Preschool inattention and impulsivity-hyperactivity: Development of a clinic-based assessment protocol
Bibliographic record
Abstract
Objective: To determine whether preschoolers classified as ADHD exhibited significantly more inattention and/or impulsivity-hyperactivity in the clinic than their typically-developing peers, using a developmentally appropriate clinical assessment protocol similar to protocols used with school-age children. Method: Fifty preschoolers participated; 25 preschoolers were classified with ADHD and matched with 25 typically-developing preschoolers. Direct clinic-based observations of behavior were analyzed and subsumed under two dimensions: inattention and impulsivity-hyperactivity. Results: In regard to inattention, compared to their typically-developing controls, the preschoolers classified with ADHD were significantly more often off-task in both low and high structure settings, and their episodes of play were significantly shorter in duration, though they did not shift activities more frequently. With regard to impulsivity-hyperactivity, preschoolers classified with ADHD were significantly more active and more talkative than their typicallydeveloping peers. Conclusions: Developmentally appropriate assessment protocols do provide convergent, clinically valuable information that may assist in the early assessment of ADHD and facilitate continuity of monitoring/assessment of ADHD symptoms into the school-age years.
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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 | 0.032 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".