Bilişsel Yanlılıklar Hemşirelik Öğrencilerinin Klinik Kararlarını Simülasyonlarda Zayıflatıyor

Özet (abstract)

Background Cognitive biases are systematic errors in human reasoning that can compromise clinical decision-making (CDM) in healthcare. While extensively studied in medicine, nursing research on cognitive biases in CDM remains limited. Aim This study aimed to explore and identify cognitive biases and examine their relationship with nursing students' clinical decision-making during a high-fidelity simulation of a deteriorating patient scenario. Design A mixed-methods design was employed, incorporating concurrent and retrospective think-aloud (TA) protocols and observational data. Methods Twenty-three final-year Bachelor of Science nursing students participated in a high-fidelity, manikin-based simulation involving a clinically deteriorating patient scenario. A catalogue of 12 cognitive biases was developed from the literature and used to code statements from concurrent and retrospective think-aloud protocols and observational data using content analysis. Results A total of 166 bias occurrences were identified across all data sources (63 concurrent TA; 51 retrospective TA; 52 observation). Representativeness was the most frequently identified bias overall, particularly in retrospective think-aloud data. Order effect was the most common bias in concurrent think-aloud data, and representativeness and order effect were the most common in observational data. Premature closure and availability were also prominent across all sources of data. Biases occurred proportionally across both Type 1 (automated/pattern recognition) and Type 2 (hypothetico-deductive) decision-making, with notable differences between concurrent and retrospective think-aloud findings. The findings also suggest that simulation may support students' awareness of cognitive bias. Conclusion High-fidelity simulation, combined with think-aloud protocols and observation, provided a useful approach for identifying cognitive biases in nursing students' clinical decision-making. The findings have implications for simulation design, debriefing practice, and nursing education.

Yazarların özeti; kaynağından alınmıştır. Frontiers in Medicine, 2026 · DOI ↗