Is the Application of Artificial Intelligence-Based Competency Assessments for Selecting Clinical Nurses Acceptable? A Qualitative Study
Background 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. Purpose 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 proce…
Interviewees and the authors see AI-based competency assessments as having potential to make selecting and hiring new nurses fairer and more efficient.
Participants doubted the evaluation method and criteria, and found preparing for the assessments challenging, so validity depends on tailored algorithms and clear criteria.
Evidence
- Peer-reviewedJournal of Nursing Research2026-10-01
How should this claim be treated?
Truvace Impact Record TRV-2026-1582, v1: “Is the Application of Artificial Intelligence-Based Competency Assessments for Selecting Clinical Nurses Acceptable? A Qualitative Study.” Truvace, 2026-10-16. /record/TRV-2026-1582 (accessed at citation time). sha256 051a7d94c9177acc…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1582 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.
ace