ReviewDigital biomarkers
Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review.
Review in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 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
50 citing papers in PubMed, 3 syntheses or guidelines pooled it, 82 citations in OpenAlex.
- Recommendations for Defining and Reporting Adherence Measured by Biometric Monitoring Technologies: Systematic Review.Journal of medical Internet research · 2022Pooled it
- Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Use of wearable biometric monitoring devices to measure outcomes in randomized clinical trials: a methodological systematic review.BMC medicine · 2020Pooled it
- Consumer wearable devices for evaluation of heart rate control using digoxin versus beta-blockers: the RATE-AF randomized trial.Nature medicine · 2024Trial
- Trial
- Modernizing the Staging of Parkinson Disease Using Digital Health Technology.Journal of medical Internet research · 2025Article
- Evaluation of a digital reporting and supporting tool in breast cancer prevention trials (KarmApp).BMC health services research · 2025Article
- Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach.Sensors (Basel, Switzerland) · 2025Article
- Article
- Digital Health Technologies for Alzheimer's Disease and Related Dementias: Initial Results from a Landscape Analysis and Community Collaborative Effort.The journal of prevention of Alzheimer's disease · 2024Review
- Methods for the Clinical Validation of Digital Endpoints: Protocol for a Scoping Review Abstract.JMIR research protocols · 2023Article
- Article
- Machine Learning Smart System for Parkinson Disease Classification Using the Voice as a Biomarker.Healthcare informatics research · 2022Article
- Living with heart failure: patient experiences and implications for physical activity and daily living.ESC heart failure · 2022Article
- Cost and Effort Considerations for the Development of Intervention Studies Using Mobile Health Platforms: Pragmatic Case Study.JMIR formative research · 2022Article
- Digital Phenotyping in Clinical Neurology.Seminars in neurology · 2022Article
- Reliability of wearable sensors-based parameters for the assessment of knee stability.PloS one · 2022Article
- A Smartphone Application as an Exploratory Endpoint in a Phase 3 Parkinson's Disease Clinical Trial: A Pilot Study.Digital biomarkers · 2022Article
- Multinational descriptive analysis of the real-world burden of headache using the Migraine Buddy application.European journal of neurology · 2021Article
- A Road Map for Remote Digital Health Technology for Motor Neuron Disease.Journal of medical Internet research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 12 institutions in 2 countries.
Funding
Abstract
backgroundThe use of mobile devices in clinical research has advanced substantially in recent years due to the rapid pace of technology development. With an overall aim of informing the future use of mobile devices in interventional clinical research to measure primary outcomes, we conducted a systematic review of the use of and clinical outcomes measured by mobile devices (mobile outcomes) in observational and interventional clinical research.
methodWe conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles on clinical research published between January 2010 and May 2016 in which mobile devices were used to measure study outcomes. We screened each publication for specific inclusion and exclusion criteria. We then identified and qualitatively summarized the use of mobile outcome assessments in clinical research, including the type and design of the study, therapeutic focus, type of mobile device(s) used, and specific mobile outcomes reported.
resultsThe search retrieved 2,530 potential articles of interest. After screening, 88 publications remained. Twenty-five percent of the publications (
conclusionMobile devices are being widely used in clinical research to assess outcomes, although their use in interventional research to assess therapeutic effectiveness is limited. For mobile devices to be used more frequently in pivotal interventional research - such as trials informing regulatory decision-making - more focus should be placed on: (1) consolidating the evidence supporting the clinical meaningfulness of specific mobile outcomes, and (2) standardizing the use of mobile devices in clinical research to measure specific mobile outcomes (e.g., data capture frequencies, placement of device). To that aim, this manuscript offers a broad overview of the various mobile outcome assessments currently used in observational and interventional research, and categorizes and consolidates this information for researchers interested in using mobile devices to assess outcomes in interventional research.
Indexed as
Identifiers
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.