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Published on: December 16, 2022
Mapping the evolution of dual-task paradigms in cognitive aging: A bibliometric analysis of research landscapes and
Shi Zhang1, Ruoning Wu2, Yuqi Xu2
1College of Integrated Traditional Chinese and Western Medicine Institute of Integrated Traditional Chinese and Western Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian Province, China.
Abstract:
The increasing burden of dementia highlights the need for sensitive and ecologically relevant tools for early detection and intervention. Dual-task (DT) paradigms have emerged as promising approaches for assessing cognitive-motor alterations. This study aimed to map the 22-year evolution of DT research in cognitive aging using bibliometric analysis. We retrieved 1347 articles from the Web of Science Core Collection (January 2003-February 15, 2025) and analyzed them using CiteSpace. Co-citation, keyword burst, and collaboration network analysis were performed to identify research evolution, hotspots, knowledge structures, and international collaborations. Research showed a progressive shift from gait-focused behavioral assessment (2003-2012) to neuroimaging-based investigations (2013-2018), and subsequently toward artificial intelligence-driven, ecologically valid approaches integrating virtual reality and multimodal sensing (2019-2025). The dual-task cost emerged as a potential candidate digital biomarker associated with neural alterations and cognitive decline, while its complementary value to traditional cognitive assessment was highlighted. Dual-task training demonstrated potential benefits for improving functional outcomes and reducing fall risk; however, heterogeneity in treatment effects indicates the need for personalized intervention strategies. DT paradigms are evolving toward potential applications in precision gerontology. The proposed assessment-intervention continuum provides a conceptual framework for future research. Standardized protocols and prospective validation of DT-derived digital phenotypes are required before clinical implementation.
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