Factor analysis of the 9-item Psychological Stress Measure in a French Canadian non-clinical student sample
Bibliographic record
Abstract
The aim of this study is to test the unidimensional 9-items factorial model, about psychological stress, with a non-clinical sample of Canadian students, evaluated by the metric principals of factorial analysis and internal consistency. A sample of 546 university students (Women = 79.6%, Men = 20.4%, Mean age = 23.2, Standard Deviation = 7.3) were used. The results of the exploratory factorial analysis (explaining about 55.3% of the total variance of the construct) and confirmatory (GFI = 0.994, AGFI = 0.991, CMIN / DF = 3.77, RMSEA = 0.071, CFI = 0.985) satisfactorily confirmed its unidimensionality. The results of the internal consistency study, obtained by Cronbach's Alpha, McDonald's Omega, Greatest Lower Bound coefficient, and also the EAP scores, ensure the accuracy of the tested model. New studies should explore and test other important metric qualities of this instrument (content validity and test-retest reliability, among others).
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".