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).

Inclusion Criteria:

• Graduate students aged between 18 and 30 years.
• Completion of the Physical Activity Readiness Questionnaire (PAR-Q) to confirm readiness for exercise.
• Completion of a sociodemographic questionnaire (including age, gender, and education level).
• Confirmation of absence of exercise contraindications (e.g., conditions that may prevent safe participation in physical activity).
• Confirmation of absence of cardiovascular disease.
• Confirmation of absence of recent lower-limb injuries (occurring within the past 3 months or less).
• Confirmation of absence of chest pain symptoms.
• Ability to provide written informed consent for voluntary participation.

Exclusion Criteria:

• Presence of exercise contraindications identified through the PAR-Q or clinical evaluation.
• History or diagnosis of cardiovascular disease (e.g., heart conditions, stroke, or related disorders).
• Recent lower-limb injuries (e.g., fractures, sprains, or surgeries) within the past 3 months.
• Experience of chest pain symptoms (e.g., angina or discomfort during physical exertion).
• Inability to complete the required questionnaires or assessments due to cognitive or language barriers.
• Presence of any uncontrolled chronic condition that could interfere with exercise participation, as determined by the researchers during screening.

Aerobic capacity test results；Smart wearable exercise data；Cloud-synced TEV metrics (intensity/duration/frequency)；Aggregated weekly values；Psychological scales (EIS/SEE-C)；Encrypted survey responses；Baseline demographics；Limited metadata (age/BMI)。

1 January 2030;

Academic researchers affiliated with accredited institutions Regulatory bodies (e.g., ethics committees) Peer reviewers for journal publication validation

Access Process:

Step 1: Submit research proposal via OpenClinica Platform Step 2: Institutional ethics approval documentation required Step 3: Data Use Agreement (DUA) signing with corresponding authors