Discrimination and mental health in Ecuadorian immigrants in Spain
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine the effects of ethnic discrimination on the mental health of Ecuadorian immigrants in Spain and to assess the roles of material and social resources. METHODS: Data were taken from the "Neighbourhood characteristics, immigration and mental health" survey conducted in 2006 in Spain. Psychological distress measured as "Possible Psychiatric Case" (PPC) was measured by the GHQ-28. A logistic regression was fitted to assess the association between PPC and discrimination. Interactions of discrimination with social and material resources were tested using product terms. RESULTS: Some 28% of the participants met our definition of PPC. About 20% of those who reported no discrimination were PPCs, rising to 30% of those who sometimes felt discriminated against and 41% of those who continually perceived discrimination. The OR for continuous discrimination was 12 (95% CI 3.5 to 40.3) among those with high financial strain, and 10 (2.4 to 41.7) when there was lack of economic support. Emotional support had an independent effect on PPC (OR 1.8, 95% CI 1.0 to 3.6, for those who reported having no friends). Social integration through a community group or association was positively related to the probability of being a PPC (OR 1.7, 95% CI 1.0 to 2.9). CONCLUSION: Ethnic discrimination is associated with psychological distress in these Ecuadorian immigrants in Spain. Discrimination effects may be exacerbated among those facing economic stress and those without economic support. These particularly vulnerable immigrants should be the subject of social and health interventions.
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How this classification was reachedexpand
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 | 0.024 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".