Evidence map›Paper›PMID 39172978›Full record

ArticlePLOS digital health2024

Feasibility characteristics of wrist-worn fitness trackers in health status monitoring for post-COVID patients in remote and rural areas.

Madeleine Wiebe, Marnie Mackay, Ragur Krishnan, Julie Tian, Jakob Larsson, Setayesh Modanloo, Christiane Job McIntosh, Melissa Sztym, Gail Elton-Smith, Alyssa Rose and 5 more

Abstract read
In one paragraph

Article in PLOS digital health, 2024. 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
–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

1 citing paper in PubMed.

  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

15 authors.

Madeleine WiebeFaculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.ORCID https://orcid.org/0009-0008-7450-7193
Marnie MackayDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Ragur KrishnanDepartment of Electrical and Computer Engineering, Faculty of Engineering University of Alberta, Edmonton, Canada.
Julie TianDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.ORCID https://orcid.org/0009-0002-0535-8426
Jakob LarssonFaculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Setayesh ModanlooDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Christiane Job McIntoshNeurosciences, Rehabilitation and Vision Strategic Clinical Network, Alberta Health Services, Edmonton, Canada.
Melissa SztymCovenant Health Rural Health Services, Edmonton, Canada.
Gail Elton-SmithCovenant Health Rural Health Services, Edmonton, Canada.
Alyssa RoseCovenant Health Rural Health Services, Edmonton, Canada.
Chester HoGlenrose Rehabilitation Hospital, Edmonton, Canada.
Andrew GreenshawDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Bo CaoDepartment of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.
Andrew ChanGlenrose Rehabilitation Hospital, Edmonton, Canada.
Jake HaywardDepartment of Emergency Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCommon, consumer-grade biosensors mounted on fitness trackers and smartwatches can measure an array of biometrics that have potential utility in post-discharge medical monitoring, especially in remote/rural communities. The feasibility characteristics for wrist-worn biosensors are poorly described for post-COVID conditions and rural populations.

methodsWe prospectively recruited patients in rural communities who were enrolled in an at-home rehabilitation program for post-COVID conditions. They were asked to wear a FitBit Charge 2 device and biosensor parameters were analyzed [e.g. heart rate, sleep, and activity]. Electronic patient reported outcome measures [E-PROMS] for mental [bi-weekly] and physical [daily] symptoms were collected using SMS text or email [per patient preference]. Exit surveys and interviews evaluated the patient experience.

resultsTen patients were observed for an average of 58 days and half [N = 5] were monitored for 8 weeks or more. Five patients [50%] had been hospitalized with COVID [mean stay = 41 days] and 4 [36%] had required mechanical ventilation. As baseline, patients had moderate to severe levels of anxiety, depression, and stress; fatigue and shortness of breath were the most prevalent physical symptoms. Four patients [40%] already owned a smartwatch. In total, 575 patient days of patient monitoring occurred across 10 patients. Biosensor data was usable for 91.3% of study hours and surveys were completed 82.1% and 78.7% of the time for physical and mental symptoms, respectively. Positive correlations were observed between stress and resting heart rate [r = 0.360, p<0.01], stress and daily steps [r = 0.335, p<0.01], and anxiety and daily steps [r = 0.289, p<0.01]. There was a trend toward negative correlation between sleep time and physical symptom burden [r = -0.211, p = 0.05]. Patients reported an overall positive experience and identified the potential for wearable devices to improve medical safety and access to care. Concerns around data privacy/security were infrequent.

conclusionsWe report excellent feasibility characteristics for wrist-worn biosensors and e-PROMS as a possible substrate for multi-modal disease tracking in post-COVID conditions. Adapting consumer-grade wearables for medical use and scalable remote patient monitoring holds great potential.

Identifiers

PMID39172978
PMCPMC11340956

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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.