Validation of the French Version of the Weiss Functional Impairment Rating Scale–Self-Report in a Large Cohort of Adult Patients With ADHD
Bibliographic record
Abstract
Objective: To analyze the psychometric properties of the French version of the Weiss Functional Impairment Rating Scale–Self Report (WFIRS-S) in a large clinical sample of adults with ADHD. Method: Patients ( N = 363) were diagnosed with ADHD according to the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) criteria. Psychometric properties of the French version of the WFIRS-S were tested including construct validity with a confirmatory factor analysis, internal structural validity with Cronbach’s alpha coefficient, external validity by correlations with the Beck Depression Inventory–II (BDI-II), and the EuroQol five-dimension (EQ-5D) questionnaire. Results: The confirmatory factor analysis found the following: root mean square error of approximation (RMSEA) = 0.061, 90% confidence interval (CI) = [0.058, 0.063]; comparative fit index (CFI) = 0.67. Cronbach’s alpha coefficient was .91. Correlations with EQ-5D descriptive index, visual analogue scale (VAS) scores, and BDI-II scores were –0.48, –0.55, and 0.53, respectively. Conclusion: The French version of the WFIRS-S is a psychometrically acceptable self-reported questionnaire for the multi-domain evaluation of functional impairments in adults with ADHD, for research and clinical purposes.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".