Evidence map›Paper›PMID 42002727›Full record

ArticleNursing & health sciences2026

Nursing Workload in Systemic Anti-Cancer Therapy Day Units: A Scoping Review and Gap Analysis.

Zhuming Bao, Jenny Harris, Nianqi Cui, Verna Lavender, Anne Marie Rafferty, Jo Armes

Abstract readScoping Review
In one paragraph

Article in Nursing & health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhuming BaoSchool of Health Sciences, University of Surrey, Surrey, UK.ORCID https://orcid.org/0000-0001-6506-3633
Jenny HarrisSchool of Health Sciences, University of Surrey, Surrey, UK.ORCID https://orcid.org/0000-0001-8933-117X
Nianqi CuiSchool of Nursing, Kunming Medical University, Kunming, China.ORCID https://orcid.org/0000-0002-7963-4887
Verna LavenderGuy's Cancer Academy, Guy's and St Thomas NHS Foundation Trust, London, UK.
Anne Marie RaffertyKing's College London, London, UK.
Jo ArmesSchool of Health Sciences, University of Surrey, Surrey, UK.

Funding

University of Surrey
6 · The paper itself

Abstract

This scoping review aims to identify, summarize, and compare evidence from studies examining nursing workload in Systemic Anti-Cancer Therapy (SACT) day units. The search included from January 2000 to 2025. Electronic databases, including MEDLINE, CINAHL, PsycINFO, EMBASE (Elsevier), ASSIA (ProQuest), Web of Science, Cochrane Library, and Global Index Medicus (WHO), were selected. A simplified search strategy was applied across platforms such as Open Gray, Google Scholar, Scopus, ProQuest Dissertations and Theses, and OAIster.20 studies were included in this review; among these, 16 studies were single centre. The studies were categorized into patient dependency workload (acuity tools, regimen-based patient dependency, and patient-based assessment) and nursing time workload. This review identified a significant gap in the literature, as the included studies largely failed to address non-patient-related care. It also highlighted that the complexity of SACT treatments influences nursing workload beyond patient numbers. This review underscores the distinct nature of nursing workload in SACT day units, the complexity and specialized nature of care required in SACT day units, and it highlights the need for refined workload measurement tools.

Indexed as

NeoplasmsWorkloadAntineoplastic AgentsEvidence GapsHumansAntineoplastic Agentsday unitsnurse staffing levelsnurse workloadnursing workforceSACT day unitsscoping reviewsystemic anti‐cancer therapy

Identifiers

PMID42002727
PMCPMC13092646

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.