International evaluation of modifiable social determinants of health on COVID-related mental health outcomes

可改变的健康社会决定因素对新冠病毒相关心理健康结果的国际评估

基本信息

项目摘要

Abstract A substantial body of research suggests that the COVID-19 pandemic has contributed to a rising incidence of mental health issues, irrespective of prior history of psychiatric diagnosis. One important driver of this phenomenon appears to be social isolation and loneliness induced by governmental policy responses such as social distancing recommendations, stay-at-home orders, and restrictions on travel. However, results thus far have been mixed across cohorts and geographic regions, and the social and individual factors underlying these differences remain poorly understood. Moreover, existing efforts have largely focused on high-income countries (HIC), which may not generalize to understudied low- and middle-income countries (LMIC), regions most impacted by the pandemic and where 85% of the world population lives. A key opportunity for mitigating future mental health impacts and increasing representation of marginalized groups in COVID-19 mental health research is to leverage individual-level longitudinal data harmonized across existing cohorts to develop a well-powered, large, global evaluation of pandemic-related mental health outcomes. Our proposal capitalizes on existing large international cohorts, establishing a COVID Global Mental Health Consortium (CGMHC) to increase our understanding of the modifiable social and individual risk factors predicting poor mental health in response to the pandemic, and to build an infrastructure to answer broader questions about the local and global determinants of COVID-19 related psychiatric outcomes, ultimately informing public policy, intervention, and prevention strategies. To accomplish this, we will integrate: (1) data from 23 international cohorts comprising mental health, sociodemographic, and social determinants of health (SDoH) from nearly 2.8 million individuals with pre- and post-pandemic assessments; (2) a novel target trial emulation framework to facilitate causal inference about the impact of specific pandemic policy strategies on mental health outcomes; and (3) recent advances in time-series modeling and novel risk prediction methods to understand the heterogeneity of mental health outcomes in response to social restrictions across a diverse range of countries. Our specific aims are to: (1) assemble longitudinal data across global cohorts, harmonizing data for downstream analyses and develop a data visualization platform for the scientific community; (2) characterize pandemic mental health trajectories along with their moderators and evaluate the evidence for a causal impact of social containment policies on psychiatric outcomes. (3) establish and formalize the CGMHC for continued research on the impact of the COVID-19 pandemic on global mental health and SDoH. Successful completion of these aims would provide a unique large-scale global cohort resource for the investigation of COVID-related mental health outcomes, inform intervention and policy strategies to mitigate future adverse impacts, and create an ongoing engine (the CGMHC) for collaborative research that can be sustained through future funding.
摘要 大量研究表明,COVID-19大流行导致了发病率的上升, 精神健康问题,无论以前是否有精神病诊断史。其中一个重要的驱动因素是 这种现象似乎是由政府的政策反应, 社交距离建议、居家令和旅行限制。然而,迄今为止的结果 在不同的群体和地理区域,以及这些因素背后的社会和个人因素中, 人们对差异仍然知之甚少。此外,现有的努力主要集中在高收入国家 (HIC),这可能不适用于研究不足的低收入和中等收入国家(LMIC), 世界上85%的人口生活在受大流行影响的地区。缓解未来的关键机会 心理健康影响和边缘化群体在COVID-19心理健康研究中的代表性增加 是利用现有队列中协调的个人水平纵向数据, 对流行病相关心理健康结果进行大规模全球评估。 我们的建议利用现有的大型国际队列,建立一个新冠病毒全球精神卫生 联盟(CGMHC),以增加我们对预测可改变的社会和个人风险因素的理解 精神健康状况不佳,以应对大流行病,并建立基础设施,以回答更广泛的问题, COVID-19相关精神病学结果的本地和全球决定因素,最终为公共政策提供信息, 干预和预防战略。为此,我们将整合:(1)来自23个国际组织的数据 队列包括心理健康,社会人口统计学和健康的社会决定因素(SDoH),从近2.8 (2)新的目标试验模拟框架, 促进关于特定流行病政策战略对精神卫生结果影响的因果推断; 以及(3)时间序列建模和新风险预测方法的最新进展,以了解 在不同的国家,心理健康结果的异质性是对社会限制的反应。 我们的具体目标是:(1)收集全球队列的纵向数据,协调数据, 下游分析,并为科学界开发一个数据可视化平台;(2)表征 流行性心理健康轨迹沿着及其调节者,并评估因果影响的证据 社会遏制政策对精神疾病的影响。(3)建立和正式化CGMHC, 研究COVID-19大流行对全球精神健康和SDoH的影响。成功完成 这些目标将提供一个独特的大规模全球队列资源的调查COVID相关的 心理健康结果,为干预和政策战略提供信息,以减轻未来的不利影响, 一个持续的引擎(CGMHC),用于合作研究,可以通过未来的资金来维持。

项目成果

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