Unlocking the daily impact of parkinson’s challenges through a comprehensive assessment using the ChulaPD ADL questionnaire
Bibliographic record
Abstract
The ChulaPD ADL questionnaire is a meticulously developed tool by experts in Parkinson's disease (PD) and movement disorders, designed to assess functional limitations in daily activities. It comprehensively evaluates 15 key aspects of daily life through 115 items, including 15 for grading limitations and 100 for ADL limitations. Validated in a pilot study with 30 PD participants, the questionnaire demonstrated strong reliability. In a larger cohort of 231 PD patients, it showed moderate to high correlations with age, Hoehn and Yahr score, levodopa equivalent dose, Montreal Cognitive Assessment, and various UPDRS scores, highlighting its effectiveness in capturing disease-related changes. A grading limitation threshold of 13 points or above was particularly effective in identifying postural instability, achieving 81.4% sensitivity and 50.7% specificity, with an area under the curve (AUC) of 0.747. This underscores its utility in reflecting disease progression and its impact on daily functions. The ChulaPD ADL questionnaire is a relevant, reliable, and valid tool for assessing activities of daily living in patients with 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".