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Adolescent Emotion Network Dynamics in Daily Life and Implications for Depression.

David M Lydon-StaleyM XiaH W MakG M Fosco
Published in: Journal of abnormal child psychology (2020)
Emotion network density describes the degree of interdependence among emotion states across time. Higher density is theorized to reflect rigidity in emotion functioning and has been associated with depression in adult samples. This paper extended research on emotion networks to adolescents and examined associations between emotion network density and: 1) emotion regulation and 2) symptoms of depression. Data from a daily diary study (t = 21 days) of adolescents (N = 151; 61.59% female; mean age = 14.60 years) were used to construct emotion network density scores. Emotion regulation was measured using The Difficulties in Emotion Regulation Scale Short Form (DERS-SF). Depression was measured using the Revised Child Anxiety and Depression Scale-Short Version (RCADS-SV). Associations between emotion network density and DERS-SF were examined through Pearson correlations. Multiple regression analyses examined associations between emotion network density and depression. Emotion network density was not associated with the DERS-SF. Follow-up analyses showed that it was positively associated with non-acceptance of emotions (a subscale of the DERS-SF). Emotion network density was positively associated with RCADS-SV depression. Non-acceptance of emotions may encourage the spread of emotion across time and states given that a feature of non-acceptance is to have secondary emotional responses to one's emotions. Emotion networks that are self-predictive may be a risk factor for adolescent depression.
Keyphrases
  • deep learning
  • depressive symptoms
  • autism spectrum disorder
  • borderline personality disorder
  • sleep quality
  • machine learning
  • young adults
  • mental health