Depression, Isolation, and Social Connectivity Online (DISCO)

抑郁、孤立和在线社交联系 (DISCO)

• 批准号: 10612642
• 负责人: ROY H. Perlis
• 金额: $ 189.38万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-09 至 2025-09-08
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10612642
• 关键词: Address; Adult; Age; Behavior; Black race; COVID-19; COVID-19 impact; COVID-19 pandemic; Censuses; Cessation of life; Characteristics; Collaborations; Communities; Computing Methodologies; Containment; Data; Data Analyses; Data Set; Depressed mood; Disease; Elderly; Elements; Enrollment; Hispanic; Household; Individual; Informatics; Internet; Intervention; Investigation; Knowledge; Loneliness; Longevity; Major Depressive Disorder; Measures; Mental Depression; Mental Health; Methods; Mood Disorders; Nature; Outcome; Patient Self-Report; Persons; Policies; Policy Analysis; Population; Risk; Risk Factors; SARS-CoV-2 infection; Schools; Scientist; Series; Social Behavior; Social Impacts; Social Interaction; Social Network; Social isolation; Social support; Subgroup; Surveys; Time; Underserved Population; United States; Variant; Virus; Vulnerable Populations; Work; behavior measurement; college; coronavirus disease; depressive symptoms; design; disability; economic impact; innovation; minority communities; multidisciplinary; novel; pandemic disease; power analysis; remote interaction; response; social; social media; stressor; underserved community; vulnerable community; young adult

Social isolation represents a risk factor for major depression across the lifespan. The COVID-19 pandemic has contributed to unprecedented disruption in social networks, as a result both of the disease itself and the measures required to contain it. Vulnerable and underserved communities have been particularly impacted in both of these regards, with greater rates of COVID-19 infection as well as greater economic and social impact of closures and restrictions. It is not surprising, then, that rates of major depressive symptoms in the United States have approached levels 3 to 4 times those observed before the pandemic. Beginning to address the rise of social disconnection and its contribution to depression requires a better understanding of the aspects of social networks most disrupted by the pandemic, and how they relate to depression, especially among individuals in vulnerable communities. Identifying targets for intervention also requires understanding how online social behavior may compensate for, or exacerbate, effects of social disconnection. Furthermore, it is necessary to understand how external factors in a community such as containment policies may contribute to or moderate social disconnection and depression. To address these critical questions, this study will use data from the Covid States Project, a 50-state survey conducted approximately every 8 weeks since April 2020, which has enrolled more than 260,000 unique individuals, including 125,000 from households earning less than $50,000 per year. Beyond symptoms of depression, the survey asks detailed questions about social networks and social support, as well as online activity, impact of COVID-19, and a range of other topics. The first aim of the study will characterize, in well-powered analysis of individual subgroups, the relationship between specific aspects of social networks and depressed mood, and identify features that may moderate these effects. In aim 2, using an innovative browser extension, the study will characterize online behavior among 1200 individuals completing the survey. In aim 3, the study will integrate survey data with longitudinal data at the state and census tract level regarding pandemic containment policies, mobility, and COVID-19 cases and death. These latter two aims will provide a novel understanding of how online behavior, and external factors, impact social networks and moderate their relationship with depression. The study will build on a highly productive collaboration for the past 2 years between the PI, with expertise in informatics methods for studying mood disorders, and the Northeastern PI, a computational social scientist with expert in large-scale surveys and investigation of social networks. The consultants, who have worked closely with the PIs on the survey, bring additional expertise in survey design and analysis, investigation of time series data including mobility data, and policy analysis. The study will identify targets for interventions to address social disconnection and its impact on depression, particularly among vulnerable populations, providing critical guidance regarding where to focus such interventions.

社会孤立是一生中患上严重抑郁症的一个危险因素。COVID-19疫情 由于疾病本身和病毒的影响，对社交网络造成了前所未有的破坏 脆弱和得不到充分服务的社区受到的影响尤其严重， 在这两个方面，COVID-19感染率更高，经济和社会影响更大 关闭和限制。因此，在美国， 各国的发病率已接近大流行前的3至4倍。开始解决 社会脱节及其对抑郁症的贡献需要更好地了解社会的各个方面， 大流行病破坏最严重的网络，以及它们与抑郁症的关系，特别是在 弱势群体。确定干预的目标还需要了解在线社交网络如何 行为可以弥补或加剧社会脱节的影响。此外，还必须 了解社区中的外部因素（如遏制政策）如何有助于或缓和 社会脱节和抑郁。为了解决这些关键问题，这项研究将使用来自新冠肺炎的数据， 国家项目，自2020年4月以来大约每8周进行一次的50个州的调查， 超过260，000个独特的个人，其中125，000人来自年收入低于50，000美元的家庭。 除了抑郁症的症状，调查还询问了有关社交网络和社会支持的详细问题， 以及在线活动、COVID-19的影响和一系列其他主题。研究的第一个目标是 在对各个亚组的有效分析中，描述特定方面之间的关系 社交网络和抑郁情绪，并确定可能缓和这些影响的功能。在aim 2中，使用 创新的浏览器扩展，这项研究将描述1200个人的在线行为， 调查.在目标3中，研究将把调查数据与州和人口普查区一级的纵向数据结合起来 关于疫情防控政策、流动性以及COVID-19病例和死亡。后两个目标将 提供了一个新的理解，如何在线行为，外部因素，影响社交网络和适度 与抑郁症的关系。这项研究将建立在过去两年富有成效的合作基础上 在PI，具有研究情绪障碍的信息学方法的专业知识，和东北PI， 计算社会科学家，擅长大规模调查和社交网络研究。的 顾问在调查中与PI密切合作，带来了调查设计方面的额外专业知识， 分析、调查包括流动性数据在内的时间序列数据以及政策分析。该研究将确定 为解决社会脱节问题及其对抑郁症的影响，特别是 这一战略为弱势群体提供了重要的指导，说明应在哪些方面重点采取这类干预措施。