ArticleScientific reports2025
Public hesitancy for AI-based detection of neurodegenerative diseases in France.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Harnessing discrete choice experiments to elicit preferred configurations of trustworthy AI augmented decision support systems for certified crop advisors.Frontiers in artificial intelligence · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation for early diagnosis tests for NDDs. We conducted a discrete choice experiment with a representative sample of the French adult population (N = 1017). Participants were asked to choose between early diagnosis tests that differed in terms of: (1) type of test (saliva vs. AI-based tests analysing electronic health records); (2) identity of the person communicating the test results; (3) sensitivity; (4) specificity; and (5) price. We calculated the weights in the decision for each attribute and examined how socio-demographic characteristics influenced them. Respondents revealed a reduced utility value when AI-based testing was involved (valuated at an average of €36.08, CI [€22.13; €50.89]) and when results were communicated by a private company (€95.15, CI [€82.01; €109.82]). We interpret these figures as the shadow price that the public attaches to medical data privacy. Beyond monetization, our representative sample of the French population appears reluctant to adopt AI-powered screening, particularly when performed on large sets of personal data. However, they would be more supportive when medical expertise is associated with the tests.
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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.