Evidence map›Paper›PMID 40184612›Full record

ArticleJournal of medical Internet research2025

Modernizing the Staging of Parkinson Disease Using Digital Health Technology.

John Michael Templeton, Christian Poellabauer, Sandra Schneider, Morteza Rahimi, Taofeek Braimoh, Fhaheem Tadamarry, Jason Margolesky, Shanna Burke, Zeina Al Masry

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. 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. Trial
  2. Article
  3. Peripheral inflammation predicts motor, cognitive, and disease progression in Parkinson's disease: A 4-year longitudinal study from the PPMI cohorts.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Article
  4. Digital Technologies for Symptom Monitoring in Parkinson Disease.Current neurology and neuroscience reports · 2026
    Review
  5. Review
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

9 authors.

John Michael TempletonBellini College of Artificial Intelligence, Cybersecurity, and Computing, University of South Florida, Tampa, FL, United States.ORCID 0000-0002-7229-9975
Christian PoellabauerKnight Foundation School of Computing and Information Sciences, Florida International University, Miami, FL, United States.ORCID 0000-0002-0599-7941
Sandra SchneiderDepartment of Communicative Sciences and Disorders, Saint Mary's College, Notre Dame, IN, United States.ORCID 0000-0002-8766-7355
Morteza RahimiKnight Foundation School of Computing and Information Sciences, Florida International University, Miami, FL, United States.ORCID 0000-0002-9704-1049
Taofeek BraimohBellini College of Artificial Intelligence, Cybersecurity, and Computing, University of South Florida, Tampa, FL, United States.ORCID 0009-0006-1508-4296
Fhaheem TadamarryBellini College of Artificial Intelligence, Cybersecurity, and Computing, University of South Florida, Tampa, FL, United States.ORCID 0000-0001-6613-013X
Jason MargoleskyDepartment of Neurology, Miller School of Medicine, University of Miami, Miami, FL, United States.ORCID 0000-0001-8976-2500
Shanna BurkeRobert Stempel College of Public Health & Social Work, Florida International University, Miami, FL, United States.ORCID 0000-0001-6969-3536
Zeina Al MasryFEMTO-ST Institute, Ecole Nationale Supérieure de Mécanique et des Mécatroniques, Besançon, France.ORCID 0000-0002-6673-0140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the complicated nature of Parkinson disease (PD), a number of subjective considerations (eg, staging schemes, clinical assessment tools, or questionnaires) on how best to assess clinical deficits and monitor clinical progression have been published; however, none of these considerations include a comprehensive, objective assessment of all functional areas of neurocognition affected by PD (eg, motor, memory, speech, language, executive function, autonomic function, sensory function, behavior, and sleep). This paper highlights the increasing use of digital health technology (eg, smartphones, tablets, and wearable devices) for the classification, staging, and monitoring of PD. Furthermore, this Viewpoint proposes a foundation for a new staging schema that builds from multiple clinically implemented scales (eg, Hoehn and Yahr Scale and Berg Balance Scale) for ease and homogeneity, while also implementing digital health technology to expand current staging protocols. This proposed staging system foundation aims to provide an objective, symptom-specific assessment of all functional areas of neurocognition via inherent device capabilities (eg, device sensors and human-device interactions). As individuals with PD may manifest different symptoms at different times across the spectrum of neurocognition, the modernization of assessments that include objective, symptom-specific monitoring is imperative for providing personalized medicine and maintaining individual quality of life.

Indexed as

Biomedical TechnologyDigital TechnologyParkinson DiseaseDigital HealthHumansWearable Electronic DevicesAIartificial intelligencedigital healthdisease classificationneurocognitionParkinson diseasepersonalized medicinewearables

Identifiers

PMID40184612
PMCPMC12008700

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.