SynthesisThe Lancet. Digital health2023
Does deidentification of data from wearable devices give us a false sense of security? A systematic review.
Synthesis in The Lancet. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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
29 citing papers in PubMed, 53 citations in OpenAlex.
- From frailty-driven to frailty-informed care in the age of wearable AI.Communications medicine · 2026Review
- Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026Article
- 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
- Sharing digital health data responsibly: Balancing open science with participant privacy.PLOS digital health · 2026Article
- Digital assessment in myasthenia gravis: evidence, validation, and a proposed framework for autoimmune heterogeneity, remote monitoring, and clinical endpoints.Frontiers in immunology · 2026Review
- Application of emerging information technologies in the prevention and control of chronic diseases.Frontiers in public health · 2026Review
- Knowledge and Recommendations of Stakeholders Regarding Ethical Oversight of Data Science Health Research: Protocol for a Qualitative Study.JMIR research protocols · 2025Article
- Protocol for a modified Delphi study of ethical oversight of data science health research (DSHR).BMJ open · 2025Article
- Consensus recommendations for measuring the impact of contraception on the menstrual cycle in contraceptive clinical trials.Contraception · 2025Article
- Neural network-assisted personalized handwriting analysis for Parkinson's disease diagnostics.Nature chemical engineering · 2025Article
- Using dataflow diagrams to support research informed consent data management communications: participant perspectives.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- What Clinicians Should Tell Patients About Wearable Devices and Data Privacy: A Narrative Review.Cureus · 2025Review
- Comparing self reported and physiological sleep quality from consumer devices to depression and neurocognitive performance.NPJ digital medicine · 2025Article
- Advancing rare disease therapeutics through digital twins: Opportunities in drug development and precision dosing.Computational and structural biotechnology journal · 2025Review
- Ethical Dimensions of Clinical Data Sharing by U.S. Health Care Organizations for Purposes beyond Direct Patient Care: Interviews with Health Care Leaders.Applied clinical informatics · 2025Article
- Advancing digital sensing in mental health research.NPJ digital medicine · 2024Review
- Cardiovascular care with digital twin technology in the era of generative artificial intelligence.European heart journal · 2024Review
- Advances in Wearable Biosensors for Healthcare: Current Trends, Applications, and Future Perspectives.Biosensors · 2024Review
- Central Hemodynamic and Thermoregulatory Responses to Food Intake as Potential Biomarkers for Eating Detection: Systematic Review.Interactive journal of medical research · 2024Review
- Concepts and applications of digital twins in healthcare and medicine.Patterns (New York, N.Y.) · 2024Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Wearable devices have made it easier to generate and share data collected on individuals. This systematic review seeks to investigate whether deidentifying data from wearable devices is sufficient to protect the privacy of individuals in datasets. We searched Web of Science, IEEE Xplore Digital Library, PubMed, Scopus, and the ACM Digital Library on Dec 6, 2021 (PROSPERO registration number CRD42022312922). We also performed manual searches in journals of interest until April 12, 2022. Although our search strategy had no language restrictions, all retrieved studies were in English. We included studies showing reidentification, identification, or authentication with data from wearable devices. Our search retrieved 17 625 studies, and 72 studies met our inclusion criteria. We designed a custom assessment tool for study quality and risk of bias assessments. 64 studies were classified as high quality and eight as moderate quality, and we did not detect any bias in any of the included studies. Correct identification rates were typically 86-100%, indicating a high risk of reidentification. Additionally, as little as 1-300 s of recording were required to enable reidentification from sensors that are generally not thought to generate identifiable information, such as electrocardiograms. These findings call for concerted efforts to rethink methods for data sharing to promote advances in research innovation while preventing the loss of individual privacy.
Indexed as
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What Socratic 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 Socratic graph.