ReviewBMC medicine2019
Building the case for actionable ethics in digital health research supported by artificial intelligence.
Review in BMC medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 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
78 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Smartphone Apps for Cardiovascular and Mental Health Care: Digital Cross-Sectional Analysis.JMIR mHealth and uHealth · 2025Pooled it
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- Technology-mediated just-in-time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review.Addiction (Abingdon, England) · 2022Pooled it
- The Sustainability Paradox in Digital Behavior Change Interventions: Narrative Ownership as a Design Principle for Lasting Change.Journal of medical Internet research · 2026Article
- Towards Human-Centered Digital Health Interventions.The Psychiatric clinics of North America · 2026Review
- Data Privacy, Ownership, and Secondary Use of Clinical Data Generated by Continuous Glucose Monitors and Mobile Health Applications: A Review.Journal of diabetes science and technology · 2026Review
- Exploring provider attitudes towards digital therapeutics for diabetes and depression.Scientific reports · 2026Article
- "I Don't Trust AI": A Generic Qualitative Analysis of College-Aged Mental Health Clients' Perceptions of Artificial Intelligence Used in Mental Health Counseling.Behavioral sciences (Basel, Switzerland) · 2026Article
- Governance for safe and responsible AI in healthcare organisations: a scoping review of frameworks.NPJ digital medicine · 2026Article
- Thinking Critically About Algorithms for Automated Detection of Behavior: 11 Guidelines for Social and Behavioral Scientists.Developmental science · 2026Article
- Metadata-Based Privacy Assessment for Mobile mHealth.Sensors (Basel, Switzerland) · 2026Article
- Cyberspatial privacy in the digital age: a proxemics-based framework with a healthcare application.BMC medical ethics · 2026Article
- Digital health tools and point solutions-pitfalls in population health program measurement.Frontiers in digital health · 2026Article
- Menopause-related brain fog as a midlife window in women's brain aging: toward ecologically valid measurement and digital phenotyping.Frontiers in human neuroscience · 2026Article
- Positive psychology 4.0: a science of consequence for a world that can no longer wait.Frontiers in psychology · 2026Article
- Immersive Virtual Reality Environments as Psychoanalytic Settings: A Conceptual Framework for Modeling Unconscious Processes Through IoT-Based Bioengineering Interfaces.Bioengineering (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Endurance Sports: Metabolic, Recovery, and Nutritional Perspectives.Nutrients · 2025Review
- Deep Learning for the Early Detection of Invasive Ductal Carcinoma in Histopathological Images: Convolutional Neural Network Approach With Transfer Learning.JMIR formative research · 2025Article
- Advancing youth co-design of ethical guidelines for AI-powered digital mental health tools.Nature. Mental health · 2025Article
- Stanford Screenomics: An Open-source Platform for Unobtrusive Multimodal Digital Trace Data Collection from Android Smartphones.medRxiv : the preprint server for health sciences · 2025Article
18 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
3 authors.
Funding
Abstract
The digital revolution is disrupting the ways in which health research is conducted, and subsequently, changing healthcare. Direct-to-consumer wellness products and mobile apps, pervasive sensor technologies and access to social network data offer exciting opportunities for researchers to passively observe and/or track patients 'in the wild' and 24/7. The volume of granular personal health data gathered using these technologies is unprecedented, and is increasingly leveraged to inform personalized health promotion and disease treatment interventions. The use of artificial intelligence in the health sector is also increasing. Although rich with potential, the digital health ecosystem presents new ethical challenges for those making decisions about the selection, testing, implementation and evaluation of technologies for use in healthcare. As the 'Wild West' of digital health research unfolds, it is important to recognize who is involved, and identify how each party can and should take responsibility to advance the ethical practices of this work. While not a comprehensive review, we describe the landscape, identify gaps to be addressed, and offer recommendations as to how stakeholders can and should take responsibility to advance socially responsible digital health research.
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.