Nursing Student Perceptions and Attitudes Toward Patients With Cancer After Education and Mentoring: Integrative Review
Bibliographic record
Abstract
BACKGROUND: Knowledge about nursing student attitudes toward patients with cancer after an educational intervention and mentoring support is limited. This review examined the literature on this topic. OBJECTIVE: This integrative review aims to explore the literature on the experiences of students who participate in an oncology elective or educational course on cancer and their attitudes toward cancer. METHODS: A comprehensive search was conducted using PubMed, CINAHL, and MEDLINE databases. Each study was systematically assessed. An evidence table was completed to identify the key aspects of each study that was reviewed. RESULTS: There is insufficient information on the impact of nursing student education on the attitudes and skills of nursing students caring for patients with cancer. An integrative review was completed on the impact of education and mentoring for nursing students on cancer care, which yielded 10 studies that were reviewed. These studies indicate that educational intervention and mentoring improve the confidence and ability of nursing students to care for patients with cancer. CONCLUSIONS: Student nurses need to be armed with knowledge, skills, and positive attitudes while caring for patients with cancer. Nursing students perform best when they have accurate information, positive role models, and mentoring by experienced oncology professionals, to support proficiency in caring for patients with cancer. The lack of knowledge of nursing students in the areas of cancer care, treatment, and patient support requires additional education and research to promote expertise and positive attitudes toward cancer and treating patients with cancer. This will support nursing students' ability to care for patients with cancer as well as develop future educational interventions to shape nursing student attitude and knowledge. This integrative review also identifies the positive impact on the attitudes of other health care professionals who have received training or education on cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".