Factors influencing death anxiety of nursing students

박정아,; 박창기,; Lee, Yoon-Ju

doi:10.7465/jkdi.2018.29.5.1227

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…In this study, uncertainty risk and opportunity were evaluated using quantile regression analysis, rather than classical regression analysis. Unlike classical regression analysis, which estimates determinants based on the conditional mean of the dependent variable, quantile regression analysis can be used when the determinants of the dependent variable for each quantile differ based on the conditional distribution of the dependent variable (Park et al, 2018 ). In other words, quantile regression analysis is a method for estimating the relationship between an explanatory variable and a dependent variable by obtaining the conditional quantile of the dependent variable.…”

Section: Methodsmentioning

confidence: 99%

Anxiety, depression, and uncertainty appraisal and factors affecting uncertainty risk and opportunity appraisal of health care workers in Korea during the COVID-19 outbreak

Kim

2023

Health Psychology and Behavioral Medicine

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Background: Due to the prolonged period of COVID-19, the uncertainty related to COVID-19 is bound to increase for healthcare workers (HCWs) in tertiary medical institutions as much as for the HCWs in dedicated hospitals. Purpose: To assess anxiety, depression, and uncertainty appraisal, and to determine the factors affecting uncertainty risk and opportunity appraisal experienced by HCWs at the forefront of COVID-19 treatment. Method: This was a descriptive, cross-sectional study. The participants were HCWs at a tertiary medical center in Seoul. HCWs included medical (doctors, nurses) and non-medical (nutritionists, pathologists, radiologists, office workers, etc.) personnel. Self-reported structured questionnaires (patient health questionnaire, generalized anxiety disorder scale, and uncertainty appraisal) were obtained. Finally, responses from 1337 people were used to evaluate factors affecting uncertainty risk and opportunity appraisal using a quantile regression analysis. Results: The average ages of medical and non-medical HCWs were 31.69 ± 7.87 and 38.66 ± 11.42 years, and the proportion of females was high. The rates of moderate to severe depression (23.23%) and anxiety (6.83%) were higher in medical HCWs. The uncertainty risk score was higher than the uncertainty opportunity score for all the HCWs. Factors that increased uncertainty opportunity were a decrease in depression in medical HCWs and a decrease in anxiety in non-medical HCWs. Increase in age was directly proportional to uncertainty opportunity in both groups. Conclusion: There is a need to devise a strategy to reduce uncertainty among HCWs who inevitably face various infectious diseases that appear in the near future. In particular, since there are various types of non-medical as well as medical HCWs in medical institutions who can prepare an intervention plan that comprehensively considers the characteristics of each occupation and the distribution of risks and opportunities of uncertainty will be able to improve the quality of life of HCWs and further promote the health of the people.

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Section: Methodsmentioning

confidence: 99%

Anxiety, depression, and uncertainty appraisal and factors affecting uncertainty risk and opportunity appraisal of health care workers in Korea during the COVID-19 outbreak

Kim

2023

Health Psychology and Behavioral Medicine

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“…Quantile regression analysis is a complementary method, and it has the advantage of constructing a linear model around τ-quantiles to determine related factors for each quantile. This method can even be used when the normality and homoscedasticity required for regression analysis are violated [ 13 ]. Therefore, in this study, by analyzing factors related to the high-risk drinking rate among yearly alcohol users at the local community level using a quantile regression analysis, we intend to produce supporting data necessary for future regional health projects in Korea.…”

Section: Introductionmentioning

confidence: 99%

Factors Related to Regional Variation in the High-risk Drinking Rate in Korea: Using Quantile Regression

Kim

Nam

2021

J Prev Med Public Health

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Objectives: This study aimed to identify regional differences in the high-risk drinking rate among yearly alcohol users in Korea and to identify relevant regional factors for each quintile using quantile regression. Methods: Data from 227 counties surveyed by the 2017 Korean Community Health Survey (KCHS) were analyzed. The analysis dataset included secondary data extracted from the Korean Statistical Information Service and data from the KCHS. To identify regional factors related to the high-risk drinking rate among yearly alcohol users, quantile regression was conducted by dividing the data into 10%, 30%, 50%, 70%, and 90% quantiles, and multiple linear regression was also performed. Results: The current smoking rate, perceived stress rate, crude divorce rate, and financial independence rate, as well as one’s social network, were related to the high-risk drinking rate among yearly alcohol users. The quantile regression revealed that the perceived stress rate was related to all quantiles except for the 90% quantile, and the financial independence rate was related to the 50% to 90% quantiles. The crude divorce rate was related to the high-risk drinking rate among yearly alcohol users in all quantiles. Conclusions: The findings of this study suggest that local health programs for high-risk drinking are needed in areas with high local stress and high crude divorce rates.

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Factors Affecting the Patient Safety Management Activity of Nursing Students: A Quantile Regression Approach

강

장

송

2020

J Korean Acad Nurs Adm

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The purpose of this study was to identify factors affecting the Patient Safety Management Activity (PSMA) of nursing students according to levels of PSMA based on the Theory of Planned Behavior (TPB). Methods: A descriptive study was used. The participants were 135 nursing students from universities in Korea. Data were collected with self-reported questionnaires through online survey. The questionnaire consisted of PSMA scale and modified version of the TBP-based questionnaire. Data were analyzed using multiple linear regression and quantile regression. Results: The average score of PSMA was 4.09±0.44 out of 5 points. In the multiple linear regression, patient safety education, subjective norm, perceived behavioral control and intention were significant factors. In the quantile regression, place of clinical practice (in 75%), patient safety education (in 50% and 90%), subjective norm (in 75%), perceived behavioral control (in 50% and 75%) and intention (in 50%) were significant factors. Conclusion: We confirmed the dynamic influences of all factors according to the levels of PSMA. It is proposed that the affecting factors according to the levels of PSMA should be considered in designing effective programs to enhance PSMA among nursing students.

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Factors influencing death anxiety of nursing students

Cited by 3 publications

References 22 publications

Anxiety, depression, and uncertainty appraisal and factors affecting uncertainty risk and opportunity appraisal of health care workers in Korea during the COVID-19 outbreak

Anxiety, depression, and uncertainty appraisal and factors affecting uncertainty risk and opportunity appraisal of health care workers in Korea during the COVID-19 outbreak

Factors Related to Regional Variation in the High-risk Drinking Rate in Korea: Using Quantile Regression

Factors Affecting the Patient Safety Management Activity of Nursing Students: A Quantile Regression Approach

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