Scientific Publications on Nursing for COVID-19 in Patients With Cancer: Scoping Review
Bibliographic record
Abstract
BACKGROUND: The needs of patients with cancer must be met, especially in times of crisis. The advent of the pandemic triggered a series of strategic actions by the nursing team to preserve the health of patients and professionals-hence the importance of studies on nursing care actions provided to patients with cancer during the COVID-19 pandemic. It is known that these patients are susceptible to severe COVID-19. However, no previous review has summarized the findings of scientific studies on nursing for COVID-19 in patients with cancer. OBJECTIVE: This study aims to map the topics addressed in scientific studies on nursing for COVID-19 in patients with cancer. METHODS: A scoping review was conducted using the methodology described in the Joanna Briggs Institute Reviewers' Manual 2015. The research question was elaborated using the population, concept, and context framework: What topics have been studied in nursing publications about COVID-19 in adult patients with cancer? The searches were carried out in 8 databases between April and November 2021 without time restrictions. RESULTS: In total, 973 publications were identified using the search strategies in the databases, and 12 papers were retrieved by consulting the references. A total of 31 (3.2%) publications were included in the final analysis, generating 4 thematic categories on the subject: "restructuring the services: how oncology nursing was adapted during the pandemic," "experiences of patients and performance of the nursing team during the COVID-19 pandemic," "protocols and recommendations for dealing with the COVID-19 pandemic," and "challenges and the role of oncology nurses facing the COVID-19 pandemic." CONCLUSIONS: Several strategies used by oncology nurses to face the COVID-19 pandemic in the international scenario were identified. Reports about the restructuring of services and the team's reactions to the pandemic predominated. However, there is a lack of reports regarding emotional support strategies for health care professionals. Another gap identified was the scarcity of clinical studies on the activities developed by oncology nurses. Therefore, there is a need for clinical research in the oncology area and emotional coping strategies to support oncology nurses.
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 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 | 0.001 |
| 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) | 0.001 | 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 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".