아동병동 입원 환아를 대상으로 간호학생이 내린 간호진단의 네트워크 분석
The Network Analysis of Nursing Diagnoses for Children Admitted in Pediatric Units Determined by Nursing Students
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Objectives: The purpose of this study was to identify key nursing diagnoses and sub groups of nursing diagnoses for children admitted in pediatric units using a Network Analysis. Methods: Data were obtained from 205 case reports submitted from nursing students who had done a clinical practicum in pediatric units. Five hundred and twenty-four NANDA-I nursing diagnoses were extracted from the case reports. Frequency, Centrality, and Clusters were generated by Network analysis with NetMiner 4.0. Results: Seventy eight different nursing diagnoses were identified. In general pediatric units, Hyperthermia was the most frequently used and highest degree centrality diagnosis. Ineffective airway clearness showed the highest between centrality. In a pediatric intensive unit, Impaired gas exchange showed the highest frequency, degree centrality, and between centrality. Four sub-groups in general pediatric units and 2 sub-groups in a pediatric intensive unit were identified. Conclusions: The results from this study could support clinical decision for selecting nursing diagnoses accurately and promptly.
Abstract
Objectives: The purpose of this study was to identify key nursing diagnoses and sub groups of nursing diagnoses for children admitted in pediatric units using a Network Analysis. Methods: Data were obtained from 205 case reports submitted from nursing students who had done a clinical practicum in pediatric units. Five hundred and twenty-four NANDA-I nursing diagnoses were extracted from the case reports. Frequency, Centrality, and Clusters were generated by Network analysis with NetMiner 4.0. Results: Seventy eight different nursing diagnoses were identified. In general pediatric units, Hyperthermia was the most frequently used and highest degree centrality diagnosis. Ineffective airway clearness showed the highest between centrality. In a pediatric intensive unit, Impaired gas exchange showed the highest frequency, degree centrality, and between centrality. Four sub-groups in general pediatric units and 2 sub-groups in a pediatric intensive unit were identified. Conclusions: The results from this study could support clinical decision for selecting nursing diagnoses accurately and promptly.
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