Objective: To achieve the grand challenge goal of unleashing the power of prevention, we must determine how and under what conditions an intervention leads to desired outcomes. These questions remain largely unknown partly due to analytical challenges involving testing mediation and moderation hypotheses with multiple dependent variables in nested data. This paper introduces multilevel structural equation modeling (MSEM) and demonstrates multilevel mediation and moderation analysis to understand the mechanisms by and contexts in which preventive interventions work. Method: Using illustrative research questions, we review the conceptual backgrounds of multilevel modeling and structural equation modeling and explain how MSEM combines these methods. We then analyze longitudinal data from a quasi-experimental study of a social and emotional learning program to examine how classroom teachers’ baseline social–emotional competence (SEC) relates to students’ year-end SEC, focusing on the mediation of instruction and the moderation of implementation leadership. Results: Teachers’ SEC was directly related to students’ year-end SEC (95% CI [.04, .95]) and indirectly related through the number of lessons delivered (95% CI [.01, .35]), controlling for students’ baseline SEC and grade level. When teachers reported more implementation leadership at baseline, however, teachers’ own SEC contributed less to the number of lessons they delivered (95% CI for interaction effect [−2.50, −.27]). MSEM techniques enabled examination of how teachers’ SEC relates to their implementation behaviors and, in turn, to students’ social and emotional development, and how these relationships are modified by implementation contexts. Conclusions: Identifying mechanisms and contexts in which students benefit from classroom-level interventions can help refine interventions and/or target implementation supports for taking preventive interventions to scale.

中文翻译：

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社会工作研究者的多层结构方程模型：健康青年发展的介绍和应用

目标：要实现释放预防力量的宏伟挑战，我们必须确定干预措施如何以及在何种条件下才能达到预期的结果。这些问题在很大程度上仍然未知，部分是由于涉及嵌套数据中具有多个因变量的测试中介和调节假设的分析难题。本文介绍了多级结构方程模型（MSEM），并演示了多级中介和调节分析，以了解预防性干预工作的机理和环境。方法：使用说明性研究问题，我们回顾了多级建模和结构方程建模的概念背景，并解释了MSEM如何结合这些方法。然后，我们对一项社会和情感学习计划的准实验研究的纵向数据进行分析，以检查课堂教师的基线社会情感能力（SEC）与学生的年终SEC之间的关系，重点是指导的中介和节制实施领导力。结果：教师的SEC与学生的年终SEC有直接关系（95％CI [.04，.95]），而与所授课数（95％CI [.01，.35]）有间接关系，用于学生的基本SEC和年级水平。但是，当教师报告说在基线时更多的实施领导力时，教师自己的SEC对他们交付的课程数量的贡献较少（互动效果的95％CI [-2.50，-。27]）。MSEM技术可以检查教师的SEC与他们的实施行为之间的关系，进而可以检查 影响学生的社交和情感发展，以及如何通过实施情境修改这些关系。结论：确定学生可以从课堂干预中受益的机制和背景可以帮助完善干预和/或目标实施支持，以扩大预防性干预的规模。