Revisiting the latent structure of ADHD: is there a 'g' factor?

J Child Psychol Psychiatry. 2010 Aug;51(8):905-14. doi: 10.1111/j.1469-7610.2010.02232.x. Epub 2010 Mar 10.

Abstract

Background: Attention-deficit/hyperactivity disorder (ADHD) is presumed to be heterogeneous, but the best way to describe this heterogeneity remains unclear. Considerable evidence has accrued suggesting that inattention versus hyperactivity-impulsivity symptom domains predict distinct clinical outcomes and may have partially distinct etiological influence. As a result, some conceptualizations emphasize two distinct inputs to the syndrome. Yet formal testing of models that would accommodate such assumptions using modern methods (e.g., second-order factor and bifactor models) has been largely lacking.

Methods: Participants were 548 children (321 boys) between the ages of 6 and 18 years. Of these 548 children, 302 children met DSM-IV criteria for ADHD, 199 were typically developing controls without ADHD, and 47 were classified as having situational or subthreshold ADHD. ADHD symptoms were assessed via parent report on a diagnostic interview and via parent and teacher report on the ADHD Rating Scale.

Results: A bifactor model with a general factor and specific factors of inattention and hyperactivity-impulsivity fit best when compared with one-, two-, and three-factor models, and a second-order factor model.

Conclusions: A bifactor model of ADHD latent symptom structure is superior to existing factor models of ADHD. This finding is interpreted in relation to multi-component models of ADHD development, and clinical implications are discussed.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Attention Deficit Disorder with Hyperactivity / classification
  • Attention Deficit Disorder with Hyperactivity / diagnosis*
  • Attention Deficit Disorder with Hyperactivity / etiology
  • Attention Deficit Disorder with Hyperactivity / psychology
  • Child
  • Diagnostic and Statistical Manual of Mental Disorders
  • Female
  • Humans
  • Male
  • Models, Psychological*
  • Personality Assessment / statistics & numerical data
  • Prognosis
  • Psychometrics