Exploring the relationship between health professionals’ artificial intelligence literacy and their attitudes toward artificial intelligence

This study aims to determine the relationship between health professionals' artificial intelligence (AI) literacy and their attitudes toward AI. This descriptive and correlational study was conducted between May and July 2024 in an educational research hospital located in eastern Turkey, encompassing 1378 health professionals. The sample size was calculated as 301 participants, with a 95% confidence interval and a 0.05 margin of error, and data collection was completed with 439 participants. 58.8% of the participants were male and 49.0% of them did not have information about the use of artificial intelligence in the field of health. Men, those in the 46-55 age group, postgraduates, those who received artificial intelligence education and those who support artificial intelligence in health showed higher AI literacy and positive attitudes. A strong positive correlation was found between AI literacy and attitudes (<i>r</i> = 0.782**; <i>r</i> = 0.710**), and some sociodemographic variables explained 62.1% and 48.9% of positive and negative attitudes, respectively. Participants exhibited moderate AI literacy, high positive and moderate negative attitudes; attitudes were significantly affected by sociodemographic factors.

Authors

Institutions

Publication Details

Journal
Informatics for Health and Social Care
Published
2026-01-07
DOI
https://doi.org/10.1080/17538157.2025.2602515
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring the relationship between health professionals’ artificial intelligence literacy and their attitudes toward artificial intelligence

Hüseyin Çapuk, Mehmet Uçar, Muhammet Faruk Yiğit
Informatics for Health and Social Care
Artificial Intelligence in Healthcare and Education
article

Exploring the relationship between health professionals’ artificial intelligence literacy and their attitudes toward artificial intelligence

Hüseyin Çapuk, Mehmet Uçar, Muhammet Faruk Yiğit
article en

Abstract

This study aims to determine the relationship between health professionals' artificial intelligence (AI) literacy and their attitudes toward AI. This descriptive and correlational study was conducted between May and July 2024 in an educational research hospital located in eastern Turkey, encompassing 1378 health professionals. The sample size was calculated as 301 participants, with a 95% confidence interval and a 0.05 margin of error, and data collection was completed with 439 participants. 58.8% of the participants were male and 49.0% of them did not have information about the use of artificial intelligence in the field of health. Men, those in the 46-55 age group, postgraduates, those who received artificial intelligence education and those who support artificial intelligence in health showed higher AI literacy and positive attitudes. A strong positive correlation was found between AI literacy and attitudes (<i>r</i> = 0.782**; <i>r</i> = 0.710**), and some sociodemographic variables explained 62.1% and 48.9% of positive and negative attitudes, respectively. Participants exhibited moderate AI literacy, high positive and moderate negative attitudes; attitudes were significantly affected by sociodemographic factors.

Informatics for Health and Social Care
Van Yüzüncü Yıl Üniversitesi (TR), Muş Alparslan University (TR), Şırnak University (TR)
Quality Education
Openalex Percentile: Top 97%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.