ArticleNPJ Parkinson's disease2025
Remote real time digital monitoring fills a critical gap in the management of Parkinson's disease.
Article in NPJ Parkinson's disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed.
- Reciprocity in research: Participant views on return of results in the WATCH-PD qualitative study.Journal of Parkinson's disease · 2026Article
- From Prototype to Clinical Workflow: Co-Developing a Wearable Hypomimia System for Parkinson's Disease.Sensors (Basel, Switzerland) · 2026Article
- Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.Journal of Parkinson's disease · 2026Review
- Deriving Motor States and Mobility Metrics from Gamified Augmented Reality Rehabilitation Exercises in People with Parkinson's Disease.Sensors (Basel, Switzerland) · 2025Article
- Quantifying device type and handedness biases in a remote Parkinson's disease AI-powered assessment.NPJ digital medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
People with Parkinson's disease (PWP) face significant gaps in care. Limited neurologist access, infrequent clinic visits, and inadequate symptom measurement culminate in suboptimal therapy and high morbidity. Quantitative Digitography (QDG) provides validated, digital metrics of the three cardinal motor signs in Parkinson's disease (PD) in real-time from 30 seconds of a mobility task on a digitography device and can be used remotely or in clinical settings. This study demonstrates the feasibility and clinical relevance of 30-day remote QDG monitoring. Participants showed excellent compliance and found the system easy to use. The QDG Mobility Score demonstrated meaningful correlation with Activities of Daily Living (ADLs), captured motor complexities across a broad PD duration, and tracked motor changes from small therapy adjustments. QDG offers providers and PWP an accessible, objective, and real-time tool to remotely monitor motor symptoms, optimize treatment, and address care gaps created by infrequent clinic visits and subjective symptom assessment.
Identifiers
What OpenQuestion holds
Registered trials
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.