Evidence map›Paper›PMID 42129868›Full record

ArticleBMC research notes2026

Knowledge, attitudes, and practices toward artificial intelligence in medicine among iranian physicians and medical students: a cross-sectional survey.

Ali Bozorg Savoji, Raha Parnia, Maryam Hajimoradi, Babak Sharif-Kashani, Farah Naghashzadeh, Zahra Hajimoradi, Hanieh Sadeghi Koupaei, Farnaz Ahmadi, Sina Kosari, Rahem Rahmati and 5 more

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Article in BMC research notes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Ali Bozorg SavojiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Raha ParniaSimon Fraser University, Vancouver, BC, Canada.
Maryam HajimoradiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Babak Sharif-KashaniLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farah NaghashzadehLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zahra HajimoradiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Hanieh Sadeghi KoupaeiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farnaz AhmadiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Sina KosariFaculty Member of Internal Medicine and Diabetes Associations of Iran, Tehran University of Medical Sciences, Tehran, Iran.
Rahem RahmatiStudents Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Mahshid HajialiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Hannaneh Yousefi-KomaLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Masoume AvateffazeliLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Elham NazariDepartment of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Elham.Nazari@sbmu.ac.ir.
Shadi ShafaghiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. shafaghishadi@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is rapidly transforming healthcare worldwide, yet the readiness of physicians and medical students to adopt AI-particularly in low- and middle-income settings-remains insufficiently understood. Examining knowledge, attitudes, and practices (KAP) toward AI is essential for informing educational priorities and implementation strategies.

objectivesThis study aimed assessing AI-related knowledge, attitudes, and practices among Iranian physicians and medical students, examine demographic differences, and identify barriers to AI adoption.

methodsA cross-sectional survey was conducted using an online convenience sampling approach across medical universities and clinical settings in Iran between June and August 2024. A validated questionnaire was developed based on a comprehensive literature review of existing KAP surveys related to artificial intelligence and digital health which assessed AI-related knowledge (3 items), attitudes (27 items), and practices (5 items). The reliability of the questionnaire was confirmed using Cronbach's alpha and ICC. Descriptive statistics and multivariable logistic regression were used to examine associations between demographic variables and KAP outcomes. Statistical significance was set at p-value < 0.05.

resultsA total of 238 participants completed the survey, including 165 physicians (69.7%) and 72 medical students (30.3%). Overall, 61.3% demonstrated good knowledge, 83.2% had positive attitudes, and 58.4% showed good AI-related practice. Medical students had higher mean knowledge scores than physicians (0.62 (SD = 0.32) vs. 0.58 (SD = 0.35); p = 0.025). Younger participants (18-25 years) showed higher mean knowledge than those aged > 65 years (0.70 (SD = 0.29) vs. 0.36 (SD = 0.36); p = 0.036). Although attitudes toward AI were uniformly positive (97.4% considered AI essential in medicine), practice levels were lower, particularly among participants aged 50-65 years (Mean practice score (SD) = 0.52 (0.21); p < 0.01). In adjusted analyses, age 50-65 years was independently associated with lower odds of good practice (AOR = 0.12; 95% CI: 0.04-0.41).

conclusionsDespite strong support for AI integration among Iranian physicians and medical students, gaps remain between positive attitudes and real-world AI use, especially among older clinicians. Structured, practice-oriented AI training and improved institutional infrastructure are needed to facilitate effective and equitable adoption of AI in Iran's healthcare system.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelHealth Knowledge, Attitudes, PracticePhysiciansStudents, MedicalAdultCross-Sectional StudiesFemaleHumansIranMaleMiddle AgedSurveys and QuestionnairesYoung AdultAI adoptionArtificial intelligenceHealthcare professionalsIranKnowledge-attitude-practiceMedical education

Identifiers

PMID42129868
PMCPMC13339692

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.