Grooved Pegboard Predicates More of Cognitive Than Motor Involvement in Parkinson’s Disease
Bibliographic record
Abstract
The Grooved Pegboard Test (GPT) was conceived as a test of manual dexterity, upper-limb motor speed, and hand-eye coordination. The aim of our study was to test the componential structure of the GPT on an archetypal model of motor impairment, Parkinson's disease (PD). A total of 45 PD patients (33 males, 12 females; age M = 67, range = 49-81; PD duration M = 10, range = 6-20 years; H/Y stage 2, range = 2-3) and 20 age- and education-matched controls (14 males, 6 females; age M = 66, range = 48-80) were included. All participants were investigated using the GPT, Short Falls Efficacy Scale-International, Frontal Assessment Battery (FAB), Montreal Cognitive Assessment (MoCA), and Non-Motor Symptom Scale. Patients were followed for 6 months, using fall diaries and monthly phone calls to define PD fallers (falls ≥ 1; n = 27) and PD nonfallers (falls = 0; n = 18). Using structural equation modeling, the GPT predicted performance on the MoCA (p < .001), but not on the FAB (p = .29). In conclusion, analysis of the structure of the GPT provided evidence about important cognitive features, in addition to the motor component of this test in PD.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".