Development and Content Validation of the Graduate Nursing Student Clinical Remediation Algorithm

Background and Purpose: Graduate nursing programs require structured processes to address clinical deficiencies while ensuring fairness and patient safety. However, existing remediation practices often lack standardization and transparency. To address this gap, a clinical remediation algorithm was developed and evaluated to assist in managing unsatisfactory clinical performance. Methods: The 26-item Graduate Nursing Student Clinical Remediation (GNS-CR) Algorithm, developed from literature and expert feedback, was reviewed by 20 invited experts in graduate nursing education. Content validity indices (CVI) were calculated at the item and scale level. Results: Item-level CVI scores ranged from .80 to 1.00, with a scale-level CVI of .923, surpassing accepted thresholds. Feedback confirmed the algorithm's clarity, logical structure, and relevance. Conclusions: The GNS-CR Algorithm demonstrated strong content validity and offers a systematic, transparent approach to clinical remediation. Future research should evaluate its effectiveness in academic and clinical settings.