ArticleDigital health
Allied health professional attitudes toward artificial intelligence in healthcare: A UK cross-sectional survey.
Article in Digital health. 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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Authors and funding
7 authors.
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Abstract
Objectives: Allied Health Professionals (AHPs) represent the second largest healthcare workforce in the United Kingdom, yet their perspectives on artificial intelligence (AI) remain underrepresented in the literature. As national policy commits to making the NHS "the most AI-enabled care system in the world", understanding AHP engagement with AI is essential for effective workforce development and implementation. Methods: An anonymous cross-sectional survey was conducted among AHPs attending a 2025 regional Research and Innovation Conference in the United Kingdom. The survey explored demographics, AI familiarity and use, perceived benefits and concerns, and views on regulation. Data were analysed using descriptive statistics, Kruskal-Wallis and chi-square tests, and exploratory binary logistic regression, following STROBE and CHERRIES guidelines. Results: Among 162 respondents from nine AHP professions, 54.9% reported personal use of large language models, while only 21.7% used AI professionally, mainly for administrative tasks. Healthcare-specific AI familiarity was low (median = 2/5). In exploratory regression analysis familiarity with healthcare AI emerged as the only significant predictor of comfort with AI-supported clinical decision-making ( Conclusions: Workplace integration of AI remains limited despite increasing accessibility of AI technologies. Comfort with clinical AI use was associated with familiarity with healthcare-specific applications and awareness of their potential uses. These findings suggest implementation efforts may benefit from improving foundational understanding of AI and its applications, alongside clear accountability frameworks.
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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 OpenQuestion graph.