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This study aims to develop and validate an innovative dynamic 9-square grid management model to improve aerobic capacity (AC) and physical activity participation among graduate students. The model integrates real-time exercise volume (quantified via smart wearable devices) and aerobic capacity (assessed by 12-minute run tests) into a two-dimensional grid, stratifying participants into five tiers for differentiated interventions.
Using a 2 × 3 mixed-design (feedback frequency: weekly vs. monthly; time points: baseline/mid/post-intervention), 32 healthy graduate students are randomized into two groups:
Weekly feedback (dynamic position updates + tailored optimization strategies).
Monthly feedback (position updates at monthly intervals).
Key components include:
Multimodal assessment: Objective exercise metrics (Huawei Band 6), AC (12-min run), psychological scales (Exercise Identity Scale, Self-Efficacy for Exercise Scale).
Tiered intervention: Customized strategies based on grid positioning (e.g., "Star Talent" optimization vs. "Urgent Attention" support).
Primary outcomes: Changes in AC, total exercise volume (TEV), exercise identity, and self-efficacy.
The study seeks to determine whether weekly dynamic feedback outperforms monthly feedback in sustaining behavioral change and enhancing physiological adaptation. Ethical approval was obtained from Anqing Normal University (AQNU2024110).
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30 participants in 2 patient groups, including a placebo group
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Data sourced from clinicaltrials.gov
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