Parent versus Teacher Ratings of Attention-Deficit/Hyperactivity Disorder Symptoms in the Preschoolers with Attention-Deficit/Hyperactivity Disorder Treatment Study (PATS)
Bibliographic record
Abstract
OBJECTIVE: To assess parent-teacher concordance on ratings of DSM-IV symptoms of attention-deficit/hyperactivity disorder (ADHD) in a sample of preschool children referred for an ADHD treatment study. METHODS: Parent and teacher symptom ratings were compared for 452 children aged 3-5 years. Agreement was calculated using Pearson correlations, Cohen's kappa, and conditional probabilities. RESULTS: The correlations between parent and teacher ratings were low for both Inattentive (r = .24) and Hyperactive-Impulsive (r = .26) symptom domains, with individual symptoms ranging from .01-.28. Kappa values for specific symptoms were even lower. Conditional probabilities suggest that teachers are only moderately likely to agree with parents on the presence or absence of symptoms. Parents were quite likely to agree with teachers' endorsement of symptoms, but much less likely to agree when teachers indicated that a symptom was not present. CONCLUSIONS: Results provide important data regarding base rates and concordance rates in this age group and support the hypothesis that preschool-aged children at risk for ADHD exhibit significant differences in behavior patterns across settings. Obtaining ratings from multiple informants is therefore considered critical for obtaining a full picture of young children's functioning.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".