Healthcare Providers' Perspectives of the Supportive Care Needs of Men With Advanced Prostate Cancer
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To examine healthcare providers' (HCPs') perceptions of the supportive care needs of men with advanced prostate cancer (APC). RESEARCH APPROACH: A qualitative, descriptive study. SETTING: Healthcare facilities caring for men with APC in a south-central region of Ontario. PARTICIPANTS: 19 nurses, physicians, and allied health providers who cared for men with APC in outpatient settings. METHODOLOGIC APPROACH: Interviews and focus groups. FINDINGS: HCPs identified four themes related to men's supportive care needs: pain and symptom management, informational needs, emotional needs, and the need for practical assistance. HCPs emphasized issues related to pain, urinary incontinence, and fatigue. They also reported that men continually ask for more information related to treatment, side effects, and prognosis. PARTICIPANTS identified a variety of barriers in meeting supportive care needs, including lack of management strategies, poor knowledge retention, and the "stoic and old-school" nature of men in this population. CONCLUSIONS: Supportive care for this population can be improved through more focused implementation of interprofessional care, with clearly defined professional roles and additional specialized roles to address prostate cancer pain, urinary incontinence, and fatigue. INTERPRETATION: Specialized roles in the management of pain, urinary incontinence, and fatigue affecting men with APC could be integrated into interprofessional care to meet supportive care needs.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".