Evidence map›Paper›PMID 40598298›Full record

ArticleBMC nursing2025

Nurses' knowledge, attitudes, and decision-making related to sepsis assessment and management in Palestinian intensive care units.

Hatem Khallaf, Moath Abu Ejheisheh, Malakeh Z Malak, Anas Shehadeh, Ahmad Ayed, Ahmad Batran, Mosaab Farajallah

Abstract read
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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

7 authors.

Hatem KhallafRed Crescent Specialized Hospital, Hebron, Palestine.
Moath Abu EjheishehFaculty of Allied Medical Sciences, Department of Nursing, Palestine Ahliya University, Bethlehem, Palestine.
Malakeh Z MalakCommunity Health Nursing, Faculty of Nursing, AL-Zaytoonah Univerity of Jordan, P.O. Box: 130, Amman, 11733, Jordan. malakehmalak@yahoo.com.
Anas ShehadehAmerican University of the Middle East, Egaila, 54200, Kuwait.
Ahmad AyedFaculty of Nursing, Arab American University, Jenin, Palestine.
Ahmad BatranFaculty of Allied Medical Sciences, Department of Nursing, Palestine Ahliya University, Bethlehem, Palestine.
Mosaab FarajallahFaculty of Allied Medical Sciences, Department of Nursing, Palestine Ahliya University, Bethlehem, Palestine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSepsis is a major global health issue leading to severe organ damage and causing 11 million deaths annually. It affects 50 million people worldwide and requires extensive knowledge and resources. Intensive care nurses play an important role in evaluating sepsis, identifying it, escalating care, and initiating treatment. This study aimed to assess the Intensive Care Unit (ICU) nurses' knowledge, attitudes, and decision-making skills related to sepsis assessment and management, and determine the factors influencing nurses' decision-making in ICUs.

methodsA cross-sectional study was conducted among ICU registered nurses in Palestine. A convenience sample of 243 participants was recruited. A structured self-reported questionnaire comprising three sections: socio-demographic characteristics, Nurses' Knowledge and Attitudes Survey, and the Nurses' Decision-Making Instrument (NDMI) was used to collect the data from April to June 2024.

resultsThe findings revealed that participants demonstrated means of 82.74 ± 16.34, 72.31 ± 22.32, and 88.36 ± 14.84 for knowledge, attitudes, and decision-making skills, respectively, reflecting high knowledge, moderate attitudes, and high decision-making skills levels. Decision-making skills were correlated with knowledge (r = 0.348, p < 0.001), attitudes (r = 0.607, p < 0.001), sex (r= -0.193, p < 0.01), and sepsis training (r = 0.607, p < 0.001). The predictors of decision-making skills were sepsis training (B = 0.413, p < 0.01), attitudes (B = 0.354, p < 0.01), and knowledge (B = 0.147, p < 0.01).

conclusionThis study highlights that ICU nurses' knowledge, attitudes, and training significantly influence their decision-making skills related to sepsis management. Targeted sepsis education programs, incorporating early recognition strategies, guideline adherence, and protocol-driven interventions, are crucial for enhancing nurses' clinical decision-making. Strengthening these educational initiatives will improve timely and evidence-based sepsis care, ultimately leading to better patient outcomes in ICUs. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AttitudesDecision-makingIntensive care unitsKnowledgeManagementSepsis

Identifiers

PMID40598298
PMCPMC12211300

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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.