How social jet lag may influence risky decision-making using machine learning

The models showed limited predictive capability with Linear Regression achieving an R² of 0.051.

• Risk decision-making varies among individuals based on uncertain options and potential losses.
• Social jet lag and basic demographic or temporal variables were examined for their influence on risk decision-making.
• 407 responses from participants aged 17-23 years were analyzed using machine learning models.
• Linear Regression outperformed Random Forest and XGBoost, suggesting available variables did not enhance predictive accuracy.
• The findings indicate that a broader range of behavioral, emotional, and contextual data is needed for effective modeling.

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