Testing the associations between poverty stigma and mental health: The role of received stigma and perceived structural stigma
Bibliographic record
Abstract
BACKGROUND: Previous research has documented how people living on low incomes in the United Kingdom (UK) and internationally experience various forms of poverty stigma. The purpose of this study was to quantitatively examine how experiences of poverty stigma are associated with mental health outcomes. METHODS: An online, cross-sectional survey was conducted with 1,000 adults living in predominantly low- and middle-income households in the UK. The survey included a questionnaire designed to measure participants' experiences of different forms of poverty stigma, as well as measures of anxiety, depression and mental well-being. FINDINGS: Exploratory and confirmatory factor analyses of the poverty stigma questionnaire supported a two-factor solution. One factor reflected participants' experiences of being mistreated and judged unfairly by other people because they live on low income (received stigma) and the other factor reflected participants' perceptions of how people living in poverty are treated by media outlets, public services and politicians (perceived structural stigma). Both received and perceived structural stigma were independently associated with anxiety, depression and mental well-being and these relationships persisted after controlling for socioeconomic indicators. There was also evidence that received stigma and perceived structural stigma partially mediated the relationships between financial hardship and mental health outcomes. DISCUSSION: Experiences of received and perceived structural poverty stigma are both associated with mental health and well-being. This suggests that addressing interpersonal and structural forms of poverty stigma may help to narrow socioeconomic inequalities in mental health.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".