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Context: Depression is among the most common mental health disorder in youth, results in significant impairment, and is associated with a higher risk of suicide. Screening is essential but assessment tools may not be appropriate across races or do not account for the complex interrelatedness of various demographics including gender, socio-economic status and race. Objectives: (1) To determine the factor structure of the Patient Health Questionnaire-Adolescent (PHQ-A) for measuring depression in a group of adolescent athletes; and (2) to determine measurement invariance between Blacks and Whites on the PHQ-A. Design: Retrospective cohort design. Setting: Data obtained from a secure database collected at a free, comprehensive, mass pre-participation physical exam (PPE) event hosted by a large health care system. Participants: Participants included 683 high school athletes (Black n=416; White n=267). Independent variables included somatic and affective factors contributing to the construct of depression measured by the PHQ-A and participant race (Black and White). Main Outcome Measures : (1) Factors upon which the construct of depression is measured and (2) measurement invariance between Blacks and Whites. Results: A two-factor model, including affective and somatic components, was specified and exhibited an adequate fit to the data (CFI&amp;gt; .90). All items exhibited moderate to high squared multiple correlation values (R2 = .10–.65), suggesting that these items resonated relatively well with participants. The two-factor model demonstrated noninvariance Black and White participants (RMSEA = .06-.08). Conclusions: Overall, the structure of the PHQ-A is supported by a two-factor model in adolescent athletes, measuring both affective and somatic symptoms of depression. A two factor PHQ-A structure is not fully invariant for the adolescents sampled across participant groups, implying that the model functions differently between Blacks and Whites sampled.

Factorial Validity and Invariance of an Adolescent Depression Symptom Screening Tool