Information from the abstract
Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder worldwide, with projections exceeding 25 million people by 2050. Its burden, however, is unevenly distributed. Many low- and middle-income countries face rapidly rising prevalence alongside profound shortages in neurological workforce, infrastructure, and access to specialised care and essential therapies. This global "Parkinson's divide" reflects not merely a funding gap, but a structural mismatch between disease burden and health-system capacity. Traditional clinic-centred models cannot scale to meet this expanding demand.This article argues that technology, when responsibly implemented, offers a structural response to this capacity gap. Telemedicine expands access by decoupling specialist expertise from geography. Wearable and domestic sensor-based technologies extend clinical visibility beyond episodic encounters, capturing real-world fluctuations, mobility changes, falls, and sleep disturbances. Artificial intelligence, positioned as augmented rather than autonomous intelligence, can transform high-volume longitudinal data into actionable insights that support triage, task-sharing, and continuity across distributed care networks. Mobile health platforms further strengthen patient agency through structured self-management and co-designed digital ecosystems.Yet innovation alone is not sufficient. Impact depends on feasibility, interoperability, workforce development, governance, and equity-first design, particularly in resource-constrained settings. Embedded within hybrid care models and life-course brain health frameworks, digital technologies can shift PD management from episodic symptom control toward longitudinal stewardship of function and resilience, helping to convert scarcity into distributed capability and narrow global inequities in Parkinson's care for our future generations.
Why this record is monitored
This record has an Impact Signal of 79/100 based on recency, source, collaboration, and bibliographic signals. It prioritizes monitoring and is not a judgment of research quality.
Related topics: Parkinson's Disease Mechanisms and Treatments · Neurological disorders and treatments · Voice and Speech Disorders
Thai researcher and institutional participation
Roongroj Bhidayasiri · Thai Red Cross Society · Chulalongkorn University · King Chulalongkorn Memorial Hospital · The Royal College Of Anesthesiologists Of Thailand
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