School of Economics and Management, Tsinghua University, Beijing, China.
Adelaide Business School, University of Adelaide, Adelaide, SA, Australia.
Front Public Health. 2022 May 19;10:791977. doi: 10.3389/fpubh.2022.791977. eCollection 2022.
There is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship.
We aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics.
A two-wave online survey of 406 managers from 26 countries was performed in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ-9) symptoms.
We found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers' anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms.
Cumulative COVID-19 statistics predicted managers' anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.
针对 2019 年冠状病毒病（COVID-19）大流行的公开统计数据作为各国心理健康预测指标的研究有限。由于经理面临特殊困难，他们在大流行期间面临患精神障碍的风险。
我们旨在使用国家层面的 COVID-19 统计数据预测各国经理的精神障碍（焦虑和抑郁）症状。
2020 年 5 月和 7 月，我们对来自 26 个国家的 406 名经理进行了两次在线调查。我们主要分析使用逻辑面板回归模型，并使用普通最小二乘回归进行稳健性检查。在样本中，26.5%的经理达到了焦虑（一般焦虑障碍-7；GAD-7）的临界值，43.5%的经理达到了抑郁（患者健康问卷-9；PHQ-9）症状的临界值。
我们发现，累计 COVID-19 统计数据（例如，累计病例、每百万人累计病例、累计死亡人数和每百万人累计死亡人数）正向预测经理的焦虑和抑郁症状，而每日 COVID-19 统计数据（每日新增病例、平滑每日新增病例、每日新增死亡人数、平滑每日新增死亡人数、每日新增病例每百万人和每日新增病例每百万人）则负向预测焦虑和抑郁症状。此外，繁殖率是一个正向预测因素，而政府封锁措施的严格程度则是一个负向预测因素。单独来看，我们发现累计死亡人数是预测焦虑和抑郁症状的最合适的单一预测指标。
累计 COVID-19 统计数据正向预测经理的焦虑和抑郁症状，而每日非累计 COVID-19 统计数据则负向预测焦虑和抑郁症状。累计死亡人数是预测焦虑和抑郁症状的最合适的单一预测指标。繁殖率是一个正向预测因素，而政府封锁措施的严格程度则是一个负向预测因素。
