Nurses' opinions and anxiety levels regarding artificial intelligence technologies

Aim: Artificial intelligence (AI) anxiety is a contemporary issue that may hinder the adoption, use, and acceptance of AI technology in nursing care. This study aims to assess nurses’opinions and anxiety levels regarding AI. Materials and Methods: This cross-sectional and descriptive study utilized self-report questionnaires distributed to 263 nurses between January and June 2023. Data were collected using the “nurses information form” and “artificial intelligence anxiety scale (AIAS)”. Results: The findings indicated that while 83.7% of nurses reported being informed about AI, only 4.9% had received formal training, and 9.1% had used AI technology in nursing care. The total mean AIAS score was 61.79±27.70, with sub-dimensions scores of 22.21±11.96 for "learning," 16.12±8.37 for “job replacement,” 13.99±7.05 for “sociotechnical blindness,” and 9.46±5.77 for “AI configuration.” Conclusion: Although nurses exhibited low levels of AI-related anxiety generally held positive views regarding AI, their use of AI in nursing practice remained minimal. Continuous education programs should be implemented to enhance AI utilization in healthcare, facilitate adaptation, improve nurses’ technological skills, and mitigate AI-related anxiety.

Authors

Publication Details

Journal
The Atlantic Journal of Medical Science and Research
Published
2025-01-01
DOI
https://doi.org/10.5455/atjmed.2024.11.019
Citations
1
Primary Topic
Health and Well-being Studies
Type
article
Field-Weighted Citation Impact
2.31
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nurses' opinions and anxiety levels regarding artificial intelligence technologies

Büşra Demir, Nihal TAŞKIRAN
1 citations
The Atlantic Journal of Medical Science and Research
Health and Well-being Studies
2.31
article

Nurses' opinions and anxiety levels regarding artificial intelligence technologies

Büşra Demir, Nihal TAŞKIRAN
article en
1 citations

Abstract

Aim: Artificial intelligence (AI) anxiety is a contemporary issue that may hinder the adoption, use, and acceptance of AI technology in nursing care. This study aims to assess nurses’opinions and anxiety levels regarding AI. Materials and Methods: This cross-sectional and descriptive study utilized self-report questionnaires distributed to 263 nurses between January and June 2023. Data were collected using the “nurses information form” and “artificial intelligence anxiety scale (AIAS)”. Results: The findings indicated that while 83.7% of nurses reported being informed about AI, only 4.9% had received formal training, and 9.1% had used AI technology in nursing care. The total mean AIAS score was 61.79±27.70, with sub-dimensions scores of 22.21±11.96 for "learning," 16.12±8.37 for “job replacement,” 13.99±7.05 for “sociotechnical blindness,” and 9.46±5.77 for “AI configuration.” Conclusion: Although nurses exhibited low levels of AI-related anxiety generally held positive views regarding AI, their use of AI in nursing practice remained minimal. Continuous education programs should be implemented to enhance AI utilization in healthcare, facilitate adaptation, improve nurses’ technological skills, and mitigate AI-related anxiety.

The Atlantic Journal of Medical Science and ResearchVol. 5(1)
Openalex Percentile: Top 16%
Health and Well-being Studies
2.31
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.

Nurses' opinions and anxiety levels regarding artificial intelligence technologies — Büşra Demir, Nihal TAŞKIRAN · The Atlantic Journal of Medical Science and Research (2025) | TGRS Research Map | TGRS