ArticleFrontiers in aging neuroscience2026
Characterizing motor-cognitive associations in Parkinson's disease using digital assessments.
Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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Who cites it
2 citing papers in PubMed.
- Integrating remote testing and machine learning to identify markers of cerebellar ataxia at home.Communications medicine · 2026Article
- Development and Preliminary Validation of ORCA-PD, an Online Rapid Cognitive Assessment for Parkinson Disease: Mixed Methods Study.Journal of medical Internet research · 2026Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional motor and cognitive assessments for people with Parkinson's disease (PD) have long faced challenges related to accessibility, scalability, and geographical diversity when administered in-person. Remote cognitive testing offers the promise of improved accessibility, reduced participant burden, and greater scalability, particularly for individuals with mobility limitations or limited access to specialized care. While remote cognitive assessments are increasingly used in PD research and clinical settings, it remains unclear whether these measures provide an informative index of PD severity. These gaps limit the interpretability and broader adoption of remote cognitive measures as accessible and scalable indicators of PD severity. To establish a benchmark, we first analyzed a large in-person dataset (PPMI;
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Registered trials
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