Development and validation of the Ryerson Social Anxiety Scales (RSAS)
Bibliographic record
Abstract
Background: Extant self-report measures of social anxiety primarily assess the breadth of social situations in which respondents feel anxious, rather than assessing severity in terms of the distress and impairment that individuals experience due to their social anxiety symptoms. This paper describes the development and validation of the Ryerson Social Anxiety Scales (RSAS; Rogojanski et al., 2019 Rogojanski, J., Hood, H. K., Vorstenbosch, V., & Antony, M. M. (2019). Social Anxiety Severity Scale. Ryerson University. [Google Scholar]; see Appendix), a new measure for assessing both the breadth of situations that trigger social anxiety and the severity (i.e., distress and impairment) associated with social anxiety, across two studies.Method/Design: Two samples of university students (N = 501 total) completed demographic and self-report symptom measures. In Study 1, participants completed the RSAS and several other measures of psychological symptoms. In Study 2, participants completed the same measures and were also assessed for the presence of Social Anxiety Disorder (SAD) using a semistructured clinical interview.Results: Across both samples, the RSAS demonstrated excellent internal consistency and incremental validity. It consistently emerged as a unique predictor of psychosocial impairment. In Study 2, increases in RSAS scores were associated with increased odds of having SAD.Conclusions: The RSAS has robust psychometric properties and fills an important gap among available measures for assessing SAD severity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".