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严重抑郁症的一个风险因素。COVID-19大流行