PTSD, depression, and treatment outcomes: A latent profile analysis among active duty personnel in a residential PTSD program

Journal of Psychiatric Research(2024)

引用 0|浏览1
暂无评分
摘要
Depression frequently co-occurs with posttraumatic stress disorder (PTSD), including among active duty service members. However, symptom heterogeneity of this comorbidity is complex and its association with treatment outcomes is poorly understood, particularly among active duty service members in residential treatment. This study used latent profile analysis (LPA) to identify symptom-based subgroups of PTSD and depression among 282 male service members in a 10-week, residential PTSD treatment program with evidence-based PTSD psychotherapies and adjunctive interventions. The PTSD Checklist–Military Version and Patient Health Questionnaire-8 were completed by service members at pre- and posttreatment and weekly during treatment. Multilevel models compared subgroups on PTSD and depression symptom change across treatment. LPA indicated four subgroups provided optimal fit: Depressive (high depression severity, low PTSD avoidance; n = 33, 11.7%), Avoidant (high PTSD avoidance, moderate depression severity; n = 89, 31.6%), Moderate (moderate PTSD and depression severity; n = 27, 9.6%), and Distressed (high PTSD and depression severity; n = 133, 47.2%). Treatment response differed across classes for both PTSD and depression outcomes (time × LPA class interaction ps < 0.001). In PTSD models, post-hoc comparisons indicated the Moderate class was associated with less PTSD symptom improvement relative to the other classes (ps < 0.006). In depression models, symptom reduction was greatest for the Distressed and Depressive subgroups relative to the other two classes (ps < 0.009). Study results provide an initial model for two prevalent, impairing disorders among service members and show how these symptom-based subgroups may differentially respond to residential PTSD treatment.
更多
查看译文
关键词
Military,Residential treatment,Comorbidity,Treatment outcome,Mixture modeling
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要