• 패션비즈니스
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• 제10권2호
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• pp.181-193
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• 2006

The purpose of this study was to examine which factors among addiction buying behavior had been affected by body image. 235 female college students were surveyed for this study. For data analysis, descriptive statistics, $x^2$-test, multiple regression were used. As the results, generally there were significantly correlated among body image, diet addiction, binge eating, cosmetic surgery addiction, compulsive behavior and shoplift tendencies. Multiple regression results revealed that diet addiction, cosmetic surgery addiction, binge eating accounted for 34.8% of the explained variance in weight obsession. Also, regression results indicated that cosmetic surgery addiction, self-esteem, and diet addiction, and cosmetic surgery obession accounted for 20.4% of the explained variance in appearance orientation. Finally, regression results pointed out that self-esteem and diet obession accounted 22.3% of the explained variance in appearance evaluation. Based on these results, fashion marketing strategies would be suggested.

• 중환자간호학회지
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• 제15권3호
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• pp.23-36
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• 2022

Purpose : This study aimed to identify the factors influencing the professional quality of life of intensive care unit (ICU) nurses working in university hospitals. Methods : A survey was conducted on 171 ICU nurses in university hospitals in B City, South Korea. This study used the Professional Quality of Life instrument, which consists of three subscales, namely, compassion satisfaction, burnout, and secondary traumatic stress. Data were analyzed using stepwise multiple regression analysis. Results : Compassion satisfaction was influenced by resilience, ICU job satisfaction, and innovation-oriented culture, and these variables explained 37.1% of the variance in compassion satisfaction. Burnout was influenced by resilience, a hierarchy-oriented culture, and ICU job satisfaction, and these variables explained 42.9% of the variance in burnout. Secondary traumatic stress was influenced by a task-oriented culture and resilience, and these variables explained 12.5% of the variance in secondary traumatic stress. Conclusion : These findings suggest the importance of improving resilience and job satisfaction to enhance the professional quality of life in ICU nurses. Moreover, creating an innovation-oriented culture rather than a hierarchical and task-oriented culture can effectively improve the professional quality of life of ICU nurses.

• 한국전자통신학회논문지
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• 제17권4호
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• pp.703-708
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• 2022

k-평균 군집화는 대표적인 클러스터링 기법이다. 하지만 성능 평가 척도와 최소 개수의 군집을 정하는 방법에 대하여 통합하지 못한 한계가 있다. 본 논문에서는 수치적으로 최소 개수의 군집을 정하는 방법을 도입한다. 설명된 분산을 통합측도로 제시한다. 최소 개수의 군집과 설명된 분산 달성을 동시에 만족하려면 주성분 해석의 부공간에서 k-평균 군집화 방법을 수행해야한다는 것을 제시하고자 한다. 패턴인식과 기계학습에서 왜 주성분 분석과 k-평균 군집화를 순차적으로 수행하는가에 대한 설명을 원론적으로 제시한다.

• 대한간호학회지
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• 제37권5호
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• pp.715-723
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• 2007

Purpose: The purposes of this study were 1) to compare the contribution of demographic-behavioral variables and psychological variables in explaining the variance of depression, 2) identify the most important predictors of depression for Korean female adolescents. Method: The participants were 840 female adolescents. Data was collected through self-report questionnaires, which were constructed to include demographic-behavioral factors, self-esteem, hostility, hopelessness, and depression. Data was analyzed using the SPSS program. Result: Female adolescents' demographic-behavioral variables explained 17% of the variance in depression, and perceived physical health status, history of physical abuse, smoking, satisfaction of body weight, parental alcohol abuse, parental divorce, and history of suicidal attempt were the significant predictors of depression for female adolescents. Psychological variables explained 50% of the variance in depression, and self-esteem, hostility, and hopelessness were the significant predictors of depression for female adolescents. The significant predictors of depression among female adolescents' demographic-behavioral variables and psychological variables were self-esteem, hostility, hopelessness, perceived physical health status, parental alcohol problem, and history of physical abuse, explaining 52% of the variance in depression. Conclusion: In order to reduce depression in female adolescents, it is necessary to design an intervention program that emphasizes improving self-esteem while reducing hostility and hopelessness.

• 한국보건간호학회지
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• 제4권2호
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• pp.25-34
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• 1990

The Purpose of this study were 1) to find out the characteristics of health promoting Ii festyles of the study samples, 2) to determine the relationships of physical health and mental health, 3) to determine the relationships of health promoting lifestyles and health status. The health promotion model was tested with a volunteer sample of 141 female students in a university in Seoul. The health promoting lifestyle was measured by the scales developed by Walker and Pender(1987). Health status was measured by Cornell medical Index. Pearson's product moment correlations and stepwise multiple regression technique were used to analyze the data. The results are summarized as follows; 1. The items with the highest frequency of the subscales of health promoting lifestyle were 'look forward to the future' $(133,\;95.0\%)$ in self actualization, 'Enjoy being touched and touching people close to me' $(122,\; 87.14\%)$ in relationships with others. The strongest correlation was between general competence In self care and nutritional practice(r=5388, P<. 0001). 2. Fatigability, frequency of illness, miscellaneous diseases, habit, mood and feeling patterns were predictive of mental health. 3. Total health promoting lifestyles explained $14\%$ of the variance for health status. Relationships with others explained $20.9\%$ of the variance for health status. In conclusion, because the most variance explained was $420.9\%$, there must be other variables not accounted for by the model. that influence health promoting behaviors. Psychological factors accounted for more variance than other factors. Intervention studies focused on psychological factors as a means of altering behaviors have great potential for the design of interventions to increase health promoting behaviors. Further testing of the model with this population should be done.

• 대한지역사회영양학회지
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• 제20권1호
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• pp.1-10
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• 2015

Objectives: This study was conducted to develop and validate Eating Behaviors Test form (EBT) for infants and young children, including eating behaviors of their parents and parental feeding practices. Methods: Draft version of EBT form was developed after a pretest on 83 mothers. It was consisted of 42 questions including 3 components; eating behavior of children, eating behavior of parents, and parental feeding practices. Using these questionnaires, the first survey was conducted on 320 infants and children, 1 to 6 year old, for exploratory factor analysis, and the second survey was collected on 731 infants and children for confirmatory factor analysis. Results: Exploratory factor analysis on 42 questions of EBT form resulted in 3 factor model for children's eating behavior, 3 factor model for parents' eating behavior, and 1 factor model for parental feeding practices. Three factors for children's eating behavior could be explained as follows; factor 1, pickiness (reliability ${\alpha}=0.89$; explanation of variance=27.79), factor 2, over activity (${\alpha}=0.80$, explanation of variance=16.51), and factor 3, irregularity (${\alpha}=0.59$, explanation of variance=10.01). Three factors for mother's eating behavior could be explained as follows; factor 1,irregularities (${\alpha}=0.73$, explanation of variance=21.73), factor 2, pickiness (${\alpha}=0.65$, explanation of variance= 20.16), and factor 3, permissiveness (${\alpha}=0.60$, explanation of variance=19.13). Confirmatory factor analysis confirmed an acceptance fit for these models. Internal consistencies for these factors were above 0.6. Conclusions: Our results indicated that EBT form is a valid tool to measure comprehensive eating and feeding behaviors for infants and young children.

• Asian-Australasian Journal of Animal Sciences
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• 제33권10호
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.

• 농업생명과학연구
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• 제50권3호
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• pp.99-117
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• 2016

ssGBLUP을 이용한 전장 유전체 연관분석(ssGWAS)을 수행하기 위하여 이용한 표현형 자료는 2010년도부터 2015년까지 농협중앙회 한우개량사업소에서 후대 검정한 한우 거세우 총 1,829두의 부분육수율자료를 이용하였다. 유전체 자료는 Illumina Bovine 50K Beadchip을 활용하였으며 표현형 자료와 매칭이 되는 개체는 674두였다. 먼저 안심, 등심, 채끝 및 갈비수율의 유전체 육종가(GEBV)를 구하고 이를 통해 SNP 표지인자에 대한 효과와 SNP 표지인자의 분산을 계산하여 형질별 전체 유전분산 대비 SNP 표지인자의 효과를 추정한 후, QTL일 가능성이 있는 효과가 높은 SNP 좌위에 대한 결과를 주요하게 조사하였다. 안심수율의 경우, 상위 20개의 전체 유전분산 대비 SNP 표지인자의 효과에서 10번 염색체에서의 효과가 가장 높았는데 12,812,193 ~ 12,922,313bp 영역에서 전체 유전분산 대비 7.32 ~ 7.34%의 효과를 나타냈다. 채끝수율은 전체 유전분산에 대한 설명력이 가장 높은 SNP 표지인자를 포함하는 염색체는 24번 염색체로 38,158,543 ~ 38,347,278bp 영역이 약 8.36 ~ 8.56%의 전체 유전분산 대비 효과를 나타내었다. 등심수율은 다른 부분육 조사형질보다 낮은 SNP 표지인자의 효과를 나타내었다. 따라서 등심의 경우 보통 크기의 효과와 작은 효과를 갖는 많은 유전자들에 의해서 형질이 발현되는 것으로 사료된다.

• Child Health Nursing Research
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• 제7권4호
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• pp.494-510
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• 2001

As a family respond to any stressful situation as a whole system, cancer diagnosis of a child, as a serious life event, could be emotional shock to destroy homeostasis of the family system. A family has a resilient capacity to adjust and adapt to stressful events. Previous studies have been focused on family stress and adaptation, but little attention has been given to family value as one of resilient factors. The data for model testing were collected from July 18, 2000 to August 30, 2000 and the analysis included 309 parents of children who are diagnosed as cancer, 18 or less years of age, and treated either hospitalized or at the outpatient clinics. The data analysis utilized SAS 6.12 and LISREL 8 for descriptive statistics, correlation, cluster analysis, factor analysis, and LISREL. The study findings are as follows. 1) Monthly income (γ=-0.28, t=-5.81) was the most important factor to explain family strain along with family support (γ=-0.11, t=-2.43), severity of children's illness (γ=0.26, t=5.22), and family stressor (γ=0.22, t=4.62). All of these factors together explained 40％ of variance in family strain. 2) Among general family value, the relationship with the parents (γ=0.28, t=4.89) and relationship with the children (γ=0.20, t=3.60) showed positive effects to family value for cancer children, while relationship with the spouse (γ=-0.19, t=-3.22) and the age of the cancer children (γ=-0.11, t=-2.21) showed negative effects. These predictors together explained 22％ of variance in family value for cancer children. 3) Family hardiness was explained mostly by family strain (γ=-0.53, t=-8.65) along with direct negative effects of family persistency and indirect negative effects of severity of children's illness, family stressor, relationship with the spouse, and the children's age. Family value for cancer children was the most important predictor with positive effect (γ=0.44, t=6.76) along with indirect effects of monthly income, relationship with the parents, relationship with the children, support from family and significant others, and confidence with the health professionals. 51％ of variance in family hardiness was explained by all of these predictors. 4) The most important predictor for family adaptation was family stressor (γ=-0.50, t=-6.85) with direct and indirect negative effects along with the severity of children's illness (γ=-0.27, t=-5.21). However, family value for cancer children showed compromised total effect (γ=-0.13, t=-1.99) with negative direct effects (γ=-0.28, t=-3.43) and positive indirect effects (γ=0.14, t=3.01). Similarly, confidence with the health professionals also showed compromised total effect (γ=0.09, t=1.99) with positive direct effects and negative indirect effects. Family hardiness showed the biggest positive direct effects while other factors such as monthly income, family stressor, family persistence, support of family and significant others, relationship with the parents, relationship with the children, and relationship with the spouse, and children's age showed indirect effects only. 39％ of variance in family adaptation was explained by all of these predictors.

• 수산경영론집
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• 제14권2호
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• pp.1-14
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• 1983

This paper considers a classification of the 88 islands located at Kyong-nam area in Korea, using by examples of 12 components of the islands. By means of principal component analysis 2 principle components were extracted, which explained a total of 73.7% of the variance. Using an eigen variable criterion (λ>1), no further principle components were discussed. Principal component 1 and 2 explained 63.4% and 10.3% of the total variance respectively, The representation of the unrelated factor scores along the first and second principal axes produced a new information with respect to the classification of the islands. Based upon the representation, 88 islands were classified into 6 groups i. e. A, B, C, D, E, and F according to similarity of the components among them in this paper. The "Group F" belongs to a miscellaneous assortment that does not fit into the logical category. category.