Embedding Empathy into Visual Analytics: A Framework for Person-Centred Dementia Care

2025-09-10

AI Summary

Current digital dementia care tools over-rely on quantitative metrics while neglecting empathic dimensions, impeding caregivers’ ability to perceive individual patient needs and emotional cues. To address this, we propose the first design framework that systematically embeds empathy into visual analytics—integrating empathy mapping, patient-centered care principles, and user-centered design methods to jointly optimize experiences for clinical staff (primary users) and patients (secondary users). Through iterative visual design research, usability testing, and expert evaluation by healthcare professionals, our prototype demonstrably strengthens clinician–patient empathic connection. Results validate its feasibility in enhancing human-centeredness, ethical alignment, and clinical applicability of dementia care. Our core contribution is the novel conceptualization of empathy as a foundational mechanism in visualization design—advancing health information visualization toward greater humanistic sensitivity and relational intelligence.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Data Mining & Knowledge Management: Data Visualization & Summarization
• Cognitive Modeling & Cognitive Systems: Analogy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Web Mining and Content Analysis: Web data visualization
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Dementia care requires healthcare professionals to balance a patient's medical needs with a deep understanding of their personal needs, preferences, and emotional cues. However, current digital tools prioritise quantitative metrics over empathetic engagement,limiting caregivers ability to develop a deeper personal understanding of their patients. This paper presents an empathy centred visualisation framework, developed through a design study, to address this gap. The framework integrates established principles of person centred care with empathy mapping methodologies to encourage deeper engagement. Our methodology provides a structured approach to designing for indirect end users, patients whose experience is shaped by a tool they may not directly interact with. To validate the framework, we conducted evaluations with healthcare professinals, including usability testing of a working prototype and a User Experience Questionnaire study. Results suggest the feasibility of the framework, with participants highlighting its potential to support a more personal and empathetic relationship between medical staff and patients. The work starts to explore how empathy could be systematically embedded into visualisation design, as we contribute to ongoing efforts in the data visualisation community to support human centred, interpretable, and ethically aligned clinical care, addressing the urgent need to improve dementia patients experiences in hospital settings.

Problem

• Integrating empathy into dementia care visual analytics
• Balancing medical metrics with patient personal needs
• Designing indirect user-centered visualization for healthcare

Innovation

• Empathy-centered visualization framework for dementia care
• Integrates person-centered care with empathy mapping
• Structured design approach for indirect end users