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Exploring the effect of explanation content and format on user comprehension and trust in healthcare
File(s)
FAIA-413-FAIA251479.pdf (877.53 KB)
Published version
Author(s)
Rago, Antonio
Palfi, Bence
Sukpanichnant, Purin
Nabli, Hannibal
Vivek, Kavyesh
Type
Conference Paper
Abstract
AI-driven tools for healthcare are widely acknowledged as potentially beneficial to health practitioners and patients, e.g. the QCancer regression tool for cancer risk prediction. However, for these tools to be trusted, they need to be supplemented with explanations. We examine how explanations’ content and format affect user comprehension and trust when explaining QCancer’s predictions. Regarding content, we deploy the SHAP and Occlusion-1 explanation methods. Regarding format, we present SHAP explanations, conventionally, as charts (SC) and Occlusion-1 explanations as charts (OC) as well as text (OT), to which their simpler nature lends itself. We conduct experiments with two sets of stakeholders: the general public (representing patients) and medical students (representing healthcare practitioners). Our experiments showed higher subjective comprehension and trust for Occlusion-1 over SHAP explanations based on content. However, when controlling for format, only OT outperformed SC, suggesting this trend is driven by preferences for text. Other findings corroborated that explanation format, rather than content, is often the critical factor.
Date Issued
2025-10-25
Date Acceptance
2025-07-10
Citation
Frontiers in Artificial Intelligence and Applications, 2025, 413: ECAI 2025, pp.5400-5407
URI
DOI
ISBN
978-1-64368-631-8
ISSN
0922-6389
Publisher
IOS Press
Start Page
5400
End Page
5407
Journal / Book Title
Frontiers in Artificial Intelligence and Applications
Volume
413: ECAI 2025
Copyright Statement
© 2025 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
License URL
Identifier
10.3233/FAIA251479
Source
The 14th Conference on Prestigious Applications of Intelligent Systems (PAIS 2025)
Publication Status
Published
Start Date
2025-10-25
Finish Date
2025-10-30
Coverage Spatial
Bologna, Italy