ReviewNPJ digital medicine2020
Verification, analytical validation, and clinical validation (V3): the foundation of determining fit-for-purpose for Biometric Monitoring Technologies (BioMeTs).
Review in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 329 papers, 4 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
329 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A patient first perspective of sleep disturbance across therapeutic areas: a systematic literature review of qualitative studies.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Pooled it
- Identifying Concepts of Physical Activity Which Are Clinically Meaningful to Patients and Care Providers: A Systematic Review of Qualitative Research.Clinical and translational science · 2025Pooled it
- Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Remote monitoring technologies for measuring cardiovascular functions in community-dwelling adults: a systematic review.GeroScience · 2023Pooled it
- Operationalizing Precision Medicine in Drug Development: Predictive Biomarkers, Companion Diagnostics, and Regulatory Pathways.Clinical pharmacology and therapeutics · 2026Review
- Wearable bioelectronics enabled by conductive hydrogels: From materials innovation to clinical translation.Materials today. Bio · 2026Review
- Noninvasive Interstitial Glucose Estimation Using Wearables and Machine Learning in Healthy Individuals and Individuals With Obesity: Observational Cohort Study.JMIR mHealth and uHealth · 2026Observational
- It Knows My Emotions Better Than I Do: Digital Phenotyping and the Contest Over Symptom Interpretation.Integrative psychological & behavioral science · 2026Article
- Toward actionable biomarkers in psychiatry: a collaborative roadmap for precision clinical trials. An ACNP position paper.NPP - digital psychiatry and neuroscience · 2026Article
- Multi-Tier Validation of a Single-Lead Wearable ECG Signal-Processing Pipeline: Clinical Comparison and Algorithmic Benchmarking on Public Expert-Annotated Databases.Sensors (Basel, Switzerland) · 2026Article
- Advancing Neurorehabilitation and Recovery Through Human Movement Quantification via Wearable Sensing.Neurorehabilitation and neural repair · 2026Article
- Unaddressed implications of the FDA's 2026 guidance on wellness devices.Nature biomedical engineering · 2026Article
- Operationalizing AI-Enabled Cardiovascular Biomarkers: A Clinician-Centered Framework for Validation, Governance, and Workflow Integration.JMIR cardio · 2026Article
- From Reactive to Proactive Healthcare: Synergizing Wearable Biomarkers and Machine Learning in Digital Therapeutics.Bioengineering (Basel, Switzerland) · 2026Review
- Dynamic Oculomics for Diagnostic Monitoring: Personal Ocular Trends, Risk Stratification and Treatment Response.Diagnostics (Basel, Switzerland) · 2026Review
- AI-Ready Multimodal Wearable Biosensors Beyond Glucose: Biofluid Sampling, Sensor Fusion, and Clinical Translation.Biosensors · 2026Review
- Large Language Models for Mental Health Prediction: Scoping Review of Bias and Clinical Utility Documentation in 2019-2024.JMIR AI · 2026Review
- When Wellness Stress Detection Enters Healthcare Workflows: An Iso-Heart-Rate, Cross-Corpus Evaluation of Wrist Wearables.Healthcare (Basel, Switzerland) · 2026Article
- Women's Health Wearables: From Continuous Signals to Actionable Digital Phenotypes Across the Reproductive Lifespan.Bioengineering (Basel, Switzerland) · 2026Article
- Evaluating digital cognitive tests for clinical use in Alzheimer's disease: A novel framework and scoping review.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
269 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
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital medicine is an interdisciplinary field, drawing together stakeholders with expertize in engineering, manufacturing, clinical science, data science, biostatistics, regulatory science, ethics, patient advocacy, and healthcare policy, to name a few. Although this diversity is undoubtedly valuable, it can lead to confusion regarding terminology and best practices. There are many instances, as we detail in this paper, where a single term is used by different groups to mean different things, as well as cases where multiple terms are used to describe essentially the same concept. Our intent is to clarify core terminology and best practices for the evaluation of Biometric Monitoring Technologies (BioMeTs), without unnecessarily introducing new terms. We focus on the evaluation of BioMeTs as fit-for-purpose for use in clinical trials. However, our intent is for this framework to be instructional to all users of digital measurement tools, regardless of setting or intended use. We propose and describe a three-component framework intended to provide a foundational evaluation framework for BioMeTs. This framework includes (1) verification, (2) analytical validation, and (3) clinical validation. We aim for this common vocabulary to enable more effective communication and collaboration, generate a common and meaningful evidence base for BioMeTs, and improve the accessibility of the digital medicine field.
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.