Appraisal of Social Concerns: A cognitive assessment instrument for social phobia
Bibliographic record
Abstract
The current study describes the validation of a new cognitive assessment measure for social phobia, entitled the Appraisal of Social Concerns (ASC). Item content is relevant to a range of social situations. The ASC can be used to tailor interventions to patients' idiosyncratic concerns. Data are presented from both clinical (n = 71) and non-clinical (n = 550) samples. Preliminary data indicate that the ASC has good internal consistency and test-retest reliability. The construct validity of the ASC is comparable to that of well-established measures in use with social phobics. A strength of the ASC is its sensitivity to the effect of treatment. An exploratory factor analysis yielded three factors tapping concerns about negative evaluation, observable symptoms, and social helplessness. Subscale scores were strongly correlated. Preliminary findings suggest that the ASC is a psychometrically sound, time efficient instrument that can be used for both clinical and research purposes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".