Measuring Nurse Knowledge, Attitudes, and Skills in Phase 1 Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Phase 1 clinical trials are the initial phase in advancing cancer treatment and testing a new drug for the first time in humans. No studies have investigated combined nurse knowledge, attitudes, and skills when administering phase 1 drugs. OBJECTIVES: This study examined oncology nurses' knowledge, attitudes, and skills; communication; and workflows regarding safe administration of phase 1 drugs. METHODS: A team at a large cancer organization in the southwestern United States conducted an exploratory, cross-sectional survey. The sample included acute and ambulatory care nurses who administer investigational drugs and clinical research nurses who oversee clinical trials. FINDINGS: Nurses scored highest in knowing the goal of a phase 1 drug and lowest in knowing which phase of investigational drug they were administering. For attitudes, confidence in administering and perceived safety when administering were the lowest mean scores. More than half had administered a phase 1 drug in the past five years. More oncology nursing experience correlated with understanding the nurse's role and negatively correlated with fear. About half of the nurses identified challenges in clinical trials workflows.
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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 | 0.031 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".