Nursing Open· 2026Q1
Toplum Hemşireleri Arasında Klinik Karar Verme: Karşılaştırmalı İnsan ve Üretken Yapay Zeka Destekli Nitel Analiz
Clinical Decision‐Making Among Community Nurses: A Comparative Human and Generative AI ‐Assisted Qualitative Analysis
- 0atıf
- Q1SCImago
- 2026yıl
Kısa özet
Üretken yapay zeka (Claude 3.5 Sonnet), simüle edilmiş vakalardan toplum hemşirelerinin klinik karar verme süreçlerini analiz ederken insan araştırmacılara benzer temalar ve alıntılar belirledi, ancak insan yorumunun yerini tutamaz.
Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.
Ana noktalar
- Toplum hemşirelerinin klinik karar verme süreci, deneyim, kontrol algısı, danışma, protokoller ve bütünsel sağlık geliştirme yönelimi ile şekillenen bağlama duyarlı bir süreçtir.
- Altı ana tema ortaya çıktı: algılanan kontrol, zorluklar, danışma, insan dışı kaynakların kullanımı, eğitim/deneyim ve hasta refahı.
- Üretken yapay zeka (Claude 3.5 Sonnet), nitel görüşme transkriptlerinin insan analiziyle karşılaştırılabilir temalar ve alıntılar belirledi.
- Yapay zeka destekli nitel analiz, şeffaf prosedürler ve insan doğrulaması gerektirir; yapay zeka profesyonel yargının altında kalmalıdır.
Yapay zekâ ile başlık ve abstract'tan üretildi; tam metin okunmaz.
Özet (abstract)
ABSTRACT Aim To explore how community nurses describe clinical decision‐making across simulated cases and to examine how themes and quotations from human thematic analysis compare with those from generative artificial intelligence‐assisted analysis. Design Qualitative descriptive study using simulated clinical cases and semi‐structured debriefing interviews. Methods Between May and July 2024, 68 academic nurses with at least 1 year of community nursing experience were recruited in Israel. Each nurse responded to four simulated cases and a debriefing interview. Three researchers analysed transcripts thematically. Separately, Claude Projects (Claude 3.5 Sonnet) analysed the same de‐identified Hebrew corpus without access to the human themes. The researchers then compared corresponding themes and illustrative quotations. Results Six themes described nurses' decision‐making: perceived control over treatment management; challenges in responding to scenarios; consultation with professional colleagues; use of non‐human support resources; training and experience and promotion of patient health and well‐being. Both analyses identified corresponding themes and sometimes selected identical or related quotations. The comparison was not a test of agreement, reliability or validity. Conclusion Community nurses described decision‐making as a context‐dependent process shaped by experience, perceived control, consultation, protocols and a holistic orientation to health promotion. Generative artificial intelligence may assist in organizing qualitative material but requires transparent procedures and human oversight. The study does not establish that AI can reproduce or substitute for human qualitative interpretation. Implications for the Profession and/or Patient Care Generative AI tools must remain subordinate to professional nursing judgement in community practice; AI‐assisted qualitative analysis requires transparent, human‐verified procedures. Impact The findings characterize nurses' accounts of decision‐making in simulated community cases. The study did not evaluate clinical effectiveness, implementation or outcomes. Reporting Method The study is reported in accordance with the Consolidated Criteria for Reporting Qualitative Research. Patient or Public Contribution No patient or public contribution. Community nurses participated as research participants.
Yazarların özeti; kaynağından alınmıştır. Nursing Open, 2026 · DOI ↗
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