The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.
Recently, agricultural sites are automating into digital agricultural smart farms by applying technologies such as big data and Internet of Things (IoT). These smart farms aim to increase production and improve crop quality by measuring the environment of crops, investigating and processing data. Production prediction is an important study in smart farm digital agriculture, which is a high-tech agriculture, and it is necessary to analyze environmental data using big data and further standardized research to manage the quality of growth information data. In this paper, environmental and production data collected from smart farm strawberry farms were analyzed and studied. Based on regression analysis, crop production prediction models were analyzed using Ridge Regression, LightGBM, and XGBoost. Among the three models, the optimal model was XGBoost, and R2 showed 82.5 percent explanatory power. As a result of the study, the correlation between the amount of positive fluid absorption and environmental data was confirmed, and significant results were obtained for the production prediction study. In the future, it is expected to contribute to the prevention of environmental pollution and reduction of sheep through the management of sheep by studying the amount of sheep absorption, such as information on the growing environment of crops and the ingredients of sheep.
Objectives: The Indonesian Ministry of Health launched isoniazid preventive therapy (IPT) in 2016, with general practitioners (GPs) at the frontline of this program. However, the extent to which GPs have internalized this program remains uncertain. The aim of this study was to identify the knowledge and attitudes of GPs towards the IPT program in Indonesia. Methods: This study used an online, self-administered questionnaire distributed via e-mail and social messaging services. A logistic regression model was employed to identify the explanatory variables influencing the level of knowledge and attitudes toward IPT among GPs in Indonesia. An empirical analysis was conducted separately for each response variable (knowledge and attitudes). Results: Of the 418 respondents, 128 (30.6%) had a good knowledge of IPT. Working at a public hospital was the only variable associated with good knowledge, with an adjusted odds ratio (aOR) of 1.69 (95% confidence interval [CI], 1.02 to 2.81). Furthermore, 279 respondents (66.7%) had favorable attitudes toward IPT. In the adjusted logistic regression analysis, good knowledge (aOR, 0.55; 95% CI, 0.34 to 0.89), 1-5 years of work experience (aOR, 2.09; 95% CI, 1.21 to 3.60), and having experienced IPT training (aOR, 0.48; 95% CI, 0.25 to 0.93), were significantly associated with favorable attitudes. Conclusions: In general, GPs in Indonesia had favorable attitudes toward IPT. However, their knowledge of IPT was limited. GPs are an essential element of the IPT program in the country, and therefore, adequate information dissemination to improve their understanding is critical for the long-term viability and quality of the IPT program in Indonesia.
Journal of Korea Entertainment Industry Association
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v.14
no.8
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pp.315-322
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2020
This study was carried out to provide basic data for prevention of burnout by measuring levels of self-efficacy, social support and burnout that nursing students experienced during clinical practice and identifying factors influencing burnout. This is a descriptive research targeting 173 junior- and senior-year nursing students in Y area, and data were collected from October 15th to November 4th 2019. For data analysis, frequencies and percentages were calculated, and t-test and ANOVA were conducted along with the Scheffé test as a post-test. In addition, Pearson's correlation coefficients and multiple regression analysis were employed. The study results are as follows. There were significant differences in self-efficacy, social support and burnout depending on grades(t= -2.20, p=.029) and major satisfaction(F=3.62, p=.029) among general characteristics of nursing students. When analyzing correlations among self-efficacy, social support and burnout of nursing students, there was a positive correlation between self-efficacy and social support(r=.214, p=.005), a negative correlation between burnout and self-efficacy(r=-.253, p<.001) and a negative correlation between burnout and social support(r=-.175, p=.021). Major satisfaction(β= -.21, p=.006) had the biggest influence on burnout, and it was followed by self-efficacy(β= -.16, p=.032) and social support(β= -.15, p=.047). The explanatory power of the model was 13.8 percent. In conclusion, it is required to improve university life satisfaction and clinical practice satisfaction and develop programs, which enhance social support and self-efficacy, for preventing burnout of nursing students during clinical practice.
The purpose of this study is to investigate the influences of leisure satisfaction and burnout on job satisfaction of clinical nurses. The Data were collected the questionnaires consisted of general characteristics, leisure-related characteristics, leisure satisfaction, and burnout, and job satisfaction. For leisure satisfaction, the relaxation factor(16.57±2.68) was the highest among the sub-domains, and physical exhaustion(23.50±3.42) was the most severe for burnout. Leisure satisfaction and job satisfaction showed a positive correlation(r=.16, p=.013), and leisure satisfaction and burnout showed a negative correlation (r=-.19, p=.003). As factors related to job satisfaction, burnout(β=-0.68, p<.001) and ER(β=-0.12, p=.014) were found, and the total explanatory power was 47.0%, of which 44.0% was burnout. The model was found to be statistically significant(F=52.26, p<.001). The results of the study were as follows, a plan to improve leisure activities and leisure satisfaction is needed to reduce burnout. Through this, we aim to help improve the quality of life of clinical nurses.
Kim, Sang Hyeon;Gwon, Su A;Kwon, Yu Jin;Kim, Se In;Kim, Ye Jin;Oh, Hye Ran;Ha, Su Young;Cha, Nam Hyun
The Journal of the Convergence on Culture Technology
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v.8
no.5
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pp.161-169
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2022
The purpose of this study performed to confirm the effect of caffeine intake and stress on sleep quality of college students. Research respondents and data collection were conducted on 269 college students through Google questionnaires from February 14 to March 13, 2022, and the research design is a descriptive survey study. Statistical analysis was performed using the SPSS 27.0 version as t-test and one way ANOVA. As a result of the study, it was found that most college students consume more caffeine than the average daily caffeine intake of Korean adults, although it is far below the recommended daily caffeine intake of Korean adults. The quality of sleep of college students is stress (r=.32, p=<).001) and caffeine intake (r=.204, p=.001). It was found that there was a positive correlation. Factors affecting sleep quality are body mass index (β=.1.19, p<.001) Stress (β=.3.37, p<.001), smoking (β=-.18, p=.001), caffeine intake (β=.15, p=.005) It was in order, and the explanatory power of the model was 24.8%.
The aim of this study was to identify the factors affecting the mental health of high school students. The participants comprised 216 students in general high school. Data collection was conducted from May 1, 2020 to May 20, 2020. The data were analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient and a multiple regression analysis. The average score for self-esteem was 3.75±0.64(1-5), perceived stress was 2.86±0.58(1-5), emotional regulation ability was 3.43±0.65(1-5) and mental health was 1.91±0.71(1-5). Mental health had a statistically significant relationship with self-esteem(r=-.64, p<.001), emotional regulation ability(r=-.61, p<.001) and perceived stress(r=.54, p<.001). The factors affecting mental health were self-esteem(β=.46, p<.001), emotional regulation ability(β=-.37, p<.001), negative perceived stress(β=.17, p=.001) ; the explanatory power of the model was 60.0%. Therefore, it will be necessary to develop a program that can help high school students improve their self-esteem and control their negative emotions in order to promote their mental health.
The Journal of the Convergence on Culture Technology
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v.9
no.3
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pp.471-480
/
2023
The purpose of this study is to confirm the effect of recording online classes and real-time video classes on other behaviors, lecture satisfaction, and lecture flow in during the COVID-19 period. Data were collected and analysis using a structured questionnaire from May 20th to June 4th in 2021 for 550 nursing students in the D University. As a result of the study, it was found that there were more others behaviors in record online classes than in real-time online classes (t=-2.00, p=.046), lecture satisfaction(t=-1.54, p=.124) and lecture flow in real-time online classes it was higher in the record online classes (t=-.63, p=.529), but it was not statistically significant. However, the 2nd year students who participated in the two types of online classes showed statistically significantly higher lecture satisfaction (t=13.55, p=.000) and lecture flow(t=4.48, p=.004). And 4 th grade students of others behaviors was statistically significantly lower (t=4.68, p=.003). In the multiple regression analysis, the main factor affecting lecture flow was lecture satisfaction, and the explanatory power of the model was 55.1% in record online classes (F=128.49, p <.01), and in real-time classes 47.2%(F=77.24, p<.01). In the future, research should be conducted to confirm the difference between the two types of online classes of the same instructor and the difference in other things, lecture satisfaction, and class commitment that appear after applying learner-centered learning.
The purpose of this descriptive research study was to investigate health beliefs and self-efficacy in respiratory infection management as factors that affect the respiratory infection prevention behavior of college students. The subjects were 178 students attending a university in K city of Gyeongsangbuk-do. Data were collected with a structured questionnaire from September 1st to October 16th of 2020. The results of this study are as follows; Health belief was significantly different from participant's gender (t=-2.86, p=.005), major classification (F=2.95, p=.034), and taking any medications (t=2.18, p=.030). Self-efficacy in respiratory infection management was significantly different from university students' gender (t=-3.56, p=<.001) and major classification (F=4.59, p=.004). Health belief (r=.276, p<.001) and self-efficacy in respiratory infection management (r=.660, p<.001) had a positive correlation with respiratory infection preventive behavior. Multiple regression analysis results show that self-efficacy in respiratory infection management (β=.66, p<.001) significantly affected respiratory infection preventive behavior. The model had an explanatory power of 43%. The findings demonstrate that the major factor influencing the respiratory infection preventive behavior of university students is self-efficacy in respiratory infection management. Therefore, in order to promote behavior to prevent respiratory infection in college students, a program that can strengthen self-efficacy in respiratory infection management should be developed.
Journal of the Korean Applied Science and Technology
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v.39
no.6
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pp.727-737
/
2022
This study was conducted to identify the factors Influencing the burnout of general hospital nurses. Method: The study subjects were 150 nurses in three general hospital. The collected data were analyzed by t-test, ANOVA, Scheffe's test, Pearson's correlation coefficient, and Multiple regression analysis. Results: The factors affecting the burnout of the subjects, multiple regression analysis results showed that emotional intelligence(β=-.441, p<.001), emotional labor(β=.403, p<.001), current position was more than responsible nurse(β=-.111, p<.018), and health status was healthy(β=-.100, p<.029). In addition, the F statistics for the fitness of the estimated regression model were 35.51(p<.001), which was very significant. The explanatory power was 79.7%. Conclusion: The results of this study showed that emotional intelligence of the general hospital nurse was the most influential factor on burnout, and the higher the position, the better the health status, the lower the emotional labor, the lower the burnout. Therefore, the results of this study suggest that it is necessary to find ways to reduce emotional labor and improve health and emotional intelligence in order to reduce burnout of nurses, and it is considered to be useful as basic data for developing intervention programs to lower burnout.
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