ArticleCurrent opinion in biomedical engineering2019
Digital phenotyping for psychiatry: Accommodating data and theory with network science methodologies.
Article in Current opinion in biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis 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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Phenotyping in Bipolar Disorder: Which Integration with Clinical Endophenotypes and Biomarkers?International journal of molecular sciences · 2020Pooled it
- Digital Phenotyping of Anxiety-Depression Comorbidity in Tele-Mental Health: Severity Coupling and Resource-Use Signatures in a Real-World Cohort.Medical sciences (Basel, Switzerland) · 2026Article
- The Effects of a Smartphone App (Feelee) to Enhance Adolescents' Emotion Regulation Skills in a Forensic Outpatient Setting: Protocol for a Multiple Single-Case Experimental Design.JMIR research protocols · 2025Article
- Sample size matters when estimating test-retest reliability of behaviour.Behavior research methods · 2025Article
- Using Active and Passive Smartphone Data to Enhance Adolescents' Emotional Awareness in Forensic Outpatient Setting: A Qualitative Feasibility and Usability Study.JMIR formative research · 2024Article
- Conceptualizing and Examining Change in Communication Research.Communication methods and measures · 2023Article
- The Feasibility and Utility of Harnessing Digital Health to Understand Clinical Trajectories in Medication Treatment for Opioid Use Disorder: D-TECT Study Design and Methodological Considerations.Frontiers in psychiatry · 2022Article
- Evaluating the utility of digital phenotyping to predict health outcomes in schizophrenia: protocol for the HOPE-S observational study.BMJ open · 2021Article
- Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study.JMIR mHealth and uHealth · 2021Article
- A New Characterization of Mental Health Disorders Using Digital Behavioral Data: Evidence from Major Depressive Disorder.Journal of clinical medicine · 2021Article
- Deriving symptom networks from digital phenotyping data in serious mental illness.BJPsych open · 2020Article
- Within-person variability in curiosity during daily life and associations with well-being.Journal of personality · 2020Article
- Digital Health and Addiction.Current opinion in systems biology · 2020Article
- Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper.Journal of medical Internet research · 2020Article
- The Digital Phenotyping Project: A Psychoanalytical and Network Theory Perspective.Frontiers in psychology · 2020Article
- The road ahead in clinical network neuroscience.Network neuroscience (Cambridge, Mass.) · 2019Review
- Cognitive Networks for Knowledge Modeling: A Gentle Introduction for Data- and Cognitive Scientists.Wiley interdisciplinary reviews. Cognitive scienceReview
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
Abstract
Digital phenotyping is the moment-by-moment quantification of our interactions with digital devices. With appropriate tools, digital phenotyping data afford unprecedented insight into our transactions with the world and hold promise for developing novel signatures of psychopathology that will aid in diagnosis, prognosis, and treatment selection of psychiatric disorders. In this review, we highlight empirical work merging digital phenotyping data, and particularly experience-sampling data collected via smartphone, with network theories of psychopathology and network science methodologies. The intensive, longitudinal, and multivariate data collected through digital phenotyping designs provide the necessary foundation for the application of network science methodologies to parsimoniously test network theories of psychopathology emphasizing causal interactions among psychiatric symptoms, as well as other phenotypes, across time.
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.