ReviewJMIR mental health2019
Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review.
Review in JMIR mental health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04775160 (Smartphone-based Ecological Momentary Intervention for Secondary Prevention of Suicidal Thoughts and Behavior), which is not on this map. Cited by 60 papers, 5 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.
Smartphone-based Ecological Momentary Intervention for Secondary Prevention of Suicidal Thoughts and Behavior: a Randomised Clinical Trial
Who cites it
60 citing papers in PubMed, 5 syntheses or guidelines pooled it, 157 citations in OpenAlex.
- Understanding Inequalities in Mobile Health Utilization Across Phases: Systematic Review and Meta-Analysis.Journal of medical Internet research · 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
- The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review.Journal of medical Internet research · 2023Pooled it
- Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.Bipolar disorders · 2022Pooled it
- Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study.Journal of medical Internet research · 2021Trial
- Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample.European journal of psychotraumatology · 2025Article
- Article
- Current challenges and opportunities in active and passive data collection for mobile health sensing: a scoping review.JAMIA open · 2025Review
- Mobile Therapeutic Attention for Treatment-Resistant Schizophrenia (m-RESIST) Solution for Improving Clinical and Functional Outcomes in Treatment-Resistant Schizophrenia: Prospective, Multicenter Efficacy Study.JMIR human factors · 2025Article
- Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study.JMIR mHealth and uHealth · 2025Observational
- The Interplay Between Sleep Apnea and Postpartum Depression.Neurology international · 2025Review
- The Effects of Self-Monitoring Using a Smartwatch and Smartphone App on Stress Awareness, Self-Efficacy, and Well-Being-Related Outcomes in Police Officers: Longitudinal Mixed Design Study.JMIR mHealth and uHealth · 2025Article
- Machine learning on a smartphone-based CPT for ADHD prediction.Frontiers in psychiatry · 2025Article
- Predicting Depressive Symptoms Using GPS-Based Regional Data in Germany With the CORONA HEALTH App During the COVID-19 Pandemic: Cross-Sectional Study.Interactive journal of medical research · 2024Article
- A control theoretic approach to evaluate and inform ecological momentary interventions.International journal of methods in psychiatric research · 2024Article
- Ethological computational psychiatry: Challenges and opportunities.Current opinion in neurobiology · 2024Review
- Advancements in Polymer-Assisted Layer-by-Layer Fabrication of Wearable Sensors for Health Monitoring.Sensors (Basel, Switzerland) · 2024Review
- Beyond rating scales: With targeted evaluation, large language models are poised for psychological assessment.Psychiatry research · 2024Review
- A systematic review of reviews on the advantages of mHealth utilization in mental health services: A viable option for large populations in low-resource settings.Global mental health (Cambridge, England) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 7 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile Therapeutic Attention for Patients with Treatment-Resistant Schizophrenia (m-RESIST) is an EU Horizon 2020-funded project aimed at designing and validating an innovative therapeutic program for treatment-resistant schizophrenia. The program exploits information from mobile phones and wearable sensors for behavioral tracking to support intervention administration.
objectiveTo systematically review original studies on sensor-based mHealth apps aimed at uncovering associations between sensor data and symptoms of psychiatric disorders in order to support the m-RESIST approach to assess effectiveness of behavioral monitoring in therapy.
methodsA systematic review of the English-language literature, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was performed through Scopus, PubMed, Web of Science, and the Cochrane Central Register of Controlled Trials databases. Studies published between September 1, 2009, and September 30, 2018, were selected. Boolean search operators with an iterative combination of search terms were applied.
resultsStudies reporting quantitative information on data collected from mobile use and/or wearable sensors, and where that information was associated with clinical outcomes, were included. A total of 35 studies were identified; most of them investigated bipolar disorders, depression, depression symptoms, stress, and symptoms of stress, while only a few studies addressed persons with schizophrenia. The data from sensors were associated with symptoms of schizophrenia, bipolar disorders, and depression.
conclusionsAlthough the data from sensors demonstrated an association with the symptoms of schizophrenia, bipolar disorders, and depression, their usability in clinical settings to support therapeutic intervention is not yet fully assessed and needs to be scrutinized more thoroughly.
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.