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Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): an exploratory analysis of a longitudinal smartwatch feasibility study

Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): an exploratory analysis of a longitudinal smartwatch feasibility study
Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): an exploratory analysis of a longitudinal smartwatch feasibility study
Introduction: people living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.

Aim: we aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.

Methods: ‘Watch Your Steps’ was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.

Results: fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.

Conclusion: in this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research.
2633-5565
Kazi, Khalid
a3f9f38e-6d79-46ca-88fc-0d286de5bb36
Ali, Syed Mustafa
8a268226-ac7f-4087-ba0a-1d6d248aa745
Selby, David A.
cd631c87-be4f-4421-8c64-d586bf8f466f
McBeth, John
98012716-66ba-480b-9e43-ac53b51dce61
van der Veer, Sabine
bc48aee3-5541-465d-991c-4ee069fb86c6
Dixon, William G.
5dddafc1-ae5f-466e-8517-8369ee750cbc
Kazi, Khalid
a3f9f38e-6d79-46ca-88fc-0d286de5bb36
Ali, Syed Mustafa
8a268226-ac7f-4087-ba0a-1d6d248aa745
Selby, David A.
cd631c87-be4f-4421-8c64-d586bf8f466f
McBeth, John
98012716-66ba-480b-9e43-ac53b51dce61
van der Veer, Sabine
bc48aee3-5541-465d-991c-4ee069fb86c6
Dixon, William G.
5dddafc1-ae5f-466e-8517-8369ee750cbc

Kazi, Khalid, Ali, Syed Mustafa, Selby, David A., McBeth, John, van der Veer, Sabine and Dixon, William G. (2023) Examining the variability of multiple daily symptoms over time among individuals with multiple long-term conditions (MLTC-M/multimorbidity): an exploratory analysis of a longitudinal smartwatch feasibility study. Journal of Multimorbidity and Comorbidity, 13. (doi:10.1177/26335565221150129).

Record type: Article

Abstract

Introduction: people living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.

Aim: we aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.

Methods: ‘Watch Your Steps’ was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.

Results: fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.

Conclusion: in this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research.

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e-pub ahead of print date: 18 January 2023

Identifiers

Local EPrints ID: 491500
URI: http://eprints.soton.ac.uk/id/eprint/491500
ISSN: 2633-5565
PURE UUID: 5a65c8ac-5710-44d9-9390-cfe87abb36ab
ORCID for Syed Mustafa Ali: ORCID iD orcid.org/0000-0001-6221-9962
ORCID for John McBeth: ORCID iD orcid.org/0000-0001-7047-2183

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Date deposited: 25 Jun 2024 16:45
Last modified: 26 Jun 2024 02:11

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Contributors

Author: Khalid Kazi
Author: David A. Selby
Author: John McBeth ORCID iD
Author: Sabine van der Veer
Author: William G. Dixon

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