Priorities for Adult Cancer Nursing Research
Bibliographic record
Abstract
Two Delphi surveys have been conducted during the past 20 years to identify cancer nursing research priorities; one in the United States and one in Canada. Sir Charles Gairdner Hospital, the State Cancer Referral Centre in Western Australia, undertook a replication of this Delphi survey to identify nursing research priorities for adult cancer nursing. The aim of this replication was to identify possible changes in priorities and account for cultural difference in the healthcare systems. A total of 45 responses were received from the first Delphi round and 30 from the second. The top ten priorities identified by this sample were different from those identified in prior studies. The top ranked research topic was "What strategies would be most helpful in allowing nurses time to provide emotional support to cancer patients and carers?" These results may stimulate discussion and re-assessment of research priorities in other adult cancer care settings.
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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 | 0.212 | 0.212 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".