Evidence map›Paper›PMID 37582816›Full record

ArticleBMC medical education2023

Psychometric properties of the persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS).

AmirAli Moodi Ghalibaf, Maryam Moghadasin, Ali Emadzadeh, Haniye Mastour

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Article in BMC medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
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12citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  12. A systematic review of AI literacy scales.NPJ science of learning · 2024
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

AmirAli Moodi GhalibafStudent Research Committee, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran.ORCID http://orcid.org/0000-0002-3892-5047
Maryam MoghadasinDepartment of Clinical Psychology, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran.ORCID http://orcid.org/0000-0002-0205-1317
Ali EmadzadehDepartment of Medical Education, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID http://orcid.org/0000-0002-4318-8184
Haniye MastourDepartment of Medical Education, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Haniye.Mastour@gmail.com.ORCID http://orcid.org/0000-0003-4893-0998

Funding

Mashhad University of Medical Sciences 992291
6 · The paper itself

Abstract

introductionThere are numerous cases where artificial intelligence (AI) can be applied to improve the outcomes of medical education. The extent to which medical practitioners and students are ready to work and leverage this paradigm is unclear in Iran. This study investigated the psychometric properties of a Persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS) developed by Karaca, et al. in 2021. In future studies, the medical AI readiness for Iranian medical students could be investigated using this scale, and effective interventions might be planned and implemented according to the results.

methodsIn this study, 502 medical students (mean age 22.66(± 2.767); 55% female) responded to the Persian questionnaire in an online survey. The original questionnaire was translated into Persian using a back translation procedure, and all participants completed the demographic component and the entire MAIRS-MS. Internal and external consistencies, factor analysis, construct validity, and confirmatory factor analysis were examined to analyze the collected data. A P ≤ 0.05 was considered as the level of statistical significance.

resultsFour subscales emerged from the exploratory factor analysis (Cognition, Ability, Vision, and Ethics), and confirmatory factor analysis confirmed the four subscales. The Cronbach alpha value for internal consistency was 0.944 for the total scale and 0.886, 0.905, 0.865, and 0.856 for cognition, ability, vision, and ethics, respectively.

conclusionsThe Persian version of MAIRS-MS was fairly equivalent to the original one regarding the conceptual and linguistic aspects. This study also confirmed the validity and reliability of the Persian version of MAIRS-MS. Therefore, the Persian version can be a suitable and brief instrument to assess Iranian Medical Students' readiness for medical artificial intelligence.

Indexed as

Students, MedicalAdultArtificial IntelligenceFemaleHumansIranMalePsychometricsReproducibility of ResultsSurveys and QuestionnairesYoung AdultArtificial intelligenceMedical educationMedical studentsPsychometric propertiesValidity and reliability

Identifiers

PMID37582816
PMCPMC10428571

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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.