Depression and its psychosocial correlates among older Asian immigrants in North America: A critical review of two decadesâ research
Bibliographic record
Abstract
This article critically reviews two decades of empirically based depression studies on older Asian immigrants (OAIs) in North America published in English. The Psychosocial Model of Late-Life Depression is proposed as the conceptual roadmap to help interpret the findings across studies. Methods: Using multiple bibliographic databases, this review systematically summarized and evaluated findings in 24 studies in terms of: (a) the prevalence and severity of depression; (b) demographic, psychosocial, cultural, and health risk factors of depression; and (c) methodological approaches and designs. Results: The results showed that depression is prevalent among OAIs and is linked to gender, recency of immigration, English proficiency, acculturation, service barriers, health status, relationship with children and family, and social support. However, considerable variability in the results, the sample sizes, and the use of measurements were also found across studies. Discussion: Recommendations for future research and the provision of clinical and community services are discussed within the psychosocial model.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".