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Phasic Versus Tonic Irritability and Associations with Family Accommodation Among Youth with Selective Mutism: A Latent Profile Analysis.

Gabrielle F FreitagStefany CoxeElise M CardinaleJami M FurrAileen HerreraJonathan S Comer
Published in: Research on child and adolescent psychopathology (2024)
Clinical presentations of selective mutism (SM) vary widely across affected youth. Although studies have explored general externalizing problems in youth with SM, research has not specifically examined patterns of irritability. Relatedly, research has not considered how affected families differentially accommodate the anxiety of youth with SM as a function of the child's temper outbursts (i.e., phasic irritability) and general angry mood (i.e., tonic irritability). Data were drawn from a sample of treatment-seeking children and adolescents with a primary diagnosis of selective mutism (N = 152; Mean age = 6.12 years; 67.11% female), and their caregivers. Latent profile analysis (LPA) was used to identify distinct profiles in SM youth that were characterized by varying levels of phasic and/or tonic irritability. Analyses further examined whether these different profiles were associated with different levels of family accommodation and global impairment. LPA identified 5 profiles: SM with No irritability, SM with Low Phasic Irritability, SM with High Phasic Irritability, SM with High Phasic and Moderate Tonic Irritability, and SM with High Phasic and High Tonic Irritability. Patterns of family accommodation and global impairment were highest among youth belonging to profiles characterized by high phasic irritability. Findings highlight separable patterns of irritability across youth with SM, with phasic irritability (i.e., temper outbursts) appearing particularly linked with increased family accommodation and overall global impairment. Assessing phasic irritability is critical for optimizing treatment in youth with SM and can be useful for flagging possible patterns of family accommodation contributing to overall impairment.
Keyphrases
  • mental health
  • physical activity
  • young adults
  • palliative care
  • depressive symptoms
  • artificial intelligence
  • bipolar disorder
  • big data
  • deep learning
  • sleep quality