Optimizing future planning in Parkinson disease: suggestions for a comprehensive roadmap from patients and care partners
Bibliographic record
Abstract
BACKGROUND: Living with Parkinson disease (PD) is complicated by an unpredictable disease course which can delay planning for future needs. This study explores patient and care partner needs related to future planning using a palliative care framework with physical, psychological, social, cultural, end-of-life, and ethical aspects of care in PD to guide analysis. METHODS: Secondary analysis of patient and care partner interviews from a randomized clinical trial comparing interdisciplinary outpatient palliative care versus standard care for individuals with PD and care partners in an academic setting. Sixty participants were interviewed (30 patients and 30 care partners) about needs related to future planning. Team-based thematic analysis was used to identify key themes. RESULTS: Many care partners and patients living with PD described a desire for information about what to expect and how to plan for the future. Participants posed multiple questions about PD progression and devised the metaphor of a "roadmap" as a guide for decision making and planning. When exploring the concept of a PD roadmap, five themes emerged: (I) desire for a comprehensive tool for future planning, such as a roadmap, (II) care partner preferences for specific future planning, (III) PD-related life changes as opportunity for future planning and decision-making, (IV) cues from family, peers, and medical professionals about "location" on the roadmap, and (V) opportunities and challenges to integrating a PD roadmap into patient-centered care. CONCLUSIONS: Patients and care partners described key needs related to future planning that can inform a comprehensive roadmap to assist with education, communication, and decision making. A roadmap tool can promote individualized anticipatory guidance and multidimensional shared decision-making discussions between patients, care partners, and the healthcare team related to PD progression.
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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 | 0.050 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".