Access and Attitudes Toward Palliative Care Among Movement Disorders Clinicians
Bibliographic record
Abstract
BACKGROUND: Neuropalliative care is an emerging field for those with neurodegenerative illnesses, but access to neuropalliative care remains limited. OBJECTIVE: We sought to determine Movement Disorder Society (MDS) members' attitudes and access to palliative care. METHODS: A quantitative and qualitative survey instrument was developed by the MDS Palliative Care Task Force and e-mailed to all members for completion. Descriptive statistics and qualitative analysis were triangulated. RESULTS: Of 6442 members contacted, 652 completed the survey. Completed surveys indicating country of the respondent overwhelmingly represented middle- and high-income countries. Government-funded homecare was available to 54% of respondents based on patient need, 25% limited access, and 21% during hospitalization or an acute defined event. Eighty-nine percent worked in multidisciplinary teams. The majority endorsed trigger-based referrals to palliative care (75.5%), while 24.5% indicated any time after diagnosis was appropriate. Although 66% referred patients to palliative care, 34% did not refer patients. Barriers were identified by 68% of respondents, the most significant being available workforce, financial support for palliative care, and perceived knowledge of palliative care physicians specific to movement disorders. Of 499 respondents indicating their training in palliative care or desire to learn these skills, 55% indicated a desire to gain more skills. CONCLUSIONS: The majority of MDS member respondents endorsed a role for palliative care in movement disorders. Many members have palliative training or collaborate with palliative care physicians. Although significant barriers exist to access palliative care, the desire to gain more skills and education on palliative care is an opportunity for professional development within the MDS. © 2021 International Parkinson and Movement Disorder Society.
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 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".