Ivana Paccoud ^1,2* Mayca Marín Valero ³ Laura Carrasco Marín ³ Noémi Bontridder ⁴ Alzhraa Ibrahim ^5,6 Jürgen Winkler ^5,7 Messaline Fomo ^1,2 Stefano Sapienza ^1,2 Fouad Khoury ⁸ Jean-Christophe Corvol ⁸ Holger Fröhlich ^10,9 Jochen Klucken ^11,12,2

• ¹ Department of Precision Health, Luxembourg Institute of Health, Luxembourg, Luxembourg
• ² Luxembourg Centre for System Biomedicine, University of Luxembourg, Luxembourg, Luxembourg, Luxembourg
• ³ Asociación Parkinson Madrid, Madrid, Asturias, Spain
• ⁴ Research Centre Information, Law and Society, Namur Digital Institute, University of Namur, Namure, Belgium
• ⁵ Center of Rare Diseases Erlangen, University hospital Erlangen, Erlangen, Bavaria, Germany
• ⁶ Department Artificial Intelligence in Biomedical Engineering, Technische Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Bavaria, Germany
• ⁷ Department of Molecular Neurology, University Hospital Erlangen, Erlangen, Bavaria, Germany
• ⁸ Sorbonne University, Paris Brain Institute – ICM, Assistance Publique Hôpitaux de Paris, Inserm, CNRS, Pitié-Salpêtrière Hospital, Paris, France
• ⁹ Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing, Sankt Augustin, North Rhine-Westphalia, Germany
• ¹⁰ Bonn Aachen International Center for Information Technology (B-IT), Bonn, North Rhine-Westphalia, Germany
• ¹¹ Luxembourg Institute of Health, Luxembourg, Luxembourg
• ¹² Centre Hospitalier de Luxembourg, Luxembourg, Luxembourg

Introduction: Parkinson's Disease (PD) affects around 8.5 million people currently with numbers expected to rise to 12 million by 2040. PD is characterized by fluctuating motor and non-motor symptoms demanding accurate monitoring. Recent advancements in digital medical devices (DMDs) like wearables and AI offer promise in addressing these needs. However, the successful implementation of DMDs in healthcare relies on patients' willingness to adopt and engage with these digital tools. Methods: To understand patient perspectives in individuals with PD, a cross-sectional study was conducted as part of the EU-wide DIGIPD project across France, Spain, and Germany. Multidisciplinary teams including neurodegenerative clinics and patient organizations conducted surveys focusing on (i) sociodemographic information, (ii) use of DMDs (iii) acceptance of using health data (iv) preferences for the DMDs use. We used descriptive statistics to understand the use of DMDs and patient preferences and logistic regression models to identify predictors of willingness to use DMDs and to share health data through DMDs. Results: In total 333 individuals with PD participated in the study. Findings revealed a high willingness to use DMDs (90.3% ) and share personal health data (97.4%,) however this differed across sociodemographic groups and was more notable among older age groups (under 65=17.9% vs over 75= 39.29%, p=0.001) and those with higher education levels less willing to accept such use of data (university level = 78.6% vs 21.43% with secondary level, p=0.025). Providing instruction on the use of DMDs and receiving feedback on the results of the data collection significantly increased the willingness to use DMDs (OR=3.57, 95% CI= 1.44-8.89) and (OR=3.77, 95% CI= 1.01-14.12), respectively.The study emphasizes the importance of considering patient perspectives for the effective deployment of digital technologies, especially for older and more advanced disease-stage patients who stand to benefit the most.