SynthesisJournal of medical Internet research2022
Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review.
Synthesis in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 3 of them syntheses that pooled it.
What it found
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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.
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Who cites it
41 citing papers in PubMed, 3 syntheses or guidelines pooled it, 70 citations in OpenAlex.
- Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review.Frontiers in digital health · 2025Pooled it
- Depressive symptom screening in elderly by passive sensing data of smartphones or smartwatches: A systematic review.PloS one · 2024Pooled it
- The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review.Journal of medical Internet research · 2023Pooled it
- Digital Phenotyping in Health Research: Scoping Review of Methods, Gaps, and Opportunities.Journal of medical Internet research · 2026Article
- Modeling Short-Term Symptom Changes and Behavioral Subtypes of Depression and Anxiety in the General Population: Observational Study Using Smartphone Data.JMIR formative research · 2026Observational
- Building the foundations for global data banking in digital phenotyping for mental health.NPP - digital psychiatry and neuroscience · 2026Review
- Clinical efficacy and safety of icodextrin dialysate for overnight dwell in continuous ambulatory peritoneal dialysis: A prospective self-controlled study.The Journal of international medical research · 2026Observational
- Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings.Internet interventions · 2026Article
- Personality Constructs Predictions Beyond FFM/Big5: A Digital Phenotyping-Based Exploration.Journal of personality · 2026Article
- A multilevel meta-analysis of passive smartphone sensing of adolescent mental health.NPJ digital medicine · 2026Article
- Predicting daily cognition and lifestyle behaviors for older adults using smart home data and ecological momentary assessment.The Clinical neuropsychologist · 2026Article
- Smartphone-Based Digital Phenotyping Across Health Conditions: Scoping Review.Journal of medical Internet research · 2026Article
- A cautionary tale for AI and machine learning in psychiatry.Translational psychiatry · 2026Review
- Sleep and Activity Patterns as Transdiagnostic Behavioral Biomarkers in Psychiatry: Longitudinal Observational Study From the DeeP-DD Study.JMIR formative research · 2025Observational
- Towards clinical subtypes in schizophrenia: integrating cognitive, functional, and digital phenotyping assessments.Molecular psychiatry · 2025Article
- Harnessing Digital Phenotyping for Early Self-Detection of Psychological Distress.Healthcare (Basel, Switzerland) · 2025Article
- A Co-Segmentation Algorithm to Predict Emotional Stress From Passively Sensed mHealth Data.Statistics in medicine · 2025Article
- The comprehensive clinical benefits of digital phenotyping: from broad adoption to full impact.NPJ digital medicine · 2025Review
- Generative multimodal large language models in mental health care: Applications, opportunities, and challenges.PLOS mental health · 2025Review
- Regulatory challenges of digital health: the case of mental health applications and personal data in South Africa.Frontiers in pharmacology · 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
9 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMental disorders are normally diagnosed exclusively on the basis of symptoms, which are identified from patients' interviews and self-reported experiences. To make mental health diagnoses and monitoring more objective, different solutions have been proposed such as digital phenotyping of mental health (DPMH), which can expand the ability to identify and monitor health conditions based on the interactions of people with digital technologies.
objectiveThis article aims to identify and characterize the sensing applications and public data sets for DPMH from a technical perspective.
methodsWe performed a systematic review of scientific literature and data sets. We searched 8 digital libraries and 20 data set repositories to find results that met the selection criteria. We conducted a data extraction process from the selected articles and data sets. For this purpose, a form was designed to extract relevant information, thus enabling us to answer the research questions and identify open issues and research trends.
resultsA total of 31 sensing apps and 8 data sets were identified and reviewed. Sensing apps explore different context data sources (eg, positioning, inertial, ambient) to support DPMH studies. These apps are designed to analyze and process collected data to classify (n=11) and predict (n=6) mental states/disorders, and also to investigate existing correlations between context data and mental states/disorders (n=6). Moreover, general-purpose sensing apps are developed to focus only on contextual data collection (n=9). The reviewed data sets contain context data that model different aspects of human behavior, such as sociability, mood, physical activity, sleep, with some also being multimodal.
conclusionsThis systematic review provides in-depth analysis regarding solutions for DPMH. Results show growth in proposals for DPMH sensing apps in recent years, as opposed to a scarcity of public data sets. The review shows that there are features that can be measured on smart devices that can act as proxies for mental status and well-being; however, it should be noted that the combined evidence for high-quality features for mental states remains limited. DPMH presents a great perspective for future research, mainly to reach the needed maturity for applications in clinical settings.
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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.