Evidence map›Paper›PMID 42577941›Full record

ArticleCureus2026

Dependence on Generative Artificial Intelligence Among Medical Students and Its Association With Critical Thinking: A Cross-Sectional Study.

Siva P M, David Sam Selva Jeyam P, Hiranmahi Gandhi K

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In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Siva P MCommunity Medicine, Tirunelveli Medical College, Tirunelveli, IND.
David Sam Selva Jeyam PCommunity Medicine, Tirunelveli Medical College, Tirunelveli, IND.
Hiranmahi Gandhi KCommunity Medicine, Madras Medical College, Chennai, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGenerative artificial intelligence (AI) (e.g., ChatGPT and Google Gemini) is exceptionally useful in the educational field for learning new concepts. However, besides its benefits, it also introduces the risk of pathological dependence on AI. Hence, this study aims to evaluate the prevalence of AI dependency and its association with critical thinking.

methodsA cross-sectional study was conducted at a government medical college in Tamil Nadu. The study population comprised undergraduate medical students. Data were collected using a structured digital questionnaire that consisted of validated Generative AI Dependency and Critical Thinking Disposition Assessment Questionnaire (CTDAQ-20) scales. Statistical analysis included non-parametric group comparisons, Spearman's rank correlation, and multiple linear regression.

resultsAmong the 722 participants, the prevalence of Generative AI usage was 695 (96.3%). Among users (n=695), the median AI dependence score was 2.1 (IQR: 1.6-2.7), with males having higher dependence than females (p=0.019) and final-year students reporting higher dependence than students in other years (p<0.001). The overall median critical thinking score was 71.0 (IQR: 64.0-77.0), with female students scoring higher (72 vs. 69; p<0.001), and first-year students having better critical thinking scores than students in other years (p=0.031). Overall, AI dependence had a significant inverse correlation with overall critical thinking (rho=-0.248, p<0.001), and multiple linear regression confirmed that higher AI dependence (B=-1.487, p<0.001) and increasing age (B=-0.868, p=0.008) were associated with lower critical thinking.

conclusionGenerative AI usage is ubiquitous among medical students. However, greater dependence on AI is independently associated with diminished critical thinking, particularly among final-year and male students. Therefore, it is hypothesized that the medical curriculum should consider incorporating assessment methods that require active learning and clinical reasoning, such as objective structured clinical examinations (OSCEs) and direct observation of procedural skills (DOPS), rather than relying primarily on traditional theory-based examinations, and should promote AI literacy that supports the use of AI as an adjunct rather than a replacement for human cognition.

Indexed as

artificial intelligence (ai)critical thinkinggenerative ai dependencymedical educationmedical students

Identifiers

PMID42577941
PMCPMC13455564

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.