Modeling the effects of education wıth artificial neural networks on anxiety level of coronary angiography patients: A randomized controlled trial
DOI:
https://doi.org/10.21276/apjhs.2017.4.4.17Keywords:
Anxiety, artificial neural network, coronary angiography, state and trait anxietyAbstract
Background: It is thought that the education to be given before the angiography procedure decreases the patients’ anxiety
level and increases effectively their continuation and adaptation to the medical treatment. Objective: To evaluate the effects
of education provided to coronary angiography patients on their state-trait anxiety level, the results of the studies obtained
experimentally were processed with artificial neural networks (ANN). Design: This study was experimental research.
Setting: The study was carried out at Angiography Unit, Heart Hospital of Erciyes University. Participants: Hundred patients
were included in the study; 50 experimental and 50 control group. Intervention: It was trained that experimental groups’ all
the patients by researcher. Measurements: The data of the research were collected with a questionnaire form and state-trait
anxiety inventory form. In addition to statistical analysis, a modeling system from obtained statistical results is implemented
using ANN. Results: The average state-trait anxiety scores before the angiography procedure decreased after the angiography
procedure for the experimental group, whereas those anxiety scores of the control group before the angiography procedure
increased after the procedure. Furthermore, the estimation of results is performed very successful in the ratio of 99% by ANN
system. Conclusion: It was seen that the education provided before the angiography procedure was effective on the state-trait
anxiety levels after the angiography. This study presented that artificial intelligence algorithms based on an ANN could be used
in systems that analyzed social and health problems.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Asian Pacific Journal of Health Sciences applies the Creative Commons Attribution (CC-BY) license to published articles. Under this license, authors retain ownership of the copyright for their content, but they allow anyone to download, reuse, reprint, modify, distribute and/or copy the content as long as the original authors and source are cited. Appropriate attribution can be provided by simply citing the original article.