Immigration, lack of control and psychological distress: Findings from the Oslo Health Study
Bibliographic record
Abstract
The aims of this study are to compare the level of psychological distress between Norwegian born and immigrants from countries with different income levels and culture, and to investigate the explanatory effect of socioeconomic and psychosocial factors, with special emphasis on lack of control (powerlessness and self-efficacy). A cross-sectional survey with self-administered questionnaire was conducted in 2000-2001 in a sample of 15,723 adults living in Oslo. Psychological distress was measured by a ten-item shortened version of Hopkins Symptom Checklist-25 items, whereas psychosocial variables were measured by various instruments. The results show that the level of psychological distress is significantly higher in immigrants from low- and middle-income countries than in the Norwegian born and the immigrants from high-income countries. They also report more powerlessness, more negative life events, less social support, less income and less paid work. It is concluded that negative life events, mainly related to social network, somatic health and economic situations, as well as lack of social support, are important mediators between immigration from low- and middle-income countries to Norway and psychological distress. Powerlessness also plays a role, but this is mainly because of a concept overlap between psychological distress and powerlessness.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".