Translation and Validation of the Toronto Pain Management Index, French–Canadian Version
Bibliographic record
Abstract
Background To provide effective pain management, nurses must have sufficient knowledge and adequate beliefs about pain management. In Quebec, however, nurses seem to be generally uninvolved in pain management, and there is little significant evidence shedding light on nurses' pain management knowledge and beliefs in postoperative settings. To perform such studies, a valid questionnaire in French to assess nurses' knowledge and beliefs is required. Some valid questionnaires are available in English, but none are available in French. Purpose This article describes the process of translation, adaptation, and preliminary validation of the Toronto Pain Management Index into French. Results For temporal stability of the Toronto Pain Management Index, French-Canadian version, the result of intraclass correlation coefficient for the total score of this questionnaire is 0.59 (CI: 0.44-0.72). Conclusion Following this process, the French version of this questionnaire has suitable face and content validity and can be used to evaluate nurses' knowledge and beliefs about pain management in postoperative settings.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".