Sudden gains and patterns of symptom change in cognitive-behavioral therapy for treatment-resistant depression.
Journal
Journal of consulting and clinical psychology
ISSN: 1939-2117
Titre abrégé: J Consult Clin Psychol
Pays: United States
ID NLM: 0136553
Informations de publication
Date de publication:
Feb 2020
Feb 2020
Historique:
entrez:
3
1
2020
pubmed:
3
1
2020
medline:
31
3
2020
Statut:
ppublish
Résumé
The sudden gain (SG; large symptom improvements in one between-session interval) has been identified as a consistent predictor of better outcomes at posttreatment and over follow-up in cognitive-behavioral therapy (CBT) for depression. Other defined trajectories of symptom change in CBT, including linear (consistent changes in depression), log-linear (symptom change concentrated in early or late sessions), one-step (substantial change in depression symptoms between two adjacent sessions), and cubic (symptom decrease, increase, and decrease), also predict better treatment outcomes. We explored whether these patterns of symptom change occurred and predicted outcome in a sample of 156 adults with treatment-resistant depression who participated in a randomized controlled trial of CBT as an adjunct to pharmacotherapy (Wiles et al., 2013). Depression symptoms were assessed weekly with the Beck Depression Inventory-II. Multilevel modeling revealed that both SGs and having a defined trajectory predicted lower depression severity at 6- and 12-month follow-up, even controlling for baseline depression symptoms, early slopes of change, and symptom variability. These findings highlight the importance of examining longitudinal data and the robustness of the sudden gain pattern. They further suggest that having a defined symptom trajectory might confer its own advantages in predicting depression outcomes. Clinicians could use weekly depression scores to identify these key patterns of change to guide treatment decisions. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
Identifiants
pubmed: 31894993
pii: 2019-80727-001
doi: 10.1037/ccp0000467
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
106-118Subventions
Organisme : e National Institute for Health Research Health Technology Assessment