Date of Award

2025

Document Type

Dissertation

Degree Name

Psychology (Ph.D.)

Department

Psychology

First Advisor

Imad Zaheer

Second Advisor

Melissa Peckins

Third Advisor

Lauren Moskowitz

Abstract

The Dual Factor Model (DFM) of mental health conceptualizes well-being and psychopathology as distinct but interrelated constructs. Unlike traditional models that focus solely on psychopathology, the DFM incorporates positive attributes such as subjective well-being, allowing for a more meaningful classification of students (Greenspoon & Falkofske, 2001; Suldo & Shaffer, 2008). Despite its increasing use in school-based research, prior studies have lacked intention in informant selection when assessing internalizing and externalizing behaviors, leading to variability in DFM construction. Given known discrepancies among self, teacher, and parent reports in mental health assessment, informant choice may significantly impact classification and predictive validity (De Los Reyes et al., 2015; Genachowski et al., 2022). However, no study has systematically compared different informant-based DFMs to determine which configurations provide the strongest predictive validity. This study analyzed a subsample of a large retrospective dataset from the Center for Adolescents Research in Schools (CAR; Kern et al., 2011), including 242 adolescents (ages 13–17). Participants were classified into DFM categories based on subjective well-being (Brief Multidimensional Students' Life Satisfaction Scale; BMLSS) and internalizing and externalizing behaviors (Behavior Assessment System for Children, Second Edition; BASC-2). This study compared six different informant iterations of the DFM and its predicative validity of anxiety, depression, and academic outcomes. Anxiety and depression symptoms were assessed using the Multidimensional Anxiety Scale for Children (MASC) and the Reynolds Adolescent Depression Scale-2 (RADS-2), while academic outcomes were measured with the Woodcock-Johnson III Tests of Achievement. Results indicated that while DFM category distribution remained stable across models, predictive validity varied. A self-report-based model (Model 3) demonstrated the strongest predictive validity for anxiety and depression. While academic outcomes lacked strong predicative validity with DFM categories across all models. These results support the need for empirical justification in DFM construction and suggest that school-based mental health assessments should consider informant selection. Future research should explore the longitudinal stability of DFM classifications, examine the role of subjective well-being in mental health trajectories, and assess the model’s utility in guiding targeted interventions for at-risk adolescents.

Download

Included in

Psychology Commons

Share

COinS