About this Research Topic
Biomarkers are biological indicators of disease that can be objectively measured and monitored. Traditionally psychiatry has suffered from a relative paucity of these, with no lab tests or medical devices available for the definitive diagnosis or monitoring of disease. However, the upward trajectory of digital capabilities over the last decade, combined with the widespread adoption of personal digital devices including smartphones and wearables, has ushered in a new age of digital biomarkers.
Digital biomarkers leverage naturalistic data collection on connected devices to produce a more holistic representation of patient functioning. Indeed, the high frequency with which digital assessments can be delivered offers a convincing trajectory towards effective, precision psychiatry: from recruiting patients who are most likely to benefit from a drug into a clinical trial, to monitoring fluctuations in mental state in real-time. This is particularly relevant as psychiatric disorders are highly heterogeneous in nature, both within and between patients: patients may experience day-to-day changes in symptom manifestation that is unique from their peers with the same diagnosis. Without the near-patient capabilities of digital tools, it would not be possible to capture the subtle fluctuations that make up a patient’s experience and, ultimately, their outcomes.
In this Research Topic, we welcome original and review articles regarding new advances in digital biomarkers to detect, assess and monitor psychiatric disorders. We encourage submissions from researchers using a variety of digital tools and techniques, such as: wearables, mobile applications, voice, biosensors, electronic patient records, social media, virtual reality, and machine learning.
Guest Topic Editor Jenny Barnett is employed by Cambridge Cognition which develops cognitive testing software and other digital markers for use in clinical research. All other Guest Topic Editors declare no competing interests with regards to the Research Topic subject.
Keywords: wearables, sensors, behaviour, health records, biomarker
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