Russians in Treatment: The Evidence Base Supporting Cultural Adaptations
Bibliographic record
Abstract
OBJECTIVE: Despite large waves of westward migration, little is known about how to adapt services to assist Russian-speaking immigrants. In an attempt to bridge the scientist-practitioner gap, the current review synthesizes diverse literatures regarding what is known about immigrants from the Former Soviet Union. METHOD: Relevant empirical studies and reviews from cross-cultural and cultural psychology, sociology, psychiatric epidemiology, mental health, management, linguistics, history, and anthropology literature were synthesized into three broad topics: culture of origin issues, common psychosocial challenges, and clinical recommendations. RESULTS: Russian speakers probably differ in their form of collectivism, gender relations, emotion norms, social support, and parenting styles from what many clinicians are familiar with and exhibit an apparent paradoxical mix of modern and traditional values. While some immigrant groups from the Former Soviet Union are adjusting well, others have shown elevated levels of depression, somatization, and alcoholism, which can inform cultural adaptations. CONCLUSIONS: Testable assessment and therapy adaptations for Russians were outlined based on integrating clinical and cultural psychology perspectives.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".