Improving Data Collection of Debt and Financial Strain to Assess Health Impacts of Economic Insecurity

改进债务和金融紧张的数据收集，以评估经济不安全对健康的影响

• 批准号: 10416007
• 负责人: Lawrence M Berger
• 金额: $ 67.09万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10416007
• 关键词: Adult; Behavior; Benchmarking; COVID-19 impact; COVID-19 pandemic; Characteristics; Child; Child Support; Cognitive; Data; Data Analyses; Data Collection; Data Reporting; Demographic Analyses; Development; Disadvantaged; Economics; Education; Employment; Equipment and supply inventories; Family; Financial Hardship; Friends; Goals; Gold; Health; Heterogeneity; Household; Income; Individual; Inequality; Intervention; Interview; Knowledge; Legal; Link; Low Income Population; Low income; Mainstreaming; Measures; Middle Class Populations; Modeling; Patient Self-Report; Performance; Personal Satisfaction; Persons; Pilot Projects; Play; Policies; Population Analysis; Poverty; Qualitative Research; Questionnaires; Race; Randomized; Reporting; Research Design; Respondent; Role; Sampling; Security; Social Welfare; Social Work; Source; Student Loan; Surveys; United States; Wisconsin; Work; cognitive interview; cost; data infrastructure; data quality; demographics; economic evaluation; economic impact; experience; experimental study; financial literacy; improved; instrument; lower income families; population health; programs; racial disparity; social; sociodemographics

Project Summary/Abstract Individual and household debt plays an increasingly important role in the dynamics of inequality in the United States. However, current data limitations impede scientific understanding of the role of indebtedness in reducing or exacerbating economic insecurity. At best, existing social surveys collect data on a subset of mainstream debts most often encountered by middle-class populations (mortgages, credit cards, auto loans, student loans), while debts common to low-income populations (payday loans, legal debts, past due bills, child support arrears, loans from employers, family, and friends) are less well represented. Without better data, scientific analyses of population health and wellbeing may understate and misidentify crucial sources of economic insecurity and disadvantage, as well as reciprocal effects of debt with poverty, health, and family functioning. This project consists of a multi-pronged data collection and analysis effort to build a stronger data infrastructure, more adequate and accurate measures of indebtedness, and best practices for analyzing various forms of indebtedness and their relation to economic hardship and financial strain for low-income families. The project has three Specific Aims: (1) To conduct qualitative cognitive and developmental interviews with low-income families on their experiences with debt and use these results to develop an enhanced survey instrument that comprehensively and accurately captures low-income debt holding; (2) To field a two-wave pilot study designed to allow comparison of data quality and accuracy when collected via the enhanced instrument versus current ‘gold standard’ instruments (instruments will be randomly assigned); and (3) To analyze linked pilot survey, high-quality administrative (employment, earnings, and benefit receipt), and individual credit report data to (a) document consistency of self- reported debt data collected via each instrument with credit report data; (b) examine whether consistency and differences by data collection instrument differ by respondent financial literacy and sociodemographic characteristics (education, race); (c) estimate associations of types and amounts of debt using the enhanced module, existing modules, and credit report data with economic hardship and financial strain; and (d) investigate the causal order of associations of (the three measures of) debt with economic hardship and financial strain. The study will be the first to provide detailed data on the full range of types and amounts of indebtedness among low-income populations and their associations with hardship and financial strain. By improving data collection and analysis, the study had the potential to identify policy levers that could reduce potential negative effects of debt on disadvantaged families and better target interventions to lessen economic insecurity and improve well-being.

项目摘要/摘要 个人和家庭甲板在不平等动态中起越来越重要的作用 美国。但是，当前的数据限制阻碍了科学的理解 减少或加剧经济不安全感的债务。充其量，现有的社会调查收集 中产阶级人口最常遇到的主流债务子集的数据 （抵押，信用卡，汽车贷款，学生贷款），而低收入人群共有的债务 （发薪日贷款，法律债务，过去的应付账单，儿童抚养费，雇员，家庭和家庭的贷款 朋友的代表不太好。没有更好的数据，对人口健康的科学分析和 福祉可能会低估和误导经济不安全感和灾难的关键来源， 以及债务与贫困，健康和家庭功能的相互影响。这个项目包括 多管齐下的数据收集和分析工作，以建立更强大的数据基础架构，更多 足够，准确的债务衡量，以及分析各种形式的最佳实践 债务及其与低收入家庭的经济困难和财务压力的关系。 项目具有三个特定的目的：（1）进行定性认知和发展访谈 低收入家庭在债务的经验中使用这些结果来发展 增强的调查工具可全面，准确地捕获低收入债务； （2）进行两波试点研究，旨在允许比较数据质量和准确性 通过增强仪器与当前的“金标准”仪器收集（仪器将是 随机分配）； （3）分析链接的试点调查，高质量行政（就业， 收益和收益收据），以及个人信用报告数据（a）自我的文档一致性 报告了通过每种工具收集的债务数据，并提供信用报告数据； （b）检查是否 一致性和数据收集工具的差异通过响应财务素养和 社会人口统计学特征（教育，种族）； （c）估计类型和金额的关联 使用增强的模块，现有模块和信用报告数据带有经济困难的债务 和财务压力； （d）研究（三个措施）关联的因果关系 经济困难和财务压力，甲板。该研究将是第一个提供有关的详细数据 低收入人群中的全部类型和债务范围及其数量 与艰辛和财务压力的关联。通过改善数据收集和分析，该研究 有可能识别有可能减少债务潜在负面影响的政策杠杆 处境不利的家庭，更好地将干预措施以减少经济不安全感并改善 福利。