Nurse-Led Telephonic Symptom Support for Patients Receiving Chemotherapy
Bibliographic record
Abstract
PROBLEM STATEMENT: The use of evidence-informed symptom guides has not been widely adopted in telephonic support. DESIGN: This is a descriptive study of nurse-led support using evidence-based symptom guides during telephone outreach. DATA SOURCES: Documentation quantified telephone encounters by frequency, length, and type of patient-reported symptoms. Nurse interviews examined perceptions of their role and the use of symptom guides. ANALYSIS: Quantitative data were summarized using univariate descriptive statistics, and interviews were analyzed using directed descriptive content analysis. FINDINGS: Symptom guides were viewed as trusted evidence-based resources, suitable to address common treatment-related symptoms. A threshold effect was a reported barrier of the guides, such that the benefit diminished over time for managing recurring symptoms. IMPLICATIONS FOR PRACTICE: Telephone outreach using evidence-based symptom guides can contribute to early symptom identification while engaging patients in decision making. Understanding nurse activities aids in developing an economical and high-quality model for symptom support, as well as in encouraging nurses to practice at the highest level of preparation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".