The JNR Reorganization Advisory Panel (JNR RAP)

Vollständiger Abstract

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<h4>Background</h4>Artificial intelligence (AI)-based competency assessments have been incorporated into nurse recruitment processes in South Korea; however, nursing applicants' and educators' experiences with these assessments, as well as their perceptions of the effectiveness of these assessments in nurse selection, have not been examined.<h4>Purpose</h4>The aim of this study was to comprehensively explore the perceptions of nursing applicants and educators of the effectiveness of AI-based competency assessments in the process of selecting new nurses for patient care roles.<h4>Methods</h4>A qualitative descriptive design was used in this study. Data were collected between February and August 2024 in South Korea. Semistructured focus group interviews were conducted with 10 nursing applicants and 10 nurse educators, including nursing professors and nurse managers, regarding their experience participating in AI-based competency assessments. Focus group interviews were conducted in five groups, each consisting of three to five participants. Data were analyzed using conventional content analysis. The COREQ (Consolidated Criteria for Reporting Qualitative Research) guidelines were used to assess study rigor.<h4>Results</h4>The analysis of the interviews revealed eight subthemes and four themes derived from 32 codes. The following four themes were identified: (a) doubts about the evaluation method and criteria, (b) efficiency of AI-based competency assessments, (c) challenges in preparing for AI-based competency assessments, and (d) improvements and alternative approaches to nurse selection.<h4>Conclusions/implications for practice</h4>This study highlights the potential of AI-based competency assessments to improve fairness and efficiency in the process of selecting and hiring new nurses. To ensure validity, developing tailored algorithms that reflect core nursing competencies and establishing clear evaluation criteria is necessary. Also, interdisciplinary collaboration is needed to support the ethical and practical integration of AI in the process of selecting and hiring new nurses.

Abstract: PubMed · Datensatz