Outcome measurement instruments in neurodegenerative diseases: Comprehensive analysis and platform construction
Year: 2025
Type: article
Abstract: Objectives: The selection of appropriate outcome measurement instruments (OMIs) in neurodegenerative disease (NDD) researches remains complex and often inconsistent. This study aims to consolidate knowledge on OMIs applied in NDD over the last two decades and to develop outcome measurement instruments in neurodegenerative diseases (NDDOMI), a web-based knowledge platform for OMIs selection. Methods: We collected clinical trials from the past two decades across six prevalent NDDs from ClinicalTrials.gov. OMIs were manually extracted, categorized, and normalized by experts. We analyzed OMI utilization patterns, cross-disease applicability, and temporal trends. Additionally, we developed NDDOMI, a knowledge resource platform, using Django, ECharts, and JavaScript. The usability of NDDOMI was assessed using the System Usability Scale and Net Promoter Score. Results: The NDDOMI platform provides an interface covering 4619 clinical trials and 2494 OMIs. On average, 4.4 instruments were utilized per trial. Fifteen instruments are shared across six NDDs. 76.75% of the trials employed more than one instruments, often in combination. A positive correlation was observed between the number of trials and the diversity of OMIs employed. The top 10 frequently employed instruments for each disease were identified, and their utilization has increased over time. The usability assessment demonstrated excellent user satisfaction with an average SUS score of 88.19. Conclusions: This study introduces a comprehensive analysis of OMI usage trends in NDD research and introduces NDDOMI platform for OMI navigation and selection. NDDOMI serves as a valuable resource for optimizing clinical research design and standardizing outcome measurement in NDD management. The NDDOMI platform is available at http://bioinf.org.cn:3134/index/.
Source: Digital Health
Authors: Hui Zong, Jiaxue Cha, Liang Tao, Muyun Shi, Yan Zhao, Ru Zhang, Bairong Shen
Language: English
Topic: Delphi Technique in Research
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,000
Awards: G4808893844, G656904356
OpenAlex ID: W4409962258
