Evidence map›Paper›PMID 33442578›Full record

ReviewDigital biomarkers2020

A Roadmap to Inform Development, Validation and Approval of Digital Mobility Outcomes: The Mobilise-D Approach.

Lynn Rochester, Claudia Mazzà, Arne Mueller, Brian Caulfield, Marie McCarthy, Clemens Becker, Ram Miller, Paolo Piraino, Marco Viceconti, Wilhelmus P Dartee and 8 more

Abstract readReview
In one paragraph

Review in Digital biomarkers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

91 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Real-world walking and activity patterns in community-dwelling older adults: a cross-sectional analysis of baseline data from the SMART-AGE trial.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2026
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31 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Lynn RochesterTranslational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.
Claudia MazzàDepartment of Mechanical Engineering, The University of Sheffield, Sheffield, United Kingdom.
Arne MuellerTranslational Medicine, Novartis Institutes for Biomedical Research, Basel, Switzerland.
Brian CaulfieldInsight Centre for Data Analytics, University College Dublin, Dublin, Ireland.
Marie McCarthyICON plc., Dublin, Ireland.
Clemens BeckerRobert Bosch Foundation for Medical Research, Stuttgart, Germany.
Ram MillerTranslational Medicine, Novartis Institutes for Biomedical Research, Basel, Switzerland.
Paolo PirainoResearch and Early Development Statistics, Bayer, Berlin, Germany.
Marco VicecontiUniversity of Bologna, Bologna, Italy.
Wilhelmus P DarteeGDD Regulatory Affairs, Novartis Pharma AG, Basel, Switzerland.
Judith Garcia-AymerichISGlobal, Barcelona, Spain.
Aida A AydemirEMD Serono, Billerica, MA, a Business of Merck KGaA, Darmstadt, Germany.
Beatrix VereijkenDepartment of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway.
Valdo ArneraERT Geneva, Geneva, Switzerland.
Nadir AmmourSanofi R&D, Clinical Sciences and Operations, Chilly-Mazarin, France.
Michael JacksoniXscient Ltd. (IXS), London, United Kingdom.
Tilo HacheTranslational Medicine, Novartis Institutes for Biomedical Research, Basel, Switzerland.
Ronenn RoubenoffTranslational Medicine, Novartis Institutes for Biomedical Research, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care.

Indexed as

Body-worn devicesDigital mobility outcomesRemote Monitoring

Identifiers

PMID33442578
PMCPMC7768123

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.