Comparing Stakeholders' Perspectives on Parkinson Disease Management and Digital Technologies: Exploratory International Survey

Clinical Snapshot

Key Findings

• P Value: P < 0.001 for healthcare professional vs patient differences

• Effect Size: Cramer's V = 0.41 for healthcare professional vs patient engagement priorities

• Primary Outcome: Stakeholder preferences for AI-based tools in Parkinson disease management

• Nnt Or Sensitivity: 76% of respondents desired symptom tracking features; significant gap between interest and actual digital tool usage

• Confidence Interval: Not reported for primary outcomes

Clinical Application

Moderate - requires consideration of digital literacy barriers and stakeholder-specific design approaches Relevant for Australian Parkinson disease management, particularly given PBS coverage for movement disorder medications and growing telehealth adoption post-COVID. May inform TGA digital therapeutics pathway and RACGP digital health guidelines Persons with Parkinson disease, their caregivers, and movement disorder specialists in developed healthcare systems

Abstract

BACKGROUND: Parkinson disease (PD) is a progressive neurodegenerative disorder that poses complex challenges for persons with PD, informal caregivers, and health care professionals. With growing interest in digital and predictive artificial intelligence (AI) tools for disease management, understanding the needs and digital readiness of these stakeholder groups is crucial. OBJECTIVE: This work aims to (1) identify digital practices for PD management among persons with PD, at-risk individuals, caregivers, and health care professionals; (2) compare these practices across groups; (3) explore stakeholder desires for AI-based tools; and (4) assess alignments and gaps to inform tailored AI solutions. METHODS: An anonymous cross-sectional online survey of an exploratory nature was distributed (from December 2024 to October 2025) in 5 languages and completed by 255 respondents. Descriptive statistics summarized responses to 41 questions, including stakeholder-specific items. χ2 tests were performed to examine stakeholder differences in desired AI features. RESULTS: Interest in predictive AI was high across stakeholder groups. Symptom tracking was the most desired feature (selected by more than 76% of the respondents), and personalized treatment recommendations came second for both persons with PD and health care professionals; however, stakeholder priorities diverged in other areas. Health care professionals rated improving patient and informal caregiver engagement as significantly more important than persons with PD did, χ21 (n=205)=34.78, P<.001, and Cramer V=0.41. Despite considerable interest, the reported use of digital tools was limited, as most persons with PD did not use symptom-tracking apps or wearables, nor were they currently monitoring their condition, although many expressed intentions to begin. CONCLUSIONS: While predictive AI tools were viewed positively across groups, there were significant gaps in stakeholder preferences, highlighting the importance of tailored, context-aware design. Early diagnosis was not prioritized by persons with PD or health care professionals, likely reflecting the complexity of diagnosing PD in the absence of disease-modifying therapies. Coupled with the emphasis placed on preventive lifestyle guidance by persons with PD and those at risk, this highlights the importance of actionability in AI-based monitoring and prediction. Such actionability may also enhance perceived relevance and uptake, given that reported interest in digital health tools and self-tracking exceeded actual use. These findings offer early-stage insight to guide the development of future AI-based solutions for PD.

References

1. 1.Luckhaus, J. L., Kharko, A., Blease, C., Almarcha-Menargues, M. L., Del Campo, N., Balula Dias, S., Alves, B., Falkenburger, B. H., Hadjileontiadis, L., Hägglund, M., Riggare, S., & Scott Duncan, T. (2026). Comparing Stakeholders' Perspectives on Parkinson Disease Management and Digital Technologies: Exploratory International Survey. JMIR Formative Research. https://doi.org/10.2196/90377