The Weiss Functional Impairment Rating Scale-Parent Form for assessing ADHD: evaluating diagnostic accuracy and determining optimal thresholds using ROC analysis
Bibliographic record
Abstract
PURPOSE: The Weiss Functional Impairment Rating Scale-Parent Form (WFIRS-P) is a 50-item scale that assesses functional impairment on six clinically relevant domains typically affected in attention-deficit/hyperactivity disorder (ADHD). As functional impairment is central to ADHD, the WFIRS-P offers potential as a tool for assessing functional impairment in ADHD. These analyses were designed to examine the overall performance of WFIRS-P in differentiating ADHD and non-ADHD cases using receiver operating characteristics (ROC) analysis. This is the first attempt to empirically determine the level of functional impairment that differentiates ADHD children from normal controls. METHODS: This observational study comprised 5-19-year-olds with physician-diagnosed ADHD (n = 476) and non-ADHD controls (n = 202). ROC analysis evaluated the ability of WFIRS-P to discriminate between ADHD and non-ADHD, and identified a WFIRS-P cut-off score that optimises correct classification. Data were analysed for the complete sample, for males versus females and for participants in two age groups (5-12 versus 13-19 years). RESULTS: Area under the curve (AUC) was 0.91 (95% confidence interval 0.88-0.93) for the overall WFIRS-P score, suggesting highly accurate classification of ADHD distinct from non-ADHD. Sensitivity (0.83) and specificity (0.85) were maximal for a mean overall WFIRS-P score of 0.65, suggesting that this is an appropriate threshold for differentiation. DeLong's test found no significant differences in AUCs for males versus females or 5-12 versus 13-19 years, suggesting that WFIRS-P is an accurate classifier of ADHD across gender and age. CONCLUSIONS: When assessing function, WFIRS-P appears to provide a simple and effective basis for differentiating between individuals with/without ADHD in terms of functional impairment. CLASSIFICATION: Disease-specific applications of QOL research.
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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 | 0.020 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".