Evidence map›Paper›PMID 38601188›Full record

ArticleDigital health

Feasibility and usability of remote monitoring in Alzheimer's disease.

Marijn Muurling, Casper de Boer, Chris Hinds, Alankar Atreya, Aiden Doherty, Vasilis Alepopoulos, Jelena Curcic, Anna-Katharine Brem, Pauline Conde, Sajini Kuruppu and 15 more

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
5.0field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 13 citations in OpenAlex.

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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

25 authors at 16 institutions in 12 countries.

Marijn MuurlingAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.ORCID https://orcid.org/0000-0001-9397-4602
Casper de BoerAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
Chris HindsNuffield Department of Population Health, University of Oxford Big Data Institute, Oxford, UK.
Alankar AtreyaNuffield Department of Population Health, University of Oxford Big Data Institute, Oxford, UK.
Aiden DohertyNuffield Department of Population Health, University of Oxford Big Data Institute, Oxford, UK.
Vasilis AlepopoulosInformation Technologies Institute, Center for Research and Technology Hellas (CERTH-ITI), Thessaloniki, Greece.
Jelena CurcicBiomedical Research, Novartis, Basel, Switzerland.
Anna-Katharine BremDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Pauline CondeDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Sajini KuruppuDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Xavier MoratóAce Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain.
Valentina SalettiLaboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Samantha GalluzziLaboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Estefania Vilarino LuisCentre de la mémoire, Université de Genève (UNIGE), Hôpitaux Universitaires de Genève, Geneva, Switzerland.
Sandra CardosoFaculdade de Medicina da, Universidade de Lisboa, Lisbon, Portugal.
Tina StukeljDepartment of Neurology, University Medical Center Ljubljana and Medical faculty, University of Ljubljana, Ljubljana, Slovenia.
Milica Gregorič KrambergerDepartment of Neurology, University Medical Center Ljubljana and Medical faculty, University of Ljubljana, Ljubljana, Slovenia.
Dora RoikDepartment of Geriatric Psychiatry, Central Institute for Mental Health, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany.
Ivan KoychevDepartment of Psychiatry, University of Oxford, Oxford, UK.
Ann-Cecilie HopøyDepartment of Old Age Psychiatry, Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway.
Emilia SchwertnerDivision of Clinical Geriatrics, Department of Neurobiology, Department of Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Mara GkiokaLaboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation (CIRI - AUTh), Balkan Center, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Dag AarslandDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Pieter Jelle VisserAlzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
RADAR-AD consortium
King's College London · GBOpen Data Institute · GBAmsterdam Neuroscience · NLCentro San Giovanni di Dio Fatebenefratelli · ITKarolinska Institutet · SEUniversity of Ljubljana · SIAristotle University of Thessaloniki · GRHeidelberg University · DEInformation Technologies Institute · GRNovartis (Switzerland) · CHStavanger University Hospital · NOUniversitat Internacional de Catalunya · ESUniversity of Bern · CHUniversity of Geneva · CHUniversity of Lisbon · PTUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Remote monitoring technologies (RMTs) can measure cognitive and functional decline objectively at-home, and offer opportunities to measure passively and continuously, possibly improving sensitivity and reducing participant burden in clinical trials. However, there is skepticism that age and cognitive or functional impairment may render participants unable or unwilling to comply with complex RMT protocols. We therefore assessed the feasibility and usability of a complex RMT protocol in all syndromic stages of Alzheimer's disease and in healthy control participants. Methods: For 8 weeks, participants (N = 229) used two activity trackers, two interactive apps with either daily or weekly cognitive tasks, and optionally a wearable camera. A subset of participants participated in a 4-week sub-study (N = 45) using fixed at-home sensors, a wearable EEG sleep headband and a driving performance device. Feasibility was assessed by evaluating compliance and drop-out rates. Usability was assessed by problem rates (e.g., understanding instructions, discomfort, forgetting to use the RMT or technical problems) as discussed during bi-weekly semi-structured interviews. Results: Most problems were found for the active apps and EEG sleep headband. Problem rates increased and compliance rates decreased with disease severity, but the study remained feasible. Conclusions: This study shows that a highly complex RMT protocol is feasible, even in a mild-to-moderate AD population, encouraging other researchers to use RMTs in their study designs. We recommend evaluating the design of individual devices carefully before finalizing study protocols, considering RMTs which allow for real-time compliance monitoring, and engaging the partners of study participants in the research.

Indexed as

Alzheimers < diseaseapps < personalised medicinedementia < diseasedigital health < generaleHealth < generalneurology < medicineremote clinical trials < studiesremote patient monitoring <personalised medicinewearables < personalised medicine

Identifiers

PMID38601188
PMCPMC11005503
OpenAlexW4394626965

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.