Inequalities in Mental Health in the Spanish Autonomous Communities: A Multilevel Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study was to analyze inequalities in the prevalence of poor mental health and their association with socioeconomic variables and with the care network in the Autonomous Communities in Spain. A cross-sectional multilevel study was performed, which analyzed individual data from the National Health Survey in Spain (ENS), in 2006 (n = 29,476 people over the age of 16). The prevalence of poor mental health was the dependent variable, measured by the General Health Questionnaire (GHQ-12 > = 3). Individual and contextual socioeconomic variables, along with mental health services in the Autonomous Communities, were included as independent variables. Models of multilevel logistic regression were used, and odds ratios (OR) were obtained, with confidence intervals (CI) of 95%. The results showed that there are inequalities in the prevalence of poor mental health in Spain, associated to contextual variables, such as unemployment rate (men OR 1.04 CI 1.01-1.07; women OR 1.02 CI 1.00-1.05). On the other hand, it was observed that inequalities in the mental health care resources in the Autonomous Communities also have an impact on poor mental health.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it