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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

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Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.

D M Lydon-Staley¹, I Barnett², T D Satterthwaite³

¹Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia 19104 USA.

Current Opinion in Biomedical Engineering

|October 26, 2019

Summary

Digital phenotyping quantifies device interactions for mental health insights. This review merges digital data with network science to understand psychopathology, aiding diagnosis and treatment.

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Area of Science:

Digital phenotyping and network science in psychiatry.

Background:

Digital phenotyping captures real-time user interactions with digital devices.
This data offers deep insights into behavior and holds potential for psychiatric disorder diagnosis and treatment.

Purpose of the Study:

To review empirical research integrating digital phenotyping data with network theories of psychopathology.
To explore the application of network science methodologies to understand complex interactions in mental health.

Main Methods:

Focus on experience-sampling data collected via smartphones.
Integration of digital phenotyping data with network theories and methodologies.
Utilizing intensive, longitudinal, and multivariate data for analysis.

Main Results:

Digital phenotyping provides a foundation for applying network science to psychopathology.
Enables testing of network theories emphasizing causal interactions among symptoms and phenotypes over time.

Conclusions:

Merging digital phenotyping with network science offers a powerful approach to understanding psychiatric disorders.
This integration can lead to novel diagnostic and prognostic signatures, improving treatment selection.