Psychological Resilience after Hurricane Sandy: the Influence of Individual- and Community-level Factors on Mental Health after a Llarge-scale Natural Disaster.

Several individual-level factors are known to promote psychological resilience in the aftermath of disasters. Far less is known about the role of community-level factors in shaping postdisaster mental health. The purpose of this study was to explore the influence of both individual- and community-level factors on resilience after Hurricane Sandy. A representative sample of household residents (N = 418) from 293 New York City census tracts that were most heavily affected by the storm completed telephone interviews approximately 13–16 months postdisaster. Multilevel multivariable models explored the independent and interactive contributions of individual- and community-level factors to posttraumatic stress and depression symptoms. At the individual-level, having experienced or witnessed any lifetime traumatic event was significantly associated with higher depression and posttraumatic stress, whereas demographic characteristics (e.g., older age, non-Hispanic Black race) and more disaster-related stressors were significantly associated with higher posttraumatic stress only. At the community-level, living in an area with higher social capital was significantly associated with higher posttraumatic stress. Additionally, higher community economic development was associated with lower risk of depression only among participants who did not experience any disaster-related stressors. These results provide evidence that individual- and community-level resources and exposure operate in tandem to shape postdisaster resilience

The geography of post-disaster mental health: spatial patterning of psychological vulnerability and resilience factors in New York City after Hurricane Sandy

Background: Only very few studies have investigated the geographic distribution of psychological resilience and associated mental health outcomes after natural or man made disasters. Such information is crucial for location-based interventions that aim to promote recovery in the aftermath of disasters. The purpose of this study therefore was to investigate geographic variability of (1) posttraumatic stress (PTS) and depression in a Hurricane Sandy affected population in NYC and (2) psychological vulnerability and resilience factors among affected areas in NYC boroughs. Methods: Cross-sectional telephone survey data were collected 13 to 16 months post-disaster from household residents (N = 418 adults) in NYC communities that were most heavily affected by the hurricane. The Posttraumatic Stress Checklist for DSM-5 (PCL-5) was applied for measuring posttraumatic stress and the nine-item Patient Health Questionnaire (PHQ-9) was used for measuring depression. We applied spatial autocorrelation and spatial regimes regression analyses, to test for spatial clusters of mental health outcomes and to explore whether associations between vulnerability and resilience factors and mental health differed among New York City\u27s five boroughs . Results: Mental health problems clustered predominantly in neighborhoods that are geographically more exposed towards the ocean indicating a spatial variation of risk within and across the boroughs. We further found significant variation in associations between vulnerability and resilience factors and mental health. Race/ethnicity (being Asian or non-Hispanic black) and disaster-related stressors were vulnerability factors for mental health symptoms in Queens, and being employed and married were resilience factors for these symptoms in Manhattan and Staten Island. In addition, parental status was a vulnerability factor in Brooklyn and a resilience factor in the Bronx. Conclusions: We conclude that explanatory characteristics may manifest as psychological vulnerability and resilience factors differently across different regional contexts. Our spatial epidemiological approach is transferable to other regions around the globe and, in the light of a changing climate, could be used to strengthen the psychosocial resources of demographic groups at greatest risk of adverse outcomes pre-disaster. In the aftermath of a disaster, the approach can be used to identify survivors at greatest risk and to plan for targeted interventions to reach them

Detecting suicide ideation in the era of social media: the population neuroscience perspective

Social media platforms are increasingly used across many population groups not only to communicate and consume information, but also to express symptoms of psychological distress and suicidal thoughts. The detection of suicidal ideation (SI) can contribute to suicide prevention. Twitter data suggesting SI have been associated with negative emotions (e.g., shame, sadness) and a number of geographical and ecological variables (e.g., geographic location, environmental stress). Other important research contributions on SI come from studies in neuroscience. To date, very few research studies have been conducted that combine different disciplines (epidemiology, health geography, neurosciences, psychology, and social media big data science), to build innovative research directions on this topic. This article aims to offer a new interdisciplinary perspective, that is, a Population Neuroscience perspective on SI in order to highlight new ways in which multiple scientific fields interact to successfully investigate emotions and stress in social media to detect SI in the population. We argue that a Population Neuroscience perspective may help to better understand the mechanisms underpinning SI and to promote more effective strategies to prevent suicide timely and at scale

Item Ordering and Computerized Classification Tests With Cluster-Based Scoring: An Investigation of the Countdown Method

The countdown method is a well-known approach to reducing the average length of screening instruments that are presented by computer. In the countdown method, testing is terminated once the result of the screener (“positive” or “negative”) has been unambiguously determined from prior answers. Previous research has examined whether presenting dichotomously scored items in order from “least to most frequently endorsed” or “most to least frequently endorsed” is more efficient when the countdown method is used. The current study describes the Mean Score procedure, an extension of the above item ordering procedures to polytomously scored items, and evaluates its efficiency relative to the distribution of other possible item orderings in 2 real-data simulations. Both simulations involve item responses to the Posttraumatic Stress Disorder (PTSD) Checklist for DSM–5 (PCL-5). In the first simulation, items were scored polytomously, and a single cutoff point was used to determine the screening result. In the second simulation, items were converted to dichotomous scores, as well as categorized into 4 clusters; a positive result for the entire assessment was obtained if and only if a positive result was obtained for each cluster. The latter simulation also investigated the effect of reordering the clusters themselves on the efficiency of the countdown method. Results indicated that the Mean Score procedure does not necessarily produce the optimal ordering, but tends to assemble an efficient item ordering relative to the distribution of possible orderings. In the second simulation, reordering the clusters themselves affected efficiency. Future research directions are suggested

Customized computer-based administration of the PCL-5 for the efficient assessment of PTSD:A proof-of-principle study

Objective: To investigate the potential of customized computer-based testing procedures to reduce the mean test length of the Posttraumatic Stress Checklist for DSM-5 (PCL-5). Method: A retrospective analysis was conducted using responses from 942 adults who had completed the full-length (20-item) PCL-5 in the aftermath of Hurricane Sandy. The abilities of 2 testing procedures, curtailment and stochastic curtailment, to lessen the instrument's mean test length while maintaining the same result as the full-length PCL-5 ("positive" or "negative") were evaluated in a post hoc simulation. Curtailment and stochastic curtailment track a respondent's answers as she takes the instrument and stop the test if future items are unable or unlikely to change the result. The performance of each procedure was recorded under 2 scoring methods: a total-score-based method and a cluster-based method. Each procedure's sensitivity, specificity, and overall agreement with the full-length PCL-5 were computed. Results: Curtailment reduced the mean test length by 40% under the total-score-based method, and by more than 70% under the cluster-based method, while exhibiting 100% sensitivity, specificity, and overall agreement with the full-length PCL-5. Stochastic curtailment reduced the mean test length by up to 88% under the total-score-based method, and up to 84% under the cluster-based method, while always exhibiting at least 92% sensitivity and 99.8% overall agreement, as well as 100% specificity, for the full-length PCL-5. Conclusions: Curtailment and stochastic curtailment have potential to enhance the efficiency of the PCL-5 when this assessment is administered by computer. The 2 procedures should be evaluated in future prospective studies. (PsycINFO Database Recor

Single-acetylene linked porphyrin nanorings

The synthesis of ethyne-linked porphyrin nanorings has been achieved by template-directed Sonogashira coupling. The cyclic hexamer and octamer are predicted by DFT to adopt low symmetry conformations, due to dihedral twists between neighboring porphyrin units, but their symmetries are effectively D6h and D8h, respectively, in solution by 1H NMR. The fluorescence spectra indicate that the singlet excited states of these nanorings are highly delocalized

Place of Residence Moderates the Risk of Infant Death in Kenya: Evidence from the Most Recent Census 2009

Background Substantial progress has been made in reducing childhood mortality worldwide from 1990–2015 (Millennium Development Goal, target 4). Achieving target goals on this however remains a challenge in Sub-Saharan Africa. Kenya’s infant mortality rates are higher than the global average and are more pronounced in urban areas as compared to rural areas. Only limited knowledge exists about the differences in individual level risk factors for infant death among rural, non-slum urban, and slum areas in Kenya. Therefore, this paper aims at 1) assess individual and socio-ecological risk factors for infant death in Kenya, and at 2) identify whether living in rural, non-slum urban, or slum areas moderated individual or socio-ecological risk factors for infant death in Kenya. Methodology We used a cross-sectional study design based on the most recent Kenya Population and Housing Census of 2009 and extracted the records of all females who had their last child born in 12 months preceding the survey (N = 1,120,960). Multivariable regression analyses were used to identify risk factors that accounted for the risk of dying before the age of one at the individual level in Kenya. Place of residence (rural, non-slum urban, slum) was used as an interaction term to account for moderating effects in individual and socio-ecological risk factors. Results Individual characteristics of mothers and children (older age, less previously born children that died, better education, girl infants) and household contexts (better structural quality of housing, improved water and sanitation, married household head) were associated with lower risk for infant death in Kenya. Living in non-slum urban areas was associated with significantly lower infant death as compared to living in rural or slum areas, when all predictors were held at their reference levels. Moreover, place of residence was significantly moderating individual level predictors: As compared to rural areas, living in urban areas was a protective factor for mothers who had previous born children who died, and who were better educated. However, living in urban areas also reduced the health promoting effects of better structural quality of housing (i.e. poor or good versus non-durable). Furthermore, durable housing quality in urban areas turned out to be a risk factor for infant death as compared to rural areas. Living in slum areas was also a protective factor for mothers with previous child death, however it also reduced the promoting effects of older ages in mothers. Conclusions While urbanization and slum development continues in Kenya, public health interventions should invest in healthy environments that ideally would include improvements to access to safe water and sanitation, better structural quality of housing, and to access to education, health care, and family planning services, especially in urban slums and rural areas. In non-slum urban areas however, health education programs that target healthy diets and promote physical exercise may be an important adjunct to these structural interventions

From pandemic to endemic: Spatial-temporal patterns of influenza-like illness incidence in a Swiss canton, 1918-1924

In pandemics, past and present, there is no textbook definition of when a pandemic is over, and how and when exactly a respiratory virus transitions from pandemic to endemic spread. In this paper we have compared the 1918/19 influenza pandemic and the subsequent spread of seasonal flu until 1924. We analysed 14,125 reports of newly stated 32,198 influenza-like illnesses from the Swiss canton of Bern. We analysed the temporal and spatial spread at the level of municipalities, regions, and the canton. We calculated incidence rates per 1000 inhabitants of newly registered cases per calendar week. Further, we illustrated the incidences of each municipality for each wave (first wave in summer 1918, second wave in fall/winter 1918/19, the strong later wave in early 1920, as well as the two seasonal waves in 1922 and 1924) on a choropleth map. We performed a spatial hotspot analysis to identify spatial clusters in each wave, using the Gi* statistic. Furthermore, we applied a robust negative binomial regression to estimate the association between selected explanatory variables and incidence on the ecological level. We show that the pandemic transitioned to endemic spread in several waves (including another strong wave in February 1920) with lower incidence and rather local spread until 1924 at least. At the municipality and regional levels, there were different patterns of spread both between pandemic and seasonal waves. In the first pandemic wave in summer 1918 the probability of higher incidence was increased in municipalities with a higher proportion of manufacturing factories (OR 2.60, 95%CI 1.42-4.96), as well as in municipalities that had access to a railway station (OR 1.50, 95%CI 1.16-1.96). In contrast, the strong fall/winter wave 1918 was very widespread throughout the canton. In general, municipalities at higher altitude showed lower incidence. Our study adds to the sparse literature on incidence in the 1918/19 pandemic and subsequent years. Before Covid-19, the last pandemic that occurred in several waves and then became endemic was the 1918-19 pandemic. Such scenarios from the past can inform pandemic planning and preparedness in current and future outbreaks