Delineating the Role of a Cohort of Clinical Research Nurses in a Pediatric Cooperative Clinical Trials Group
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To describe the roles and responsibilities of the clinical research nurse (CRN). DESIGN: A descriptive design was used to reveal the roles of pediatric oncology CRNs. SETTING: The Children's Oncology Group (COG) password protected Web site. SAMPLE: 85 nurses who performed clinical research associate work within COG. METHODS: The Clinical Trials Nursing Questionnaire was used to investigate the roles and responsibilities of CRNs. MAIN RESEARCH VARIABLES: Protocol assessment, protocol planning, subject recruitment, informed consent process, investigational product, implementation and evaluation, data management, and professional nursing role. FINDINGS: The study found that 55% of respondents (n = 47) were employed in a hospital setting, the majority (81%) had more than five years of oncology experience, and the average age of respondents was 45.56 years (range = 24-65 years). CRNs rated all role components as very important, with the consent process being of greatest importance. Eighty-nine percent reported experiencing autonomy and independence in the role. CONCLUSIONS: Clinical specialization of RNs has increased significantly in the past several decades. Acknowledging that nurses are responsible for performing many different roles that are critical to the successful completion of clinical trials is crucial. IMPLICATIONS FOR NURSING: Evaluation of this dual role is still in its infancy, but articulating the role of CRNs in the conduct and context of clinical research is an important first step.
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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 | 0.197 | 0.421 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.011 |
| 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; both teacher heads agree on what is shown here.
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".