Cancer follow-up care. Patients' perspectives.
Bibliographic record
Abstract
OBJECTIVE: To assess family physicians' and specialists' involvement in cancer follow-up care and how this involvement is perceived by cancer patients. DESIGN: Self-administered survey. SETTING: A health region in New Brunswick. PARTICIPANTS: A nonprobability cluster sample of 183 participants. MAIN OUTCOME MEASURES: Patients' perceptions of cancer follow-up care. RESULTS: More than a third of participants (36%) were not sure which physician was in charge of their cancer follow-up care. As part of follow-up care, 80% of participants wanted counseling from their family physicians, but only 20% received it. About a third of participants (32%) were not satisfied with the follow-up care provided by their family physicians. In contrast, only 18% of participants were dissatisfied with the follow-up care provided by specialists. Older participants were more satisfied with cancer follow-up care than younger participants. CONCLUSION: Cancer follow-up care is increasingly becoming part of family physicians' practices. Family physicians need to develop an approach that addresses patients' needs, particularly in the area of emotional 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 | 0.001 | 0.007 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".