The Context of Oncology Nursing Practice
Bibliographic record
Abstract
BACKGROUND: In oncology, where the number of patients is increasing, there is a need to sustain a quality oncology nursing workforce. Knowledge of the context of oncology nursing can provide information about how to create practice environments that will attract and retain specialized oncology nurses. OBJECTIVE: The aims of this review were to determine the extent and quality of the literature about the context of oncology nursing, explicate how "context" has been described as the environment where oncology nursing takes place, and delineate forces that shape the oncology practice environment. METHODS: The integrative review involved identifying the problem, conducting a structured literature search, appraising the quality of data, extracting and analyzing data, and synthesizing and presenting the findings. RESULTS: Themes identified from 29 articles reflected the surroundings or background (structural environment, world of cancer care), and the conditions and circumstances (organizational climate, nature of oncology nurses' work, and interactions and relationships) of oncology nursing practice settings. CONCLUSIONS: The context of oncology nursing was similar yet different from other nursing contexts. The uniqueness was attributed to the dynamic and complex world of cancer control and the personal growth that is gained from the intense therapeutic relationships established with cancer patients and their families. IMPLICATIONS FOR PRACTICE: The context of healthcare practice has been linked with patient, professional, or system outcomes. To achieve quality cancer care, decision makers need to understand the contextual features and forces that can be modified to improve the oncology work environment for nurses, other providers, and patients.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".