Priorities in healthcare provision in Parkinson's disease from the perspective of Parkinson Nurses: A focus group study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Through their expertise and diverse skills, Parkinson Nurses are key care providers for people with Parkinson's disease. They are seen as an important profession for person-centered and multidisciplinary care, considered priorities in Parkinson's care delivery. Currently, however, little is known about the priorities that this profession itself defines for the care of Parkinson's patients and how they perceive their own role in the care process. Objective: To explore the perspective of Parkinson Nurses on care priorities in people with Parkinson's disease. Design: Qualitative study. Settings: The iCare-PD study served as the object of study by establishing an interdisciplinary, person-centered and nurse-led care model in several European countries and Canada. The nurses who participated in this model were part of the study. Participants: Six Parkinson Nurses participated in the study. Methods: We conducted a thematic focus group, adopting the paradigm of pragmatism to draft an interview guide. The focus group was based on the inspiration card method and followed recommendations for co-creation processes. Results: Parkinson Nurses define care priorities for Parkinson's in areas of education, multi-professionalism, and need-orientation. They see themselves as mediators and coordinators of care delivery processes. Conclusions: In line with international recommendations, Parkinson Nurses prioritize key aspects of multidisciplinary and person-centered care. At the same time, however, the nurses also name care priorities that go beyond the international recommendations. It is therefore crucial to integrate the perspective of this important profession into recommendations for the delivery of healthcare for people with Parkinson's.Tweetable abstract How do
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it