Lenferink Lonneke I M, de Keijser Jos, Smid Geert E, Djelantik A A A Manik J, Boelen Paul A
Department of Clinical Psychology and Experimental Psychopathology, Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, the Netherlands.
Department of Clinical Psychology, Faculty of Social Sciences, Utrecht University, Utrecht, the Netherlands.
Eur J Psychotraumatol. 2017 Mar 10;8(1):1298311. doi: 10.1080/20008198.2017.1298311. eCollection 2017.
: Hundreds of individuals lost one or more significant others in the MH17 plane crash in 2014 in Ukraine. The current study is the first to explore subgroups of disaster-bereaved individuals based on presence of psychopathology clusters. This may inform the development of diagnostic instruments and tailored interventions. : Aims of the current study were to examine (1) subgroups based on presence of prolonged grief disorder (PGD), major depressive disorder (MDD), and posttraumatic stress disorder (PTSD) symptom clusters and (2) associations between class membership, disaster-related variables (i.e. experiencing multiple losses, conducting multiple burials for the same deceased, and time to confirmation of death), and a sense of unrealness. : Self-rated PGD (10 items of the Traumatic Grief Inventory represented in two symptom clusters), MDD (16-item Quick Inventory Of Depressive Symptomatology represented in one symptom cluster), and PTSD (20-item PTSD Checklist for DSM-5 represented in four symptom clusters) from 167 participants were subjected to latent class analysis to identify subgroups (i.e. classes). Correlates of class membership were assessed using the three-step approach. : A three-class solution yielded the best model fit. Class 1 (Resilient class; 20.0%) was predominantly characterized by low probability of PGD, MDD, and PTSD symptom clusters, class 2 (PGD class; 41.8%) by moderate to high probability of presence of PGD, and class 3 (Combined class; 38.2%) by moderate to high probability of presence of PGD, MDD, and PTSD symptom clusters. Compared with the Resilient class, a sense of unrealness was more likely to be experienced by individuals in the PGD class and the Combined class. : Our results indicate that subgroups of disaster-bereaved individuals can be distinguished based on the presence of PGD, MDD, and PTSD symptom clusters. A sense of unrealness was the strongest distinguishing feature of the subgroups.
2014年在乌克兰发生的马航MH17客机坠毁事件中，数百人失去了一位或多位重要亲人。当前这项研究首次基于精神病理学集群的存在情况，对灾难丧亲个体的亚组进行了探索。这可能为诊断工具的开发和针对性干预提供信息。：本研究的目的是检验：（1）基于持续性悲伤障碍（PGD）、重度抑郁症（MDD）和创伤后应激障碍（PTSD）症状集群存在情况的亚组；（2）类别归属、与灾难相关的变量（即经历多重损失、为同一逝者进行多次葬礼以及确认死亡的时间）和不真实感之间的关联。：对167名参与者的自我评定PGD（创伤性悲伤量表的10个项目，分为两个症状集群）、MDD（16项抑郁症状快速检查表，分为一个症状集群）和PTSD（用于《精神疾病诊断与统计手册》第5版的20项PTSD检查表，分为四个症状集群）进行潜在类别分析，以识别亚组（即类别）。使用三步法评估类别归属的相关因素。：一个三类解决方案产生了最佳模型拟合。第1类（适应良好类；20.0%）的主要特征是PGD、MDD和PTSD症状集群出现的概率较低，第2类（PGD类；41.8%）的主要特征是PGD出现的概率为中度至高概率，第3类（合并类；38.2%）的主要特征是PGD、MDD和PTSD症状集群出现的概率为中度至高概率。与适应良好类相比，PGD类和合并类的个体更有可能体验到不真实感。：我们的结果表明，可根据PGD、MDD和PTSD症状集群的存在情况区分灾难丧亲个体的亚组。不真实感是这些亚组最显著的区别特征。
