Application Of A Model Based On Fuzzy Logic For Evaluating Nursing Diagnostic Accuracy Of Students.

dc.creatorLopes, Maria Helena Baena de Moraes
dc.creatorJensen, Rodrigo
dc.creatorda Cruz, Diná de Almeida Lopes Monteiro
dc.creatorMatos, Fabiana Gonçalves de Oliveira Azevedo
dc.creatorSilveira, Paulo Sérgio Panse
dc.creatorOrtega, Neli Regina Siqueira
dc.date2013-Sep
dc.date2015-11-27T13:31:48Z
dc.date2015-11-27T13:31:48Z
dc.date.accessioned2018-03-29T01:17:54Z
dc.date.available2018-03-29T01:17:54Z
dc.identifierInternational Journal Of Medical Informatics. v. 82, n. 9, p. 875-81, 2013-Sep.
dc.identifier1872-8243
dc.identifier10.1016/j.ijmedinf.2013.04.010
dc.identifierhttp://www.ncbi.nlm.nih.gov/pubmed/23746432
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/200664
dc.identifier23746432
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1300897
dc.descriptionTo describe a model for assessing nursing diagnostic accuracy and its application to undergraduate students, comparing students' performance according to the course year. This model, based on the theory of fuzzy sets, guides a student through three steps: (a) the student must parameterize the model by establishing relationship values between defining characteristic/risk factors and nursing diagnoses; (b) presentation of a clinical case; (c) the student must define the presence of each defining characteristic/risk factors for the clinical case. Subsequently, the model computes the most plausible diagnoses by taking into account the values indicated by the student. This gives the student a performance score in comparison with parameters and diagnoses that were previously provided by nursing experts. These nursing experts collaborated with the construction of the model indicating the strength of the relationship between the concepts, meaning, they parameterized the model to compare the student's choice with the expert's choice (gold standard), thus generating performance scores for the student. The model was tested using three clinical cases presented to 38 students in their third and fourth years of the undergraduate nursing course. Third year students showed superior performance in identifying the presence of defining characteristic/risk factors, while fourth year students showed superior performance in the diagnoses by the model. The Model for Evaluation of Diagnostic Accuracy Based on Fuzzy Logic applied in this study is feasible and can be used to evaluate students' performance. In this regard, it will open a broad variety of applications for learning and nursing research. Despite the ease in filling the printed questionnaires out, the number of steps and fields to fill in may explain the considerable number of questionnaires with incorrect or missing data. This was solved in the digital version of the questionnaire. In addition, in more complex cases, it is possible that an expert opinion can lead to a wrong decision due to the subjectivity of the diagnostic process.
dc.description82
dc.description875-81
dc.languageeng
dc.relationInternational Journal Of Medical Informatics
dc.relationInt J Med Inform
dc.rightsfechado
dc.rightsCopyright © 2013 Elsevier Ireland Ltd. All rights reserved.
dc.sourcePubMed
dc.subjectAged
dc.subjectCardiovascular Diseases
dc.subjectFemale
dc.subjectFuzzy Logic
dc.subjectHumans
dc.subjectLung Diseases
dc.subjectMiddle Aged
dc.subjectNursing Diagnosis
dc.subjectQuestionnaires
dc.subjectSoftware
dc.subjectStudents, Nursing
dc.subjectDecision Support Techniques
dc.subjectEducational Technology
dc.subjectFuzzy Logic
dc.subjectNursing Diagnosis
dc.titleApplication Of A Model Based On Fuzzy Logic For Evaluating Nursing Diagnostic Accuracy Of Students.
dc.typeArtículos de revistas


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