Measuring Hand Dexterity in People With Parkinson’s Disease: Reliability of Pegboard Tests
Bibliographic record
Abstract
IMPORTANCE: Knowledge regarding the reliability of pegboard tests when used to measure dexterity in people with Parkinson's disease (PD) is currently limited. OBJECTIVE: To examine the test-retest and interrater reliability of the 9-Hole Peg Test (9HPT) and Purdue Pegboard Test (PPT) in people with PD. DESIGN: Cross-sectional observational study. For test-retest reliability, tests were completed on 2 days, 1 wk apart, in the "on" phase and "end-of-dose" period of participants' medication cycle. For interrater reliability, occupational therapists and physical therapists rated prerecorded pegboard test performance of participants with PD. SETTING: Test-retest reliability was determined in participants' homes or in a university department. Interrater reliability was determined in a university department or a hospital setting. PARTICIPANTS: Test-retest reliability was determined with volunteers diagnosed with PD (N = 30). Interrater reliability was determined with a convenience sample of occupational and physical therapists (N = 11). OUTCOMES AND MEASURES: The 9HPT and PPT are commonly used measures of manual dexterity. RESULTS: PPT subtests showed higher test-retest reliability (intraclass correlation coefficients [ICCs] ≥ .90) in both phases of the medication cycle compared with the 9HPT (ICCs = .70-.81). Minimal detectable change scores indicated acceptable measurement error for both tools. Interrater reliability for recorded performance of each measure was very good (ICCs > .99), with no calculable measurement error. CONCLUSIONS AND RELEVANCE: Although both tools showed adequate test-retest and interrater reliability, results suggest that the PPT may be a more reliable measure of dexterity loss in people with PD. WHAT THIS ARTICLE ADDS: This study informs the clinical measurement of the loss of manual dexterity in people with PD, a frequent problem reported by people living with this disorder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".