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DIEN Expert System Version 1 to formulate nursing diagnoses
María Margarita Fanning Balarezo1,1, María Rosa Vásquez Pérez2, Oscar Efrain Capuñay Uceda3
1Universidad Nacional Pedro Ruiz Gallo. Lambayeque- Perú. mfanning@unprg.edu.pe Universidad Nacional Pedro Ruiz Gallo Universidad Nacional Pedro Ruiz Gallo Lambayeque Perú mfanning@unprg.edu.pe.
Introduction:
Students and professionals' difficulty in formulating nursing diagnoses underlines the need to use tools based on expert systems.
Objective:
To develop an expert system to formulate nursing diagnoses and to evaluate their attributes.
Materials And Methods:
This technological-descriptive study was conducted in two phases. The first phase was the design and construction of the expert system and the evaluation of its attributes (usability, functionality, reliability, and portability). In the second phase, 68 people participated, including students and nurses. Two questionnaires were applied, one to evaluate usability (validated by exploratory factor analysis, with a Cronbach's alpha reliability of 0.93) and the other to evaluate the remaining attributes (validated with Aiken's V: 0.91; with a Cronbach's alpha reliability of 0.91). The data were processed in Excel, using descriptive statistics.
Results:
An expert system was designed using the NANDA International 2021-2023 as its knowledge base. Its interface allows users to input age group, characteristics, and factors, generating diagnostic labels. Most users rated the attributes of usability (79.41%), functionality (82.35%), reliability (77.94%), and portability (86.76%) as "very good."
Discussion:
The DIEN Expert System Version 1 develops skills to identify characteristics and related or risk factors. It familiarizes users with the standardized nursing language and strengthens critical thinking to formulate contextualized diagnoses for the person cared for.
Conclusion:
The DIEN Version 1 enables the use of standardized nursing diagnostic language, as it demonstrates the scientific and systematized work in care. The favorable opinion of its attributes by most participants predicts its acceptance in training and care settings.
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