Optimal exercise modalities and dose for enhancing intelligence in children and adolescents: a Bayesian network meta-analysis

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Authors: Yan Wang, Junyu Wang, Lin Zhang, Chengji Wang, Guotuan Wang, Changdong Li, Yuan Yuan, Bopeng Qiu, Yong Yang
Cited by: 0
References: 54

Abstract

Background: To compare the effects of various exercise modalities on intelligence and determine the optimal exercise dose for children and adolescents. Methods: A systematic review and Bayesian network meta-analysis following PRISMA guidelines was conducted. Four databases were searched up to 1 April 2025. Eligible RCTs involved participants aged 5-18 years and assessed exercise interventions with intelligence outcomes (general, fluid, or crystallized). Standardized mean differences (SMDs) with corresponding 95% confidence interval or credible intervals were calculated. Dose-response relationships were analyzed using model-based network meta-analysis. Results: Fifteen RCTs with 3,400 participants were included. Exercise was linked to small-to-moderate improvements in general (SMD = 0.59), fluid (SMD = 0.43), and crystallized intelligence (SMD = 0.64). Dual-task balance training (DTBT) produced the most consistent and significant benefits across all domains. Yoga and multi-component exercise also showed positive effects. Optimal outcomes were achieved with sessions lasting ≥117.7 min, three times weekly, totaling 220 min per week for at least 11.12 weeks. An inverted U-shaped dose-response curve indicated diminishing returns beyond the optimal frequency and duration. Conclusion: DTBT is the most effective exercise modality for improving intelligence in children and adolescents. The findings provide evidence-based guidance for designing school and clinical exercise programs to support cognitive development during growth.

Fields of Study & Subjects

Physical Activity and Health Cognitive Abilities and Testing Children's Physical and Motor Development

Publication details

Journal / source
Frontiers in Physiology
Volume
16
Pages
1685099–1685099
Publication date
15 January 2026
Language
EN