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Setting digital psychiatry in motion: towards dynamic digital markers for digital phenotyping
Axel Constant1, C Emre Koksal2, Lena Palaniyappan3
1School of Engineering and Informatics, The University of Sussex, Brighton, UK. axel.constant.pruvost@gmail.com.
NPP - Digital Psychiatry and Neuroscience
|March 13, 2026
Summary
Digital phenotyping, using smartphone data, can now better track mental health changes over time. A new dynamic approach captures these time-varying patterns, offering deeper insights into psychopathology.
Area of Science:
- Psychiatry
- Digital Health
- Computational Neuroscience
Background:
- Digital phenotyping leverages smartphone and wearable data for in situ assessment of behavioral and biosocial markers.
- Traditional entropy-based measures offer static insights, overlooking crucial temporal dynamics in psychiatric conditions.
Purpose of the Study:
- To introduce a dynamic modeling approach for digital data in mental health research.
- To enhance the capture of time-varying aspects of mental disorders using digital markers.
Main Methods:
- Developing and applying dynamic modeling techniques to digital phenotyping data.
- Analyzing time-varying patterns in behavioral and biosocial markers.
Main Results:
- Dynamic digital markers provide a more accurate representation of psychopathology.
- The proposed approach captures critical temporal dependencies missed by traditional methods.
Conclusions:
- Dynamic modeling of digital data offers superior insights into the fluctuating nature of mental disorders.
- This approach improves the understanding of regulatory mechanisms in psychopathology.
