• Journal of Korean Academy of Nursing
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• v.22 no.3
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• pp.271-296
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• 1992

The purposes of this study were 1) to identify patterns and trends of studies of anxiety and stress and 2) to provide direction on which to base further research. Research studies of anxiety and stress were selected from journals of medical and nursing schools, the Korean Nurse, the Korean Nurses' Academic Society Journal, the Central Journal of Medicine, the New Medical Journal, Monthly Nurse, and from theses and dissertations, which had been conducted for the 20 years from 1970 to 1990. The total population of the studies numbered 463. Seven studies were excluded from the analysis because of duplication, so that 252 studies of anxiety and 204 of stress were analyzed. These studies were analyzed for 1) time of publication or presentation, 2) research design, 3) characteristics of subjects used in each study, 4) types of correlated variables, and 5) types of nursing interventions. Findings obtained in the study were as follows : 1. The number of studies related to anxiety and stress has increased rapidly since the early 1980's. 2. The studies were primarily descriptive throughout the 20 years. However, correlational studies, comparative studies and experimental studies slowly increased. 3. Anxiety studies tend to be conducted more on patients and stress studies with normal subjects in non - experimental research. However, experimental studies were conducted more with patients than with normal subjects. 4. In correlational studies, the trend was to study physical conditions in relation to anxiety, and coping and adaptation in relation to stress. 5. In experimental studies, teaching and information therapy and relaxation were the most popular interventions for anxiety, and supportive care for stress. On the bases of these findings, the following recommendations were made : 1. These patterns of studies related to anxiety and stress in Korea need to be compared with studies conducted in other countries. 2. More attention is needed in terms of research design, reliability and validity of tools, and results of statistical analysis. 3. Meta -analysis should be done to analyze and integrate the results of various studies. 4. For theory testing and identification of useful intervention methods, experimintal studies with the same protocols must be conducted rather than more descriptive studies.

• The Journal of Information Systems
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• v.27 no.4
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• pp.1-33
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• 2018

Purpose The purpose of this study is to review topic and survey methodological trends in 'The Journal of Information Systems' in order to present the practical guidelines for the future IS research. By attempting to conduct a meta-analysis on both topic and survey methodological trends, this study could provide researchers wishing to pursue this line of work further with what can be done to improve IS disciplines. Design/methodology/approach In this study, we have reviewed 185 papers that were published in 'The Journal of Information Systems' from 2010 to 2018 and classified them based on topics studied and survey methodologies used. The classification guidelines, which was developed by Palvia et al.(2015), has been used to capture the topic trends. We have also employed Struab et al.(2004)s' guidelines for securing rigor of validation issues. By using two guidelines, this study could also present topic and rigor trends in 'The Journal of Information Systems' and compare them to those trends in International Journals. Findings Our findings have identified dominant research topics in 'The Journal of Information Systems'; 1) social media and social computing, 2) IS usage and adoption, 3) mobile computing, 4) electronic commerce/business, 5) security and privacy, 6) supply chain management, 7) innovation, 8) knowledge management, and 9) IS management and planning. This study also could offer researchers who pursue this line of work further practical guidelines on mandatory (convergent and discriminant validity, reliability, and statistical conclusion validity), highly recommended (common method bias testing), and optional validations (measurement invariance testing for subgroup analysis, bootstrapping methods for testing mediating effects).

• Journal of Oriental Neuropsychiatry
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• v.34 no.3
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• pp.181-212
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• 2023

Objectives: To examine the efficacy and safety of cupping therapy for insomnia disorder and provide clinical evidence that could contribute to further research. Methods: We searched randomized controlled trials (RCTs) that verified effects of cupping therapy for insomnia disorder from 11 domestic and foreign databases. Included studies were evaluated using Risk of Bias (RoB). Results: Nineteen RCTs were selected. Wet cupping was more frequently used than dry cupping. Moving cupping was mostly used among dry cupping methods. Dry cupping was mainly performed in Bladder Meridian on the back. Wet cupping was mainly performed on BL18, LR14, and BL15. The most common treatment period was 4 weeks. The average number of treatments per week was about 2.4 times for all types of cupping, about 3.2 times for dry cupping and about 1.9 times for wet cupping. All selected studies showed a significant sleep improvement compared to the control group. As a result of the meta-analysis, in terms of effective rate, SAS score, and SDS score, the wet cupping in combination with acupuncture was significantly more effective than acupuncture alone, although the quality of selected RCTs was low. Conclusions: Cupping therapy is effective for insomnia disorder. Based on results of this study, it is reasonable to use wet cupping two times per week on BL18, LR14, and BL15 or use moving cupping three times per week in Bladder Meridian on the back for 4 weeks to treat insomnia disorder.

• Korean Journal of Clinical Pharmacy
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• v.33 no.4
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• pp.290-304
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• 2023

Background: Innovative Alzheimer's disease drugs received approval in the United States in 2021 and 2023. This study aims to assess the safety and efficacy of these novel treatments, elucidate their mechanisms of action, and compare their impact on cognitive function improvement with approved drugs. Methods: We conducted a comprehensive search of pivotal clinical studies related to Alzheimer's disease treatments in PubMed/Medline, Embase, and the Cochrane Library databases from January 1st, 2020 to December 31st, 2022. Meta-analysis was performed using RevMan 5.4 software. Results: A total of 14 studies were included in this systematic review. When compared to the placebo, the new drugs did not exhibit a statistically significant effect on MMSE (Mini-Mental State Examination) (mean difference= -0.04, 95% confidence intervals [CIs]: -0.31, 0.23, N=3662, I²=0%). However, they demonstrated a significant impact on ADAS-cog (Alzheimer's Disease Assessment Scale-Cognitive Subscale) (standardized mean difference= -0.15, 95% CIs: -0.2, -0.1, N=6710, I²=17%). When compared to the approved drugs, the new drugs showed a statistically significantly lower effect on MMSE (test for subgroup difference Chi²=23.13, N = 5870, p<0.00001) but showed only a trend of decreased efficacy on ADAS-cog (Chi²=1.16, N = 8670, p=0.28). Conclusion: New drugs yielded diverse clinical endpoint results compared to the placebo, and in comparison to existing approved drugs, they exhibited lower efficacy in improving cognitive function. The safety profile of these new drugs, as reported in clinical trials, was generally well-tolerated.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.4
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• pp.215-223
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• 2024

Purpose: Patients who receive frequent blood transfusions are at an elevated risk of developing hepatic fibrosis due to iron overload in the liver. In this study, we evaluated the effectiveness of transient elastography (TE) (FibroScan^®) for assessing liver fibrosis in patients with pediatric cancer. Methods: We enrolled 106 consecutive cases of acute leukemia in individuals under 21 years of age. The participants were followed for 2 years. Based on their serum ferritin (SF) levels, the patients were divided into two groups: group 1 (SF≥300 ng/mL) and group 2 (SF<300 ng/mL). A liver FibroScan^® was performed, and a p-value of less than 0.05 was considered statistically significant. Results: Among the various parameters in the liver function test (LFT), alkaline phosphatase was significantly higher in a subgroup of patients aged 5-8 years in group 2 compared to those in group 1. The indices of liver fibrosis determined by TE, including the FibroScan score, controlled attenuation parameter score, steatosis percentage, and meta-analysis of histological data in viral hepatitis score, as well as indirect serum markers of liver fibrosis such as the aminotransferase (AST)/alanine aminotransferase (ALT) ratio, Fibrosis 4 score, and AST to platelet ratio index, did not differ significantly between the two groups. The association between the TE results and LFT parameters was only significant for ALT. Conclusion: Transfusion-associated iron overload does not have a significant correlation with severe liver fibrosis. FibroScan^® is not a sensitive tool for detecting early stages of fibrosis in survivors of pediatric leukemia.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.15-28
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• 2016

The purpose of this study is to investigate the changes of students' modeling ability in terms of 'meta-modeling knowledge' and 'modeling practice' through co-construction of scientific model. Co-construction of scientific model instructions about astronomy were given to 41 middle-school students. The students were given a before and after instruction modeling ability tests. The results show that students' 'meta-modeling knowledge' has changed into a more scientifically advanced thinking about models and modeling after the instruction. Students were able to be aware that 'they could express their thoughts using models', 'many models could be used to explain a single phenomena' and 'scientific models may change' through co-construction modeling process. The change in the 'modeling practice' of the students was divided into four cases (the level improving, the level lowering, the high-level maintaining, the low-level maintaining) depending on the change of pre-posttest levels. The modeling practice level of most students has improved through the instruction. These changes were influenced by co-construction process that provides opportunities to compete and compare their models to other models. Meanwhile, the modeling practice level of few students has lowered or maintained low level. Science score of these students at school was relatively high and they thought that the goal of learning is to get a higher score in exams by finding the correct answer. This means that students who were kept well under traditional instruction may feel harder to adapt to co-construction of scientific model instruction, which focuses more on the process of constructing knowledge based on evidences.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Asia pacific journal of information systems
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• v.19 no.4
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• pp.47-75
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• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.169-178
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• 2020

The reductions of troops/human resources, and improvement in combat power have made Korean Department of Defense actively adapt 4th Industrial Revolution technology (Artificial Intelligence, Big Data). The defense information system has been developed in various ways according to the task and the uniqueness of each military. In order to take full advantage of the 4th Industrial Revolution technology, it is necessary to improve the closed defense datamanagement system.However, the establishment and usage of data standards in all information systems for the utilization of defense big data and artificial intelligence has limitations due to security issues, business characteristics of each military, anddifficulty in standardizing large-scale systems. Based on the interworking requirements of each system, data sharing is limited through direct linkage through interoperability agreement between systems. In order to implement smart defense using the 4th Industrial Revolution technology, it is urgent to prepare a system that can share defense data and make good use of it. To technically support the defense, it is critical to develop Multi Repository Meta-Data Management (MRMM) that supports systematic standard management of defense data that manages enterprise standard and standard mapping for each system and promotes data interoperability through linkage between standards which obeys the Defense Interoperability Management Development Guidelines. We introduced MRMM, and implemented by using vocabulary similarity using machine learning and statistical approach. Based on MRMM, We expect to simplify the standardization integration of all military databases using artificial intelligence and bigdata. This will lead to huge reduction of defense budget while increasing combat power for implementing smart defense.