Validation of a French Canadian version of the Organizational Policies and Practices (OPP) questionnaire
Bibliographic record
Abstract
Organizational factors are potentially powerful in accounting for work-related chronic disability following a musculoskeletal disorder. This study documents the psychometric qualities of the French Canadian version of the Organizational Policies and Practices questionnaire (OPP) [1] on a population of nurses (N=124). By excluding the two items composing the ergonomic practices factor, a factorial structure identical to that obtained by the OPP's authors is obtained for the disability management policies and practices factor, the people-oriented culture factor and the safety climate factor. The internal consistency coefficients (Cronbach's alpha) are satisfactory while the coefficients intraclass are less than those obtained by the authors in the test-retest. However, the test-retest interval is greater in this study. Consistent relationships are observed between the dimensions of the OPP and three job-related psychosocial indicators: perceived stress, social support and satisfaction. This suggests a good construct validity for the OPP. Although additional validation efforts are recommended, all of the results obtained support the validity and reliability of the French Canadian version of the OPP. This version can be used to examine the importance of organizational aspects in studies on the prevention of chronic disability.
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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 | 0.010 | 0.019 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".