ArticleSensors (Basel, Switzerland)2022
E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders Analyzing Long-Term Multimodal Data from Wearables and Video Captures.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 58 citations in OpenAlex.
- Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review.BMJ open · 2025Pooled it
- Utility of Consumer-Grade Wearable Devices for Inferring Physical and Mental Health Outcomes in Severe Mental Illness: Systematic Review.JMIR mental health · 2025Pooled it
- Psychotic relapse prediction via biomarker monitoring: a systematic review.Frontiers in psychiatry · 2024Pooled it
- Using Passive Sensing to Predict Psychosis Relapse: An In-Depth Qualitative Study Exploring Perspectives of People With Psychosis.Schizophrenia bulletin · 2026Article
- Using AI to Detect Psychosis Relapse: Scoping Review.JMIR mental health · 2026Article
- Accuracy of Machine Learning Models in Predicting Clinical Outcomes in Bipolar Disorder: A Systematic Review.Brain sciences · 2026Review
- Application of artificial intelligence in schizophrenia rehabilitation management: a systematic scoping review.Translational psychiatry · 2026Article
- Longitudinal measurements of inhibitory cognitive performance in patients with schizophrenia and bipolar disorder.Schizophrenia research. Cognition · 2026Article
- Clinical psychopathology-based early relapse prediction model using speech and language in psychosis.Schizophrenia research. Cognition · 2026Review
- Digital tools for assessing bipolar disorder: A scoping review of the current landscape.Neuroscience applied · 2026Article
- Heart Rate Variability in the Detection of Cognitive Fatigue Through Transfer Learning.Advances in experimental medicine and biology · 2026Article
- The Use of Artificial Intelligence for Personalized Treatment in Psychiatry.Current psychiatry reports · 2025Review
- Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.JMIR mental health · 2025Observational
- Diagnostic digital phenotyping in schizophrenia-spectrum disorders: a systematic review.NPJ digital medicine · 2025Article
- Use of Artificial Intelligence in Mental Healthcare, Health Psychology, and Related Research: A Narrative Review to Address Challenges and Opportunities.Health science reports · 2025Article
- Mapping EEG Metrics to Human Affective and Cognitive Models: An Interdisciplinary Scoping Review from a Cognitive Neuroscience Perspective.Biomimetics (Basel, Switzerland) · 2025Review
- Relapse prediction using wearable data through convolutional autoencoders and clustering for patients with psychotic disorders.Scientific reports · 2025Article
- The comprehensive clinical benefits of digital phenotyping: from broad adoption to full impact.NPJ digital medicine · 2025Review
- A systematic review of passive data for remote monitoring in psychosis and schizophrenia.NPJ digital medicine · 2025Article
- Towards a secure cloud repository architecture for the continuous monitoring of patients with mental disorders.Frontiers in digital health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 5 institutions in 1 country.
Funding
Abstract
Wearable technologies and digital phenotyping foster unique opportunities for designing novel intelligent electronic services that can address various well-being issues in patients with mental disorders (i.e., schizophrenia and bipolar disorder), thus having the potential to revolutionize psychiatry and its clinical practice. In this paper, we present e-Prevention, an innovative integrated system for medical support that facilitates effective monitoring and relapse prevention in patients with mental disorders. The technologies offered through e-Prevention include: (i) long-term continuous recording of biometric and behavioral indices through a smartwatch; (ii) video recordings of patients while being interviewed by a clinician, using a tablet; (iii) automatic and systematic storage of these data in a dedicated Cloud server and; (iv) the ability of relapse detection and prediction. This paper focuses on the description of the e-Prevention system and the methodologies developed for the identification of feature representations that correlate with and can predict psychopathology and relapses in patients with mental disorders. Specifically, we tackle the problem of relapse detection and prediction using Machine and Deep Learning techniques on all collected data. The results are promising, indicating that such predictions could be made and leading eventually to the prediction of psychopathology and the prevention of relapses.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.