A Rural Health Model for Parkinson's Care: The Clients’ Perspective
Bibliographic record
Abstract
Access to specialist Parkinson's disease (PD) services is limited in rural Australia. This study aimed to describe patient experiences of a novel health care model for PD introduced into a rural Australian health center. The program provided specialist PD services, which included a Parkinson's specialist nurse based at the center and a metropolitan-based Parkinson's specialist neurologist who used telehealth to consult remotely with the program's patients. Patient experiences of the program were captured using the Patient-Centered Questionnaire for PD. Scores included the overall patient-centered score (OPS, range 0-3), subscale experience scores (SES, range 0-3), and quality improvement scores (QIS, range 0-9). The mean (SD) OPS for 52 participants was 1.9 (0.5), a moderate patient-centeredness experience. Most subscale experiences were rated highly, including empathy and Parkinson's expertise (mean 2.4, SD 0.6) and accessibility of health care (mean 2.3, SD 0.8). Experience of provision of tailored information was poorly rated (mean 1.3, SD 0.6). Overall, patient needs were met by this program. Trialing the program at other rural health centers is now required.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".