Dose-response relationships of sensorimotor-based interventions on balance performance in older adults: A systematic review and meta-regression analysis
Abstract
Falls are a severe public health challenge for older adults. Although sensorimotor-based interventions can remodel balance, their quantitative dose-response trajectories remain unknown, often leading to blindly accumulated doses. We aimed to identify optimal intervention strategies by deconstructing these non-linear dynamics. A comprehensive search of five databases up to February 2026 identified relevant randomized controlled trials (RCTs). We constructed a random-effects model using the standardized mean difference (Hedges’ g). Restricted cubic spline (RCS) and meta-regression models explored the non-linear dynamics of total intervention dose and the moderating effects of age. We included 24 studies comprising 1,110 participants. Sensorimotor-based interventions significantly improved dynamic balance (Timed Up and Go Test [TUGT]: g = −0.89, Q = 78.19; low-certainty evidence), static balance (Berg Balance Scale [BBS]: g = 0.94, Q = 21.14; high-certainty evidence), and neuromuscular control, including Center of Pressure with eyes open (COP-EO: g = −0.66, Q = 8.19; low-certainty evidence) and Center of Pressure with eyes closed (COP-EC: g = −0.34, Q = 3.54; moderate-certainty evidence). The RCS model suggested significant non-linear dose dependency for dynamic balance (P non-linearity = 0.004), indicating a potential relative attenuation of effect sizes near a cumulative dose of 1000 minutes. Conversely, static balance showed no significant dose association. Increasing age significantly attenuated dynamic balance benefits (p = 0.047) but did not negatively affect static stability. The adaptive trajectories of dynamic and static balance responding to sensorimotor interventions diverge fundamentally. Based on these non-linear dose-response fluctuations and age-related characteristics, continuous time accumulation may not guarantee proportional linear returns. Optimizing fall prevention requires shifting toward precise interventions that consider dose-efficiency and age stratification rather than a “more is better” approach. Systematic Review Registration: INPLASY202630061.
Article Details
Authors (5)
Song Chen
Department of Applied Physics, School of Medical Imaging
Pengwei Chen
Lu Huang
Institute of Analytical Chemistry and Instrument for Life Science, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology
Wenhao Guo
Yuanji Zhong