Validation of the French-Canadian Pelvic Girdle Questionnaire
Bibliographic record
Abstract
OBJECTIVE: Pain in the pelvic girdle area is commonly reported during pregnancy and the postpartum period, and its impact on quality of life is considerable. The Pelvic Girdle Questionnaire (PGQ), developed in 2011 in Norway, is the only condition-specific tool assessing pelvic girdle pain-related symptoms and disability. The questionnaire was recently translated and adapted for the French-Canadian population. The objective of this study was to assess the measurement properties of the previously translated French-Canadian PGQ. METHODS: Eighty-two women with pelvic girdle pain were included in this validation study. The French-Canadian PGQ, pain intensity Numeric Rating Scale, and Oswestry Disability Index were completed by participants at baseline, 48 hours later, and 3 to 6 months later to assess test-retest reliability, construct validity, responsiveness, floor and ceiling effects, and internal consistency. RESULTS: Reliability analyses indicated an intraclass correlation coefficient of 0.841 (95% confidence interval [CI] 0.750-0.901) for the global score. Construct validity analyses indicated a Spearman rank correlation coefficient of 0.696 with the Oswestry Disability Index. Responsiveness analyses identified an effect size of 0.908 (95% CI 0.434-1.644) and an area under the receiver operating characteristics curve of 0.823 (95% CI 0.692-0.953). There was no floor or ceiling effect, and internal consistency analyses indicated a Cronbach α of .933 for the activity subscale and .673 for the symptom subscale. CONCLUSION: Overall, the French-Canadian version of the PGQ is reliable, valid, and responsive, suggesting that it can be implemented in both research and clinical settings to assess functional limitations in pregnant and postpartum women.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".