Family physicians' involvement in palliative cancer care
Bibliographic record
Abstract
BACKGROUND: Family physicians' (FPs) long-term relationships with their oncology patients position them ideally to provide primary palliative care, yet their involvement is variable. We examined perceptions of FP involvement among outpatients receiving palliative care at a cancer center and identified factors associated with this involvement. METHODS: Patients with advanced cancer attending an oncology palliative care clinic (OPCC) completed a 25-item survey. Eligible patients had seen an FP within 5 years. Binary multivariable logistic regression analyses were conducted to identify factors associated with (1) having seen an FP for palliative care within 6 months, and (2) having a scheduled/planned FP appointment. RESULTS: Of 258 patients, 35.2% (89/253) had seen an FP for palliative care within the preceding 6 months, and 51.2% (130/254) had a scheduled/planned FP appointment. Shorter travel time to FP (odds ratio [OR] = 0.67, 95% confidence interval [CI] = 0.48-0.93, p = 0.02), the FP having a 24-h support service (OR = 1.96, 95% CI = 1.02-3.76, p = 0.04), and a positive perception of FP's care (OR = 1.05, 95% CI = 1.01-1.09, p = 0.01) were associated with having seen the FP for palliative care. English as a first language (OR = 2.90, 95% CI = 1.04-8.11, p = 0.04) and greater ease contacting FP after hours (OR = 1.33, 95% CI = 1.08-1.64, p = 0.008) were positively associated, and female sex of patient (OR = 0.51, 95% CI = 0.30-0.87, p = 0.01) and travel time to FP (OR = 0.66, 95% CI = 0.47-0.93, p = 0.02) negatively associated with having a scheduled/planned FP appointment. Number of OPCC visits was not associated with either outcome. CONCLUSION: Most patients had not seen an FP for palliative care. Accessibility, availability, and equity are important factors to consider when planning interventions to encourage and facilitate access to FPs for palliative care.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".