帕金森病患者对数字医疗设备与AI驱动个性化医疗健康数据使用观点的调查表1

数据集获取（Figshare）

• 源站标题：Table 1_Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson’s Disease.docx
• DOI：10.3389/fneur.2024.1453243.s001
• 发布日期：2024-12-04
• 文件数：1 个
• 文件总体积：690.23 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_Patient_perspectives_on_the_use_of_digital_medical_devices_and_health_data_for_AI-driven_personalised_medicine_in_Parkinson_s_Disease_docx/27958116

命令行下载

curl -L -o "Table 1_Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson’s Disease.docx" "https://ndownloader.figshare.com/files/50966520"

文件清单

• Table 1_Patient perspectives on the use of digital medical devices and health data for AI-driven personalised medicine in Parkinson’s Disease.docx（690.23 KB）

文件总体积 690.23 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

IntroductionParkinson’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.
MethodsTo 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.
ResultsIn 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.
ConclusionThe 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.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fneur.2024.1453243.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_Patient_perspectives_on_the_use_of_digital_medical_devices_and_health_data_for_AI-driven_personalised_medicine_in_Parkinson_s_Disease_docx/27958116）。