Subtypes Versus Severity Differences in Attention-Deficit/Hyperactivity Disorder in the Northern Finnish Birth Cohort

University of Notre Dame, Notre Dame, IN, USA.
Journal of the American Academy of Child & Adolescent Psychiatry (Impact Factor: 7.26). 01/2008; 46(12):1584-93. DOI: 10.1097/chi.0b013e31815750dd
Source: PubMed


To investigate whether behaviors of inattention, hyperactivity, and impulsivity among adolescents in Northern Finland reflect qualitatively distinct subtypes of ADHD, variants along a single continuum of severity, or of severity differences within subtypes.
Latent class models, exploratory factor models, and factor mixture models were applied to questionnaire data of ADHD behaviors obtained from the Northern Finland Birth Cohort (NFBC). Latent class models correspond to qualitatively distinct subtypes, factor analysis corresponds to severity differences, and factor mixture analysis allows for both subtypes and severity differences within subtypes.
A comparison of the different models shows that models that distinguish between a low scoring majority class (unaffecteds) and a high scoring minority class (affecteds), and allow for two factors (inattentive, hyperactive-impulsive) with severity differences provide the best fit.
The analysis provides support that a high-scoring minority group (8.8% of males and 6.8% of females) likely reflects an ADHD group in the Northern Finland Birth Cohort, whereas the majority of the population falls into a low-scoring group of unaffecteds. Distinct factors composed of items of inattention and hyperactivity-impulsivity are evident for both sexes with considerable variability in severity within each class.

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    • "In the current study we will explore whether factor mixture modelling (FMM), a relatively new and promising technique, which combines aspects of LCA and FA (Lubke and Muthén, 2005; Clark et al., 2013), is more suitable to describe both differences in symptom categories and in depression severity in the general population. FMM has already been shown to be successful in describing the underlying psychopathology of other mental disorders, such as attention-deficit/hyperactivity disorder (Lubke et al., 2007), panic disorder (Roberson-Nay and Kendler, 2011) and alcohol use disorder (Jackson et al., 2014), and of major depression in a treatment seeking clinical population (Sunderland et al., 2013). Some studies described in Appendix A that tried to validate the distinct subtypes of depression by examining their demographic and clinical correlates found indications for differential, potential aetiological mechanisms. "
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    • "One should also be clear whether the major goal of using FMM is to model nonnormality in an otherwise fairly conventional latent trait structure (i.e., factor mixture models that enforce strict invariance) or whether one is more interested in modeling latent subgroups that differ in qualitatively interesting ways, such as factor loadings (Masyn et al., 2010). Some of the most informative applications of FMMs to date have compared models that reflect plausible competing conceptions about the latent structure of psychopathology and that draw directly on prior theory (e.g., Lubke et al., 2007; Shevlin & Elklit, 2012). "
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    • "Finally, we examined correlations between parent and child cognitive performance across three different levels of attention symptoms. Previous work has suggested nonlinear relationships between symptoms and behavior (Lubke et al. 2007). Children's scores on the attention survey were broken into three equal-sized groups. "
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