Anxiety and Depression: Congruent, Separate, or Both?1
Bibliographic record
Abstract
This study investigated whether using state‐trait distinctions of both depression and anxiety would allow for further identification of the unique and overlapping features of these two symptom structures. Three hundred and seventy‐one undergraduate students (122 men, 249 women) responded to questionnaires exploring both state and trait depression and anxiety. Results revealed that women reported higher levels of depression and anxiety for all measures except for state anxiety, where men scored higher than women. Results also demonstrated stronger within‐construct correlations (i.e., state depression with trait depression) than between construct correlations (i.e., state depression with trait anxiety), supporting the distinctness of the two constructs. The uniqueness of depression and anxiety was further supported by factor analysis. Overlap in symptoms also occurred, but the correlations were generally stronger for congruent symptom types (i.e., state depression and state anxiety rather than state depression and trait anxiety). Results are discussed in terms of viewing depression and anxiety as distinct constructs with overlapping features.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".