Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity):Citation formats

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@article{24b9cddfd00c4fc0a707e9658f73afaa,
title = "Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity):: A longitudinal observational study",
abstract = "Introduction:People 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.Aim:The 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:“Watch Your Steps” was a prospective observational study, administering multiple questions and active tasks over 90 days. Adults with more than one clinician diagnosed long term conditions were loaned Fossil{\textregistered} Sport smartwatches, pre-loaded with the study app. Around 20 questions were prompted per day. Daily completion rates were calculated to describe engagement patterns over time, and to explore how these varied by patient characteristics and question type.Results:Fifty three people with MLTC-M took part in the study. Around half were male (n=26; 49%) and the majority had a white ethnic background (n=45; 85%). About a third of participants engaged with the smartwatch app nearly every day. The overall completion rate of symptom questions was 45% (IQR 23-67%) across all study participants. Older patients and those with greater MLTC-M were more engaged, although engagement was not significantly different between genders. Conclusion:It was feasible for people living with MLTC-M to report multiple symptoms per day over three 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.",
author = "Ali, {Syed Mustafa} and David Selby and Khalid Kazi and Katherine Dempsey and Elaine Mackey and Nicola Small and {van der Veer}, Sabine and Brian McMillan and Peter Bower and Benjamin Brown and John Mcbeth and William Dixon",
year = "2021",
month = dec,
day = "7",
doi = "10.1177/26335565211062791",
language = "English",
volume = "11",
journal = "Journal of Multimorbidity and Comorbidity",
issn = "2633-5565",
publisher = "Sage Publications Ltd",

}

RIS

TY - JOUR

T1 - Engagement with consumer smartwatches for tracking symptoms of individuals living with multiple long-term conditions (multimorbidity):

T2 - A longitudinal observational study

AU - Ali, Syed Mustafa

AU - Selby, David

AU - Kazi, Khalid

AU - Dempsey, Katherine

AU - Mackey, Elaine

AU - Small, Nicola

AU - van der Veer, Sabine

AU - McMillan, Brian

AU - Bower, Peter

AU - Brown, Benjamin

AU - Mcbeth, John

AU - Dixon, William

PY - 2021/12/7

Y1 - 2021/12/7

N2 - Introduction:People 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.Aim:The 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:“Watch Your Steps” was a prospective observational study, administering multiple questions and active tasks over 90 days. Adults with more than one clinician diagnosed long term conditions were loaned Fossil® Sport smartwatches, pre-loaded with the study app. Around 20 questions were prompted per day. Daily completion rates were calculated to describe engagement patterns over time, and to explore how these varied by patient characteristics and question type.Results:Fifty three people with MLTC-M took part in the study. Around half were male (n=26; 49%) and the majority had a white ethnic background (n=45; 85%). About a third of participants engaged with the smartwatch app nearly every day. The overall completion rate of symptom questions was 45% (IQR 23-67%) across all study participants. Older patients and those with greater MLTC-M were more engaged, although engagement was not significantly different between genders. Conclusion:It was feasible for people living with MLTC-M to report multiple symptoms per day over three 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.

AB - Introduction:People 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.Aim:The 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:“Watch Your Steps” was a prospective observational study, administering multiple questions and active tasks over 90 days. Adults with more than one clinician diagnosed long term conditions were loaned Fossil® Sport smartwatches, pre-loaded with the study app. Around 20 questions were prompted per day. Daily completion rates were calculated to describe engagement patterns over time, and to explore how these varied by patient characteristics and question type.Results:Fifty three people with MLTC-M took part in the study. Around half were male (n=26; 49%) and the majority had a white ethnic background (n=45; 85%). About a third of participants engaged with the smartwatch app nearly every day. The overall completion rate of symptom questions was 45% (IQR 23-67%) across all study participants. Older patients and those with greater MLTC-M were more engaged, although engagement was not significantly different between genders. Conclusion:It was feasible for people living with MLTC-M to report multiple symptoms per day over three 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.

U2 - 10.1177/26335565211062791

DO - 10.1177/26335565211062791

M3 - Article

C2 - 34869047

VL - 11

JO - Journal of Multimorbidity and Comorbidity

JF - Journal of Multimorbidity and Comorbidity

SN - 2633-5565

ER -