Evidence map›Paper›PMID 42505163›Full record

ArticleEuropean journal of investigation in health, psychology and education2026

Development and Validation of the ATRAI Questionnaire to Assess Attitudes Toward Large Language Models in Clinical Setting (ATRAI-LLM).

Roman V Reshetnikov, Yuriy A Vasilev, Yuliya F Shumskaya, Dina A Akhmedzyanova, Yulya A Alymova, Anton V Vladzymyrskyy, Ilya A Tyrov, Olga V Omelyanskaya, Ivan A Blokhin

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Article in European journal of investigation in health, psychology and education, 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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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Roman V ReshetnikovResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Yuriy A VasilevResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Yuliya F ShumskayaResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-8521-4045
Dina A AkhmedzyanovaResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0001-7705-9754
Yulya A AlymovaResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.
Anton V VladzymyrskyyResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-2990-7736
Ilya A TyrovMoscow Health Care Department, 127006 Moscow, Russia.
Olga V OmelyanskayaResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-0245-4431
Ivan A BlokhinResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department, 127051 Moscow, Russia.ORCID 0000-0002-2681-9378

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLarge language models (LLMs) are increasingly integrated into real-world medical practice as chatbots for answering clinical queries. However, the perceptions of this technology among its end-users remain understudied. Existing research on physicians' attitudes toward LLMs relies on non-validated questionnaires, raising concerns about the accuracy and reliability of the findings. The aim of this study is to develop and validate a questionnaire to assess physicians' attitudes toward LLM-based chatbots used as a reference tool for answering queries.

methodsThe instrument was based on the previously developed and validated ATRAI-14 questionnaire assessing radiologists' attitudes toward artificial intelligence. Items for the new questionnaire were formulated and refined through focus group testing. Validation involved 562 physicians of various specialties working in medical institutions within the Moscow healthcare system. Some respondents had prior experience working with medical LLMs. We assessed face, content, construct, and criterion validity. Criterion validity was evaluated through correlation between respondents' self-assessed attitudes toward LLMs measured by visual analogue scale (VAS), and construct validity through confirmatory factor analysis.

resultsThe resulting ATRAI-LLM questionnaire comprised 19 items (8 in the background part and 11 in the main part). The questionnaire demonstrated acceptable internal consistency (Cronbach's α = 0.770, McDonald's ω

conclusionsATRAI-LLM is a validated instrument for assessing physicians' attitudes toward LLMs as a knowledge base.

Indexed as

artificial intelligenceattitudelarge language modelssurveys and questionnaires

Identifiers

PMID42505163
PMCPMC13409597

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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.