The dual‐factor model (DFM) of mental health affords educators an expanded view of student social–emotional and behavioral functioning and may help identify students in need of school‐based mental health services who would otherwise go unnoticed with traditional screening methods. With a focus on integrating subjective well‐being into the conceptualization of mental health, the DFM may be one paradigm to aid in supporting students. However, without greater clarity regarding accurate and feasible methods of measuring student functioning and grouping behaviors into the DFM, schools may not be able to utilize this strategy within broader multi‐tiered systems of support. As such, this study explores the stability of the DFM categories over the course of one school year and compares student grouping using theoretically‐informed cut‐score analysis and empirically informed mixture modeling. Results indicate that data may be best represented by different types of DFM latent groups over the course of one school year and may have little congruence with cut‐score methods of categorization. Implications for the utility of the DFM for providing a comprehensive picture of school‐wide mental health are discussed.

中文翻译：

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双因素心理健康模型：通过混合模型和得分降低进行验证

心理健康的双因素模型（DFM）为教育者提供了学生的社会情感和行为功能的扩展视图，并可以帮助确定需要学校心理健康服务的学生，否则他们将无法使用传统的筛查方法。DFM着重于将主观幸福感融入心理健康的概念中，可能是帮助学生的一种范例。但是，如果没有更准确地了解衡量学生功能和将行为分组为DFM的准确可行的方法，学校可能无法在更广泛的多层支持系统中使用该策略。因此，这项研究探索了一个学年中DFM类别的稳定性，并使用理论上有根据的切分分析和经验丰富的混合模型对学生分组进行了比较。结果表明，在一个学年的过程中，不同类型的DFM潜在群体可能最好地代表了数据，并且与得分高的分类方法几乎没有一致性。讨论了DFM实用程序对学校范围内心理健康状况的全面了解的含义。