On the Role of Human-Precision Medicine Interaction in HCI-for-Health

Precision Medicine (PM) is increasingly adopted in clinical and consumer health contexts, with a growing body of HCI research engaging with PM-related technologies and practices. In this paper, we adopt a reflective and critical stance to examine how PM technologies may unsettle interactional assumptions commonly held in HCI-for-health. Building on recent discussions of Human-Precision Medicine Interaction (HPMI), we consider the role such a lens may play when probabilistic, model-derived evidence resists experience-based validation, when personalised prediction carries long-term psychological implications, and when trust and accountability are distributed across stakeholders. We identify five provocations that surface recurring interactional tensions in PM systems, alongside minimal criteria for recognising when HPMI-level attention may be needed. We outline a set of directions for HCI research in PM, and position these contributions as a basis for reconsidering how HCI engages with uncertainty, responsibility, and long-horizon health risks in data-driven medicine.

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Publication Details

Journal
Lancaster EPrints (Lancaster University)
Published
2026-03-31
Primary Topic
Digital Mental Health Interventions
Type
article
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article

On the Role of Human-Precision Medicine Interaction in HCI-for-Health

Albert Tenesa, John Vines, Yuhao Sun
Lancaster EPrints (Lancaster University)
Digital Mental Health Interventions
article

On the Role of Human-Precision Medicine Interaction in HCI-for-Health

Albert Tenesa, John Vines, Yuhao Sun
article en

Abstract

Precision Medicine (PM) is increasingly adopted in clinical and consumer health contexts, with a growing body of HCI research engaging with PM-related technologies and practices. In this paper, we adopt a reflective and critical stance to examine how PM technologies may unsettle interactional assumptions commonly held in HCI-for-health. Building on recent discussions of Human-Precision Medicine Interaction (HPMI), we consider the role such a lens may play when probabilistic, model-derived evidence resists experience-based validation, when personalised prediction carries long-term psychological implications, and when trust and accountability are distributed across stakeholders. We identify five provocations that surface recurring interactional tensions in PM systems, alongside minimal criteria for recognising when HPMI-level attention may be needed. We outline a set of directions for HCI research in PM, and position these contributions as a basis for reconsidering how HCI engages with uncertainty, responsibility, and long-horizon health risks in data-driven medicine.

Lancaster EPrints (Lancaster University)
Openalex Percentile: Top 4%
Digital Mental Health Interventions
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