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metadata.dc.type: Artigo de Periódico
Title in Portuguese: Classification tree for the assessment of sedentary lifestyle among hypertensive
Author: Martins, Larissa Castelo Guedes
Lopes, Marcos Venícios de Oliveira
Guedes, Nirla Gomes
Menezes, Angélica Paixão de
Farias, Odaleia de Oliveira
Santos, Naftale Alves dos
Issue Date: Jan-2016
Publisher: Investigación y educación en enfermería
Keywords: Diabetes Mellitus Tipo 2
Diagnóstico de Enfermagem
Nursing Diagnosis
Citation: MARTINS, L. C. G. et al. Classification tree for the assessment of sedentary lifestyle among hypertensive. Investigacion y Educacion en Enfermeria, Medellin, v. 34, n. 2, p. 113-119, jan./apr. 2016.
Abstract: Objective. To develop a classification tree of clinical indicators for the correct prediction of the nursing diagnosis “Sedentary lifestyle” (SL) in people with high blood pressure (HTN). Methods. A cross- sectional study conducted in an outpatient care center specializing in high blood pressure and Mellitus diabetes located in northeastern Brazil. The sample consisted of 285 people between 19 and 59 years old diagnosed with high blood pressure and was applied an interview and physical examination, obtaining socio- demographic information, related factors and signs and symptoms that made the defining characteristics for the diagnosis under study. The tree was generated using the CHAID algorithm ( Chi-square Automatic Interaction Detection ). Results. The construction of the decision tree allowed establishing the interactions between clinical indicators that facilitate a probabilistic analysis of multiple situations allowing quantify the probability of an individual presenting a sedentary lifestyle. The tree included the clinical indicator Choose daily routine without exercise as the first node. People with this indicator showed a probability of 0.88 of presenting the SL. The second node was composed of the indicator Does not perform physical activity during leisure, with 0.99 probability of presenting the SL with these two indicators. The predictive capacity of the tree was established at 69.5%. Conclusion. Decision trees help nurses who care HTN people in decision- making in assessing the characteristics that increase the probability of SL nursing diagnosis, optimizing the time for diagnostic inference.
ISSN: Print version 0120-5307
Appears in Collections:DENF - Artigos publicados em revistas científicas

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