Adopting AI in healthcare: the role of Perceived Usefulness, Ease of Use, and Behavioural Intention among Dutch healthcare professionals
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2025-07-01
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en
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Abstract
As artificial intelligence (AI) continues to transform sectors worldwide, its adoption in healthcare
remains limited despite its potential to reduce administrative burden, improve diagnostics, and enhance
care quality. This study investigates the factors influencing Dutch healthcare professionals’ adoption of
AI tools, applying the Technology Acceptance Model (TAM). The research focuses on how Perceived
Usefulness, Perceived Ease of Use, Perceived Risk, and Facilitating Conditions shape Behavioural
Intention to Use and Actual Use of AI in clinical practice.
A cross-sectional survey was conducted among 112 healthcare professionals working across
various Dutch healthcare settings. Multiple regression, mediation, and moderation analyses were
performed using SPSS. The findings reveal that perceived usefulness and facilitating conditions are
significant positive predictors of behavioural intention to use AI, while perceived risk negatively impacts
this intention. Perceived ease of use did not significantly predict behavioural intention overall, although
it did play a significant role for professionals aged 35 and above. Facilitating conditions were found to
positively affect both perceived usefulness and perceived ease of use. Mediation analysis showed that
the effect of facilitating conditions on behavioural intention was mediated by perceived usefulness, but
not by ease of use. Instead, facilitating conditions did have a direct significant effect on behavioural
intention. Behavioural intention was a strong predictor of actual AI use.
These findings highlight the central role of perceived usefulness and organizational support in
driving AI adoption. They also suggest that training programs and implementation strategies should be
tailored to age-related differences in ease of use concerns. This research extends TAM by integrating
contextual variables and offers practical implications for healthcare organizations aiming to facilitate
effective AI integration. By addressing barriers such as risk perception and lack of support, the adoption
of AI in healthcare can be enhanced to reduce workforce pressure and improve care delivery
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Faculteit der Managementwetenschappen