Psychometric properties of Persian version of Cognitive Behavioural Avoidance Scale: results from student, general population and clinical samples in Iran
Bibliographic record
Abstract
BACKGROUND: There is no published evidence about the psychometric properties of the Cognitive Behavioral Avoidance Scale (CBAS) in Eastern cultures. AIMS: The current research evaluated the psychometric properties of a Persian version of the CBAS. METHOD: The research consisted of two studies. In Study 1, a university student sample (n = 702) completed the CBAS, the Beck Depression Inventory-II, the Thought Control Questionnaire and the Anxious Thoughts Inventory. In Study 2, a general population sample (n = 384) and a clinical sample (n = 152) completed the CBAS, the Young Compensation Inventory and the Depression, Anxiety, Stress Scale-21. RESULTS: Exploratory factor analysis of the data from Study 1 suggested a four-factor solution for CBAS. The CBAS had acceptable internal consistency and test-re-test reliability, and showed significant correlations with depression symptoms and anxious thoughts. Confirmatory factor analysis of the data from Study 2 indicated good fit between the four-factor model and data. The CBAS had a significant relationship with depression, anxiety and stress symptoms, but no associations with schema compensatory behaviour strategy. Finally, the CBAS and its subscales successfully distinguished a clinical sample from a general population sample. CONCLUSIONS: The findings provide preliminary evidence for reliability and validity of the CBAS among Iranian student, general population and clinical samples.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".