An international 20 country patient and physician survey of the usability and acceptability of Stepped Care pathway in Parkinson’s disease
Bibliographic record
Abstract
Parkinson's disease (PD) is not a single condition and has multiple heterogeneous presentations with several endophenotypes as well as collateral factors affecting care and health. However, clinical consultations globally often miss these important aspects in clinic. The Stepped Care pathway of care was developed from PD patients' opinion and attempts to combine these gaps in care in a simple 3-stage clinical paradigm. We conducted a survey across twenty (20) countries to explore the views of clinicians and PD patients on the process, acceptability and need of the Stepped Care pathway. A structured questionnaire was administered in both affluent and under-resourced clinics, capturing data from a multi-ethnic and diverse patient base. 99% patients (White, Asian and Black) felt Stepped Care toolkit asked relevant questions addressing needs and concerns in PD care that are often missed, and 96% agreed with the importance of using this toolkit during Outpatient Clinic visits. Moreover, a significant majority of PD patients (96%) felt Stepped Care makes them understand their condition better. 92% of clinicians indicated that the Stepped care toolkit could be an effective asset in clinical practice, while 91% of clinicians agreed that the toolkit provides holistic care which is often missed in clinic. This novel global survey of the efficacy and useability of Stepped Care for PD is overwhelmingly endorsed by PD patients and clinicians from a diverse, multi-ethnic background across high- and low- income countries. Stepped Care can be used in clinical practice in order to ensure a holistic and comprehensive care for 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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".