# Advancing Medical Illustration in Patient Education Materials: from Art to Science

> **NIH NIH R01** · NORTHEASTERN UNIVERSITY · 2024 · $377,535

## Abstract

PROJECT SUMMARY/ABSTRACT
Advancing Medical Illustration in Patient Education Materials: from Art to Science
Despite the enormous effort and expense spent in the creation of medical illustrations, there has
been no systematic empirical evaluation to date of the impact of varying illustration elements and
styles on patient comprehension of the concepts that were intended to be conveyed in the
illustration or patient anxiety induced by the illustration. In this effort we will first develop a domain
ontology that systematically describes the space of medical illustration styles in current use. We
will then use this ontology to guide the creation of a public domain corpus of patient education
documents that exhibit the most important illustration distinctions identified in the ontology, along
with knowledge tests for each. This corpus will be used to conduct an evaluation involving 8,100
individuals to assess the impact of different illustration styles on comprehension and anxiety.
Finally, we will explore the use of Embodied Conversational Agents that simulate face-to-face
conversation with a health provider, to explain patient education documents, both on 2D displays
and in immersive Virtual Reality, evaluated in a randomized study involving 300 participants.

## Key facts

- **NIH application ID:** 10915437
- **Project number:** 5R01LM014084-02
- **Recipient organization:** NORTHEASTERN UNIVERSITY
- **Principal Investigator:** TIMOTHY W. BICKMORE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $377,535
- **Award type:** 5
- **Project period:** 2023-09-01 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10915437

## Citation

> US National Institutes of Health, RePORTER application 10915437, Advancing Medical Illustration in Patient Education Materials: from Art to Science (5R01LM014084-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10915437. Licensed CC0.

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