• Korean Journal of Clinical Laboratory Science
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• v.45 no.2
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• pp.60-65
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• 2013

Data from repeated measurements are accomplished through repeatedly processing the same subject under different conditions and different points of view. The power of testing enhances the choice of pertinent analysis methods that agrees with the characteristics of data concerned and the situation involved. Along with the clinical example, this paper compares the analysis of the variance on ex-post tests, gain score analysis, analysis by mixed design and analysis of covariance employable for repeating measure. Comparing the analysis of variance on ex post test, and gain score analysis on correlations, leads to the fact that the latter enhances the power of the test and diminishes the variance of error terms. The concluded probability, identified that the gain score analysis and the mixed design on interaction between "between subjects factor" and "within subjects factor", are identical. The analysis of covariance, demonstrated better power of the test and smaller error terms than the gain score analysis. Research on four analysis method found that the analysis of covariance is the most appropriate in clinical data than two repeated test with high correlation and ex ante affects ex post.

• Korean Journal of Adult Nursing
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• v.21 no.2
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• pp.245-256
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• 2009

Purpose: To describe the lived experience of nursing students when faced with clinical judgment in a nursing practicum at the hospital. Methods: A descriptive research design was utilized. Participants were 79 students in the clinical practicum. Participant consent was obtained for ethical protection. Data were collected from August to December 2007 using a semi-structured questionnaire. Content analysis was utilized for data analysis. Results: Two categories and 5 themes were extracted from the data for 'difficult' and 'easy' clinical judgments. For the student category, the two themes were 'knowledge' and 'skill', while the three themes for the clinical education environment category were, 'judgment of clinical symptoms and signs', 'differences between theory and practice' and 'human relationships'. For coping, 2 categories and 5 themes were extracted for the difficult clinical judgment situation, while one category and one theme were found for the easy clinical judgment situation. Conclusion: To develop students' clinical judgment, there is need to develop the method of clinical skills using simulation in clinical teaching. For future research, a study on factors affecting clinical judgment of nursing students in hospitals is needed.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.317-327
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• 2009

In adaptive designs important components of clinical trials may be changed based on the results of interim analysis. Several international guidelines point out that such interim analysis should be performed by independent experts who do not participate in clinical trials when adaptive designs are used in therapeutic confirmatory clinical trials, and if not, it may cause bias. The international guidelines recommend the establishment of independent data monitoring committee for conducting interim analysis independently.

• Korean Journal of Clinical Laboratory Science
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• v.44 no.4
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• pp.239-244
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• 2012

This study aims to analysis the curriculum problems and its improvements and to investigate curricula satisfaction among the students majoring in Clinical Pathology. A college used as a population, and 80 effective survey data were collected by sampling the graduates who carried out the clinical field training in third grade year. For statistical analysis of the collected data, the Stata(version 12.0) statistical package was used for frequency analysis, pearson correlations test and multiple regression analysis. The results of the analysis were as follows; First, the result showed that the synthetical theory curriculum has an positive effect on curricula satisfaction. Second, it was found that extension of both the clinical field training and laboratory and practice education have an significant influence direction of positiveness on curricula satisfaction. Third, as the problems of curriculum, the students selected shortage of english subjects connected with the job. We must intensify additional subjects (english ability) for job as the improvement of curriculum. Accordingly, academic, industrial circles and students are supposed to jointly seek for the plan for the enhancement of clinical field training satisfaction.

• The Korean Journal of Health Service Management
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• v.12 no.4
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• pp.203-217
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• 2018

Objectives : This study aimed to investigate the clinical practice ability and satisfaction of clinical training of health-medical information management major students. Methods : The data were collected from 68 persons from students finished clinical training at medical record (information) team using self administered questionnaires. The data were analyzed using t-test, ANOVA and correlation with SPSS 22.0 version. Results: Performance of data collection, data management, and data analysis were analyzed in three areas of the job area. In terms of academic characteristics and correlation, they were not related to the level of satisfaction with the practical experience. Conclusions : Research on a virtuous cycle clinical practice program that analyzes the factors by assessing the satisfaction level of clinical practice in each area of health care information management will be conducted continuously.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.27-35
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• 2023

This study was a cross-sectional descriptive survey study that confirms the effect on subjects that prefer clinical practice in order to prepare basic data for efficient clinical practice guidance for nursing college students. The study participants were 201 students attending C University, and the data collection period was from October 1 to October 15, 2022. The collected data were analyzed using SPSS 18.0 as descriptive statistics, Pearson correlation, Chi square test, ANOVA test, and Multiple regression test. As a result of the analysis, it was found that clinical decision-making and critical thinking were correlated under the statistical significance level (r=.730, p<0.01). The most favorite clinical practice department was community nursing, and male students preferred community nursing the most (Male=45.6%, χ²=.000), female students were found to prefer similar levels of practical subjects with child nursing , adult nursing, and maternal nursing(χ²=000).Clinical decision-making was found to be higher in students who preferred community nursing at a statistical significance level than those who preferred child nursing (F=4.91, p<0.01). Critical thinking was higher among students who preferred adult nursing than those who preferred other subjects (F=4.65, p<0.01). Through the analysis results, it was found that general characteristics vary, but clinical decision-making ability and critical thinking affect the preference of clinical practice subjects. Therefore, based on the results of this study, the professor of clinical practice suggests the development of a program to foster clinical decision-making and critical thinking to make students interested in clinical practice subjects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.187-195
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• 2019

Recently, it has become possible to collect, store, process, and analyze data generated in various fields by the development of the technology related to the big data. These big data technologies are used for clinical results analysis and the optimization of clinical trial design will reduce the costs associated with health care. Therefore, in this paper, we are going to analyze clinical results and present guidelines that can reduce the period and cost of clinical trials. First, we use Sqoop to collect clinical results data from relational databases and store in HDFS, and use Hive, a processing tool based on Hadoop, to process data. Finally we use R, a big data analysis tool that is widely used in various fields such as public sector or business, to analyze associations.

• Communications for Statistical Applications and Methods
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• v.30 no.1
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• pp.1-19
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• 2023

Observational data with missing or incomplete data are common in biomedical research. Multiple imputation is an effective approach to handle missing data with the ability to decrease bias while increasing statistical power and efficiency. In recent years propensity score (PS) matching has been increasingly used in observational studies to estimate treatment effect as it can reduce confounding due to measured baseline covariates. In this paper, we describe in detail approaches to competing risk analysis in the setting of incomplete observational data when using PS matching. First, we used multiple imputation to impute several missing variables simultaneously, then conducted propensity-score matching to match statin-exposed patients with those unexposed. Afterwards, we assessed the effect of statin exposure on the risk of heart failure-related hospitalizations or emergency visits by estimating both relative and absolute effects. Collectively, we provided a general methodological framework to assess treatment effect in incomplete observational data. In addition, we presented a practical approach to produce overall cumulative incidence function (CIF) based on estimates from multiple imputed and PS-matched samples.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• Journal of Korean Public Health Nursing
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• v.19 no.2
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• pp.217-228
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• 2005

Purpose: The purpose of this study is to understand nursing students' experiences during clinical practice at a public health center. Method: This research used narrative inquiry far data collection. From April 2005 to June 2006, data collection was conducted by open-ended interview, questionnaire and close observation. The participants, who were student nurses, were willing to take part in this study. Results: On the basis of these data, the experiences of clinical practice at public health center were: 1) when the student nurses begin clinical practice at public health centers for the first time, most of the students feel fearful, nervous and stressed. They also mentioned having a hard time being polite to clients and the staff. 2) The students had new experiences at the health public center compared with clinical practice. Especially, the student nurses who were determined to be good nurses were doing home visiting care service. Not only did they have the opportunity to confirm their identity as nurses, but also the students change their career course from clinical nursing to public health nursing. 4) They reflected on themselves after home visiting care service. Conclusion: On the basis of these findings, the following recommendations are made. 1) Data collection and analysis are needed, net only through the narrative method, but also through other various qualitative methods. 2) Comparative study is necessary to enhance clinical experiences through the analysis of the interfering factors and the original experiences.