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Journals / ESTÜDAM Halk Sağlığı Dergisi / 2026 / Cilt: 11 Sayı: 2

Assessment of dependence on artificial intelligence and associated factors among medical students

Tıp öğrencilerinde yapay zekaya bağımlılık ve ilişkili faktörlerin değerlendirilmesi

Sevil Akbulut Zencirci(BİLECİK ŞEYH EDEBALİ ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0002-5308-9737
Pages
131–140
Publication Date
2026-05-15
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AI Summary & Key Takeaways

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

In line with these findings, raising awareness, promoting balanced use, and strengthening academic self-efficacy and social support may be beneficial in reducing the risk of AI dependence.

📌 3 Key Takeaways

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Objective & Hypothesis:This study aimed to assess the level of dependence on artificial intelligence (AI) among medical students and to identify its associated factors.
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Key Findings & Data:The study population of this cross-sectional study consisted of 236 medical students in years 1–4 at a university in November 2025.
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Conclusion & Impact:In line with these findings, raising awareness, promoting balanced use, and strengthening academic self-efficacy and social support may be beneficial in reducing the risk of AI dependence.
🔬Design:Survey & Empirical Study
📍Scope:2025 Verileri
⚙️Variables:Yapay zeka · bağımlılık · tıp öğrencileri

Abstract

This study aimed to assess the level of dependence on artificial intelligence (AI) among medical students and to identify its associated factors. The study population of this cross-sectional study consisted of 236 medical students in years 1–4 at a university in November 2025. Data were collected using a questionnaire that included sociodemographic characteristics, AI usage characteristics, the Scale for Dependence on AI (DAI), the Academic Self-Efficacy Scale (ASES), and the Multidimensional Scale of Perceived Social Support (MSPSS). The mean age of the participants was 20.02±1.65 years, and 49.2% were male. DAI scores ranged from 5 to 25, with a mean of 11.04±4.08. Higher mean DAI scores were observed among students who used AI for more than 30 minutes daily, checked AI without intending to use it, and used it for academic and social chatting/emotional sharing purposes (p<0.05). DAI scores showed a weak negative correlation with ASES scores (r=-0.235) and a moderate negative correlation with MSPSS scores (r=-0.376; p<0.001). In hierarchical regression analysis, dependence on AI was associated with daily AI use duration, checking AI without intention, using AI for academic and social chatting/emotional sharing purposes, academic self-efficacy, and perceived social support. In line with these findings, raising awareness, promoting balanced use, and strengthening academic self-efficacy and social support may be beneficial in reducing the risk of AI dependence.

Özet

Çalışmada tıp öğrencilerinin yapay zekaya (YZ) bağımlılık düzeyleri ve ilişkili faktörlerin değerlendirilmesi amaçlandı. Kesitsel tasarımdaki çalışmanın araştırma grubunu, Kasım 2025’te bir üniversitede öğrenim gören 1–4. sınıf tıp öğrencisi 236 kişi oluşturmuştur. Veriler sosyodemografik özellikler, yapay zeka kullanım özellikleri ile Yapay Zekaya Bağımlılık Ölçeği (YZBÖ), Akademik Özyeterlik Ölçeği (AÖÖ) ve Çok Boyutlu Algılanan Sosyal Destek Ölçeği (ÇBASDÖ)’nün yer aldığı anket formu ile toplandı. Katılımcıların yaş ortalaması 20,02±1,65 olup, %49,2’si erkekti. YZBÖ puanları 5–25 arasında değişmekte olup ortalaması 11,04±4,08 idi. Yapay zekayı günlük 30 dakikadan fazla kullananlarda, kullanma niyeti olmadığı halde kontrol edenlerde ve akademik ile sosyal sohbet/duygusal paylaşım amaçlı kullananlarda YZBÖ puan ortalaması daha yüksekti (p<0,05). YZBÖ ile AÖÖ arasında zayıf (r=-0,235), ÇBASDÖ ile orta düzeyde negatif ilişki saptandı (r=-0,376; p<0,001). Hiyerarşik doğrusal regresyon analizinde, yapay zekaya bağımlılığın; günlük yapay zekâ kullanım süresi, kullanma niyeti olmadan yapay zekayı kontrol etme, yapay zekayı akademik ve sosyal sohbet/duygusal paylaşım amacıyla kullanma, akademik öz-yeterlik ve algılanan sosyal destek ile ilişkili olduğu bulundu. Bu bulgular doğrultusunda, farkındalığın artırılması, dengeli kullanımın teşvik edilmesi ve akademik öz-yeterlik ile sosyal desteğin güçlendirilmesi, yapay zekâ bağımlılığı riskini azaltmada yararlı olabilir.

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Cite This Article

Zencirci, S. A. (2026). Assessment of dependence on artificial intelligence and associated factors among medical students. ESTÜDAM Halk Sağlığı Dergisi, Cilt: 11 Sayı: 2, 131–140. https://doi.org/10.35232/estudamhsd.1915530

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