Measurement Properties and Cross-Cultural Invariance of the French Decisional Conflict Scale in Chronic Pain: Secondary Analysis of the DECIDE-PAIN Survey
Bibliographic record
Abstract
OBJECTIVES: Evidence on the validity of the French version of the Decisional Conflict Scale (DCS) remains limited, especially among people living with chronic noncancer pain in Canada. This study examined the measurement properties of the French 16-item DCS and assessed its cross-cultural measurement invariance in this population. METHODS: We conducted a secondary analysis of a pan-Canadian cross-sectional online survey following the Consensus-Based Standards for the Selection of Health Measurement Instruments guidance. We evaluated score distribution, including ceiling and floor effects. We assessed readability, internal consistency, structural validity of a hypothesized 5-factor model, and convergent and discriminant validities. We tested measurement invariance between the French and English versions. RESULTS: We analyzed data from 270 French-speaking Canadians (mean age = 51; 60% male; 54.8% with less than a university diploma; and 70.4% with limited health literacy). The French DCS showed good readability (Flesch-Kincaid Grade Level: 5.6), no ceiling or floor effects for the total score, and high internal consistency (ω = 0.95). The 5-factor structure was supported (CFI = 0.98). Convergent validity was confirmed (AVE: 0.61-0.72), but discriminant validity was poor (AVE < squared interfactor correlations). Measurement invariance was supported at configural, metric, scalar, and strict levels when compared with 985 English-speaking respondents (mean age = 51; 47.5% male; 50% with less than a university diploma; and 71.3% with limited health literacy). CONCLUSIONS: The French 16-item DCS has acceptable measurement properties and cross-cultural measurement invariance in people living with chronic noncancer pain. Further research is necessary to enhance its validity, possibly by reexamining its factor structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".