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Research exploring the longitudinal course of posttraumatic stress disorder (PTSD) symptoms has documented four modal trajectories (low, remitting, high, and delayed), with proportions varying across studies. Heterogeneity could be due to differences in trauma types and patient demographic characteristics.
Methods
This analysis pooled data from six longitudinal studies of adult survivors of civilian-related injuries admitted to general hospital emergency departments (EDs) in six countries (pooled N = 3083). Each study included at least three assessments of the clinician-administered PTSD scale in the first post-trauma year. Latent class growth analysis determined the proportion of participants exhibiting various PTSD symptom trajectories within and across the datasets. Multinomial logistic regression analyses examined demographic characteristics, type of event leading to the injury, and trauma history as predictors of trajectories differentiated by their initial severity and course.
Results
Five trajectories were found across the datasets: Low (64.5%), Remitting (16.9%), Moderate (6.7%), High (6.5%), and Delayed (5.5%). Female gender, non-white race, prior interpersonal trauma, and assaultive injuries were associated with increased risk for initial PTSD reactions. Female gender and assaultive injuries were associated with risk for membership in the Delayed (v. Low) trajectory, and lower education, prior interpersonal trauma, and assaultive injuries with risk for membership in the High (v. Remitting) trajectory.
Conclusions
The results suggest that over 30% of civilian-related injury survivors admitted to EDs experience moderate-to-high levels of PTSD symptoms within the first post-trauma year, with those reporting assaultive violence at increased risk of both immediate and longer-term symptoms.
This study aimed to examine factors associated with receipt of post-disaster support from network (eg, family or friends) and non-network (eg, government agencies) sources.
Methods
Participants (n=409) were from a population-based sample of Hurricane Sandy survivors surveyed 25-28 months post-disaster. Survivors were asked to imagine a future disaster and indicate how much they would depend on network and non-network sources of support. In addition, they reported on demographic characteristics, disaster-related exposure, post-traumatic stress, and depression. Information on the economic and social resources in survivors’ communities was also collected.
Results
Multilevel multivariable regression models found that lack of insurance coverage and residence in a neighborhood wherein more persons lived alone were associated with survivors anticipating less network and non-network support. In addition, being married or cohabiting was significantly associated with more anticipated network support, whereas older age and having a high school education or less were significantly associated with less anticipated network support.
Conclusions
By having survivors anticipate a future disaster scenario, this study provides insight into predictors of post-disaster receipt of network and non-network support. Further research is needed to examine how these findings correspond to survivors’ received support in the aftermath of future disasters. (Disaster Med Public Health Preparedness. 2018;12:711-717)
We aimed to explore how individually experienced disaster-related stressors and collectively experienced community-level damage influenced perceived need for mental health services in the aftermath of Hurricane Sandy.
Methods
In a cross-sectional study we analyzed 418 adults who lived in the most affected areas of New York City at the time of the storm. Participants indicated whether they perceived a need for mental health services since the storm and reported on their exposure to disaster-related stressors (eg, displacement, property damage). We located participants in communities (n=293 census tracts) and gathered community-level demographic data through the US Census and data on the number of damaged buildings in each community from the Federal Emergency Management Agency Modeling Task Force.
Results
A total of 7.9% of participants reported mental health service need since the hurricane. Through multilevel binomial logistic regression analysis, we found a cross-level interaction (P=0.04) between individual-level exposure to disaster-related stressors and community-level building damage. Individual-level stressors were significantly predictive of individual service needs in communities with building damage (adjusted odds ratio: 2.56; 95% confidence interval: 1.58-4.16) and not in communities without damage.
Conclusion
Individuals who experienced individual stressors and who lived in more damaged communities were more likely to report need for services than were other persons after Hurricane Sandy. (Disaster Med Public Health Preparedness. 2016;10:428–435)
To demonstrate a spatial epidemiologic approach that could be used in the aftermath of disasters to (1) detect spatial clusters and (2) explore geographic heterogeneity in predictors for mental health and general wellness.
Methods
We used a cohort study of Hurricane Ike survivors (n=508) to assess the spatial distribution of postdisaster mental health wellness (most likely resilience trajectory for posttraumatic stress symptoms [PTSS] and depression) and general wellness (most likely resilience trajectory for PTSS, depression, functional impairment, and days of poor health) in Galveston, Texas. We applied the spatial scan statistic (SaTScan) and geographically weighted regression.
Results
We found spatial clusters of high likelihood wellness in areas north of Texas City and spatial concentrations of low likelihood wellness in Galveston Island. Geographic variation was found in predictors of wellness, showing increasing associations with both forms of wellness the closer respondents were located to Galveston City in Galveston Island.
Conclusions
Predictors for postdisaster wellness may manifest differently across geographic space with concentrations of lower likelihood wellness and increased associations with predictors in areas of higher exposure. Our approach could be used to inform geographically targeted interventions to promote mental health and general wellness in disaster-affected communities. (Disaster Med Public Health Preparedness. 2016;10:261–273)