Clinical Importance of Parent Ratings of Everyday Cognitive Abilities in Children with Learning and Attention Problems
Bibliographic record
Abstract
This study addressed two issues: first, whether parental reports contribute information over and above a standardized psychometric assessment, and second, whether parental reports of everyday cognitive functioning might be useful in distinguishing between children with reading disabilities (RD), attention-deficit/hyperactivity disorder (ADHD), and combined ADHD + RD. Parent-reported information on 159 children with learning or attention problems was obtained using a questionnaire called the Parent Ratings of Everyday Cognitive and Academic Abilities (PRECAA). Psychometric information used for comparison included the Woodcock-Johnson Psychoeducational Battery-Revised, the Bruininks-Oseretsky Test of Motor Proficiency-Short Form, the Vocabulary and Block Design subtests of the Wechsler Intelligence Scale for Children, 3rd edition, and the Developmental Test of Visual-Motor Integration. The PRECAA was found to be sensitive to group differences between children with RD and children with ADHD and combined ADHD + RD. Its inclusion resulted in a significant increase in the number of children correctly classified compared to the use of psychometric measures alone. The PRECAA correctly classified more children (66%) than did the standard psychometric measures (50%). In fact, a very high percentage of children with ADHD (81%) were correctly classified using the PRECAA. These findings suggest that the PRECAA may be a useful aid to clinicians in the identification of children with learning and attention problems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".