Using machine learning to predict sudden gains in intensive treatment for PTSD.
Machine learning
Massed treatment
PTSD
Predictors
Sudden gains
Treatment outcomes
Veterans
Journal
Journal of anxiety disorders
ISSN: 1873-7897
Titre abrégé: J Anxiety Disord
Pays: Netherlands
ID NLM: 8710131
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
28
10
2022
revised:
12
09
2023
accepted:
06
10
2023
pubmed:
24
10
2023
medline:
24
10
2023
entrez:
23
10
2023
Statut:
ppublish
Résumé
Sudden gains have been found in PTSD treatment across samples and treatment modality. Sudden gains have consistently predicted better treatment response, illustrating clear clinical implications, though attempts to identify predictors of sudden gains have produced inconsistent findings. To date, sudden gains have not been examined in intensive PTSD treatment programs (ITPs). This study explored the occurrence of sudden gains in a 3-week and 2-week ITP (n = 465 and n = 235), evaluated the effect of sudden gains on post-treatment and follow-up PTSD severity while controlling for overall change, and used three machine learning algorithms to assess our ability to predict sudden gains. We found 31% and 19% of our respective samples experienced a sudden gain during the ITP. In both ITPs, sudden gain status predicted greater PTSD symptom improvement at post-treatment (t
Identifiants
pubmed: 37871453
pii: S0887-6185(23)00121-4
doi: 10.1016/j.janxdis.2023.102783
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
102783Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors have no known conflicts of interest to disclose.