Evidence map›Paper›PMID 34825432›Full record

ArticleJournal of nursing management2022

Defining nursing workload predictors: A pilot study.

Dhurata Ivziku, Federica Maria Pia Ferramosca, Lucia Filomeno, Raffaella Gualandi, Maddalena De Maria, Daniela Tartaglini

Abstract read
In one paragraph

Article in Journal of nursing management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

  1. Article
  2. Hospital-Based Robotic Applications in Nursing Practice: A Scoping Review.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2026
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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.

Dhurata IvzikuDepartment of Nursing Innovation and Development, Campus Bio-Medico of Rome University Hospital, Rome, Italy.ORCID https://orcid.org/0000-0003-0091-7524
Federica Maria Pia FerramoscaDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
Lucia FilomenoDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
Raffaella GualandiDepartment of Health Professions, Campus Bio-Medico of Rome University Hospital, Rome, Italy.
Maddalena De MariaDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
Daniela TartagliniDepartment of Health Professions, Campus Bio-Medico of Rome University Hospital, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo explore predictors of perceived nursing workload in relation to patients, nurses and workflow.

backgroundNursing workload is important to health care organisations. It determines nurses' well-being and quality of care. Nevertheless, its predictors are barely studied.

methodsA cross-sectional prospective design based on the complex adaptive systems theory was used. An online survey asked nurses to describe perceived workload at the end of every shift. Data were gathered from five medical-surgical wards over three consecutive weeks. We received 205 completed surveys and tested multivariate regression models.

resultsPatient acuity, staffing resources, patient transfers, documentation, patient isolation, unscheduled activities and patient specialties were significant in predicting perceived workload. Nurse-to-patient ratio proved not to be a predictor of workload.

conclusionsThis study significantly contributed to literature by identifying some workload predictors. Complexity of patient care, staffing adequacy and some workflow aspects were prominent in determining the shift workload among nurses. IMPLICATIONS FOR NURSING MANAGEMENT: Our findings provide valuable information for top and middle hospital management, as well as for policymakers. Identification of predictors and measurement of workload are essential for optimizing staff resources, workflow processes and work environment. Future research should focus on the appraisal of more determinants.

Indexed as

Nursing Staff, HospitalWorkloadCross-Sectional StudiesHumansPersonnel Staffing and SchedulingPilot ProjectsProspective Studieshospitalnursingstaffingworkflowworkload

Identifiers

PMID34825432
PMCPMC9300160

What OpenQuestion holds

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LicenceCC BY
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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.