Health-Related Quality of Life of Australians with Parkinson Disease: A Comparison with International Studies
Bibliographic record
Abstract
PURPOSE: This study describes the health-related quality of life (HRQOL) of Australians living with Parkinson disease (PD) and compares the findings to international reports. METHODS: The Parkinson's Disease Questionnaire-39 (PDQ-39) was used to measure HRQOL in 210 individuals with PD living in Australia. In parallel, a tailored literature search identified previous studies on HROQL in people with PD. A quantitative meta-analysis with a random-effects model was used to compare the HRQOL of individuals with PD living in Australia and other countries. RESULTS: The mean PDQ-39 summary index (SI) score for this sample of Australians with PD was 20.9 (SD 12.7). Ratings for the dimension of social support and stigma were significantly lower than ratings for bodily discomfort, mobility, activities of daily living, cognition, and emotional well-being. Comparing the Australian and international PD samples revealed a significant heterogeneity in overall HRQOL (I(2)=97%). The mean PDQ-39 SI scores for Australians were lower, indicating better HRQOL relative to samples from other countries. CONCLUSIONS: This Australian sample with PD perceived their HRQOL as poor, although it was less severely compromised than that of international samples. While further research is required, these findings can inform the clinical decision-making processes of physiotherapists.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".