Evidence map›Paper›PMID 38223165›Full record

ArticleJournal of multimorbidity and comorbidity

Users' views on the use of a smartwatch app to collect daily symptom data in individuals with multiple long-term conditions (Multimorbidity): A qualitative study.

Cassandra Kenning, Peter Bower, Nicola Small, Syed Mustafa Ali, Benjamin Brown, Katherine Dempsey, Elaine Mackey, Brian McMillan, Caroline Sanders, Ilina Serafimova and 3 more

Open access · diamondAbstract 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

13 authors at 2 institutions in 1 country.

Cassandra KenningCentre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-6041-4051
Peter BowerCentre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-9558-3349
Nicola SmallCentre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0002-7879-7967
Syed Mustafa AliCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-9393-9049
Benjamin BrownCentre for Health Informatics, Division of Informatics, Imaging and Data Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-9975-4782
Katherine DempseyCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Elaine MackeyCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.
Brian McMillanCentre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0002-0683-3877
Caroline SandersCentre for Primary Care and Health Services Research, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0002-0539-928X
Ilina SerafimovaCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, 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.ORCID https://orcid.org/0000-0003-0929-436X
William G DixonCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-5881-4857
John McBethCentre for Epidemiology Versus Arthritis, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK.ORCID https://orcid.org/0000-0001-7047-2183
Manchester Academic Health Science Centre · GBUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Long-term conditions are a major burden on health systems. One way to facilitate more research and better clinical care among patients with long-term conditions is to collect accurate data on their daily symptoms (patient-generated health data) using wearable technologies. Whilst evidence is growing for the use of wearable technologies in single conditions, there is less evidence of the utility of frequent symptom tracking in those who have more than one condition. Aims: To explore patient views of the acceptability of collecting daily patient-generated health data for three months using a smartwatch app. Methods: Watch Your Steps was a longitudinal study which recruited 53 patients to track over 20 symptoms per day for a 90-day period using a study app on smartwatches. Semi-structured interviews were conducted with a sub-sample of 20 participants to explore their experience of engaging with the app. Results: In a population of older people with multimorbidity, patients were willing and able to engage with a patient-generated health data app on a smartwatch. It was suggested that to maintain engagement over a longer period, more 'real-time' feedback from the app should be available. Participants did not seem to consider the management of more than one condition to be a factor in either engagement or use of the app, but the presence of severe or chronic pain was at times a barrier. Conclusion: This study has provided preliminary evidence that multimorbidity was not a major barrier to engagement with patient-generated health data via a smartwatch symptom tracking app.

Indexed as

Multimorbiditypatient-generated health dataqualitativesmartwatchuser engagement

Identifiers

PMID38223165
PMCPMC10785716
OpenAlexW4390701296

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.