ArticleNPJ digital medicine2018
Data mining for health: staking out the ethical territory of digital phenotyping.
Article in NPJ digital medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 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
81 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Digital Markers for Passive Remote Monitoring of Bipolar Disorder: Systematic Review.JMIR mental health · 2026Pooled it
- Toward Participatory Precision Health With Co-Designed Recommendations: Systematic Review of Just-in-Time Adaptive Interventions in Adolescents and Young Adults.Journal of medical Internet research · 2026Pooled it
- Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial.Journal of medical Internet research · 2021Trial
- Digital doppelgangers in psychiatry.Discover mental health · 2026Review
- Beyond RCTs-Better Research Designs and Methods for Psychosocial Efficacy Studies in Mental Health.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2026Review
- Rethinking Ethics for an Era of Trusted Computational Tools.The Psychiatric clinics of North America · 2026Review
- Mental Health Professionals' Perspectives on Digital Remote Monitoring in Services for People with Psychosis.Schizophrenia bulletin · 2026Article
- Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Health Care: Qualitative Study.JMIR mental health · 2026Article
- Are artificial intelligence chatbots safe for suicide risk assessment? A narratively synthesized review of current evidence.Global mental health (Cambridge, England) · 2026Review
- AI-enabled passive digital phenotyping of experiential negative symptoms in schizophrenia-spectrum disorders: a narrative review on the path from sensing to clinical endpoints.Frontiers in psychiatry · 2026Review
- Reimagining paediatric care: technology, trust, and the global movement for child-centred innovation.Frontiers in medicine · 2026Review
- Power without limits: exploring emotional regulation, moral authority, and psychiatric overreach through theFrontiers in psychiatry · 2026Review
- Adaptive emotion-aware chatbot for mental health diagnosis using recurrent reinforcement learning and transformer models.Frontiers in artificial intelligence · 2026Article
- Stakeholder Criteria for Trust in Artificial Intelligence-Based Computer Perception Tools in Health Care: Qualitative Interview Study.Journal of medical Internet research · 2025Article
- Objective risk and protective factors for momentary and daily loneliness:using digital phenotyping and temporal analysis.Npj mental health research · 2025Article
- Harnessing Digital Phenotyping for Early Self-Detection of Psychological Distress.Healthcare (Basel, Switzerland) · 2025Article
- The ethics of data mining in healthcare: challenges, frameworks, and future directions.BioData mining · 2025Review
- Digital speech biomarkers can measure acute effects of levodopa in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Investigating Awareness and Acceptance of Digital Phenotyping in Dhaka's Korail Slum: Qualitative Study.JMIR formative research · 2025Article
21 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Digital phenotyping uses smartphone and wearable signals to measure cognition, mood, and behavior. This promising new approach has been developed as an objective, passive assessment tool for the diagnosis and treatment of mental illness. Digital phenotyping is currently used with informed consent in research studies but is expected to expand to broader uses in healthcare and direct-to-consumer applications. Digital phenotyping could involve the collection of massive amounts of individual data and potential creation of new categories of health and risk assessment data. Because existing ethical and regulatory frameworks for the provision of mental healthcare do not clearly apply to digital phenotyping, it is critical to consider its possible ethical, legal, and social implications. This paper addresses four major areas where guidelines and best practices will be helpful: transparency, informed consent, privacy, and accountability. It will be important to consider these issues early in the development of this new approach so that its promise is not limited by harmful effects or unintended consequences.
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.