Related Experiment Video
Updated: Aug 12, 2025
03:53
Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
1.3K
Sex Differences in COVID-19 Infection Fear in a Community Sample of Korean Adults Using Quantile Regression
Hyunjoo Na1, Young-Eun Jung2, Chang Park3
1College of Nursing, The Catholic University of Korea, Seoul, Korea.
Journal of Korean Medical Science
|January 31, 2023
Summary
This study found that women experience greater fear of coronavirus disease 2019 (COVID-19) infection than men, particularly at lower levels of fear. These sex differences in COVID-19 fear were statistically significant.
Area of Science:
- Psychology
- Public Health
- Sociology
Background:
- The COVID-19 pandemic has heightened public anxiety and fear of infection.
- Understanding demographic variations in fear responses is crucial for targeted public health interventions.
- Previous research indicates potential sex differences in emotional responses to health crises.
Purpose of the Study:
- To investigate the relationship between sex and the level of fear of COVID-19 infection.
- To examine how sex influences the distribution of COVID-19 infection fear within a population.
- To explore potential correlations between COVID-19 infection fear, sex, and depressive symptoms.
Main Methods:
- A community sample of 483 Korean adults was surveyed using a quota sampling strategy.
- Self-report questionnaires assessed COVID-19 infection fear, depressive symptoms, and demographic characteristics.
- Quantile regression analysis was employed to examine the association between sex and COVID-19 infection fear across different levels of fear.
Main Results:
- Significant differences in both COVID-19 infection fear (P = 0.001) and depression (P = 0.008) were observed between males and females.
- Sex was a significant predictor of COVID-19 infection fear.
- Women reported significantly higher levels of COVID-19 infection fear compared to men, especially at the milder end of the fear spectrum (20th and 30th percentiles).
Conclusions:
- Sex is a significant factor influencing the fear of COVID-19 infection.
- Women exhibit greater fear of COVID-19 infection than men, particularly in the mild fear categories.
- Findings highlight the need to consider sex-specific approaches in mental health support and public health messaging related to infectious disease outbreaks.
More Related Videos
Related Concept Videos
01:29Bias in Epidemiological Studies
481
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
481
01:12Relative Risk
271
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
271
01:20Comparing the Survival Analysis of Two or More Groups
245
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
245
01:25Statistical Methods for Analyzing Epidemiological Data
461
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
461
01:27Confounding in Epidemiological Studies
214
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
214
01:14Wilcoxon Signed-Ranks Test for Median of Single Population
200
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
200