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Talking about diseases; developing a model of patient and public-prioritised disease phenotypes

Medicine and Health

Talking about diseases; developing a model of patient and public-prioritised disease phenotypes

K. Slater, P. N. Schofield, et al.

This research develops a novel phenotype model representing the public's perspective on disease using social media data, revealing 24,618 new phenotype associations. Conducted by Karin Slater, Paul N. Schofield, and their team, it highlights the importance of integrating public views to improve clinical awareness and understanding across healthcare stakeholders.

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~3 min • Beginner • English
Abstract
Deep phenotyping uses standardised terminologies to create comprehensive phenotypic descriptions that facilitate secondary analysis, evidence synthesis, and clinical awareness. Most existing disease–phenotype knowledge bases reflect an academic perspective derived from literature and experimental databases, potentially misaligned with patient and public priorities. Using social media data, the authors develop a phenotype model representing a public perspective on disease and compare it to a model constructed from biomedical databases and literature. From social media, 52,108 possible disease–phenotype associations were identified across 311 diseases. A total of 24,618 novel phenotype associations not present in the biomedical/literature model were found across 304 diseases, of which 14,531 were significant. Social media-derived phenotypes over-represented manifestations affecting quality of life and phenotypes related to endocrine, digestive, and reproductive systems. Clinical expert review judged social media-derived associations similarly well-established as literature-derived associations and noted differences in their presence in clinical encounters. The social media phenotype model yields a perspective that differs significantly from existing resources and provides numerous novel associations. Integrating public perspectives into phenotype resources may enhance clinical awareness, support secondary analyses, and bridge understanding across healthcare stakeholders.
Publisher
npj Digital Medicine
Published On
Sep 30, 2024
Authors
Karin Slater, Paul N. Schofield, James Wright, Paul Clifft, Anushka Irani, William Bradlow, Furqan Aziz, Georgios V. Gkoutos
Tags
phenotype model
social media data
disease perspective
novel associations
clinical encounters
public opinion
healthcare integration
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