Assessing differential item functioning for the Social Appearance Anxiety Scale:a Scleroderma atient-centred Intervention Network (SPIN) Cohort Study
Bibliographic record
Abstract
Objectives The Social Appearance Anxiety Scale (SAAS) is a 16-item questionnaire developed to evaluate fear of appearance-based evaluation by others. The primary objective of this research was to investigate the existence of differential item functioning (DIF) for the 16 SAAS items, comparing patients who completed the SAAS in English and French, either to confirm that scores are comparable or provide guidance on calculating comparable scores. A secondary research objective was to investigate the existence of DIF based on sex and disease status. A tertiary research objective was to assess DIF related to language, sex, and disease status on the recently developed SAAS-5. Design This was a cross-sectional analysis using baseline data from patients enrolled in the Scleroderma Patient-centred Intervention Network (SPIN). Setting SPIN patients included in the present study were enrolled at 43 centres in Canada, USA, UK, France and Australia, with questionnaires completed in April 2014 to July 2019. Participants 1640 SPIN patients completed the SAAS in French (n=600) or English (n=1040). Primary and secondary measures The SAAS was collected along with demographic and disease characteristics. Results Six items were identified with statistically significant language-based DIF, four with sex-based DIF and one with disease type-based DIF. However, factor scores before and after accounting for DIF were similar (Pearson correlation >0.99), and individual score differences were small. This was true for both the full and shortened versions of the SAAS. Conclusion SAAS and SAAS-5 scores are comparable across language, sex, and disease-type, despite small differences in how patients respond to some items.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".