Effectiveness of cognitive-motor dual task training in preventing falls in community older adults: A meta-analysis and systematic review

Background: Cognitive-motor dual task training has shown great significance in reducing the risk of falls and improving gait and balance function in the older persons, and is increasingly emerging in the field of sports rehabilitation.However, the effects of cognitive-motor dual task training are not well-understood. Objective: To evaluate the effectiveness of cognitive-motor dual task training in preventing falls in community older adults. Design: Systematic review. Methods: A librarian-designed search of the Cochrane Library, PubMed, Web of Science, EMBASE, CINAHL, CBM, CNKI, and Wanfang databases was conducted to identify studies in English or Chinese on randomized controlled trials up to 10 May 2024. Two researchers independently screened the literature by reading the titles and abstracts of the trials to determine whether a study was eligible for inclusion. Primary and secondary outcomes were compared between the intervention and control groups. A fixed- or random-effects meta-analysis model was used to determine the mean difference, based on the results of the heterogeneity test. Results: Compared to traditional fall prevention interventions, cognitive-motor dual-task training can effectively improve the gait, static and dynamic(>12-week) balance function of community older adults, enhance executive function, and reduce the risk of falls. The effect of dual-task training on enhancing lower-extremity muscle strength and reducing the fear of falling in community-dwelling older adults remains controversial. Conclusions: Cognitive-motor dual-task training interventions could effectively prevent falls in community older individuals. Higher quality, larger sample size, and long-term follow-up studies are needed to further verify the long-term effectiveness of cognitive-motor dual-task training training in preventing falls in community older individuals. No Patient or Public Contribution: Our paper is a systematic review and meta-analysis and such details don't apply to our work. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.