Psychometric Evaluation of the Social Anxiety Scale for Adolescents in a School-based Sample of Korean Youths: A Rasch Analysis
Bibliographic record
Abstract
PURPOSE: This study evaluated the Korean Social Anxiety Scale for Adolescents (K-SAS-A) using Rasch analysis, examined gender-related differential item functioning (DIF), and assessed measurement precision in a school-based sample. METHODS: Self-report data from 481 Korean adolescents (ages 14-16; 49.9% girls) were analyzed with the Andrich Rating Scale Model. We evaluated category functioning, item fit, dimensionality (PCA of residuals), local independence (residual correlations), reliability/separation, and gender DIF (ETS classification). RESULTS: The original five-category scale showed insufficient separation between categories 2 and 3; collapsing to a four-category format improved category functioning and overall fit. Seven items (#2, #5, #9, #10, #11, #13, #15) were removed based on misfit and content considerations. The refined instrument satisfied unidimensionality (first contrast eigenvalue = 1.8) and local independence (residual |r| ≤ .28). Person separation = 2.22 (reliability = .83; ≈3.3 strata); item separation = 8.11 (reliability = .99). In the full item set, two items (#1, #18) showed slight-to-moderate gender DIF; no meaningful DIF remained in the proposed nine-item short form, which consists of items #3, #4, #6, #7, #8, #12, #14, #16, and #17. CONCLUSIONS: A four-category response format and a nine-item short form yield a unidimensional, reliable measure of adolescent social anxiety with reduced respondent burden. Minor redundancy between two items (#6, #12) warrants consideration in future refinements.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".