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Deductive Care Methodology: Describing and testing modes of care research.
Enfermería clínica (English Edition) 2024 April 12
OBJECTIVE: Define the modes of procedure of the Deductive Care Methodology (DCM) in the generation of knowledge about person's health care.
METHODOLOGY: Design and test of the DCM modes based on three phases: mapping of the MDC, generation of models from this methodology and testing of the models through studies in a clinical context.
RESULTS: The MDC presents five levels of abstraction with three modes broken down to 16 types. The modes are: Philosophical Mode to conceptualize and obtain generalities about reality, Mathematical Mode to operate with generalities, and Physical Mode to operationally verify, validating the results and the predictive capacity of the model. This MDC allows the creation of three models: Knowledge Model about Person Care, an ontology of care, Vulnerability Model about the person and Taxonomic Triangulation Model for knowledge management. All models generate products for computational knowledge management. In addition, the models are applied in teaching and generate research with more than a hundred participations in conferences and journals, of which five impact publications (from 2008 to 2022) classified in the categories of Nursing and Informatics are analysed.
CONCLUSIONS: The MDC collects prior knowledge to work with certainties, evidence and applying inferences that do not depend on the number of cases or inductive designs. This research presents a formal structure of the MDC with an interdisciplinary orientation between Health Sciences and Computer Sciences.
METHODOLOGY: Design and test of the DCM modes based on three phases: mapping of the MDC, generation of models from this methodology and testing of the models through studies in a clinical context.
RESULTS: The MDC presents five levels of abstraction with three modes broken down to 16 types. The modes are: Philosophical Mode to conceptualize and obtain generalities about reality, Mathematical Mode to operate with generalities, and Physical Mode to operationally verify, validating the results and the predictive capacity of the model. This MDC allows the creation of three models: Knowledge Model about Person Care, an ontology of care, Vulnerability Model about the person and Taxonomic Triangulation Model for knowledge management. All models generate products for computational knowledge management. In addition, the models are applied in teaching and generate research with more than a hundred participations in conferences and journals, of which five impact publications (from 2008 to 2022) classified in the categories of Nursing and Informatics are analysed.
CONCLUSIONS: The MDC collects prior knowledge to work with certainties, evidence and applying inferences that do not depend on the number of cases or inductive designs. This research presents a formal structure of the MDC with an interdisciplinary orientation between Health Sciences and Computer Sciences.
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