Factor structure and validity of the State-Trait Inventory for Cognitive and Somatic Anxiety.
Why this work is in the frame
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Bibliographic record
Abstract
The State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA; Ree, French, MacLeod, & Locke, 2008) is a relatively new measure of anxiety. The current research investigated the factor structure and reliability of scores on the STICSA and the validity of the interpretation of STICSA scores in a sample of undergraduate students. Participants completed a battery of self-report questionnaires online, including measures of anxiety, depression, affect, and social desirability. Scores on the 4 subscales of the STICSA-Trait Cognitive, Trait Somatic, State Cognitive, and State Somatic-exhibited good internal consistencies (αs ≥ .92). Results of a confirmatory factor analysis provided support for a hierarchical model of the STICSA including a global anxiety factor plus 4 specific factors corresponding to the STICSA subscales. Support was also found for a four-factor model, with factors corresponding to the STICSA subscales. Pearson product-moment correlations with other measures of anxiety provided evidence of the convergent validity of the interpretation of STICSA scores, and Pearson product-moment correlations with measures of depression and affect provided evidence of the divergent validity of the interpretation of STICSA scores. The STICSA is the only existing self-report anxiety measure that contains scales measuring state and trait anxiety as well as cognitive and somatic anxiety. Comparisons between the convergent and divergent validity of test score interpretations of the STICSA and the State-Trait Anxiety Inventory (STAI; Spielberger et al., 1983) revealed that the STICSA has better convergent validity with measures of somatic anxiety and better divergent validity with measures of depression and affect. (PsycINFO Database Record
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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) | 0.000 | 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 it