Details

Autor(en) / Beteiligte

• Kuranova, Anna
• Wigman, Johanna T W
• Menne-Lothmann, Claudia
• Decoster, Jeroen
• van Winkel, Ruud
• Delespaul, Philippe
• Drukker, Marjan
• de Hert, Marc
• Derom, Catherine
• Thiery, Evert
• Rutten, Bart P F
• Jacobs, Nele
• van Os, Jim
• Oldehinkel, Albertine J
• Booij, Sanne H
• Wichers, Marieke
• Santana, Geilson Lima

Titel

Network dynamics of momentary affect states and future course of psychopathology in adolescents

Ist Teil von

• PloS one, 2021-03, Vol.16 (3), p.e0247458-e0247458

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2021

Quelle

EZB-FREE-00999 freely available EZB journals

Beschreibungen/Notizen

• Recent theories argue that an interplay between (i.e., network of) experiences, thoughts and affect in daily life may underlie the development of psychopathology. To prospectively examine whether network dynamics of everyday affect states are associated with a future course of psychopathology in adolescents at an increased risk of mental disorders. 159 adolescents from the East-Flanders Prospective Twin Study cohort participated in the study. At baseline, their momentary affect states were assessed using the Experience Sampling Method (ESM). The course of psychopathology was operationalized as the change in the Symptom Checklist-90 sum score after 1 year. Two groups were defined: one with a stable level (n = 81) and one with an increasing level (n = 78) of SCL-symptom severity. Group-level network dynamics of momentary positive and negative affect states were compared between groups. The group with increasing symptoms showed a stronger connections between negative affect states and their higher influence on positive states, as well as higher proneness to form 'vicious cycles', compared to the stable group. Based on permutation tests, these differences were not statistically significant. Although not statistically significant, some qualitative differences were observed between the networks of the two groups. More studies are needed to determine the value of momentary affect networks for predicting the course of psychopathology.