2020 至 2022 年大流行相关担忧对印度心理健康的影响

Youqi Yang, Anqi Sun, Lauren Zimmermann, Bhramar Mukherjee
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引用次数: 0

摘要

本研究探讨了 2020 年至 2022 年与大流行相关的担忧如何影响印度成年人的心理健康。研究利用全球 COVID-19 趋势和影响调查(N = 2,576,174 人)的数据,探讨了担忧变量(经济压力、粮食不安全和 COVID-19 相关健康担忧)与自我报告的抑郁和焦虑症状之间的关联。我们的分析以完整病例(N = 747,996 例)为基础,采用调查加权模型,并对人口统计学和日历时间进行了调整。研究发现,这些担忧与心理健康结果之间存在明显关联,其中经济压力是影响抑郁(调整后赔率:2.36;95% 置信区间:[2.27, 2.46])和焦虑(调整后赔率:1.91;95% 置信区间:[1.81, 2.01])的最重要因素。)带有交互项的模型显示,性别、居住状况和日历时间是影响调节因素。这项研究表明,Facebook 等社交媒体平台可以有效地收集大规模调查数据,以跟踪公共卫生危机期间的心理健康趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of pandemic-related worries on mental health in India from 2020 to 2022

Impact of pandemic-related worries on mental health in India from 2020 to 2022
This study examines how pandemic-related worries affected mental health in India’s adults from 2020 to 2022. Using data from the Global COVID-19 Trends and Impact Survey (N = 2,576,174), it explores the associations between worry variables (financial stress, food insecurity, and COVID-19-related health worries) and self-reported symptoms of depression and anxiety. Our analysis, based on complete cases (N = 747,996), used survey-weighted models, adjusting for demographics and calendar time. The study finds significant associations between these worries and mental health outcomes, with financial stress being the most significant factor affecting both depression (adjusted odds ratio, aOR: 2.36; 95% confidence interval, CI: [2.27, 2.46]) and anxiety (aOR: 1.91; 95% CI: [1.81, 2.01])). Models with interaction terms revealed gender, residential status, and calendar time as effect modifiers. This study demonstrates that social media platforms like Facebook can effectively gather large-scale survey data to track mental health trends during public health crises.
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