What do primary care nurses and radiation therapists in a Canadian cancer centre think about clinical trials?
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: Clinical trials are integral to progress in cancer management. While doctors' attitudes to clinical trials have been documented, there is little or no literature on the perception of trials from the perspective of other clinicians who treat trial patients. The purpose of this phenomenological study was to explore nurses' and radiation therapists' (RTs) perceptions of clinical trials in their cancer centre. METHODS: This study was conducted in a Canadian cancer centre where over 50 clinical trials actively recruit patients at any one time. Nurses and RTs were interviewed to explore their perceptions of clinical trials. RESULTS: The following themes emerged from the analysis: (1) nurses and RTs perceived a variety of ethical concerns associated with clinical trials; (2) treating patients enrolled in clinical trials was perceived to add to the workload of RTs; (3) nurses and RTs did not perceive meaningful involvement in clinical trials as an option; and (4) the additional workload and ethical concerns associated with trials were off-set by the view that patients' interests outweighed those of nurses and RTs. DISCUSSION: Nurses and RTs should be invited to provide input regarding trial procedures and be acknowledged for their work associated with clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.045 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.036 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".