Évaluation de la structure factorielle et des qualités psychométriques de l'Échelle de Fatigue Pandémique parmi la population adulte québécoise: Evaluation of the factorial structure and psychometric qualities of the Pandemic Fatigue Scale among Quebec adult population
Bibliographic record
Abstract
OBJECTIVE: The objective of the study is to evaluate the factorial structure and the psychometric qualities of the Pandemic Fatigue Scale among the Quebec adult population. METHOD: The data analyzed come from a web survey conducted in October 2021 among 10 368 adults residing in Quebec. The scale's factor structure and invariance by gender, age and language used to complete the questionnaire were tested using confirmatory factor analyses. Convergent and divergent validity were also assessed. Finally, the reliability of the scale was estimated from the alpha and omega coefficients. RESULTS: The analyzes suggest the presence of a bidimensional structure in the sample of Quebec adults with informational fatigue and behavioral fatigue. The invariance of the measure is noted for sex, for age subgroups and for the language used for the questionnaire. The results of convergent and divergent validity provide additional evidence for the validity of the scale. Finally, the reliability of the scale scores is excellent. CONCLUSION: The results support the presence of a bidimensional structure as in the initial work of Lilleholt et al. They also confirm that the scale has good psychometric qualities and that it can be used among the adult population of Quebec.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".