ArticleJAAD international2026
Development and validation of the Oxford Attitudes to Artificial Intelligence in Medicine Scale.
Article in JAAD international, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Contemporary AI attitude scale research: a systematic mapping review and bibliometric analysis.Frontiers in psychology · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Public willingness to accept medical artificial intelligence (AI) tools affect the potential real-world impact of these evolving technologies. We therefore developed and validated the Oxford Attitudes to Artificial Intelligence in Medicine Scale (OAAIMS), an instrument designed to assess public and patient attitudes towards AI use in healthcare. Methods: Candidate domains and items were generated through literature review, expert panels, and open-ended surveys, then administered to demographically representative samples (the United Kingdom Results: Exploratory factor analysis supported a 20-item, 4-factor structure with domains of Benefit (9 items), Trust (5 items), Task-specific Comfort (3 items), and Concerns (3 items). Confirmatory factor analysis showed good fit (root mean squared error of approximation = 0.055; standardized root mean squared residual = 0.037; comparative fit index = 0.963). Internal consistency was high for the total scale (ω = 0.95 UK, 0.96 US) and subscales (ω = 0.81-0.94). OAAIMS correlated with general AI attitudes (r = 0.70-0.71) and minimally with vaccine hesitancy (|r| ≤ 0.14). Each 1-point increase in OAAIMS score reduced the odds of preferring AI-free care by 8% to 9% (UK odds ratio of association [OR] 0.91, US OR 0.92; both Discussion: The OAAIMS is a brief, psychometrically robust scale capturing 4 distinct domains of public attitudes toward medical AI, developed using demographically representative samples. Conclusion: The OAAIMS can serve as a baseline descriptor, outcome measure, or stratification variable in trials and implementation studies, permitting quantifiable tracking of patient-centered barriers and allowing for de-risking nascent technologies. OAAIMS is an informatics-ready instrument for baselining, stratifying, and longitudinally monitoring public acceptance of medical AI in trials and health-system implementations.
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What OpenQuestion holds
Registered trials
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.