Evidence map›Paper›PMID 39056543›Full record

Observational studyMovement disorders clinical practice2024

Patient Experience and Feasibility of a Remote Monitoring System in Parkinson's Disease.

Bart R Maas, Daniël H B Speelberg, Gert-Jan de Vries, Giulio Valenti, Andreas Ejupi, Bastiaan R Bloem, Sirwan K L Darweesh, Nienke M de Vries

Abstract readObservational Study
In one paragraph

Observational study in Movement disorders clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

8 authors.

Bart R MaasDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Center of Expertise for Parkinson and Movement Disorders, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0003-4732-8014
Daniël H B SpeelbergDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Center of Expertise for Parkinson and Movement Disorders, Nijmegen, The Netherlands.
Gert-Jan de VriesPhilips Research-Healthcare, Eindhoven, The Netherlands.
Giulio ValentiPhilips Research-Healthcare, Eindhoven, The Netherlands.
Andreas EjupiPhilips Research-Healthcare, Eindhoven, The Netherlands.
Bastiaan R BloemDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Center of Expertise for Parkinson and Movement Disorders, Nijmegen, The Netherlands.
Sirwan K L DarweeshDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Center of Expertise for Parkinson and Movement Disorders, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0002-4361-4593
Nienke M de VriesDepartment of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behavior, Center of Expertise for Parkinson and Movement Disorders, Nijmegen, The Netherlands.ORCID https://orcid.org/0000-0002-1972-2703

Funding

ZonMw 91619142
6 · The paper itself

Abstract

backgroundRemote monitoring systems have the potential to measure symptoms and treatment effects in people with Parkinson's disease (PwP) in the home environment. However, information about user experience and long-term compliance of such systems in a large group of PwP with relatively severe PD symptoms is lacking.

objectiveThe aim was to gain insight into user experience and long-term compliance of a smartwatch (to be worn 24/7) and an online dashboard to report falls and receive feedback of data.

methodsWe analyzed the data of the "Bringing Parkinson Care Back Home" study, a 1-year observational cohort study in 200 PwP with a fall history. User experience, compliance, and reasons for noncompliance were described. Multiple Cox regression models were used to identify determinants of 1-year compliance.

resultsWe included 200 PwP (mean age: 69 years, 37% women), of whom 116 (58%) completed the 1-year study. The main reasons for dropping out of the study were technical problems (61 of 118 reasons). Median wear time of the smartwatch was 17.5 h/day. The online dashboard was used by 77% of participants to report falls. Smartphone possession, shorter disease duration, more severe motor symptoms, and less-severe freezing and balance problems, but not age and gender, were associated with a higher likelihood of 1-year compliance.

conclusionsThe 1-year compliance with this specific smartwatch was moderate, and the user experience was generally good, except battery life and data transfer. Future studies can build on these findings by incorporating a smartwatch that is less prone to technical issues.

Indexed as

Feasibility StudiesParkinson DiseaseAccidental FallsAgedAged, 80 and overCohort StudiesFemaleHumansMaleMiddle AgedMonitoring, AmbulatoryPatient CompliancePatient SatisfactionSmartphoneTelemedicineexperiencefeasibilityParkinson's diseaseremote monitoringwearable sensors

Identifiers

PMID39056543
PMCPMC11489606

What Socratic holds

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LicenceCC BY
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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 Socratic graph.