Evidence map›Paper›PMID 41993039›Full record

ArticleFrontiers in digital health2026

Assessing nurses' attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale.

Shnara Svetlanova, Balnur Iskakova, Dinara Makhanbetkulova, Aurelija Blazeviciene, Laila Nazarova, Nadira Aitambayeva, Nazerke Narymbayeva, Bibinur Sydykova, Tamara Abdirova, Ainur Qumar

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Article in Frontiers in digital health, 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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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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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Shnara SvetlanovaDepartment of Health Policy and Management, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
Balnur IskakovaDepartment of Health Policy and Management, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
Dinara MakhanbetkulovaDepartment of Nursing, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
Aurelija BlazevicieneDepartment of Nursing, Faculty of Nursing, Medical Academy, Lithuanian University of Health Sciences, Kaunas, Lithuania.
Laila NazarovaKazakhstan Medical University "KSPH", Almaty, Kazakhstan.
Nadira AitambayevaKazakhstan Medical University "KSPH", Almaty, Kazakhstan.
Nazerke NarymbayevaKazakhstan Medical University "KSPH", Almaty, Kazakhstan.
Bibinur SydykovaKazakhstan Medical University "KSPH", Almaty, Kazakhstan.
Tamara AbdirovaKazakhstan Medical University "KSPH", Almaty, Kazakhstan.
Ainur QumarDepartment of Health Policy and Management, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Artificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored. This study aimed to evaluate the psychometric properties of a previously validated nine-item scale measuring nurses' knowledge and attitudes toward AI and to describe preliminary findings from primary healthcare centre (PHC) nurses in Almaty, Kazakhstan. Methods: A cross-sectional survey was conducted among 400 nurses from eight randomly selected PHCs in Almaty. The English version of the questionnaire assessing sociodemographic characteristics, knowledge of AI, and attitudes toward AI among nurses was translated and adapted in Kazakh and Russian languages. Exploratory factor analysis (EFA) was performed on 60% of the sample ( Results: Most participants were female (94%, Conclusions: The validated scale demonstrated excellent psychometric properties in Kazakhstani context and has the potential to be used more broadly across the Central Asian region. While nurses exhibited positive perceptions of AI's clinical and operational benefits, gaps in specific knowledge suggest a need for targeted educational interventions.

Indexed as

artificial intelligenceattitudesKazakhstannursespsychometric validation

Identifiers

PMID41993039
PMCPMC13081779

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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 Socratic graph.