睡眠质量作为儿童和青少年多发疾病行为网络中的潜在干预目标：一种机器学习和计算机模拟网络干预研究

With the transformation of lifestyles, the phenomenon of multimorbidity among children and adolescents has become increasingly severe. Therefore, identifying key behaviors and formulating precise, prioritized intervention strategies are vital for improving the situation of multimorbidity among children and adolescents. This study aims to explore this key issue from a multi-methodological perspective. A total of 10,182 children and adolescents were included. The random forest model in machine learning was utilized, and mean decrease in Gini were used to measure the importance of behaviors; a be