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
{"title":"Clusters Based on Within-Treatment Symptom Trajectories as Predictors of Dropout in Treatment for Posttraumatic Stress Disorder and Substance Use Disorder.","authors":"Elizabeth Alpert, Adam Kaplan, David Nelson, David W Oslin, Melissa A Polusny, Erin P Ingram, Shannon M Kehle-Forbes","doi":"10.1080/15504263.2024.2355953","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objective:</b> 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. <b>Methods:</b> 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. <b>Results:</b> 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. <b>Conclusions:</b> Identifying within-treatment symptom trajectories associated with dropout can help clinicians intervene to maximize outcomes. ClinicalTrials.gov Identifier: NCT01211106.</p>","PeriodicalId":46571,"journal":{"name":"Journal of Dual Diagnosis","volume":" ","pages":"1-21"},"PeriodicalIF":1.5000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Dual Diagnosis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/15504263.2024.2355953","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Journal of Dual Diagnosis is a quarterly, international publication that focuses on the full spectrum of complexities regarding dual diagnosis. The co-occurrence of mental health and substance use disorders, or “dual diagnosis,” is one of the quintessential issues in behavioral health. Why do such high rates of co-occurrence exist? What does it tell us about risk profiles? How do these linked disorders affect people, their families, and the communities in which they live? What are the natural paths to recovery? What specific treatments are most helpful and how can new ones be developed? How can we enhance the implementation of evidence-based practices at clinical, administrative, and policy levels? How can we help clients to learn active recovery skills and adopt needed supports, clinicians to master new interventions, programs to implement effective services, and communities to foster healthy adjustment? The Journal addresses each of these perplexing challenges.