Perceived factors influencing nurses' use of evidence-informed protocols for remote cancer treatment-related symptom management: A mixed methods study
Bibliographic record
Abstract
PURPOSE: To assess factors perceived to influence nurses' use of symptom protocols when providing remote management for oncology patients. METHOD: A mixed methods descriptive study was guided by the Knowledge-to-Action Framework. In 2013, 8 focus groups and 7 interviews were conducted with 49 nurses or patients/family members in three ambulatory oncology programs within different provincial healthcare systems. Role-play with a protocol was used during nurse focus groups/interviews. Nurses who provided remote symptom support received a survey. Data was triangulated using thematic analysis guided by the Ottawa Model of Research Use. RESULTS: Over 90% of nurses provide telephone support during regular hours only. These symptom protocols were being used by 14% of nurses at one program. Nurses rated the protocols positively for content and format (>85%) but 20% indicated too complex. Protocol facilitators were systematic approach, comprehensive, and evidence-based. Protocol barriers were too long, not for symptom clusters, and inadequate space for documenting. To facilitate use, nurses need to enhance their knowledge (73%) and skills (58%), get access to resources, and obtain performance feedback. Nurse barriers included the learning curve, being unaware of protocols, and feeling tied to a script. Organizational barriers were communication challenges with patients, lack of electronic charting, and no clear direction to use them (54%). CONCLUSIONS: Several barriers and facilitators were perceived to influence the use of symptom protocols. Nurses and patients/family members identified similar factors. Interventions are needed to overcome barriers to nurses using the protocols such as education, clear organizational mandate, and integration with documentation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".