A cross-sectional study on benefits, barriers, and adoption factors of artificial intelligence in the clinical laboratory

Objectives: The objective of this study was to systematically assess laboratory medical professionals’ perceptions of artificial intelligence (AI). Materials and Methods: This exploratory cross-sectional study examines the opportunities, risks, and acceptance factors of AI from the perspective of laboratory medical professionals. The survey was based on standardized Likert scale questionnaires, including analytic hierarchy process (AHP) analyses. Statistical analysis: Likert scales were numerically coded, and dichotomous variables were recorded as binary values. Decisions were weighted using Saaty’s AHP, including consistency checks (consistency ratio <0.1), supplemented by descriptive statistics and non-parametric tests (Wilcoxon signed-rank test, α = 0.05). Results: The quantitative analysis showed a low level of previous experience with AI, but a predominantly positive attitude: AI was perceived significantly more often as an opportunity than as a risk (mean 4.22 vs. mean 2.5) ( p < 0.001). Participants with <20 years of professional experience consistently rated positive aspects (e.g., quality improvement and reduced workload) higher than their more experienced colleagues. An AHP opportunity analysis identified time savings as the most important benefit, followed by improved diagnostic quality and reduced workload. In the AHP risk analysis, professional uncertainty was prioritized ahead of liability issues and technological dependence. Conclusion: Laboratory medical professionals see AI primarily as an opportunity. In addition to technological requirements and foreseeable clinical benefits, legal and ethical framework conditions and employee acceptance must also be taken into account as a further dimension to drive forward AI implementations.

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Publication Details

Journal
Journal of Laboratory Physicians
Published
2026-11-07
DOI
https://doi.org/10.25259/jlp_358_2025
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

A cross-sectional study on benefits, barriers, and adoption factors of artificial intelligence in the clinical laboratory

Bernhard Strasser, Sebastian Georg Mustafa
2 links
Journal of Laboratory Physicians
Artificial Intelligence in Healthcare and Education
article

A cross-sectional study on benefits, barriers, and adoption factors of artificial intelligence in the clinical laboratory

Bernhard Strasser, Sebastian Georg Mustafa
article en

Abstract

Objectives: The objective of this study was to systematically assess laboratory medical professionals’ perceptions of artificial intelligence (AI). Materials and Methods: This exploratory cross-sectional study examines the opportunities, risks, and acceptance factors of AI from the perspective of laboratory medical professionals. The survey was based on standardized Likert scale questionnaires, including analytic hierarchy process (AHP) analyses. Statistical analysis: Likert scales were numerically coded, and dichotomous variables were recorded as binary values. Decisions were weighted using Saaty’s AHP, including consistency checks (consistency ratio <0.1), supplemented by descriptive statistics and non-parametric tests (Wilcoxon signed-rank test, α = 0.05). Results: The quantitative analysis showed a low level of previous experience with AI, but a predominantly positive attitude: AI was perceived significantly more often as an opportunity than as a risk (mean 4.22 vs. mean 2.5) ( p < 0.001). Participants with <20 years of professional experience consistently rated positive aspects (e.g., quality improvement and reduced workload) higher than their more experienced colleagues. An AHP opportunity analysis identified time savings as the most important benefit, followed by improved diagnostic quality and reduced workload. In the AHP risk analysis, professional uncertainty was prioritized ahead of liability issues and technological dependence. Conclusion: Laboratory medical professionals see AI primarily as an opportunity. In addition to technological requirements and foreseeable clinical benefits, legal and ethical framework conditions and employee acceptance must also be taken into account as a further dimension to drive forward AI implementations.

Journal of Laboratory PhysiciansVol. 18
Klinikum Wels-Grieskirchen (AT)
Good health and well-being
Openalex Percentile: Top 23%
Artificial Intelligence in Healthcare and Education
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