The Factor Structure and Gender Invariance of ADHD Symptoms in College Students

Abstract

Previous studies examining the factor structure of attention-deficit/hyperactivity disorder (ADHD) symptoms in adults using self-report measures have shown mixed results, supporting two-, three-, and bifactor solutions. The current study further investigated the structure of ADHD symptoms in adults using the Current Symptoms Scale and rigorous model evaluation in a sample of 892 college students. Confirmatory factor analysis was used to analyze and compare five-factor structures; a single-factor model, a two-factor model, a three-factor model, and two bifactor models. A single-factor model with correlated residuals best fit the data. Factor correlations with nearly all related constructs (i.e., symptoms of oppositional defiant disorder, depression, impairment, previous ADHD diagnosis, grades, and substance use) were significant in the expected directions and the model was invariant across gender. These findings contribute to a growing body of work suggesting a unidimensional factor may best represent ADHD symptoms in adults. Implications are discussed.

Factor structure, measurement invariance, and scoring practices of the strengths and weaknesses of ADHD–symptoms and normal behavior.

“…The relevance of this unidimensional construct is that it embeds the items of both dimensions with their respective weights, allowing a more appropriate and comprehensive interpretation of the SWAN. This unitary construct, according to Flory et al (2021), is not novel from the unidimensional ADHD Barkley's proposal (Barkley, 1997). Also, according to Toplak et al (2009) and Normand et al (2012), the general factor follows an integral idea of symptoms which overlap and interact with the ADHD pathways (Sonuga- Barke et al, 2008).…”

Revisiting the Effect of Varying the Number of Response Alternatives in Clinical Assessment: Evidence From Measuring ADHD Symptoms

“…Given that the number of response categories was small (i.e., less than 5), ordinal factor analyses were conducted using the diagonally weighted least square estimation method, which is the default estimator in Mplus (Muthén & Muthén, 1998. 3 Based on findings in a previous study examining the factor structure of ADHD (Flory et al, 2020), we adopted a one-factor model with correlated residuals among three items (i.e., "fidgets with hands," "shifted around excessively," and "acts as if driven by motor"). 4 The same ordinal factor analysis model was fitted to data with three different response formats.…”