Income and psychological distress: the role of the social environment.
Bibliographic record
Abstract
BACKGROUND: This article examines the relationship between lower income and the risk of experiencing high psychological distress over twelve years. DATA AND METHODS: Data from the first 12 years of the longitudinal National Population Health Survey (1994/1995 through 2006/2007) were analysed. Proportional hazards modelling was conducted to determine whether lower household income was associated with a greater risk of experiencing high distress, when adjusting for sociodemographic characteristics and baseline health status. It was also used to examine the relationship between reporting a stressor and experiencing a subsequent episode of distress. RESULTS: Overall, 11% of the initial sample experienced at least one episode of high distress during the 12 years of the study. Low-income respondents were at a significantly higher risk of becoming psychologically distressed, and many of the stressors were associated with a significantly higher risk of becoming distressed. Stressors accounted for 22% of the relationship between low income and distress for men, and more than a third of this relationship for women. INTERPRETATION: Low income is an important risk factor for becoming psychologically distressed, and stressors account for part of this increased risk.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".