Journal of psychiatric research · 2017
A latent class analysis of PTSD symptoms among inner city primary care patients.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Rahman Akm Fazlur, Manatunga Amita, Guo Ying, Peng Limin, Warnock Megan, Ressler Kerry J, Jovanovic Tanja
Аннотация
OBJECTIVES: Examine evidence for different subclasses of posttraumatic stress disorder (PTSD) symptoms in a sample of trauma exposed, low-income, predominantly African American men and women. Assess the relationship between PTSD subclasses with major depressive disorder (MDD) and types of trauma experienced.
METHOD: Latent class analysis (LCA) using a multivariate normal mixture model on the 17-item PTSD Symptom Scale (PSS) was used to identify latent subclasses of PTSD symptoms (N = 5063).
RESULTS: LCA suggested four subclasses of PTSD symptoms: (1) High severity and comorbidity (n = 932, 92.2% current PTSD, 88.7% MDD, 82% both), characterized by high PTSD symptoms, depression, and comorbidity of PTSD and MDD; (2) Moderate severity (n = 1179, 56.5% current PTSD, 53.9% MDD, 34.5% both), which had high avoidance and hyper-vigilance symptoms compared to the other symptoms; (3) Low PTSD and high depression (n = 657, 12.8% current PTSD, 49.9% MDD, 8.8% both) which had high insomnia but otherwise low PTSD symptoms and high depression; and (4) Resilient (n = 2295, 2.0% current PTSD, 16.4% MDD, and 0.6% both) characterized by low mean scores on all PTSD symptoms and depression.
CONCLUSIONS: The results suggest avoidance and hyper-vigilance are important symptoms in PTSD development and insomnia may be an important indicator for depression. The combination of severe insomnia, avoidance, and hyper-vigilance may be key symptoms for comorbidity of PTSD and MDD. Future studies should focus on these symptoms to better target people at high risk for developing PTSD or MDD.
METHOD: Latent class analysis (LCA) using a multivariate normal mixture model on the 17-item PTSD Symptom Scale (PSS) was used to identify latent subclasses of PTSD symptoms (N = 5063).
RESULTS: LCA suggested four subclasses of PTSD symptoms: (1) High severity and comorbidity (n = 932, 92.2% current PTSD, 88.7% MDD, 82% both), characterized by high PTSD symptoms, depression, and comorbidity of PTSD and MDD; (2) Moderate severity (n = 1179, 56.5% current PTSD, 53.9% MDD, 34.5% both), which had high avoidance and hyper-vigilance symptoms compared to the other symptoms; (3) Low PTSD and high depression (n = 657, 12.8% current PTSD, 49.9% MDD, 8.8% both) which had high insomnia but otherwise low PTSD symptoms and high depression; and (4) Resilient (n = 2295, 2.0% current PTSD, 16.4% MDD, and 0.6% both) characterized by low mean scores on all PTSD symptoms and depression.
CONCLUSIONS: The results suggest avoidance and hyper-vigilance are important symptoms in PTSD development and insomnia may be an important indicator for depression. The combination of severe insomnia, avoidance, and hyper-vigilance may be key symptoms for comorbidity of PTSD and MDD. Future studies should focus on these symptoms to better target people at high risk for developing PTSD or MDD.
Предметные рубрики MeSH
AdolescentAdultBlack or African AmericanAgedAnxietyAvoidance LearningComorbidityMajor Depressive DisorderFemaleGeorgiaHumansLatent Class AnalysisMaleMiddle AgedPsychological TraumaSeverity of Illness IndexSleep Initiation and Maintenance DisordersStress Disorders, Post-TraumaticUrban PopulationYoung Adult