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<p>In order to maintain the advancement of child protection, the active construction of Children’s Homes has become a significant undertaking at the grassroots level of Chinese governance. This study aims to identify the drivers and their interactions that influence the Indoor environmental quality of Children’s Homes in Xi’an from a child-centric perspective. To this end, physical environment measurements and questionnaires were employed to collect quantitative data, and Random forest and Bayesian hyperparameter optimisation algorithms were used to quantify the relative importance ranking of the drivers and their interaction effects. The results demonstrate that the four drivers with the largest contribution are Interior decoration satisfaction, Color satisfaction, Usage requirements satisfaction, and Desk satisfaction. Additionally, the driver under different output labels exhibits varying contributions. Color satisfaction has the largest contribution when the output label is dissatisfaction, while Interior decoration satisfaction has the largest contribution when the output label is satisfaction. Furthermore, there are significant interactions between most of the drivers. The interaction is significantly stronger when the output label is satisfaction than when the output label is dissatisfaction. The present study offers quantitative recommendations for the construction of child-friendly Children’s Homes, which will contribute to the enhancement of the child welfare system.</p>

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The Driving Factors and Interactions Affecting the Prediction of Indoor Environmental Quality Satisfaction in Children’s Homes

  • 期刊论文

  • 发表日期：

    2025年4月16日

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  • Sisi Liu,
  • Jingyuan Zhao,
  • Ruixin Ji

摘要

In order to maintain the advancement of child protection, the active construction of Children’s Homes has become a significant undertaking at the grassroots level of Chinese governance. This study aims to identify the drivers and their interactions that influence the Indoor environmental quality of Children’s Homes in Xi’an from a child-centric perspective. To this end, physical environment measurements and questionnaires were employed to collect quantitative data, and Random forest and Bayesian hyperparameter optimisation algorithms were used to quantify the relative importance ranking of the drivers and their interaction effects. The results demonstrate that the four drivers with the largest contribution are Interior decoration satisfaction, Color satisfaction, Usage requirements satisfaction, and Desk satisfaction. Additionally, the driver under different output labels exhibits varying contributions. Color satisfaction has the largest contribution when the output label is dissatisfaction, while Interior decoration satisfaction has the largest contribution when the output label is satisfaction. Furthermore, there are significant interactions between most of the drivers. The interaction is significantly stronger when the output label is satisfaction than when the output label is dissatisfaction. The present study offers quantitative recommendations for the construction of child-friendly Children’s Homes, which will contribute to the enhancement of the child welfare system.