Clusters Based on Within-Treatment Symptom Trajectories as Predictors of Dropout in Treatment for Posttraumatic Stress Disorder and Substance Use Disorder

Elizabeth Alpert, Adam Kaplan, David Nelson, David W. Oslin, Melissa A. Polusny, Erin P. Ingram, Shannon M. Kehle-Forbes

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Dropout rates are high in treatments for co-occurring posttraumatic stress disorder (PTSD) and substance use disorders (SUDs). We examined dropout predictors in PTSD-SUD treatment. Methods: Participants were 183 veterans receiving integrated or phased motivational enhancement therapy and prolonged exposure. Using survival models, we examined demographics and symptom trajectories as dropout predictors. Using latent trajectory analysis, we incorporated clusters based on symptom trajectories to improve dropout prediction. Results: Hispanic ethnicity (integrated arm), Black or African American race (phased arm), and younger age (phased arm) predicted dropout. Clusters based on PTSD and substance use trajectories improved dropout prediction. In integrated treatment, participants with consistently-high use and low-and-improving use had the highest dropout. In phased treatment, participants with the highest and lowest PTSD symptoms had lower dropout; participants with the lowest substance use had higher dropout. Conclusions: Identifying within-treatment symptom trajectories associated with dropout can help clinicians intervene to maximize outcomes. ClinicalTrials.gov Identifier: NCT01211106.

Original languageEnglish (US)
JournalJournal of Dual Diagnosis
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
©, This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.

Keywords

  • Posttraumatic stress disorder
  • bayesian statistics
  • dropout
  • latent trajectory analysis
  • substance use disorder
  • therapy process

PubMed: MeSH publication types

  • Journal Article

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