, and area under the curve calculations derived from the confusion matrix. Results: The prevalence of sexual experiences initially decreased during the COVID-19 pandemic, but later increased. "Variable importance" for predicting sexual experiences, ranked in the top six, included week and weekday sedentary time and internet usage time, followed by ease of cigarette purchase, age at first alcohol consumption, smoking initiation, breakfast consumption, and difficulty purchasing alcohol. Conclusion: Education and support programs for promoting adolescent sexual health, based on the top-ranking important variables, should be integrated with health behavior intervention programs addressing internet usage, smoking, and alcohol consumption. We recommend active utilization of the random forest analysis method to develop high-performance predictive models for effective disease prevention, treatment, and nursing care.
Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.
Following the COVID-19 pandemic, congestion within container terminals has led to a significant increase in waiting time and turnaround time for external trucks, resulting in a severe inefficiency in gate-in and gate-out operations. In response, port authorities have implemented a Vehicle Booking System (VBS) for external trucks. It is currently in a pilot operation. However, due to issues such as information sharing among stakeholders and lukewarm participation from container transport entities, its improvement effects are not pronounced. Therefore, this study proposed a deep learning-based predictive model for external trucks turnaround time as a foundational dataset for addressing problems of waiting time for external trucks' turnaround time. We experimented with the presented predictive model using actual operational data from a container terminal, verifying its predictive accuracy by comparing it with real data. Results confirmed that the proposed predictive model exhibited a high level of accuracy in its predictions.
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