Evidence map›Paper›PMID 41286824›Full record

ArticleBMC nursing2025

The effect of repeated simulation-based disaster education on nursing students' self-efficacy in disaster response.

Ebru Konal Korkmaz, Aynur Uysal Toraman

Abstract read
In one paragraph

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
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

2 authors.

Ebru Konal KorkmazFaculty of Nursing, Public Health Nursing Department, Ege University, İzmir, Turkey. ebruknl@gmail.com.
Aynur Uysal ToramanFaculty of Nursing, Public Health Nursing Department, Ege University, İzmir, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to its geographic and climatic characteristics, Turkey faces a high risk of natural disasters such as earthquakes, floods, and landslides. Therefore, nurses must be competent in all phases of the disaster management cycle. However, the current state of nursing education in Turkey is inadequate, leaving students feeling unprepared and uncertain about their roles and responsibilities in disaster situations. Furthermore, no studies have evaluated the use of standardized patient simulations in disaster nursing in Turkey. The objective of the present study is to evaluate the effect of repeated standardized patient simulation-based disaster training on nursing students’ self-efficacy.

methodsA quasi-experimental study was carried out with 44 fourth-year nursing students. The disaster nursing course includes theory and practice. Within the scope of the study, theoretical training and laboratory practices were carried out on obstetric evaluation and pregnancy follow-up in disasters, care practices after abortion, family planning counselling in disasters, sexual and reproductive health. After training, two repeated standardized patient simulations were conducted. Data were analyzed using SPSS version 25.0.

resultsThe median score for disaster nursing practice skills increased among students as a result of repeated simulations, and significant differences were found between applications (p < 0.001). Additionally, a significant difference was found in the median scores on the Disaster Response Self-Efficacy Scale before and after the first and repeated standardized patient simulations s(p < 0.001).

conclusionsSimulation-based education improved nursing students’ disaster nursing skills and increased their disaster response self-efficacy. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Disaster nursingNursing educationPatient simulationSimulation

Identifiers

PMID41286824
PMCPMC12642286

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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.