Psychometric properties of a brief version of the COVID‐19 Stress Scales (CSS‐B) in young adult undergraduates
Bibliographic record
Abstract
We extracted items to create a brief version of the COVID-19 Stress Scale (i.e., CSS-B) and examined its psychometric properties in young adults. A sample of 1318 first- and second-year undergraduates from five Canadian universities (mean [SD] age = 19.27 [1.35] years; 77.6% women) completed an online cross-sectional survey that included the CSS-B as well as validated measures of anxiety and depression. The 18-item CSS-B fit well on both a 5-factor and a hierarchical model indicating that the five CSS-B dimensions may be factors of the same over-arching construct. The CSS-B factor structure displayed lower-order and higher-order configural and metric invariance across sites but not scalar invariance indicating that the intercepts/means were not consistent across sites. The CSS dimensions were positively related to measures of general anxiety and depression but not so strongly as to indicate that they are measuring the same construct. The CSS-B scale is a valid measure of COVID-19 stress among young adults. It is recommended that this shorter version of the scale be considered for use in longer surveys to avoid participant fatigue.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".