Background <p>Neurosurgical nursing is a high-demand specialized field requiring comprehensive professional competency. In 2023 when this study commenced, no standardized, validated competency evaluation framework existed for Chinese neurosurgical specialist nurses, and no official certification program was available. Although the Chinese Nursing Association launched neurosurgical specialist nurse certification in 2025, a structured, evidence-based assessment tool remains lacking, leaving a critical gap in clinical nursing talent training and management. This study aimed to construct competency evaluation indicators for neurosurgical specialist nurses.</p> Methods <p>A mixed-methods Delphi-AHP research design was adopted. Based on systematic literature retrieval, theoretical research, and group discussions, the initial draft of Competency for Neurosurgical Specialist Nurses was preliminarily formulated. A systematic literature review was conducted in 5 domestic and foreign databases from 2018 to 2023, with clear inclusion and exclusion criteria; 15 experts with rich neurosurgical nursing experience were selected for expert consultation. Subsequently, two rounds of expert consultations using the Delphi method were conducted to modify, add, and delete indicators, and the analytic hierarchy process (AHP) was used to determine the weight of each indicator.</p> Results <p>The effective questionnaire response rates for both rounds of expert consultations were both 100%. The expert authority coefficients of the two rounds were 0.907 and 0.913, respectively. The Kendall’s concordance coefficients for the two rounds were 0.164 and 0.343,&lt; 0.01). Finally, a set of competency evaluation indicators for neurosurgical specialist nurses was developed, including 5 first-level indicators, 14&#xa0;s-level indicators, and 64 third-level indicators; among them, Professional Theoretical Knowledge and Professional Skills had the highest comprehensive weights (both 0.3717).</p> Conclusion <p>The competency evaluation indicators for neurosurgical specialist nurses constructed in this study show good expert authority, high consensus and acceptable methodological validity verified by Delphi and AHP methods, provide a structured reference for training, assessment, and management of neurosurgical specialist nurses.</p>

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Developing competency evaluation indicators for neurosurgical specialist nurses: a Delphi-AHP study

  • Limei Song,
  • Wei Li,
  • Zheng Wang

摘要

Background

Neurosurgical nursing is a high-demand specialized field requiring comprehensive professional competency. In 2023 when this study commenced, no standardized, validated competency evaluation framework existed for Chinese neurosurgical specialist nurses, and no official certification program was available. Although the Chinese Nursing Association launched neurosurgical specialist nurse certification in 2025, a structured, evidence-based assessment tool remains lacking, leaving a critical gap in clinical nursing talent training and management. This study aimed to construct competency evaluation indicators for neurosurgical specialist nurses.

Methods

A mixed-methods Delphi-AHP research design was adopted. Based on systematic literature retrieval, theoretical research, and group discussions, the initial draft of Competency for Neurosurgical Specialist Nurses was preliminarily formulated. A systematic literature review was conducted in 5 domestic and foreign databases from 2018 to 2023, with clear inclusion and exclusion criteria; 15 experts with rich neurosurgical nursing experience were selected for expert consultation. Subsequently, two rounds of expert consultations using the Delphi method were conducted to modify, add, and delete indicators, and the analytic hierarchy process (AHP) was used to determine the weight of each indicator.

Results

The effective questionnaire response rates for both rounds of expert consultations were both 100%. The expert authority coefficients of the two rounds were 0.907 and 0.913, respectively. The Kendall’s concordance coefficients for the two rounds were 0.164 and 0.343,< 0.01). Finally, a set of competency evaluation indicators for neurosurgical specialist nurses was developed, including 5 first-level indicators, 14 s-level indicators, and 64 third-level indicators; among them, Professional Theoretical Knowledge and Professional Skills had the highest comprehensive weights (both 0.3717).

Conclusion

The competency evaluation indicators for neurosurgical specialist nurses constructed in this study show good expert authority, high consensus and acceptable methodological validity verified by Delphi and AHP methods, provide a structured reference for training, assessment, and management of neurosurgical specialist nurses.