• Asian-Australasian Journal of Animal Sciences
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• v.18 no.2
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• pp.151-157
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• 2005

Sheep production is affected by genetic and non-genetic factors. A knowledge of these factors is essential for efficient management and for the accurate estimation of breeding values. The objective of this study was to establish the non-genetic factors which affect birth weight and weaning weight in Dorper, Mutton Merino and indigenous Sabi sheep breeds. A total of 2,625 birth and weaning weight records from Grasslands Research Station collected from 1991 through 1993, were used. The records were collected from indigenous Sabi (939), Dorper (807) and Mutton Merino (898) sheep. A mixed classification model containing the fixed effects of year, birth status and sex was used for identification of non-genetic factors. Sire within breed was included as a random effect. Two factor interactions and three factor interactions were important in indigenous Sabi, Mutton Merino and Dorper sheep. The mean birth weights were 4.37${\pm}$0.04 kg, 4.62${\pm}$0.04 kg and 3.29${\pm}$0.04 kg for Mutton Merino, Dorper and Sabi sheep, respectively. Sire had significant effects (p<0.05) on birth weight in Mutton Merino and indigenous Sabi sheep. Year of lambing had significant effects (p<0.05) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep. The effect of birth status was non significant in Dorper and Mutton Merino sheep while effect of birth status was significant on birth weight in indigenous Sabi sheep. In Indigenous Sabi sheep lambs born as singles (3.30${\pm}$0.05 kg) were 0.23 kg heavier than twins (3.07${\pm}$0.05 kg), in Mutton Merino lambs born as singles (3.99${\pm}$0.08 kg) were 0.07 kg heavier than twins (3.92${\pm}$0.08 kg) and in Dorper lambs born as singles (4.41${\pm}$0.04 kg) were 0.02 kg heavier than twins (4.39${\pm}$0.04 kg). On average males were heavier than females (p<0.05) weighing (3.32${\pm}$0.04 kg vs. 3.05${\pm}$0.07 kg) in indigenous Sabi, 4.73${\pm}$0.03 kg vs. 4.08${\pm}$0.05 in Dorper and 4.26${\pm}$0.07 kg vs. 3.66${\pm}$0.09 kg in Mutton Merino sheep. Two way factor interactions of sire*year, year*sex and sex*birth status had significant effects (p<0.05) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep while the effect of year*birth status was non significant on birth weight in Indigenous Sabi sheep. The three way factor interaction of year*sex*birth status had a significant effect (p<0.01) on birth weight in indigenous Sabi and Mutton Merino. Tupping weight fitted as a covariate had significant effects (p<0.001) on birth weight in indigenous Sabi, Mutton Merino and Dorper sheep. The mean weaning weights were 17.94${\pm}$0.31 kg, 18.19${\pm}$0.28 kg and 14.39${\pm}$0.28 kg for Mutton Merino, Dorper and Indigenous Sabi sheep, respectively. Effects of sire and sire*year were non significant on weaning weight in Dorper and Mutton Merino while year, sex and sex*year interaction had significant effects (p<0.001) on weaning weight. On average males were heavier than females (p<0.001) at weaning. The respective weaning weights were 18.05${\pm}$0.46 kg, 18.68${\pm}$0.19 kg, 14.14${\pm}$0.15 kg for males and 16.64${\pm}$0.60 kg, 16.41${\pm}$0.31 kg, 12.64${\pm}$0.32 kg for females in Mutton Merino, Dorper and Indigenous Sabi sheep. Lambs born as singles were significantly heavier at weaning than twins, 0.05 kg, 0.06 kg and 0.78 kg for Mutton Merino, Dorper and Indigenous Sabi sheep, respectively. Effect of tupping weight was highly significant on weaning weight. The three way factor interaction year*sex*birth status had a significant effect (p<0.01) on weaning weight. Correction for environmental effects is necessary to increase accuracy of direct selection for birth weight and weaning weight.

• Korea Journal of Hospital Management
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• v.9 no.1
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• pp.66-94
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• 2004

The objective of this study is to examine how to maximize the efficiency of hospital management by minimizing the unit cost of hospital operation. For this purpose, this paper proposes to develop a model of the profit maximization based on the cost minimization dictum using the statistical tools of arriving at the maximum likelihood values. The preliminary survey data are collected from the annual statistics and their analyses published by Korea Health Industry Development Institute and Korean Hospital Association. The maximum likelihood value statistical analyses are conducted from the information on the cost (function) of each of 36 hospitals selected by the random stratified sampling method according to the size and location (urban or rural) of hospitals. We believe that, although the size of sample is relatively small, because of the sampling method used and the high response rate, the power of estimation of the results of the statistical analyses of the sample hospitals is acceptable. The conceptual framework of analyses is adopted from the various models of the determinants of hospital costs used by the previous studies. According to this framework, the study postulates that the unit cost of hospital operation is determined by the size, scope of service, technology (production function) as measured by capacity utilization, labor capital ratio and labor input-mix variables, and by exogeneous variables. The variables to represent the above cost determinants are selected by using the step-wise regression so that only the statistically significant variables may be utilized in analyzing how these variables impact on the hospital unit cost. The results of the analyses show that the models of hospital cost determinants adopted are well chosen. The various models analyzed have the (goodness of fit) overall determination (R2) which all turned out to be significant, regardless of the variables put in to represent the cost determinants. Specifically, the size and scope of service, no matter how it is measured, i. e., number of admissions per bed, number of ambulatory visits per bed, adjusted inpatient days and adjusted outpatients, have overall effects of reducing the hospital unit costs as measured by the cost per admission, per inpatient day, or office visit implying the existence of the economy of scale in the hospital operation. Thirdly, the technology used in operating a hospital has turned out to have its ramifications on the hospital unit cost similar to those postulated in the static theory of the firm. For example, the capacity utilization as represented by the inpatient days per employee tuned out to have statistically significant negative impacts on the unit cost of hospital operation, while payroll expenses per inpatient cost has a positive effect. The input-mix of hospital operation, as represented by the ratio of the number of doctor, nurse or medical staff per general employee, supports the known thesis that the specialized manpower costs more than the general employees. The labor/capital ratio as represented by the employees per 100 beds is shown to have a positive effect on the cost as expected. As for the exogeneous variable's impacts on the cost, when this variable is represented by the percent of urban 100 population at the location where the hospital is located, the regression analysis shows that the hospitals located in the urban area have a higher cost than those in the rural area. Finally, the case study of the sample hospitals offers a specific information to hospital administrators about how they share in terms of the cost they are incurring in comparison to other hospitals. For example, if his/her hospital is of small size and located in a city, he/she can compare the various costs of his/her hospital operation with those of other similar hospitals. Therefore, he/she may be able to find the reasons why the cost of his/her hospital operation has a higher or lower cost than other similar hospitals in what factors of the hospital cost determinants.

• Pediatric Infection and Vaccine
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• v.23 no.2
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• pp.109-116
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• 2016

Purpose: Recent observational studies have found that vitamin D deficiency is associated with respiratory tract infections. However, randomized controlled trials (RCTs) regarding the efficacy of vitamin D in childhood respiratory tract infection (RTI) have yield inconsistent results. We performed a systematic review and meta-analysis to evaluate the association between vitamin D supplementation and the risk of RTI. Methods: A comprehensive search was conducted using MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trial. Randomized controlled trials of vitamin D supplementation for prevention of RTI in children were included for the analysis. Cochrane Collaboration's tool for assessing the risk of bias was used to assess the quality of the studies. Pooled risk ratios with 95% confidence intervals (CIs) were meta-analyzed using Review Manager 5.3. Results: A total of seven RCTs were included in the meta-analysis. According to a random-effects model, the risk ratio for vitamin D supplementation was 0.82 (95% CI: 0.69-0.98) and $I^2=62%$ for heterogeneity. On subgroup analysis, heterogeneity decreased in the subgroup with follow-up less than 1 year, participants ${\geq}5years$ of age, patients subgroup, and subgroup with dosing daily. Funnel plot showed that there might be publication bias in the field. Conclusions: The present meta-analysis supports a beneficial effect of vitamin D supplementation for the prevention of RTI in children. However, the result should be interpreted with caution due to limitations including a small number of available RCTs, heterogeneity among the studies, and potential publication bias.

• Journal of Society of Preventive Korean Medicine
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• v.4 no.2
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• pp.119-141
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• 2000

The current industrial health service is shifting to health improvement business with 1st primary prevention-focused service from secondary and tertiary prevention-focused business, and Oriental medicine can provide such primary prevention-focused service due to the characteristics of its science. In particular, the advanced concept of health improvement can match the science of health care of Oriental medicine. Notably, what is most important in health improvement is our lifestyle, This does not underestimate the socio-environmental factors, which have lessened their importance due to modernism. The approach of Oriental medicine weighs more individuals' lifestyle and health care through self-cultivation. This matches the new model of advanced health business. Oriental medicine is less systemized than Western medicine, but it can provide ample contents that enhance health. If we conceive health-improvement program based on the advantages provided by these two medical systems, this will influence workers to the benefit of their health. Also, health Program needs to define factors that determine individual lives, and to provide information and technologies essential to our lives. The Oriental medicine approach puts more stress on a subject's capabilities than it does on the effect his surrounding environment can have. This needs to be supported theoretically by not only defining the relations between an individual's health state and his lifestyle, but also identifying the degree to which an individual in the industrial work place practices health improvement lifestyle . This is the first step toward initiating health-improvement business . In order to do this, this researcher conducted a survey by taking random samplings from workers, and can draw the following conclusions from it. 1 The sampled group is categorized into', by sender, female 6.6%, and male 93.4%, with males dominant; by marriage status , unmarried 43.9% and married 55.6%, with both similar percentage, and, by age, below 30, 48.4%, between 30 and 39, 27.4%, between 40 and 49, 18.2%, and over 50, 6.0%. The group further is categorized into; by education, middle school or under 1.7%, high school 30.5%, and junior college or higher 65.8% with high school and higher dominant: and by income, below 1.7 million won 24.2%, below 2.4 million won 14.8%, and above 2.4 million 6.3% Still, the group by job is categorized into collegians with 23.9%, office worker with 10.3%, and professionals with 65.8% , and this group does not include workers engaged in production that are needed for this research, but mostly office workers . 2. The subjects selected for this survey show their degree of practicing health-improvement lifestyle at an average of 2.63, health management pattern at 2.64, and health-related awareness at 2.62 The sub-divisions of health-improvement lifestyle show social emotion (2.87), food (2.66). favorite food (2.59), and leisure activities (2.52), in this order for higher points. It further shows health awareness (2.47) and safety awareness (2.40), lower points than those in health management pattern . 3. In the area of using leisure time for health-improvement, males, older people, married, and people with higher income earn higher marks. And, in the area of food management, the older and married earn higher marks . In the area of favorite food management, females, lower-income bracket, and lower-educated show higher degree of practice , while in the area of social emotion management, the older. married, and higher-income bracket show higher marks. In addition, in the area of health awareness, the older, married, and people with higher-income show higher degree of practice. 4. To look at correlation by overall and divisional health-improvement practice degree , this researcher has analyzed the data using Person's correlation coefficient. The lifestyle shows significant correlation with its six sub-divisions, and use of leisure time, food, and health awareness all show significant correlation with their sub-divisions. And. the social emotion and safety awareness show significant correlation with all sub-divisions except favorite food management.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.19-32
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• 2020

The purpose of this study was to investigate the influence factors of the university level centering on the entrepreneurial performance of the university students and full-time faculties in the situation of increasing interest in entrepreneurial university. In order to achieve the purpose of the study, a panel data was established from 2015 to 2018 on the basis of the university notification data. The panel data included universities with data on the number of university students and full-time faculty founders for at least two years. Through this, four year data from 154 universities were used for analysis. As an analysis method, frequency analysis and descriptive statistics were conducted to understand the characteristics of the university. Since then, panel negative binomial regression analysis has been conducted in consideration of the longitudinal features and distribution of the data. Also, based on the Hausman test results, the results were interpreted based on random effect model. The results of this study are as follows. First, as a result of the analysis of the entrepreneurial performance and the change trend of the domestic university from 2015 to 2018, the entrepreneurial performance of the university has been steadily increasing in the last four years, and the increase in the number of university student entrepreneurs was relatively higher than the full-time faculties. Second, economic and educational approaches need to be combined to promote university students' start-ups. The university factors that promote the start-up of university students were found to be scholarships, start-up grants, startup lectures, and startup clubs. Third, the openness and regional characteristics of the univeristy can promote the establishment of university students. Fourth, the establishment of a research environment and support for start-ups for full-time faculty members can enhance their start-up performance. The university factors that promote the start-up of full-time faculty were research funds and staffes who support start-up. The conclusions drawn from these findings are as follows. First, overall efforts are needed to develop into an entrepreneurial university. Second, in order to change into an entrepreneurial university, direct support for entrepreneurship is needed. Third, as an entrepreneurial university, it is necessary to find a way to bridge the gap by university according to region and size. Fourth, it is necessary to reinforce the support for linking the research results of universities to start-ups. Fifth, it is necessary to improve the atmosphere for full-time faculty members to be entrepreneur.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.2
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• pp.101-110
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• 2019

Objectives : It is not clear which clinical variables are most closely associated with delirium in the Intensive Care Unit (ICU). By comparing clinical data of ICU delirium and non-delirium patients, we sought to identify variables that most effectively differentiate delirium from non-delirium. Methods : Medical records of 6,386 ICU patients were reviewed. Random Subset Feature Selection and Principal Component Analysis were utilized to select a set of clinical variables with the highest discriminatory capacity. Statistical analyses were employed to determine the separation capacity of two models-one using just the selected few clinical variables and the other using all clinical variables associated with delirium. Results : There was a significant difference between delirium and non-delirium individuals across 32 clinical variables. Richmond Agitation Sedation Scale (RASS), urinary catheterization, vascular catheterization, Hamilton Anxiety Rating Scale (HAM-A), Blood urea nitrogen, and Acute Physiology and Chronic Health Examination II most effectively differentiated delirium from non-delirium. Multivariable logistic regression analysis showed that, with the exception of vascular catheterization, these clinical variables were independent risk factors associated with delirium. Separation capacity of the logistic regression model using just 6 clinical variables was measured with Receiver Operating Characteristic curve, with Area Under the Curve (AUC) of 0.818. Same analyses were performed using all 32 clinical variables;the AUC was 0.881, denoting a very high separation capacity. Conclusions : The six aforementioned variables most effectively separate delirium from non-delirium. This highlights the importance of close monitoring of patients who received invasive medical procedures and were rated with very low RASS and HAM-A scores.

• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.57-81
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• 2011

The purpose of this study was to explore the quality of life of musically talented students as measured by their external experiences (e.g., activities, companions) and internal experiences (e.g., flow, emotion). The participants in this study were 33 musically talented students (10 males, 23 females) aged 13 to 19. Study data were collected for 7 consecutive days using the Experience Sampling Method (ESM), which employs a cellular-phone as a signaling device. The results were as follows: First, in response to the 1625 random signals, musically talented students reported that 40.9% of their time was spent on productive activities. An additional 33.4% of time was used for maintenance activities and the rest of their time was spent on leisure/social activities. Also, musically talented students reported that 48.5% of their time was spent alone. When they were alone, they spent a lot of time engaging in productive activities (44.3%). Second, in order to measure the flow of their life, two methods were used. One used a 4-channel flow model (i.e. apathy, boredom, flow, anxiety) and the other used 8 dimensions and conditions of the flow experience (i.e. concentration, self-consciousness disappears, action and awareness merge, distorted sense of time, freedom from worry about failure, clear goals, immediate feedback, balance between challenges and skills). According to the former, when engaged in music-related activities, musically talented students usually reported flow (54.0%), while they felt apathy (41.3%) for daily routines activities. According to the latter method, musically talented students experienced flow for most productive activities, while they experienced flow least for maintenance activities. Emotional variables of ESF are comprised of 10 semantic scales (i.e. happy-sad, strong-weak, active-passive, sociablelonely, proud-ashamed, involved-detached, excited-bored, clear-confused, relaxed-worried, cooperative-competitive). Musically talented students reported experiencing the most positive emotion for social activities and experiencing the most negative emotion for maintenance activities. Results of this study assert that musically talented students had to trade off immediate enjoyment for developing their special gifts. They could not afford as much time for socializing with friends, and they had to spend more time alone compared to their peers without such gifts. Consequently, they were found to deprive themselves of the spontaneous good times that teenagers usually thrive on. They were helped in this respect by their autotelic personality traits, especially their strong need for achievement and endurance. The downside, however, is that the moment-to-moment quality of their moods suffered. The argument concerning musically talented students applies for all adolescents. The choices that talented students must make between immediate gratification and long-term development, and between solitude and companionship, are the same choices every young person must make, regardless of her or his level of talent. All of us have gifts that are potentially useful and worthy of being appreciated. But to develop these latent talents we must cultivate them, and this takes time and the investment of mental energy. The lifestyle that musically talented students develop can show us some of the choices all of us must make in order to cultivate our gifts.

• Journal of Animal Science and Technology
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• v.47 no.5
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• pp.703-710
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• 2005

Data from Hanwoo steers and bull calves were analyzed to see the phenotypic and genetic relationships between carcass traits from four different covariance models. Four models fit test station and test period as fixed effect of contemporary group and sire as random effect assuming paternal half-sib relationships among animals. Each model fits one of linear covariate (s) of different slaughter end points-age at slaughter in the first order, age at slaughter in the first and second order, slaughter weight or back fat thickness at 12-13th rib of cold carcass. Age at slaughter in its second order was not significant. Age at slaughter accounted for signifi- cant amount of genetic variances and covariances of carcass traits. Heritability estimates of back fat thickness, rib eye area, carcass weight, marbling score and dressing percentage were 0.34, 0.22, 0.24, 0.42 and 0.18, respectively at constant age basis. The genetic correlation between carcass weight and the other variables were all positive and low to high in magnitude. Genetic correlations between back fat thickness and rib eye area and between marbling score and dressing percentage were low but negative. Variance and covariance structure between these traits were shifted to a great extent when these variables were regressed on slaughter weight or on back fat thickness. These two covariates counteracted to each other but they adjusted each carcass variable or their interrelationship according to differential growth of body components, bone, muscle and fat. Slaughter weight tended to decrease genetic variances and covariances of carcass weight and between component traits and back fat thickness tended to increase those of rib eye area and between rib eye area and carcass weight.

• Health Policy and Management
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• v.12 no.2
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• pp.23-42
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• 2002

The purpose of this study was to analyze the results of 133 studies related to patient compliance published between 1980 and 2001 and to assess the effectiveness of intervention on compliance by using meta-analysis. We collected the existing literatures by using web and manual search 'patient compliance', 'sick role behavior', 'major clinical disease', and 'intervention' as key words and by reviewing content of journals related to medicine, nursing and public health. The compliance interventions were classified by theoretical focus into educational, behavioral, and affective categories within which specific intervention strategies were further distinguished. The compliance indicators broadly represent five classes of compliance-related assessments: (1) health outcomes (eg, blood pressure and hospitalization), (2) direct indicators (eg, urine and blood tracers and weight change), (3) indirect indicators (eg, pill count and refill records), (4) subjective report (eg, patients' or others' reports), (5) utilization (appointment making and keeping, use of preventive services). Quantitative meta-analysis was performed by MetaKorea program which was developed for meta-analysis in Korea. Among the 133 articles, 10 studies were selected through the qualitative meta-analysis process, and then only 6 studies were selected for the quantitative meta-analysis finally. The interventions produced significant effects for all the compliance indicators with the magnitude of common effect size (4.1192) than the non-intervention group in a random effect model. The largest effects were each study for patient of hypertension using health outcome such as blood pressure (0.4679) and diabetes mellitus using direct indicator such as glucose level in blood and urine (0.7753). These results suggest that strategic interventions showed clear advantage for improvement of patient compliance compared with non-intervention group.