JOURNAL ARTICLE
Application of NANDA‐I nursing diagnoses, nursing interventions classification, and nursing outcomes classification in research and practice of cardiac rehabilitation nursing: A scoping review.
Published In: International Journal of Nursing Knowledge, 2024, v. 35, n. 3. P. 256 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Duan, Xinyu; Ding, Yongxia; Ning, Yan; Luo, Mingyue 3 of 3
Abstract
Purpose: To describe the current application status of NANDA‐I nursing diagnoses, Nursing Interventions Classification (NIC), and Nursing Outcomes Classification (NOC) in cardiac rehabilitation nursing and identify useful NANDA‐I, NIC, and NOC (NNN) linkages for clinical nursing practitioners. Methods: This scoping review was performed in accordance with the Joanna Briggs Institut guidelines. We systematically searched eight databases, and the literature search took place between June and July 2023. The characteristics and results of the studies were synthesized and analyzed in a narrative way. Findings: The application of NANDA‐I nursing diagnosis, NIC and NOC in cardiac rehabilitation nursing can be divided into three topics: the content, value and effect of NANDA‐I nursing diagnosis, NIC and NOC. Conclusion: The application of NANDA‐I, NIC, and NOC in the field of cardiac rehabilitation nursing shows positive effects on the whole, which can provide more standardized theoretical guidance, improve nursing outcomes in clinical settings, and enhance nursing quality. Implications for nursing practice: This experience report will guide nurses to use NANDA‐I, NIC, and NOC for better cardiac rehabilitation care. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Nursing Knowledge. 2024/07, Vol. 35, Issue 3, p256
- Document Type:Article
- Subject Area:Nursing and Allied Health
- Publication Date:2024
- ISSN:2047-3087
- DOI:10.1111/2047-3095.12441
- Accession Number:178441588
- Copyright Statement:Copyright of International Journal of Nursing Knowledge is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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