Training Oncology Nurses to Use Remote Symptom Support Protocols: A Retrospective Pre-/Post-Study
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To evaluate the impact of training on nurses' satisfaction and perceived confidence using symptom protocols for remotely supporting patients undergoing cancer treatment. DESIGN: Retrospective pre-/post-study guided by the Knowledge-to-Action Framework. SETTING: Interactive workshops at three ambulatory oncology programs in Canada. SAMPLE: 107 RNs who provide remote support to patients with cancer. METHODS: Workshops included didactic presentation, role play with protocols, and group discussion. Post-training, a survey measured satisfaction with training and retrospective pre-/post-perceived confidence in the ability to provide symptom support using protocols. One-tailed, paired t-tests measured change. MAIN RESEARCH VARIABLES: Satisfaction with the workshop and perceived confidence in the ability to provide symptom support and use protocols. FINDINGS: Twenty-two workshops, 30-60 minutes each, were conducted with 107 participants. Ninety completed the survey. Compared to preworkshop, postworkshop nurses had improved self-confidence to assess, triage, and guide patients in self-care for cancer treatment-related symptoms, and use protocols to facilitate symptom assessment, triage, and care. Workshops were rated as easy to understand, comprehensive, and provided new information on remote symptom management. Some specified that the workshop did not provide enough time for role play, but most said they would recommend it to others. CONCLUSIONS: The workshop increased nurses' perceived confidence with providing remote symptom support and was well received. IMPLICATIONS FOR NURSING: Subsequent workshops should ensure adequate time for role play to enhance nurses' skills in using protocols and documenting symptom support.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".