Validation of NANDA international nursing diagnoses at postoperative intensive care unit: quasi-experimental study

Author:

Serkova Dagmar1ORCID,Mareckova Jana2ORCID

Affiliation:

1. Department of Nursing and Midwifery, Faculty of Medicine , University of Ostrava , Czech Republic

2. Department of Anthropology and Health Sciences, Faculty of Education , Palacky University of Olomouc , Czech Republic

Abstract

Abstract Aim. 1. Implement repeated validation of three NANDA International nursing diagnoses before and after their experimental classification in daily nursing practice at an intensive care unit for adults, at a medium-sized hospital. 2. Identify statistically significant differences in Diagnostic Content Validation (DCV) values between the two validations. Material and methods. Fehring’s DCV model was used for validation of NANDA International diagnoses. The sample of assessors consisted of 33 experts in the first stage and of 31 experts in the second stage, the experts were in both cases ICU nurses. Nursing diagnoses were experimentally applied in practice for 3 months. The data were processed using descriptive statistics, Wilcoxon matched pairs test and paired t-test. Results. Total DCV scores of diagnoses after the first validation: Impaired gas exchange 00030 with DCV 0.67; Risk for disuse syndrome 00040 with DCV 0.69 and Risk for aspiration 00039 with DCV 0.73. The DCV values after the second validation were as follows: 0.63; 0.64 and 0.78 respectively. Conclusions. Nursing diagnoses: Impaired gas exchange 00030, Risk for disuse syndrome 00040 and Risk for aspiration 00039 are valid for nursing diagnostics of adult lucid postoperative intensive care unit patients at a medium-sized hospital.

Publisher

Walter de Gruyter GmbH

Subject

General Nursing

Reference13 articles.

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2. 2. Herdman TH, Kamitsuru S, Eds. NANDA International, Inc. Nursing Diagnoses: Definitions and Classification, 2018-2020. New York: Thieme; 2017.

3. 3. Thoroddsen A, Ehrenberg A, Sermeus W, et al. A survey of nursing documentation, terminologies and standards in European countries. NI 2012: Proceedings of the 11th International Congress on Nursing Informatics; 2012, p. 240.

4. 4. Fehring JR. Methods to validate nursing diagnoses. Heart and Lung.1987;16(6 Pt 1):625–629.

5. 5. Bocková S, Marečková J, Zapletalová J. Content validation of the diagnosis Ineffective Breathing Pattern. Kontakt. 2015;17(1):e24–e31.

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