Evidence map›Paper›PMID 31583283›Full record

ArticleNPJ digital medicine2019

Feasibility and utility of a clinician dashboard from wearable and mobile application Parkinson's disease data.

Jordan J Elm, Margaret Daeschler, Lauren Bataille, Ruth Schneider, Amy Amara, Alberto J Espay, Michal Afek, Chen Admati, Abeba Teklehaimanot, Tanya Simuni

Abstract read
In one paragraph

Article in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 3 pooled it
–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

39 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Digital Technologies for Symptom Monitoring in Parkinson Disease.Current neurology and neuroscience reports · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Observational
  18. Article
  19. Article
  20. Detecting the symptoms of Parkinson's disease with non-standard video.Journal of neuroengineering and rehabilitation · 2024
    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

10 authors.

Jordan J Elm1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425 USA.
Margaret Daeschler2The Michael J. Fox Foundation for Parkinson's Research, New York, NY USA.
Lauren Bataille2The Michael J. Fox Foundation for Parkinson's Research, New York, NY USA.
Ruth Schneider3University of Rochester, Rochester, NY USA.
Amy Amara4University of Alabama at Birmingham, Birmingham, AL USA.ORCID 0000-0003-0762-9656
Alberto J Espay5University of Cincinnati Medical Center, Cincinnati, OH USA.
Michal Afek6Advanced Analytics Department, Intel, Petach Tikva, Israel.
Chen Admati6Advanced Analytics Department, Intel, Petach Tikva, Israel.
Abeba Teklehaimanot1Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425 USA.
Tanya Simuni7Northwestern University Feinberg School of Medicine, Chicago, IL USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile and wearable device-captured data have the potential to inform Parkinson's disease (PD) care. The objective of the Clinician Input Study was to assess the feasibility and clinical utility of data obtained using a mobile health technology from PD patients. In this observational, exploratory study, PD participants wore a smartwatch and used the

Indexed as

Health servicesParkinson's diseasePrognostic markers

Identifiers

PMID31583283
PMCPMC6761168

What OpenQuestion holds

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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 OpenQuestion graph.