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. 2024 Dec 4:15:1453243.
doi: 10.3389/fneur.2024.1453243. eCollection 2024.

Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson's Disease

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

Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson's Disease

Ivana Paccoud et al. Front Neurol. .

Abstract

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.

Conclusion: 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.

Keywords: Adoption of AI; Parkinson’s Disease; acceptance of digital medical devices; patient preferences; patient-centeredness; personalized medicine; trust; use of health data.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Use and Willingness to use DMDs by country and age groups. (A) Use of DMDs. (B) Willingness to use DMDs.
Figure 2
Figure 2
Willingness to share personal health data through DMDs for healthcare purposes by age and educational level. (A) Willingness to share health data by age. (B) Willingness to share health data by educational level.
Figure 3
Figure 3
Confidence in AI for clinical decision support by educational level.
Figure 4
Figure 4
Concerns about handling DMDs by age and disease duration. (A) Concerns by age. (B) Concerns by disease duration.
Figure 5
Figure 5
Preferences for using smartphones by disease duration and educational level. (A) Preferences for smartphones by PD duration. (B) Preferences for smartphones by education.
See this image and copyright information in PMC

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