Bridging Ontologies of Neurological Conditions: Towards Patient-Centered Data Practices in Digital Phenotyping Research and Design

Amidst the increasing datafication of healthcare, deep digital phenotyping is being explored in clinical research to gather comprehensive data that can improve understanding of neurological conditions. However, participants currently do not have access to this data due to researchers' apprehension around whether such data is interpretable or useful. This study focuses on patient perspectives on the potential of deep digital phenotyping data to benefit people with neurodegenerative diseases, such as ataxias, Parkinson's disease, and multiple system atrophy. We present an interview study (n=12) to understand how people with these conditions currently track their symptoms and how they envision interacting with their deep digital phenotyping data. We describe how participants envision the utility of this deep digital phenotyping data in relation to multiple stages of disease and stakeholders, especially its potential to bridge different and sometimes conflicting understandings of their condition. Looking towards a future in which patients have increased agency over their data and can use it to inform their care, we contribute implications for shaping patient-driven clinical research practices and deep digital phenotyping tools that serve a multiplicity of patient needs.

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Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757562
Primary Topic
Mental Health and Patient Involvement
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article
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article

Bridging Ontologies of Neurological Conditions: Towards Patient-Centered Data Practices in Digital Phenotyping Research and Design

Krzysztof Z. Gajos, Naveena Karusala, Faye X. Yang, Anoopum S. Gupta et al.
Proceedings of the ACM on Human-Computer Interaction
Mental Health and Patient Involvement
article

Bridging Ontologies of Neurological Conditions: Towards Patient-Centered Data Practices in Digital Phenotyping Research and Design

Krzysztof Z. Gajos, Naveena Karusala, Faye X. Yang, Anoopum S. Gupta, J. H. So
article en

Abstract

Amidst the increasing datafication of healthcare, deep digital phenotyping is being explored in clinical research to gather comprehensive data that can improve understanding of neurological conditions. However, participants currently do not have access to this data due to researchers' apprehension around whether such data is interpretable or useful. This study focuses on patient perspectives on the potential of deep digital phenotyping data to benefit people with neurodegenerative diseases, such as ataxias, Parkinson's disease, and multiple system atrophy. We present an interview study (n=12) to understand how people with these conditions currently track their symptoms and how they envision interacting with their deep digital phenotyping data. We describe how participants envision the utility of this deep digital phenotyping data in relation to multiple stages of disease and stakeholders, especially its potential to bridge different and sometimes conflicting understandings of their condition. Looking towards a future in which patients have increased agency over their data and can use it to inform their care, we contribute implications for shaping patient-driven clinical research practices and deep digital phenotyping tools that serve a multiplicity of patient needs.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Georgia Institute of Technology (US), Harvard University (US), Harvard University Press (US), Massachusetts General Hospital (US)
Openalex Percentile: Top 54%
Mental Health and Patient Involvement
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Bridging Ontologies of Neurological Conditions: Towards Patient-Centered Data Practices in Digital Phenotyping Research and Design — Krzysztof Z. Gajos, Naveena Karusala, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS