Healthcare use before and after suicide attempt in refugees and Swedish-born individuals
Bibliographic record
Abstract
PURPOSE: There is a lack of research on whether healthcare use before and after a suicide attempt differs between refugees and the host population. We aimed to investigate if the patterns of specialised (inpatient and specialised outpatient) psychiatric and somatic healthcare use, 3 years before and after a suicide attempt, differ between refugees and the Swedish-born individuals in Sweden. Additionally, we aimed to explore if specialised healthcare use differed among refugee suicide attempters according to their sex, age, education or receipt of disability pension. METHODS: All refugees and Swedish-born individuals, 20-64 years of age, treated for suicide attempt in specialised healthcare during 2004-2013 (n = 85,771 suicide attempters, of which 4.5% refugees) were followed 3 years before and after (Y - 3 to Y + 3) the index suicide attempt (t0) regarding their specialised healthcare use. Annual adjusted prevalence with 95% confidence intervals (CIs) of specialised healthcare use were assessed by generalized estimating equations (GEE). Additionally, in analyses among the refugees, GEE models were stratified by sex, age, educational level and disability pension. RESULTS: Compared to Swedish-born, refugees had lower prevalence rates of psychiatric and somatic healthcare use during the observation period. During Y + 1, 25% (95% CI 23-28%) refugees and 30% (95% CI 29-30%) Swedish-born used inpatient psychiatric healthcare. Among refugees, a higher specialised healthcare use was observed in disability pension recipients than non-recipients. CONCLUSION: Refugees used less specialised healthcare, before and after a suicide attempt, relative to the Swedish-born. Strengthened cultural competence among healthcare professionals and better health literacy among the refugees may improve healthcare access in refugees.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".