Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.

doi:10.2196/75774

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Community

Back to search

Article

Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.

JMIR mental health - 12 Dec 2025

Garyfalli Vasiliki, Kalisperakis Emmanouil, Smyrnis Alexandros, Lazaridi Marina, Karantinos Thomas, Mantas Asimakis, Filntisis Panagiotis P, Efthymiou Niki, Zlatintsi Athanasia, Maragos Petros, Smyrnis Nikolaos

Abstract excerpt

Background: Digital phenotyping refers to the objective measurement of human behavior via devices such as smartphones or watches and constitutes a promising advancement in personalized medicine. Digital phenotypes derived from heart rate, mobility, or sleep schedule data have been used in psychiatry to either diagnose individuals with psychotic disorders or to predict relapse as a binary outcome. Machine learning...

Read the complete abstract on PubMed

Topics

Humans
Psychotic Disorders
Male
Female
Adult

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Longitudinal Studies

Phenotype

Heart Rate

Middle Aged

Sleep

Accelerometry

Smartphone

Psychiatric Status Rating Scales

Source

Open in PubMed Open full text

Identifiers

PMID: 41385790
DOI: 10.2196/75774
PMCID: PMC12700515

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 23 Oct 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.PMID 41385790Read ↗

Smartwatch digital phenotypes predict positive and negative symptom variation in a longitudinal monitoring study of patients with psychotic disordersSemantic proximity Read ↗

Digital phenotyping for predicting relapse in psychiatric disorders: a systematic review of passive sensing approaches.Semantic proximity Read ↗

Machine Learning Identifies Digital Phenotyping Measures Most Relevant to Negative Symptoms in Psychotic Disorders: Implications for Clinical Trials.Semantic proximity Read ↗

Systematic Review of Digital Phenotyping and Machine Learning in Psychosis Spectrum Illnesses.Semantic proximity Read ↗

Passive Digital Phenotyping for Identifying Dynamic Symptom Patterns: Toward Precision Monitoring in PsychiatrySemantic proximity Read ↗

Advancing psychiatry with transdiagnostic targets for digital phenotypingSemantic proximity Read ↗

Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study.Semantic proximity Read ↗

The analysis of heart rate variability and accelerometer mobility data in the assessment of symptom severity in psychotic disorder patients using a wearable Polar H10 sensorSemantic proximity Read ↗

Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry?Semantic proximity Read ↗

Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.