Neurologists' Attitudes and Perceptions on Palliative Care
Bibliographic record
Abstract
Background and Objectives: Despite significant advances in the treatment of neurologic disorders, many conditions require complex care planning and advanced care planning. Neurologists are in a unique position because they are integral in providing patient centered care, understanding neurologic disease and illness trajectory, and how disease can affect patients' sense of self and values. Currently, little is known about neurologists' perceptions and challenges in care planning and palliative care for their patients. Methods: Neurologists from one Canadian academic institution participated in a 30-minute semistructured interview from November 2022 to April 2023. Interviews were conducted until saturation was reached and confirmed. Interviews occurred online through a secure platform or in-person and were recorded. Data were analyzed using a constant comparative method using constructivist grounded theory. Member checking was conducted post interview. Results: Ten neurologists participated across a broad spectrum of neurology experience and subspecialties. We developed a detailed theory of understanding neurologists' attitudes and perceptions of palliative care. When neurologists delay or fail to initiate care planning discussions or palliative care, it results from a complex interplay between patient, physician, and resource accessibility factors. Certain contextual factors, such as a first visit or follow-up, inpatient vs outpatient setting, clinic culture, and the type of clinic practice, are factors that can influence these conversations. As a result, physicians may fail to use available resources, or they may involve other care providers or refer to subspecialty neurologic clinics. However, this delay can still lead to patient and provider harm. Opportunities to improve care exist with continuing education opportunities for trainees and staff, collaboration with palliative care specialists, and health systems support, such as increasing public awareness to address misconceptions about palliative care and resource availability. Discussion: Our findings identify that failure or delay to initiate care planning and palliative care by neurologists results from a complex interplay between local culture, experience, context, practice type, and patient factors. Opportunities to improve care include increasing educational opportunities, building integrated and collaborative practices, and dedicated health systems support.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".