Home foreclosure and risk of psychiatric morbidity during the recent financial crisis
Bibliographic record
Abstract
BACKGROUND: A defining feature of the US economic downturn of 2008-2010 was the alarming rate of home foreclosure. Although a substantial number of US households have experienced foreclosure since 2008, the effects of foreclosure on mental health are unknown. We examined the effects of foreclosure on psychiatric symptomatology in a prospective, population-based community survey. METHOD: Data were drawn from the Detroit Neighborhoods and Health Study (DNHS), waves 1 and 2 (2008-2010). A probability sample of predominantly African-American adults in Detroit, Michigan participated (n=1547). We examined the association between home foreclosure between waves 1 and 2 and increases in symptoms of DSM-IV major depression and generalized anxiety disorder (GAD). RESULTS: The most common reasons for foreclosure were an increase in monthly payments, an increase in non-medical expenses and a reduction in family income. Exposure to foreclosure between waves 1 and 2 predicted symptoms of major depression and GAD at wave 2, controlling for symptoms at wave 1. Even after adjusting for wave 1 symptoms, sociodemographics, lifetime history of psychiatric disorder at wave 1 and exposure to other financial stressors between waves 1 and 2, foreclosure was associated with an increased rate of symptoms of major depression [incidence density ratio (IDR) 2.4, 95% confidence interval (CI) 1.6-3.6] and GAD (IDR 1.9, 95% CI 1.4-2.6). CONCLUSIONS: We provide the first prospective evidence linking foreclosure to the onset of mental health problems. These results, combined with the high rate of home foreclosure since 2008, suggest that the foreclosure crisis may have adverse effects on the mental health of the US population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".