The Beck Anxiety Inventory–Trait (BAIT): A Measure of Dispositional Anxiety Not Contaminated by Dispositional Depression
Bibliographic record
Abstract
We describe development of the Beck Anxiety Inventory–Trait (BAIT), a measure of trait anxiety. In Study 1 with 191 undergraduates, the BAIT correlated higher with another trait-anxiety measure than with state anxiety and trait depressiveness and lower with depressiveness than the other trait-anxiety measure did. In Study 2 (Ns of 149 undergraduates initially and 107 at 3 weeks later), the BAIT demonstrated convergent validity against the Beck Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988 Beck, A. T., Epstein, N., Brown, G. and Steer, R. A. 1988. An inventory for measuring clinical Anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56: 893–897. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) and self-rated trait anxiety plus discriminant validity against abstract curiosity. In Study 3 (Ns of 161 undergraduates initially and 121 at 3 weeks later), the BAIT correlated more highly with another anxiety measure than with depression, stress, positive affect, and negative affect. It also showed good internal consistency across studies and high stability in Studies 2 and 3, higher than the BAI's in Study 2. Factor analyses across studies all supported 2 factors, 1 Somatic and 1 Subjective.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".