Examining Anxiety and Depression Comorbidity Among Chinese and European Canadian University Students
Bibliographic record
Abstract
Clark and Watson’s tripartite model of comorbidity between anxiety and depression has been well-supported by empirical evidence among European descent samples in North America. Its applicability to Chinese biculturals remains to be challenged due to two Chinese-specific symptom reporting style in somatization and under-endorsement of positive affect. The current study began with an evaluation of a revised Clark and Watson’s tripartite model of comorbidity by adopting a comprehensive assessment of anxiety- and depression-specific component, and by incorporating cognitive aspects of symptomatology. The revised model’s applicability to a Chinese Canadian university sample was then empirically tested, followed by an investigation of the potential impact of cultural experiences on symptomatology. Item response theory (IRT)–informed statistical analyses were applied to each of the 14 anxiety and depression symptom measures that 251 European Canadian and 206 Chinese Canadian university student participants completed to remove items that functioned differentially across samples. Sample-specific exploratory factor analyses identified a two-factor structure (Affective-Somatic and Cognitive) among the Chinese Canadian sample, and a three-factor structure (Mixed, Cognitive, and Autonomic Hyperarousal) among the European Canadian sample. Worry and Autonomic Hyperarousal scales reflected the most between-group structural differences. These results indicated that different cultural groups responded differently to clinical assessment items commonly used in North America, and that applicability of the tripartite model of comorbidity across cultural groups was limited. Symptom factors were found related to specific (i.e., negative acculturative experiences and collective self-esteem) but not to generic indicators of acculturation (i.e., Chinese or Canadian Orientation).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".