• Korean Journal of Adult Nursing
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• v.18 no.1
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• pp.71-80
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• 2006

Purpose: This study was to investigate the factors influencing the quality of life of patients with hemophilia and to provide the data for health promoting intervention in order to improve their quality of life. Method: The subjects of this study were involved 186 male patients with hemophilia by convenience sampling. These results were analyzed statistically by frequency, percentage, t-test, ANOVA, Pearson Correlation Coefficient, and Stepwise multiple regression. Results: There were significant differences in the quality of life according to the frequency of bleeding. Quality of life showed negative relationships and health problems, bleeding, limitation of joint motion, and depression with stepwise Multiple Regression analysis for quality of life revealed that the most powerful predictor was depression. Depression, health problem, and limitation of joint motion accounted for 64.6% of the variance in the quality of life of patients with hemophilia. Conclusion: Therefore it is necessary to develop nursing interventions with these variables to increase the quality of life for patients with hemophilia.

• Journal of muscle and joint health
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• v.19 no.3
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• pp.272-281
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• 2012

Purpose: The purpose of this study was to identify levels of perceived stigma, self-esteem, quality of life and factors influencing on quality of life in people with Hansens' disease. Methods: The subjects were 128 people in Sorokdo National Hospital, two nursing homes, and three settlements. The stigma scale, self-esteem scale, and World Health Organization's quality of life instrument were used. Data were collected through self-reported questionnaires from July to August, 2010 and analyzed by t-test, ANOVA, Ducan's multiple range test, Pearson's correlation coefficients, and stepwise multiple regression by SAS. Results: The level of perceived stigma was 3.93, self-esteem was 26.2, quality of life was 2.78. Self-esteem was positively associated with quality of life. Through the multiple regression, it was found that self-esteem and job were factors influencing of quality of life with 43% of predictability. Conclusion: It was found that self-esteem and job were important for people with Hansen's disease. To improve the quality of life in people with Hansen's disease, it is necessary to develop nursing interventions fostering self-esteem and decreasing perceived stigma.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.3 no.2
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• pp.183-199
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• 1996

The Purpose of this study is to develop and test a nursing model which can be applied to prediction of the quality of life for the patient receiving hemodialysis. A hypothetical model was constructed on Johns & Meleis's empowerment model framework which has 3 contsructs(stress, resource, empowerment). 6 Factors(perceived stress, self-esteem as personal resource, perceived social support as social resource, perceived fertigue, perceived health status & self efficacy as empowerment) were selected to pre dict the quality of life of receiving hemodialysis patients. 4 Factors(self-esteem, perceived social support, perceived health status & self efficacy) had direct effects on the quality of life significantly. Self-esteem had indirect effect on the quality of life via perceived heath status significantly. Perceived social support had indirect effect on the quality of life via self-effcacy significantly. Perceived stress had no direct and indirect effect on the quality of life significantly. Revised model from hypothetical model showed better fit to the data by eliminating unsignificant path. From results of this study we suggest that to improve quality of life of hemodialysis patient nurses provide nursing interventions which improve self-esteem, perceived social support, self-efficacy & perceived health status.

• Journal of Gastric Cancer
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• v.15 no.2
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• pp.121-126
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• 2015

Purpose: We evaluated the socio-personal and clinical factors that can affect preoperative quality of life to determine how to improve preoperative quality of life in patients with gastric cancer. Materials and Methods: The preoperative quality of life data of 200 patients (68 females and 132 males; mean age $58.9{\pm}12.6years$) with gastric cancer were analyzed according to socio-personal and clinical factors. The Korean versions of the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core (QLQ) 30 and the EORTC QLQ-STO22, a gastric cancer-specific module, were used to assess quality of life. Patients were asked to complete the questionnaire preoperatively by themselves. Results: Patients with a higher academic background and stage I disease tended to have higher global health status scores. Highly educated younger men had better physical functioning scores. Highly educated and well-nourished patients with stage I cancer had higher role functioning scores. Married patients had better emotional scores. The symptom scales were affected by sex, age, education level, nutrition, and cancer stage. Conclusions: Preoperative quality of life in patients with gastric cancer can be improved by nutritional support and treatment of symptoms caused by disease progression. Psychological support may be helpful for patients with a poor quality of life.

• Journal of Distribution Science
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• v.22 no.4
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• pp.115-126
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• 2024

Purpose: This study aims to explore the citizens' perceptions of the smart city distribution strategy and its impact on quality of life, classifying generations into two groups: Generation X with Baby Boomers, and Millennials with Generation Z. This study formulated research questionsto explore how both generational groups perceive the impact of smart city experience, government's role, technology development, economic, social, and environmental factors, and institutional improvement on quality of life. Additionally, this study explored the influence of quality of life on city evaluation, life satisfaction, and the expected growth of the city. Research design, data and methodology: This study employed an online survey conducted by well-known research organization. This study utilized factor and regression analysis for data analysis. Results: This study revealed that the impact of smart city experience, technology development and social value on quality of life demonstrated significance in both generational groups. Additionally, the study identified significant results regarding the influence of quality of life on city evaluation, life satisfaction, and the expected growth of the city. Conclusions: The findings suggest that, for the development of smart cities, stakeholders should particularly consider economic value and environment aspects, as these factors ultimately impact on quality of life.

• Research in Community and Public Health Nursing
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• v.28 no.1
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• pp.1-12
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• 2017

Purpose: The purpose of this study is to examine factors affecting quality of life among grandparents raising their grandchildren. Methods: This study carried out a secondary analysis of data from the 2014 Korean Longitudinal Study of Aging (KLoSA) and Statistics Korea. Data collected from 224 grandparents who reported raising their grandchildren were analyzed using descriptive statistics, independent t-test, ANOVA, pearson correlation coefficient, and multilevel regression analysis. Results: The mean score of the participants' quality of life was 62.63. Significant predictors of quality of life of the grandparents included subjective health status, last year's total house income, number of last year's travels, frequency of last year's movie seeing, and number of children's parks per 100,000 population. Conclusion: These results suggest that public health nurses in improving quality of life of grandparents focus on children's parks and formal social supports as community factors as well as regular exercise as an individual factor in order to be more effective.

• The Korean Journal of Health Service Management
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• v.12 no.4
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• pp.139-154
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• 2018

Objectives: The aim of this study was to examine factors influencing health-related quality of life of waged workers. Methods: This study used data from the Seventh Korea National Health and Nutrition Examination Survey. Data were analyzed with the $x^2-test$, t-test, ANOVA, and multiple regression. Results: The significant predictors of health-related quality of life were depression, subjective health status, age, activity limitation, education, worker status, monthly income, drinking, smoking, physical injury, stress, and moderate physical activity. Conclusions: Personal health characteristics, psychological characteristics, socioeconomic characetrictics and working characetrictics affect health-related quality of life. Health-related quality of life is also affected by social structural problems such as socioeconomic factors and employment instabilitye. In addition to the development of health care programs to improve health-related quality of life of twaged workers, policy changes are needed to improve the social structure.

• Journal of Korean Critical Care Nursing
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• v.16 no.3
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• pp.73-86
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• 2023

Purpose : This study aimed to identify the factors affecting the quality of life of lung transplant patients. Method : The participants were patients who received lung transplants at a general hospital in City Y. Data were collected through structured questionnaires from June 2023 to August 2023. General characteristics, lung transplantation-related characteristics, quality of life, functional disability, treatment compliance, social support, anxiety, and depression-were measured. For data analysis, hierarchical multiple regression was performed using SPSS/WIN 29.0. Results : In the final model, quality of life was associated with income, self-help group attendance, functional disability, social support, treatment compliance, and anxiety and depression. Together, they explained 61.2% of the total variance in the results. Conclusion : Our findings suggest that improving lung transplant patients' quality of life requires active intervention in stress management to perform treatment instructions well, a social support system that can help them financially, and encouraging and participating in social activities as patients.

• Journal of Families and Better Life
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• v.7 no.2
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• pp.127-144
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• 1989

The resulting rapid urbanization in the several decades caused increasing residential mobility. The purpose of this study is to analyse systematically the effects of residential mobility on the family quality of life and the factors that cause residential mobility. For this purpose, 976 housewives were sampled from the households in Seoul. The data were analysed by such statistical methods as multiple regression, crosstabulation, ANOVA test and path analysis. The main results obtained are as follows; 1) A significant proportion of the urban households are experienced frequent residential mobility. 2) Among the factors that affect residential mobility, the most important factors are family income, tenure type, and residential satisfaction. 3) Residential satisfaction is an important intervening variable in residential mobility. 4) It has been observed that family quality of life was affected by residential mobility patterns. Analysis has revealed that quality of life de eloped remarkably by changing for residential location, especially in education environment for their children.

• Journal of Home Health Care Nursing
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• v.27 no.2
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• pp.156-168
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• 2020

Purpose: This study aimed to examine factors influencing health-related quality of life (HRQOL) and compare them between young-aged and old-aged patients with cancer. Methods: Data of 291 patients (young-aged: 168, old-aged: 123) were obtained from the 10th wave of the 2015 Korea Health Panel Survey. The HRQOL was measured using the Korean version of Euro-QoL-5D. Independent t-test, analysis of variance, and multiple regression analysis were performed to identify factors influencing HRQOL. Results: The average HRQOL score was 0.87±0.10 and 0.82±0.15 among young-aged and old-aged, respectively. The factors differed partially between the two groups. For young-aged, the influencing factors were activity restriction, subjectively perceived health status, and smoking. For old-aged, the influencing factors were activity restriction, subjective health status, and unmet healthcare needs. Conclusion: Strategies to improve the HRQOL of elderly adults need to be developed considering the age group. Additionally, studies that include clinical factors such as symptoms are required to prepare need-based practical approaches for better quality of life of such patients.