ReviewCurrent psychiatry reports2020
Digital Health Around Clinical High Risk and First-Episode Psychosis.
Review in Current psychiatry reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- "It's like having a friend in your pocket." the service user experience of the Actissist digital health intervention for early psychosis: a qualitative study.BMC psychiatry · 2025Trial
- Early Intervention in Psychosis: Perceptions, Strengths, Criticalities, and Improvement Proposals from the Perspective of Italian Mental Healthcare Professionals.Community mental health journal · 2026Article
- Using AI to Detect Psychosis Relapse: Scoping Review.JMIR mental health · 2026Article
- Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program.Schizophrenia (Heidelberg, Germany) · 2025Article
- The Goldberg-Huxley model of the pathway to psychiatric care: 21st-century systematic review.BJPsych open · 2023Review
- Relapse prediction in schizophrenia with smartphone digital phenotyping during COVID-19: a prospective, three-site, two-country, longitudinal study.Schizophrenia (Heidelberg, Germany) · 2023Article
- Digital Mental Health Challenges and the Horizon Ahead for Solutions.JMIR mental health · 2021Article
- Anomaly detection to predict relapse risk in schizophrenia.Translational psychiatry · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThis review aims to examine relapse definitions and risk factors in psychosis as well as the role of technology in relapse predictions and risk modeling. RECENT
findingsThere is currently no standard definition for relapse. Therefore, there is a need for data models that can account for the variety of factors involved in defining relapse. Smartphones have the ability to capture real-time, moment-to-moment assessment symptomology and behaviors via their variety of sensors and have high potential to be used to create prediction and risk modeling. While there is still a need for further research on how technology can predict and model relapse, there are simple ways to begin incorporating technology for relapse prediction in clinical care.
Indexed as
Identifiers
32880764What 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.