Evidence map›Paper›PMID 39538279›Full record

ArticleBMC nursing2024

Designing and evaluating ECG interpretation software for undergraduate nursing students in Iran: a non-equivalent control group pretest-posttest design.

Noushin Kohan, Nasrin Navabi, Maryam Karbasi Motlagh, Fatemeh Ahmadinia

Abstract read
In one paragraph

Article in BMC nursing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Review
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

4 authors.

Noushin KohanDepartment of Medical Education, Department of eLearning in Medical Education, Smart University of Medical Sciences, Tehran, Iran.
Nasrin NavabiNursing and Midwifery Department, Faculty of Nursing and Midwifery, Fatemeh Zahra University of Medical Sciences, Ramsar, Iran.
Maryam Karbasi MotlaghDepartment of Medical Education, Education Development Center, Tehran University of Medical Sciences, Tehran, Iran.
Fatemeh AhmadiniaEducation Development Center, Mazandaran University of Medical Sciences, Imam Square (RA), Joybar Three Ways, At the Beginning of the Valiasr Highway (AS), Sari, Mazandaran Province, Iran. Ahmadinia.fatemeh@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is essential for nurses to interpret electrocardiograms accurately in cardiac care and emergency departments. Despite rigorous training, nursing students frequently encounter challenges in mastering electrocardiogram interpretation. The purpose of our study was to evaluate the effectiveness of an electrocardiogram interpretation software specifically designed for Iranian nursing students enrolled in undergraduate programs.

methodsA nonequivalent control group pretest-posttest design was conducted at Ramsar University of Medical Sciences in 2020. Using the census sampling method, 75 nursing students from the two educational hospitals were recruited. Participants were divided into two intervention groups and a control group according to their rotations at their respective hospitals. The software contains evidence-based guidelines, interactive learning modules, practice exercises, and real-life examples. Statistical analyses, including chi-square tests and t tests, were conducted using descriptive and inferential statistics.

resultsA comparison of the two groups according to demographic characteristics, such as sex, age, was not statistically significant (p > 0.05). The knowledge and skills of the individuals in the control group significantly improved in comparison to those before the intervention. The use of software enhanced students' ability to interpret electrocardiograms. Moreover, there was no statistically significant difference between the intervention and control groups in terms of knowledge and skills of electrocardiogram interpretation. Nursing students reported higher levels of satisfaction after using the software.

conclusionMoreover, undergraduate nursing students were able to learn more using electrocardiogram interpretation software combined with traditional teaching methods. Combining these two methods in a blended learning approach can improve learning. This software can be integrated into nursing curricula to assist nursing students in interpreting electrocardiograms.

Indexed as

Computer applicationsElectrocardiogramNursingQuasi-experimentalSoftwareStudentStudy

Identifiers

PMID39538279
PMCPMC11562660

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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.