Palliative care physicians’ motivations for models of practicing in the community: A qualitative descriptive study
Bibliographic record
Abstract
BACKGROUND: Internationally, both primary care providers and palliative care specialists are required to address palliative care needs of our communities. Clarity on the roles of primary and specialist-level palliative care providers is needed in order to improve access to care. This study examines how community-based palliative care physicians apply their roles as palliative care specialists, what motivates them, and the impact that has on how they practice. DESIGN: A qualitative descriptive study using semi-structured virtual interviews of community-based palliative care specialists. We asked participants to describe their care processes and the factors that influence how they work. SETTING/PARTICIPANTS: A qualitative descriptive study using semi-structured virtual interviews of community-based palliative care physicians in Ontario, Canada was undertaken between March and June 2020. At interview end, participants indicated whether their practice approaches aligned with one or more models depicted in a conceptual framework that includes consultation (specialist provides recommendations to the family physician) and takeover (palliative care physician takes over all care responsibility from the family physician) models. RESULTS: Of the 14 participants, 4 worked in a consultation model, 8 in a takeover model, and 2 were transitioning to a consultation model. Different motivators were found for the two practice models. In the takeover model, palliative care physicians were primarily motivated by their relationships with patients. In the consultation model, palliative care physicians were primarily motivated by their relationships with primary care. These differing motivations corresponded to differences in the day-to-day processes and outcomes of care. CONCLUSIONS: The physician's personal or internal motivators were drivers in their practice style of takeover versus consultative palliative care models. Awareness of these motivations can aid our understanding of current models of care and help inform strategies to enhance consultative palliative care models.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".