Objective: Aggression with impulsivity and reactivity (AIR) may distinguish a subset of youth from those with attention problems, rule-breaking behavior, or mood disorders, potentially with differential treatment response. Yet, DSM-5 and ICD-10 do not include an AIR diagnosis. Thus, we empirically grouped youths into profiles based on AIR, manic, depressive, rule-breaking, and self-harm behaviors; examined which profiles replicated across three samples; and characterized profile sets on demographic and clinical features.Method: After harmonizing data from three samples (n = 679, n = 392, n = 634), Latent Profile Analysis (LPA) assigned youth to profiles based on caregiver-reported measures of AIR, manic, depressive, rule-breaking, and self-harm behaviors. Profiles from each sample were grouped into sets based on profile similarity. Analyses tested differences in diagnoses, sex, and race, age, functioning, and mood severity. Results: Eight-profile solutions fit best. Seven profiles replicated across samples: high AIR and self-harm, lower depressive and manic scores; high AIR, manic symptoms, and self-harm; high depression symptoms; three smaller sets with high manic and depressive symptoms and moderate AIR; and two high rates of bipolar diagnoses and family bipolar history. Two sets were high on both AIR and mood symptoms, were the most impaired, and had the highest comorbidity.Conclusions: Analyses support an empirical definition of AIR, separate from mood disorders. Profile sets distinguished by level of AIR and mood symptoms differed in demographic and diagnostic characteristics as well as functioning. Importantly, a set emerged with high AIR but low mood indicators and with high rates of ADHD and ODD, but not mood disorder.
Objective: Aggression with impulsivity and reactivity (AIR) may distinguish a subset of youth from those with attention problems, rule-breaking behavior, or mood disorders, potentially with differential treatment response. Yet, DSM-5 and ICD-10 do not include an AIR diagnosis. Thus, we empirically grouped youths into profiles based on AIR, manic, depressive, rule-breaking, and self-harm behaviors; examined which profiles replicated across three samples; and characterized profile sets on demographic and clinical features.Method: After harmonizing data from three samples (n = 679, n = 392, n = 634), Latent Profile Analysis (LPA) assigned youth to profiles based on caregiver-reported measures of AIR, manic, depressive, rule-breaking, and self-harm behaviors. Profiles from each sample were grouped into sets based on profile similarity. Analyses tested differences in diagnoses, sex, and race, age, functioning, and mood severity. Results: Eight-profile solutions fit best. Seven profiles replicated across samples: high AIR and self-harm, lower depressive and manic scores; high AIR, manic symptoms, and self-harm; high depression symptoms; three smaller sets with high manic and depressive symptoms and moderate AIR; and two high rates of bipolar diagnoses and family bipolar history. Two sets were high on both AIR and mood symptoms, were the most impaired, and had the highest comorbidity.Conclusions: Analyses support an empirical definition of AIR, separate from mood disorders. Profile sets distinguished by level of AIR and mood symptoms differed in demographic and diagnostic characteristics as well as functioning. Importantly, a set emerged with high AIR but low mood indicators and with high rates of ADHD and ODD, but not mood disorder.
Authors: Andrea S Young; Eric A Youngstrom; Robert L Findling; Kathryn Van Eck; Dana Kaplin; Jennifer K Youngstrom; Joseph Calabrese; Ekaterina Stepanova Journal: J Clin Child Adolesc Psychol Date: 2019-07-25
Authors: Eric Youngstrom; Oren Meyers; Christine Demeter; Jen Youngstrom; Laura Morello; Richard Piiparinen; Norah Feeny; Joseph R Calabrese; Robert L Findling Journal: Bipolar Disord Date: 2005-12 Impact factor: 6.744