Comparison of Performance on ADHD Quality of Care Indicators: Practitioner Self-Report Versus Chart Review
Bibliographic record
Abstract
Objective: This study compared practitioner self-report of ADHD quality of care measures with actual performance, as documented by chart review. Method: In total, 188 practitioners from 50 pediatric practices completed questionnaires in which they self-reported estimates of ADHD quality of care indicators. A total of 1,599 charts were reviewed. Results: The percentage of patients for whom practitioners self-reported that they used evidence-based care was higher in every performance category when compared with chart review, including higher use of parent and teacher rating scales during assessment and treatment compared with chart review. Self-reported use of Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) criteria during assessment was also higher than by chart review. The actual number of days until the first contact after starting medication was nearly three times longer than self-report estimates. Conclusion: Practitioners overreport performance on quality of care indicators. These differences were large and consistent across ADHD diagnostic and treatment monitoring practices. Practitioner self-report of ADHD guideline adherence should not be considered a valid measure of performance.
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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 | 0.016 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".