Comparing probable case identification of developmental coordination disorder using the short form of the Bruininks‐Oseretsky Test of Motor Proficiency and the Movement ABC
Bibliographic record
Abstract
Aim Despite its widespread current use in research and its potential for future application, the validity of the short form of the Bruininks-Oseretsky Test of Motor Proficiency (BOTMP-SF) when administered by trained lay assessors is not known. This paper reports the results of case identification using the Movement Assessment Battery for Children (M-ABC) in a group of children scoring below the sixth percentile on the BOTMP-SF. Methods The BOTMP-SF was administered by trained research assistants to 2058 children. In total, 24 of 128 children aged 10 (n = 10), 11 (n = 10) or 12 (n = 4) scoring below the sixth percentile were randomly selected for further assessment by a paediatric occupational therapist using the M-ABC and the Kaufman Brief Intelligence Test. Results Twenty-one of 24 children positive for motor co-ordination problems on the BOTMP-SF scored below the 15th percentile of the M-ABC, a positive predictive value (PPV) of 0.88 [95% confidence interval (CI) = 0.69 to 0.96]. Fifteen of these children were below the fifth percentile (PPV = 0.63; 95% CI = 0.43 to 0.79). Conclusions The BOTMP-SF seems to be a reasonable alternative to case identification when clinical assessment with the M-ABC is not feasible. Further research is needed to examine the sensitivity and specificity of the short form when used for this purpose.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".