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TRUVACE RECORD VERSION
record: TRV-2026-1944
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-19T22:03:16.240115Z
status: published
lens: p_space
sector: health
headline: Determinants of Artificial Intelligence Adoption in Aesthetic Practice: A Cross-Sectional Study
dek: Background The integration of artificial intelligence (AI) into plastic and aesthetic surgery is advancing rapidly, with applications in preoperative image analysis, outcome simulation, and complication prediction. However, the adoption of AI-based systems in clinical practice remains limited, and the psychological and structural determinants of adoption among plastic surgery physicians are not fully understood. This study examines the cognitive, emotional, and structural factors influencing AI adoption intentio…
gain_title: (none)
problem_title: Among surveyed plastic and aesthetic surgery physicians, AI anxiety and perceived structural barriers reduce intention to adopt AI tools, which helps explain why clinical use remains limited.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Among surveyed plastic and aesthetic surgery physicians, AI anxiety and perceived structural barriers reduce intention to adopt AI tools, which helps explain why clinical use remains limited.
problem_evidence: the adoption of AI-based systems in clinical practice remains limited | emotional concerns and structural barriers act as significant impediments
quick_read: A cross-sectional survey of 102 physicians, including specialists, senior residents and certified cosmetic medicine practitioners, tested which psychological and structural factors shape their intention to adopt AI. It used an extended UTAUT model that added AI anxiety and perceived barriers to performance and effort expectancy.

The results suggest that adoption depends on more than the technical capability of AI tools. Physician anxiety and organisational obstacles can slow uptake even where applications such as image analysis and outcome simulation exist. The survey measured intentions, not actual use, so the extent to which these attitudes change real practice remains unclear.
limitation: The evidence comes from a cross-sectional survey of only 102 physicians and measures adoption intentions rather than observed AI use, so it cannot establish causation or long-term behaviour.
tag: Evidence-backed problem
key_points: Performance expectancy had a positive association with behavioural intention to adopt AI (β = 0.431). | AI anxiety was negatively associated with adoption intention (β = -0.251). | Perceived clinical utility and ease of use were identified as the primary drivers of adoption. | The authors call for educational programmes, transparent AI systems and ethically grounded regulatory frameworks.
rundown: The study responds to the rapid advance of AI in plastic and aesthetic surgery, including preoperative image analysis, outcome simulation and complication prediction, set against limited clinical adoption.

Data came from a quantitative survey and were analysed with exploratory factor analysis, Pearson's correlation and multiple linear regression. The model treated performance expectancy, effort expectancy, AI anxiety and perceived barriers as determinants of behavioural intention.

The authors conclude that sustainable integration of AI into aesthetic surgical practice will need targeted training, systems whose workings are transparent, and regulatory frameworks grounded in ethics.
sources:
- peer_reviewed | Aesthetic Plastic Surgery | https://doi.org/10.1007/s00266-026-06321-0 | 2026-10-16
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