Validating the Use of the Evaluation Tool of Children’s Handwriting–Manuscript to Identify Handwriting Difficulties and Detect Change in School-Age Children
Bibliographic record
Abstract
In this study we sought to validate the discriminant ability of the Evaluation Tool of Children's Handwriting-Manuscript in identifying children in Grades 2-3 with handwriting difficulties and to determine the percentage of change in handwriting scores that is consistently detected by occupational therapists. Thirty-four therapists judged and compared 35 pairs of handwriting samples. Receiver operating characteristic (ROC) analyses were performed to determine (1) the optimal cutoff values for word and letter legibility scores that identify children with handwriting difficulties who should be seen in rehabilitation and (2) the minimal clinically important difference (MCID) in handwriting scores. Cutoff scores of 75.0% for total word legibility and 76.0% for total letter legibility were found to provide excellent levels of accuracy. A difference of 10.0%-12.5% for total word legibility and 6.0%-7.0% for total letter legibility were found as the MCID. Study findings enable therapists to quantitatively support clinical judgment when evaluating handwriting.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".