ArticleJournal of medical Internet research2026
Effects of Type and Timing of Clinician-Facing AI Support on Patient Trust in Medical Consultations: 2 Vignette Experiments.
Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: AI-based clinical decision support systems are increasingly integrated into medical practice, creating hybrid decision-making processes in which physicians and AI systems jointly contribute to clinical judgments. Yet, how different forms of such AI support affect patients' trust in hybrid medical decisions remains poorly understood. Objective: This study aimed to examine how the type and the timing of physician AI support influence potential patients' trust in the medical decisions, perceptions of the hybrid decision-making process, and intentions to follow the medical advice. Methods: In 2 preregistered vignette-based online experiments, 489 (study 1) and 570 (study 2) members of the general public in Germany imagined 4 medical consultations, in which the physician used no AI support, descriptive AI support (informational or visual assistance), or diagnostic AI support (preliminary diagnostic suggestions). Study 2 additionally manipulated the timing of AI support, namely, whether the physician reviewed AI advice after having made an independent own assessment (sequential decision-making) or not (concurrent decision-making). Participants rated their trust in the medical decisions, trustworthiness of the medical provider, uniqueness neglect, and willingness to follow the medical advice on 7-point Likert scales, with greater values representing stronger agreement. Linear mixed-effects models were used for quantitative analyses. Open-ended responses (N=2607) were analyzed qualitatively to identify recurring themes regarding trust in AI-supported decisions. Results: In study 1, the physician's use of diagnostic AI support compared with descriptive AI support produced significantly lower mean ratings of trust in the medical decisions (5.00 vs 5.37; Conclusions: The use of AI to support physicians appears more acceptable when used for analytical rather than decisional support, or when physicians' decisional independence is visibly retained, suggesting that trust in AI-supported medical decisions depends not only on whether physicians use AI support but also on subjective perceptions of how it is used.
Indexed as
Identifiers
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.