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: 10669577
• 负责人: Lawrence M Berger
• 金额: $ 66.9万
• 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/10669577
• 关键词: Adult; Behavior; COVID-19 impact; COVID-19 pandemic; Characteristics; Child; Child Support; Cognitive; Data; Data Analyses; Data Collection; Data Reporting; Demographic Analyses; Development; Disadvantaged; Disparity population; Economics; Education; Employment; Equipment and supply inventories; Family; Family Demographies; Financial Hardship; Friends; Goals; 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; 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; economic evaluation; economic impact; experience; experimental study; financial literacy; health assessment; 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.

项目总结/文摘