Chronic Pain and Mood Disorders in Asian Americans
Bibliographic record
Abstract
Purpose: Pain and mood disorder frequently coexist. Yet, for Asian Americans (AAs), scant information about pain and mood disorder is available. Our aims were to compare (1) the rates of pain and mood disorders and (2) the magnitude of associations between pain and mood disorders between AAs and European Americans (EAs), and across different Asian subgroups. Methods: An analytical data was constructed from the Collaborative Psychiatric Epidemiology Studies (CPES), a representative sample of community-residing U.S. adults (n = 9,871). Pain morbidity was assessed by self-report. Mood disorders, including major depression and anxiety disorders, were assessed using the diagnostic interview. Analysis included descriptive statistics and multivariate logistic regression modeling. All analyses were weighted to approximate the U.S. populations, and controlled for sociodemographic and immigration characteristics. Results: Greater proportion of EAs, compared to AAs, endorsed lifetime pain (56.8% vs. 35.8%). Having life pain disorders elevated the likelihood of lifetime mood disorder by more than 2-folds (weight adjusted odds ratio (WAOR): 2.12, 95% CI: 1.77, 2.55). Having pain disorders over the past 12 months elevated the likelihood of mood disorder in the same time period by more than 3-folds (WAOR: 3.29, 95% CI: 2.02, 5.37) among AAs. The magnitude of the association between pain and psychiatric morbidity were greater in Vietnamese Americans compared to other AAs and EAs. Discussion: The conventional belief that rates of pain and mood disorders are greater in AAs than EAs may need to be further examined. Vietnamese Americans may be particularly vulnerable for experience of comorbid pain and mood disorders.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".