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 (BMC Nursing)
Abstract Background It 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. Methods A 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. Results A 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. Conclusion Moreover, 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.