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TRV-2026-0906Version 1 · Certified

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TRUVACE RECORD VERSION
record: TRV-2026-0906
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-08-27T06:05:52.267744Z
status: published
lens: trace
sector: health
headline: Attitudes, perceptions, and UTAUT-based factors influencing the acceptance of medical artificial intelligence among Chinese oncology healthcare professionals: a national cross-sectional survey
dek: Objectives To conduct a nationwide survey among professionals working in oncology departments in China to investigate their attitudes, perceptions, and experiences regarding medical artificial intelligence (AI), and to explore and compare the factors influencing AI behavioral intention (BI; willingness to adopt AI) between physicians and nurses using the Unified Theory of Acceptance and Use of Technology (UTAUT). Materials and methods A nationwide cross-sectional survey was conducted among professionals in oncol…
gain_title: Among Chinese oncology professionals, higher trust in system reliability and higher effort expectancy were associated with stronger behavioral intention to adopt medical AI.
problem_title: Despite high awareness, most Chinese oncology professionals have not practically integrated medical AI, with only 17.7% reporting both hearing of and using it and 67.7% hearing but never using it.
trace_subject: adoption and use of medical AI among Chinese oncology healthcare professionals
gain_reading: Among Chinese oncology professionals, higher trust in system reliability and higher effort expectancy were associated with stronger behavioral intention to adopt medical AI.
gain_evidence: TR and EE are associated with the intention to use AI
problem_reading: Despite high awareness, most Chinese oncology professionals have not practically integrated medical AI, with only 17.7% reporting both hearing of and using it and 67.7% hearing but never using it.
problem_evidence: Only 17.7% reported having both heard of and used medical AI | 67.7% had heard of it but never used it | There is a significant "awareness-usage gap" among Chinese oncology professionals
quick_read: A nationwide cross-sectional survey of 610 oncology professionals in China (188 physicians, 422 nurses) examined attitudes toward medical AI using the UTAUT model. Only 17.7% had both heard of and used medical AI while 67.7% had heard but never used it, indicating an awareness-usage gap.

The analysis matters because trust in system reliability and effort expectancy emerged as key correlates of intention to use AI, with different patterns for physicians versus nurses. Uncertainty remains about whether intention translates into sustained clinical integration and how training or validation protocols would change actual use.
limitation: Findings are based on a cross-sectional survey of 610 oncology professionals in China, limiting causal inference and generalizability beyond this population and setting.
tag: Dual reading
key_points: Nationwide survey included 610 valid responses: 188 physicians (30.8%) and 422 nurses (69.2%) from oncology departments across China. | UTAUT framework with structural equation modeling tested 6 constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, and trust. | Subgroup SEM found for physicians both EE (b2 = .257) and TR (b2 = .486) were significant predictors of behavioral intention.
rundown: The survey collected sociodemographic characteristics, awareness, perceptions, and user experiences, then applied UTAUT to evaluate perceptions and model associations between behavioral intention and six latent constructs.

Authors conclude hospital management should implement differentiated training and local validation protocols that address unique technical and ethical concerns of physicians and nurses respectively to bridge the gap.
sources:
- peer_reviewed | JAMIA Open | https://doi.org/10.1093/jamiaopen/ooag154 | 2026-08-25
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