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Evaluation of the effectiveness of artificial intelligence assisted interactive screen-based simulation in breast self-examination: An innovative approach in nursing students

dc.contributor.authorSimsek-Cetinkaya, Sahika
dc.contributor.authorCakir, Selda Karaveli
dc.date.accessioned2026-01-04T19:03:53Z
dc.date.issued2023-08-01
dc.description.abstractBreast self-examination is important in the early diagnosis of breast cancer. The use of traditional education methods is insufficient for student nurses to gain breast self-examination skills in nurse education. New and different education methods are needed to gain skills in nurse education.The aim of this study was to evaluate the effectiveness of artificial intelligence-assisted screen-based simulations practice and standard patient simulation in teaching breast self-examination skills in nursing undergraduate students.This study was a comparative intervention trial.This study was conducted at a university in XX, in XXX in the first semesters of the academic years 2022-2023.This study enlisted 103 students enrolled in first year in a nursing department. Students were randomized into artificial intelligence-assisted screen-based simulations practice group (n = 52) and standard patient simulation group (n = 51). Data were collected using student description form, breast self-examination checklist, student satisfaction and self-confidence in learning scale, Spielberger's state and trait anxiety inventory.The highest score regarding the total score means of breast self-examination skills belonged to the standard patient simulation group, and the differences between the groups were found to be statistically significant (p < 0.05). Although the mean score of anxiety levels of the students' artificial intelligence-assisted screen-based simulations practice group was higher than the standard patient simulation (p < 0.05). The mean score of the students' satisfaction with the simulation was higher in artificial intelligence-assisted screen-based simulations practice group than the standard patient simulation group (p < 0.05).The results of the research showed that the use of artificial intelligence-assisted simulation learning increased students' satisfaction, but at the same time students' anxiety increased. In addition, artificial intelligence-assisted simulation learning is not as effective as standard patient simulation learning in gaining breast self-examination skills.
dc.description.urihttps://doi.org/10.1016/j.nedt.2023.105857
dc.description.urihttps://pubmed.ncbi.nlm.nih.gov/37253303
dc.identifier.doi10.1016/j.nedt.2023.105857
dc.identifier.issn0260-6917
dc.identifier.openairedoi_dedup___::f128233c9b752630191f9324775215b0
dc.identifier.pubmed37253303
dc.identifier.scopus2-s2.0-85160049379
dc.identifier.startpage105857
dc.identifier.urihttps://hdl.handle.net/20.500.12597/40944
dc.identifier.volume127
dc.identifier.wos001010344500001
dc.language.isoeng
dc.publisherElsevier BV
dc.relation.ispartofNurse Education Today
dc.rightsCLOSED
dc.subjectPatient Simulation
dc.subjectArtificial Intelligence
dc.subjectHumans
dc.subjectLearning
dc.subjectEducation, Nursing, Baccalaureate
dc.subjectStudents, Nursing
dc.subjectClinical Competence
dc.subject.sdg4. Education
dc.subject.sdg3. Good health
dc.titleEvaluation of the effectiveness of artificial intelligence assisted interactive screen-based simulation in breast self-examination: An innovative approach in nursing students
dc.typeArticle
dspace.entity.typePublication
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New and different education methods are needed to gain skills in nurse education.The aim of this study was to evaluate the effectiveness of artificial intelligence-assisted screen-based simulations practice and standard patient simulation in teaching breast self-examination skills in nursing undergraduate students.This study was a comparative intervention trial.This study was conducted at a university in XX, in XXX in the first semesters of the academic years 2022-2023.This study enlisted 103 students enrolled in first year in a nursing department. Students were randomized into artificial intelligence-assisted screen-based simulations practice group (n = 52) and standard patient simulation group (n = 51). 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