Evaluation of the Dementia Apraxia Test in Parkinson’s Disease Patients
Bibliographic record
Abstract
INTRODUCTION: Ideomotor apraxia, a disorder of skilled movements affecting limbs and/or face, can be seen in patients with Parkinson's disease (PD), yet tests of apraxia in PD are rare. The aim of this project was to evaluate the psychometric properties and validity of the Dementia Apraxia Test (DATE) in a PD sample. METHODS: 118 PD patients were included. Besides DATE performance, motor and non-motor burden, cognition, and activity of daily living (ADL) function were assessed. Patients were classified as cognitively impaired (n = 41) or non-cognitively impaired (n = 77). RESULTS: Interrater reliability of the DATE (sub-)scores between video ratings and on-site ratings by the investigator was good (0.81 ≤ rk ≤ 0.87). Items were mostly easy to perform, especially the buccofacial apraxia items, which had also low discriminatory power. DATE scores were associated with cognition and ADL function. DATE performance was confounded by motor impairment and patients' age; however, when analysed for both cognitive groups separately, the correlation between DATE and motor performance was not significant. DISCUSSION/CONCLUSION: The DATE seems to be an objective and predominantly valid apraxia screening tool for PD patients, with a few items needing revision. Due to the potential effect of motor impairment and age, standardized scores adjusting for these confounders are needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".