ArticleNPJ digital medicine2025
Accessing AI mammography reports impacts patient follow-up behaviors: the unintended consequences of including AI in patient portals.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Should AI results be disclosed in mammography reports? A randomised survey study of patient responses to concordant and discordant interpretations.European radiology · 2026Trial
- AI in mammography reporting: transparency, trust, and the patient perspective.European radiology · 2026Article
- Letter to the Editor: Radiologist burnout-AI's true black box.European radiology · 2026Article
- Investigating Placebos and Controls Used in Large Language Model-Based Chatbot Intervention Trials: Protocol for a Methodological Review.JMIR research protocols · 2026Article
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Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although artificial intelligence (AI) tools are growing in breast imaging, little research has examined how to communicate AI findings in patient portals. English-speaking US women with ≥1 prior mammogram (n = 1623) were randomized to one of thirteen conditions. All participants viewed a radiologist report negative for breast cancer; twelve conditions included an AI report with one of four AI scores (0, 29 [no suspicion of cancer]; 31, 50 [suspicion of cancer]), presented alone, with an abnormality cutoff threshold, or with both the threshold and the AI's False Discovery Rate (FDR) or False Omission Rate (FOR). Participants reported whether they would consult an attorney for litigation if advanced cancer were detected one year later (primary outcome). Secondary outcomes included follow-up decisions, concern for cancer, and trust. Litigation was higher when AI was included, especially when AI concluded suspicion of cancer. Providing the FDR/FOR reduced litigation; similar effects were observed for follow-up behaviors.
Identifiers
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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.