Evidence map›Paper›PMID 41563342›Full record

ArticleAge and ageing2026

Establishing global standards on wearable technology for measuring mobility in ageing populations: an international consensus exercise.

Marla K Beauchamp, Cassandra D'Amore, Parminder Raina, William McIlroy, Nurudeen Adesina, Matthew Ahmadi, Lisa Alcock, Clemens Becker, Aiden Doherty, Alan Donnelly and 17 more

Abstract readConsensus Statement
In one paragraph

Article in Age and ageing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Review
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

27 authors.

Marla K BeauchampFaculty of Health Sciences, School of Rehabilitation Sciences, McMaster University, Hamilton, Ontario, Canada.ORCID 0000-0003-2843-388X
Cassandra D'AmoreDepartment of Physical Therapy, The University of British Columbia, Vancouver, British Columbia, Canada.ORCID 0000-0001-5374-444X
Parminder RainaMcMaster Institute for Research on Aging, McMaster University, Hamilton, Ontario, Canada.
William McIlroyDepartment of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Nurudeen AdesinaHealth and Care Research Centre, Anglia Ruskin University, Cambridge, UK.
Matthew AhmadiSchool of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0002-3115-338X
Lisa AlcockFaculty of Medical Sciences, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, Tyne and Wear, UK.
Clemens BeckerUnit Digitale Geriatrie, UniversitätsKlinikum Heidelberg, Heidelberg, BW, Germany.
Aiden DohertyNuffield Department of Population Health, University of Oxford, Oxford, UK.
Alan DonnellyHealth Research Institute, University of Limerick, Limerick, County Limerick, Ireland.
Dale W EsligerSchool of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK.
Sally A M FentonSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK.ORCID 0000-0002-3732-1348
Daniel FullerDepartment of Community Health and Epidemiology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.ORCID 0000-0002-2015-2955
Judith Garcia-AymerichNCDs and Environment, ISGlobal, Barcelona, Catalonia, Spain.ORCID 0000-0002-7097-4586
Jeffery M HausdorffCenter for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
Katie HeskethSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK.ORCID 0000-0003-3409-3906
Melvyn HillsdonDepartment of Public Health & Sports Sciences, University of Exeter, Exeter, UK.
Stephanie A PrinceCentre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, Ontario, Canada.
Julie RichardsonFaculty of Health Sciences, School of Rehabilitation Sciences, McMaster University, Hamilton, Ontario, Canada.
Jennifer A SchrackDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-9244-9267
Emmanuel StamatakisSchool of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.ORCID 0000-0001-7323-3225
Karen Van OoteghemDepartment of Kinesiology and Health Sciences, University of Waterloo, Waterloo, Ontario, Canada.
Thomas W WainwrightOrthopaedic Research Institute, Bournemouth University, Poole, UK.ORCID 0000-0001-7860-2990
Amal A WanigatungaDepartment of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-5763-5184
Max James WesternCentre for Motivation and Behaviour Change, Department for Health, University of Bath, Bath, UK.ORCID 0000-0003-1107-8498
Afroditi StathiSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, UK.
Consensus Facilitator Group collaborative author group

Funding

Labarge Centre for Mobility in AgingMcMaster Institute for Research on Aging (MIRA)UK Research and Innovation Ageing Networks
6 · The paper itself

Abstract

backgroundMobility, defined as movement in all its forms, is a hallmark of healthy ageing. As wearable technologies become increasingly integrated into population health surveillance and ageing research, the absence of standardised terminology, measurement protocols and reporting practices presents a major barrier to progress. This consensus exercise aimed to establish minimum standards for measuring mobility with wearable technology in ageing populations and set priorities for future research in the field.

methodsA two-day, in-person consensus meeting was convened with 24 international experts in ageing, mobility and digital health. Using a modified nominal group technique facilitated by a trained moderator, participants engaged in structured small-group brainstorming, followed by iterative large-group discussions. Consensus was achieved through anonymised digital voting on proposed measures, principles and priorities.

findingsConsensus (≥80% agreement) was reached on 20 core device-derived mobility measures and 30 guiding principles for the optimal use of wearable technology in older populations. Experts also identified and ranked 16 priority areas for future research, with the top five including: (i) longitudinal studies and data collection, (ii) digital biomarkers and health outcomes, (iii) contextual data capture, (iv) algorithm development and validation and (v) integration with healthcare systems. INTERPRETATIONS: These consensus-based standards provide a foundational framework for the consistent and transparent use of wearable devices in ageing research and practice. They can inform the development of regulations and guidelines, support harmonisation across studies and chart a path for future research to enhance the utility and impact of wearable technologies in ageing populations.

Indexed as

AgingHealthy AgingMobility LimitationWearable Electronic DevicesAgedAge FactorsHumansPredictive Value of Testsaccelerometersdigital biomarkergaitolder peoplephysical activitystep count

Identifiers

PMID41563342
PMCPMC12821365

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.