Dual factor mental health model: Validation through mixture modeling and cut scores

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.