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Journals / Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi / 2026 / Cilt: 34 Sayı: Uygarlığın Dönüşümü: Yapay Zekâ Özel Sayı

ARTIFICIAL INTELLIGENCE ANXIETY, JOB STRESS, AND TURNOVER INTENTION: AN ANALYSIS ON HEALTHCARE WORKERS

YAPAY ZEKÂ KAYGISI, İŞ STRESİ VE İŞTEN AYRILMA NİYETİ: SAĞLIK ÇALIŞANLARI ÜZERİNDE BİR ANALİZ

İsmail Biçer(PAMUKKALE ÜNİVERSİTESİ)0000-0003-1878-0546
Pages
109–124
Publication Date
2025-07-20
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The analysis results indicate that AI anxiety has a statistically significant and positive effect on both job stress and turnover intention.

📌 3 Key Takeaways

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Objective & Hypothesis:Artificial intelligence (AI) anxiety refers to the discomfort or fear individuals may experience due to the expected negative outcomes and risks associated with the deployment of artificial intelligence in various social fields.
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Key Findings & Data:The sample of the research consists of 275 healthcare workers employed in a private hospital.
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Conclusion & Impact:The analysis results indicate that AI anxiety has a statistically significant and positive effect on both job stress and turnover intention.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay zekâ kaygısı · İş stresi · İşten ayrılma niyeti

Abstract

Artificial intelligence (AI) anxiety refers to the discomfort or fear individuals may experience due to the expected negative outcomes and risks associated with the deployment of artificial intelligence in various social fields. In this context, the aim of the study is to analyze the impact of healthcare workers' AI anxiety perceptions on their job stress and turnover intentions. The sample of the research consists of 275 healthcare workers employed in a private hospital. The impact of AI anxiety on job stress and turnover intention was assessed using structural equation modeling. According to the findings, healthcare workers report very high levels of job stress, high levels of turnover intention, and above-average levels of AI anxiety. The analysis results indicate that AI anxiety has a statistically significant and positive effect on both job stress and turnover intention. In this context, health institutions and administrators have important duties to eliminate anxiety caused by artificial intelligence. In conclusion, in this era of digital and intelligent transformation, researching how healthcare workers perceive AI and how they respond to it is of vital importance.

Özet

Yapay zekâ kaygısı, bireylerin çeşitli toplumsal alanlarda yapay zekânın konuşlandırılmasıyla ilişkili beklenen olumsuz sonuçlar ve riskler nedeniyle yaşayabilecekleri huzursuzluk veya korkuyu ifade etmektedir. Bu kapsamda çalışmanın amacı sağlık çalışanlarının yapay zekâ kaygısı algılarının, iş stresi algıları ve işten ayrılma niyetleri üzerindeki etkisini analiz etmektedir. Araştırmanın örneklemini bir özel hastanede görev yapan 275 sağlık çalışanı oluşturmaktadır. Yapay zekâ kaygısının iş stresi ve işten ayrılma niyeti üzerindeki etkisi yapısal eşitlik modellemesi kullanılarak değerlendirilmiştir. Araştırmadan elde edilen bulgulara göre sağlık çalışanlarının iş stresi seviyelerinin çok yüksek olduğu, işten ayrılma niyetlerinin yüksek olduğu ve yapay zekâ kaygı seviyelerinin ortalamanın üzerinde olduğu tespit edilmiştir. Yapılan analiz sonuçlarına göre yapay zekâ kaygısının iş stresi ve işten ayrılma niyeti üzerinde istatistiksel olarak anlamlı ve pozitif bir etkisi bulunmuştur. Bu kapsamda yapay zekâ kaynaklı kaygının ortadan kaldırılması için sağlık kurumları ve yöneticilere önemli görevler düşmektedir. Sonuç olarak dijital ve akıllı dönüşümün bu çağında, sağlık çalışanlarının yapay zekayı nasıl algıladıklarını ve buna nasıl tepki verdiklerini araştırmak hayati önem taşımaktadır.

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Cite This Article

Biçer, İ. (2025). ARTIFICIAL INTELLIGENCE ANXIETY, JOB STRESS, AND TURNOVER INTENTION: AN ANALYSIS ON HEALTHCARE WORKERS. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, Cilt: 34 Sayı: Uygarlığın Dönüşümü: Yapay Zekâ Özel Sayı, 109–124. https://doi.org/10.35379/cusosbil.1667342

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