Evidence map›Paper›PMID 34869047›Full record

ArticleJournal of multimorbidity and comorbidity

Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity): A longitudinal observational study.

Syed Mustafa Ali, David A Selby, Kazi Khalid, Katherine Dempsey, Elaine Mackey, Nicola Small, Sabine N van der Veer, Brian Mcmillan, Peter Bower, Benjamin Brown and 2 more

Abstract read
In one paragraph

Article in Journal of multimorbidity and comorbidity. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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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

12 authors.

Syed Mustafa AliCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.ORCID 0000-0001-9393-9049
David A SelbyCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
Kazi KhalidCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
Katherine DempseyCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
Elaine MackeyCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
Nicola SmallCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
Sabine N van der VeerCentre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Brian McmillanNIHR School for Primary Care Research, Centre for Primary Care and Health Services Research, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and health, Manchester Academic Health Science Centre Manchester, University of Manchester, Manchester, UK.ORCID 0000-0002-0683-3877
Peter BowerNIHR Policy Research Unit for Older People and Frailty, Centre for Primary Care and Health Services Research, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and health, Manchester Academic Health Science Centre Manchester, University of Manchester, Manchester, UK.
Benjamin BrownCentre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
John McBethCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.
William G DixonCentre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.

Funding

Medical Research Council MC_PC_17172
6 · The paper itself

Abstract

introductionPeople living with multiple long-term conditions (multimorbidity) (MLTC-M) experience an accumulating combination of different symptoms. It has been suggested that these symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices.

aimThe aim of this study was to investigate longitudinal user engagement with a smartwatch application, collecting survey questions and active tasks over 90 days, in people living with MLTC-M.

methods

resultsFifty three people with MLTC-M took part in the study. Around half were male ( = 26; 49%) and the majority had a white ethnic background (

conclusionIt was feasible for people living with MLTC-M to report multiple symptoms per day over 3 months. User engagement appeared as good as other mobile health studies that recruited people with single health conditions, despite the higher daily data entry burden.

Indexed as

Multiple long-term conditions (multimorbidity)patient-generated health datasmartwatchuser engagement

Identifiers

PMID34869047
PMCPMC8637784

What OpenQuestion holds

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Registered trials

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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.