Routine Clinical Data, Speech, Video, Mobile Data, and Wearables for Precision Psychiatry

Psychiatric care and services worldwide increasingly use electronic health records (EHRs) and other digital systems that capture rich longitudinal information about patients’ diagnoses, treatments, somatic comorbidities, laboratory and imaging findings, and socio-occupational functioning. In parallel, advances in digital phenotyping, speech and video analysis, and medical informatics have created unprecedented opportunities to extract objective correlates and ecologically valid markers of psychopathology from routine clinical interactions between patients and health care professionals.This Research Topic aims to bring these strands together by focusing on the use of electronic health records and other routine clinical data, including speech and video, to advance precision psychiatry across diagnostic spectra and care settings. We welcome contributions that leverage real-world data generated during standard care—such as structured and unstructured EHR data, clinical notes, PACS or other imaging archives, audio and video recordings from clinical interviews, telepsychiatry sessions, and digital traces from clinical platforms—to improve assessment, prognosis, monitoring, and treatment decision-making.We are particularly interested in:- Development, validation, and implementation of machine learning and statistical models using EHR and routine clinical data to predict onset, relapse, treatment response, side effects, or functional outcomes in psychiatric populations.- Methods and applications that integrate speech and language features, vocal or facial markers, and other multimodal digital signals into EHR-based models, including work using routinely recorded clinical interviews or telepsychiatry sessions for digital phenotyping.- Studies quantifying the clinical utility, acceptability, and ethical implications of EHR- and speech/video-based tools, including impact on workflows, patient–clinician relationships, equity and bias, consent and governance, and regulatory considerations.- Methodological and conceptual contributions that address issues of data quality, missingness, sample selection bias, fairness, calibration, external validation, reporting standards, and reproducibility in real-world psychiatric data science.By prioritizing routine clinical data streams, this Research Topic seeks to move beyond highly controlled proof-of-concept studies and toward scalable, ethically grounded tools that can be embedded in mental health services. We encourage submissions that demonstrate cross-disciplinary collaboration between psychiatry, psychology, clinical informatics, computer science, speech and video processing, ethics, law, and health services research. Contributions across the lifespan, diagnostic categories, and global settings are welcome, including work from low- and middle-income countries where real-world data may be especially valuable for resource allocation and service planning.Ultimately, this collection aims to chart the next steps for translating EHR-, speech-, and video-based analytics into robust, patient-centered, and equitable precision psychiatry.In line with Frontiers in Psychiatry article types and to maximize interdisciplinarity, we particularly welcome:- Original Research (including multimodal models, implementation studies, and impact evaluations)- Brief Research Reports and Clinical Trial protocols using routine data- Methods articles presenting new pipelines, toolkits, or infrastructures for integrating EHR, speech, and video data- Systematic Reviews, Scoping Reviews, and Meta-analyses on EHR-based prediction, speech/video biomarkers, and digital phenotyping in psychiatry- Perspectives, Opinion, and Policy and Practice Reviews on ethics, governance, equity, and implementation of routine-data analytics in mental health services Topic editors: Alexandra Korda, Athanasia Zlatintsi, Stefan Borgwardt, Kyriaki Neophytou Source: https://www.frontiersin.org/research-topics/81993/routine-clinical-data-speech-video-mobile-data-and-wearables-for-precision-psychiatry