Attributing Fuzzy Values to Nursing Diagnoses and Their Elements: The Specialists' Opinion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)PurposeTo test the viability of to use specialists' opinions to establish degrees of membership between nursing diagnoses and its elements (defining characteristics or risk factors), based on the concepts of fuzzy sets theory. This strategy may feasibly mapping the specialist's knowledge on the diagnostic task. MethodsSpecialists were invited to reflect on the relationship between diagnoses and elements using linguistic variables, with a numerical representation. FindingsWe generated four matrices of 28 diagnoses and 62 elements. Out of 905 possibilities, we identified 286 relationships, represented in graphs. ConclusionsThe strategy was able to identify degrees of membership between nursing diagnoses and elements. ImplicationsIt seems that this method, if expanded, would contribute to refining and mapping the NANDA-I terminology. ObjetivoTestar a viabilidade de utilizar a opiniAo de especialistas para estabelecer graus de pertinencia entre diagnosticos de enfermagem e seus elementos (caracteristicas definidoras ou fatores de risco), baseado nos conceitos da Teoria dos Conjuntos Fuzzy. Esta estrategia podera viabilizar o mapeamento do conhecimento do especialista na tarefa diagnostica. MetodosEspecialistas foram convidados a refletir na relacAo existente entre diagnosticos e elementos, utilizando variaveis linguisticas, com representacAo numerica. ResultadosForam geradas quatro matrizes de 28 diagnosticos e 62 elementos. Dentre 905 possibilidades, foram identificadas 286 relacoes, representadas em grafos. ConclusoesA estrategia foi adequada para identificar graus de pertinencia entre diagnosticos de enfermagem e elementos. ImplicacoesVislumbra-se que esta metodologia, se expandida, contribua ao refinamento e mapeamento da classificacAo NANDA-I.243134141University of Sao Paulo's School of NursingFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [2010/10158-2]CNPq [2009/14232-5

Application of a model based on fuzzy logic for evaluating nursing diagnostic accuracy of students

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Purpose: To describe a model for assessing nursing diagnostic accuracy and its application to undergraduate students, comparing students' performance according to the course year. Methods: 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. Results: 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. Conclusions: 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. Limitations: 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. (C) 2013 Elsevier Ireland Ltd. All rights reserved.829875881Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq