Patient-Reported Experience of Care by Prostate Cancer Specialist Nursing Service
Bibliographic record
Abstract
Aims - The Prostate Cancer Specialist Nursing Program (PCSNP), which was established by the Prostate Cancer Foundation of Australia in 2012, aimed to provide nationwide direct care to men with prostate cancer and subsequently improve their experience. This report describes men’s experience of the PCSN service during the program implementation. Methods - 567 men with prostate cancer who had at least one contact with a Prostate Cancer Specialist Nurse (PCSN) were recruited from 12 health centres across Australia during the implementation period. Participants completed a questionnaire assessing the extent of their satisfaction and experience of the PCSN service in relation to information, treatment and care, practical support, general care, and communication with the nurse. Results - More than 90% of the participants agreed/strongly agreed that the PCSNs provided information to them. Regarding general care, 90% agreed/strongly agreed that their cancer treatment went smoothly at each stage. In terms of communication with the nurse, more than 95% agreed/strongly agreed that they were given helpful answers to questions about their cancer and treatment, and they could contact the PCSN when necessary. For treatment and care, participants agreed/strongly agreed that they were provided information about health services or health professionals (91%), and their concerns were heard and acted upon (89%). One quarter or more participants did not agree that the PCSNs provided practical support, such as bill paying, arranging transport or accommodation for treatment. Overall, nearly all participants were satisfied (78% very satisfied, 7% moderately satisfied and 13% satisfied) with the level of support provided by the PCSN. Conclusions - These results show that men with prostate cancer had a positive experience of care in their interaction with the prostate cancer specialist nurses. This was most evident in services related to information, treatment and general care, and communication.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".