Evidence map›Paper›PMID 38836188›Full record

ArticleSAGE open nursing

Decoding Nursing Job Demands: A Multicenter Cross-Sectional Descriptive Study Assessing Nursing Workload in Hospital Medical-Surgical Wards.

Dhurata Ivziku, Raffaella Gualandi, Federica Maria Pia Ferramosca, Marzia Lommi, Maria Ymelda Tolentino Diaz, Barbara Raffaele, Graziella Montini, Barbara Porcelli, Alessandro Stievano, Gennaro Rocco and 4 more

Abstract read
In one paragraph

Article in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

14 authors.

Dhurata IvzikuDirection of Health Professions, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Raffaella GualandiDirection of Health Professions, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Federica Maria Pia FerramoscaDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
Marzia LommiLocal Health Authority Roma 2, Rome, Italy.ORCID https://orcid.org/0000-0001-5904-1032
Maria Ymelda Tolentino DiazLocal Health Authority Roma 2, Rome, Italy.
Barbara RaffaeleLocal Health Authority Roma 2, Rome, Italy.
Graziella MontiniLocal Health Authority Roma 2, Rome, Italy.
Barbara PorcelliLocal Health Authority Roma 2, Rome, Italy.
Alessandro StievanoDepartment of Clinical and Experimental Medicine, University of Messina, Messina, Italy.
Gennaro RoccoDepartment of Nursing, Catholic University "Our Lady of Good Counsel", Tirana, Albania.
Ippolito NotarnicolaDepartment of Nursing, Catholic University "Our Lady of Good Counsel", Tirana, Albania.ORCID https://orcid.org/0000-0002-4828-8811
Roberto LatinaDepartment of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialities, University of Palermo, Palermo, Italy.
Anna De BenedictisClinical Directory, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.
Daniela TartagliniDirection of Health Professions, Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nursing workload is largely studied but poorly explored under physical, mental, and emotional dimensions. Currently, only a limited number of variables have been linked to nursing workload and work contexts. Purpose: The study aimed to investigate whether it is feasible to identify variables that consistently correlate with nursing workload and others that are specific to the context. Methods: We employed a descriptive correlational analysis and a cross-sectional design. Data were collected through a survey distributed to registered nurses working across Italy, at the conclusion of randomly assigned morning or afternoon shifts. Results: We received 456 surveys from 195 shifts, collected from nurses in four public and two private hospitals. Commonly associated variables with nursing workload dimensions included patient complexity of care, admission/discharge or transfer, informing patients/relatives, contacting physicians, and unscheduled activities. Variables categorized as setting-specific were patient isolation and specialties, nurse-to-patient ratio, adequacy of staff in the shift, peer collaboration, healthcare documentation, educating others, and medical urgency. Conclusions: In summary, certain variables consistently correlate with nursing workload across settings, while others are specific to the context of care. It is imperative for nurses and nurse managers to measure the nursing workload in various dimensions, enabling the prompt implementation of improvement actions.

Indexed as

emotional workloadhospitalsmetal workloadnursesphysical workloadworkflowworking conditionsworkloadworkplace

Identifiers

PMID38836188
PMCPMC11149452

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.