影响 COVID-19 封锁期间青少年心理健康的因素:孟加拉国横断面研究

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS IEEE Transactions on Computational Social Systems Pub Date : 2024-01-31 DOI:10.1109/TCSS.2024.3350087
Al Muktadir Munam;Ahammad Hossain
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引用次数: 0

摘要

2019 年冠状病毒病(COVID-19)大流行自 2019 年开始以来已威胁到全球经济、生计和身心健康。本研究旨在探讨 COVID-19 大流行如何影响具有代表性的孟加拉国青年样本的心理健康,并找出影响因素。通过社交媒体,采用横断面方法,要求 390 人参与在线调查。采用卡方检验法检验心理健康状况与其他变量之间的关联。结果发现,由于封锁,分别有 59.3% 和 21% 的参与者在心理健康方面受到严重和中度影响。心理健康状况不佳与家庭状况、职业、婚姻状况、避免握手、清洁和消毒常用物品和表面、社区知识、对生计的影响、食物供应、日常行为、对教育的影响以及对心理健康的影响密切相关。为了确定解释变量对心理健康状况调整赔率(AOR)的影响,采用了一个 95% 置信区间(CI)的多项式逻辑回归(MLR)模型,P 值小于 0.05。MLR 的结果显示,年龄、婚姻状况、参与者的家庭成员因 COVID-19 生病的风险、对工资的影响、身体和精神虐待、封闭的学校等显著预测了心理健康结果。这项研究有助于深入了解 COVID-19 爆发期间的心理健康情况。
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Factors Influencing Mental Health Among Youth During the COVID-19 Lockdown: A Cross-Sectional Study in Bangladesh
The Coronavirus Disease of 2019 (COVID-19) pandemic has threatened the global economy, livelihoods, and physical and mental health since it began in 2019. This study aimed to examine how the COVID-19 pandemic affected the mental health of a representative sample of Bangladeshi youth and to identify the influencing factors. Through social media, 390 people were asked to participate in an online survey using the cross-sectional methodology. The chi-square test was used to examine the associations between the status of mental health and other variables. It was found that because of the lockdown, 59.3% and 21% of the participants were severely and moderately affected in terms of mental health, respectively. Poor mental health outcomes are strongly associated with family status, profession, marital status, avoiding shaking hands, cleaning and disinfecting objects and surfaces which are frequently used, knowledgeable community, impact on livelihood, food availability, routine behavior, impact on education, and impact on mental health. A multinomial logistic regression (MLR) model with 95% confidence interval (CI) with a p-value < 0.05 was used to determine the effect of explanatory variables on the adjusted odds ratio (AOR) of mental health status. The results of MLR showed that age, marital status, the risk of participants of their family members getting sick from COVID-19, impact on wages, physical and mental abuse, closed schools, etc., significantly predicted mental health outcomes. This study facilitated a deeper understanding of mental health during the COVID-19 outbreak.
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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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