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Although mania is the hallmark symptom of bipolar I disorder (BD-I), most patients initially present for treatment with depressive symptoms. Misdiagnosis of BD-I as major depressive disorder (MDD) is common, potentially resulting in poor outcomes and inappropriate antidepressant monotherapy treatment. Screening patients with depressive symptoms is a practical strategy to help healthcare providers (HCPs) identify when additional assessment for BD-I is warranted. The new 6-item Rapid Mood Screener (RMS) is a pragmatic patient-reported BD-I screening tool that relies on easily understood terminology to screen for manic symptoms and other BD-I features in <2 minutes. The RMS was validated in an observational study in patients with clinically confirmed BD-I (n=67) or MDD (n=72). When 4 or more items were endorsed (“yes”), the sensitivity of the RMS for identifying patients with BP-I was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. To more thoroughly understand screening tool use among HCPs, a 10-minute survey was conducted.
A nationwide sample of HCPs (N=200) was selected using multiple HCP panels; HCPs were asked to describe their opinions/current use of screening tools, assess the RMS, and evaluate the RMS versus the widely recognized Mood Disorder Questionnaire (MDQ). Results were reported by grouped specialties (primary care physicians, general nurse practitioners [NPs]/physician assistants [PAs], psychiatrists, and psychiatric NPs/PAs). Included HCPs were in practice <30 years, spent at least 75% of their time in clinical practice, saw at least 10 patients with depression per month, and diagnosed MDD or BD in at least 1 patient per month. Findings were reported using descriptive statistics; statistical significance was reported at the 95% confidence interval.
Among HCPs, 82% used a tool to screen for MDD, while 32% used a tool for BD. Screening tool attributes considered to be of the greatest value included sensitivity (68%), easy to answer questions (66%), specificity (65%), confidence in results (64%), and practicality (62%). Of HCPs familiar with screening tools, 70% thought the RMS was at least somewhat better than other screening tools. Most HCPs were aware of the MDQ (85%), but only 29% reported current use. Most HCPs (81%) preferred the RMS to the MDQ, and the RMS significantly outperformed the MDQ across valued attributes; 76% reported that they were likely to use the RMS to screen new patients with depressive symptoms. A total of 84% said the RMS would have a positive impact on their practice, with 46% saying they would screen more patients for bipolar disorder.
The RMS was viewed positively by HCPs who participated in a brief survey. A large percentage of respondents preferred the RMS over the MDQ and indicated that they would use it in their practice. Collectively, responses indicated that the RMS is likely to have a positive impact on screening behavior.
To better characterize brain-based mechanisms of polygenic liability for psychopathology and psychological traits, we extended our previous report (Liu et al. Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci. Psychological Medicine, 2017), focused solely on schizophrenia, to test the association between multivariate psychophysiological candidate endophenotypes (including novel measures of θ/δ oscillatory activity) and a range of polygenic scores (PGSs), namely alcohol/cannabis/nicotine use, an updated schizophrenia PGS (containing 52 more genome-wide significant loci than the PGS used in our previous report) and educational attainment.
A large community-based twin/family sample (N = 4893) was genome-wide genotyped and imputed. PGSs were constructed for alcohol use, regular smoking initiation, lifetime cannabis use, schizophrenia, and educational attainment. Eleven endophenotypes were assessed: visual oddball task event-related electroencephalogram (EEG) measures (target-related parietal P3 amplitude, frontal θ, and parietal δ energy/inter-trial phase clustering), band-limited resting-state EEG power, antisaccade error rate. Principal component analysis exploited covariation among endophenotypes to extract a smaller number of meaningful dimensions/components for statistical analysis.
Endophenotypes were heritable. PGSs showed expected intercorrelations (e.g. schizophrenia PGS correlated positively with alcohol/nicotine/cannabis PGSs). Schizophrenia PGS was negatively associated with an event-related P3/δ component [β = −0.032, nonparametric bootstrap 95% confidence interval (CI) −0.059 to −0.003]. A prefrontal control component (event-related θ/antisaccade errors) was negatively associated with alcohol (β = −0.034, 95% CI −0.063 to −0.006) and regular smoking PGSs (β = −0.032, 95% CI −0.061 to −0.005) and positively associated with educational attainment PGS (β = 0.031, 95% CI 0.003–0.058).
Evidence suggests that multivariate endophenotypes of decision-making (P3/δ) and cognitive/attentional control (θ/antisaccade error) relate to alcohol/nicotine, schizophrenia, and educational attainment PGSs and represent promising targets for future research.
On October 10, 2020, the Memorial Sloan Kettering Cancer Center Supportive Care Service hosted their first-ever United States (US) World Hospice and Palliative Care Day (WHPCD) Celebration. The purpose of this article is to describe the US inaugural event in alignment with the broader goals of WHPCD and provide lessons learned in anticipation of the second annual conference to be held on October 5–6, 2021.
Description of the inaugural event in the context of COVID-19 and WHPCD, co-planning conference team reflection, and attendee survey responses.
The Worldwide Hospice Palliative Care Alliance initially launched WHPCD in 2005 as an annual unified day of action to celebrate and support hospice and palliative care around the world. The US-based innovative virtual conference featured 23 interprofessional hospice and palliative care specialists and patient and family caregiver speakers across nine diverse sessions addressing priorities at the intersection of COVID-19, social injustice, and the global burden of serious health-related suffering. Two primary aims guided the event: community building and wisdom sharing. Nearly 270 registrants from at least 16 countries and one dozen states across the US joined the free program focused on both personal and professional development.
Significance of results
Unlike many other academic conferences and professional gatherings that were relegated to online forums due to pandemic-related restrictions, the US WHPCD Celebration was intentionally established to create a virtual coming together for collective reflection on the barriers and facilitators of palliative care delivery amid vast societal change. The goal to ensure a globally relevant and culturally inclusive agenda will continue to draw increased participation at an international level during future annual events. Finally, the transparent and respectful sharing of palliative care team experiences in the year preceding the conference established a safe environment for both individual expression and scholarly discussion.
When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).
This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere.
We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent.
Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding.
These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.
Ecosystem modeling, a pillar of the systems ecology paradigm (SEP), addresses questions such as, how much carbon and nitrogen are cycled within ecological sites, landscapes, or indeed the earth system? Or how are human activities modifying these flows? Modeling, when coupled with field and laboratory studies, represents the essence of the SEP in that they embody accumulated knowledge and generate hypotheses to test understanding of ecosystem processes and behavior. Initially, ecosystem models were primarily used to improve our understanding about how biophysical aspects of ecosystems operate. However, current ecosystem models are widely used to make accurate predictions about how large-scale phenomena such as climate change and management practices impact ecosystem dynamics and assess potential effects of these changes on economic activity and policy making. In sum, ecosystem models embedded in the SEP remain our best mechanism to integrate diverse types of knowledge regarding how the earth system functions and to make quantitative predictions that can be confronted with observations of reality. Modeling efforts discussed are the Century ecosystem model, DayCent ecosystem model, Grassland Ecosystem Model ELM, food web models, Savanna model, agent-based and coupled systems modeling, and Bayesian modeling.
Emerging from the warehouse of knowledge about terrestrial ecosystem functioning and the application of the systems ecology paradigm, exemplified by the power of simulation modeling, tremendous strides have been made linking the interactions of the land, atmosphere, and water locally to globally. Through integration of ecosystem, atmospheric, soil, and more recently social science interactions, plausible scenarios and even reasonable predictions are now possible about the outcomes of human activities. The applications of that knowledge to the effects of changing climates, human-caused nitrogen enrichment of ecosystems, and altered UV-B radiation represent challenges addressed in this chapter. The primary linkages addressed are through the C, N, S, and H2O cycles, and UV-B radiation. Carbon dioxide exchanges between land and the atmosphere, N additions and losses to and from lands and waters, early studies of SO2 in grassland ecosystem, and the effects of UV-B radiation on ecosystems have been mainstays of research described in this chapter. This research knowledge has been used in international and national climate assessments, for example the IPCC, US National Climate Assessment, and Paris Climate Accord. Likewise, the knowledge has been used to develop concepts and technologies related to sustainable agriculture, C sequestration, and food security.
Antarctica's ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their ‘buttressing’ effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttressing by investigating the ‘end-member’ scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1–12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91–5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong function of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments.
The Tennessee Department of Health (TDH) investigated a hepatitis A virus (HAV) outbreak to identify risk factors for infection and make prevention recommendations.
Healthcare workers (HCWs) or patients with laboratory-confirmed acute HAV infection during October 1, 2018–January 10, 2019.
HCWs with suspected or confirmed hepatitis A infections were interviewed to assess their exposures and activities. Patient medical records and hospital administrative records were reviewed to identify common exposures. We conducted a site investigation to assess knowledge of infection control practices among HCWs. Serum specimens from ill persons were tested for HAV RNA by polymerase chain reaction (PCR) and genotyped.
We identified 6 HCWs and 2 patients with laboratory-confirmed HAV infection. All cases likely resulted from exposure to a homeless patient with a history of recreational substance use and undiagnosed HAV infection. Breaches in hand hygiene and use of standard precautions were identified. HAV RNA was detected in 7 serum specimens and all belonged to an identical strain of HAV genotype 1b.
A hepatitis A outbreak among hospital patients and HCWs resulted from exposure to a single patient with undiagnosed HAV infection. Breakdowns in infection control practices contributed to the outbreak. The likelihood of nosocomial transmission can be reduced with proper hand hygiene, standard precautions, and routine disinfection. During community outbreaks, medical providers can better prevent ongoing transmission by including hepatitis A in the differential diagnosis among patients with a history of recreational substance use and homelessness.
Little is known about the determinants of community integration (i.e. recovery) for individuals with a history of homelessness, yet such information is essential to develop targeted interventions.
We recruited homeless Veterans with a history of psychotic disorders and evaluated four domains of correlates of community integration: perception, non-social cognition, social cognition, and motivation. Baseline assessments occurred after participants were engaged in supported housing services but before they received housing, and again after 12 months. Ninety-five homeless Veterans with a history of psychosis were assessed at baseline and 53 returned after 12 months. We examined both cross-sectional and longitudinal relationships with 12-month community integration.
The strongest longitudinal association was between a baseline motivational measure and social integration at 12 months. We also observed cross-sectional associations at baseline between motivational measures and community integration, including social, work, and independent living. Cross-lagged panel analyses did not suggest causal associations for the motivational measures. Correlations with perception and non-social cognition were weak. One social cognition measure showed a significant longitudinal correlation with independent living at 12 months that was significant for cross-lagged analysis, consistent with a causal relationship and potential treatment target.
The relatively selective associations for motivational measures differ from what is typically seen in psychosis, in which all domains are associated with community integration. These findings are presented along with a partner paper (Study 2) to compare findings from this study to an independent sample without a history of psychotic disorders to evaluate the consistency in findings regarding community integration across projects.
In an initial study (Study 1), we found that motivation predicted community integration (i.e. functional recovery) 12 months after receiving housing in formerly homeless Veterans with a psychotic disorder. The current study examined whether the same pattern would be found in a broader, more clinically diverse, homeless Veteran sample without psychosis.
We examined four categories of variables as potential predictors of community integration in non-psychotic Veterans: perception, non-social cognition, social cognition, and motivation at baseline (after participants were engaged in a permanent supported housing program but before receiving housing) and a 12-month follow-up. A total of 82 Veterans had a baseline assessment and 41 returned for testing after 12 months.
The strongest longitudinal association was between an interview-based measure of motivation (the motivation and pleasure subscale from the Clinical Assessment Interview for Negative Symptoms) at baseline and measures of social integration at 12 months. In addition, cross-lagged panel analyses were consistent with a causal influence of general psychiatric symptoms at baseline driving social integration at 12 months, and reduced expressiveness at baseline driving independent living at 12 months, but there were no significant causal associations with measures of motivation.
The findings from this study complement and reinforce those in Veterans with psychosis. Across these two studies, our findings suggest that motivational factors are associated at baseline and at 12 months and are particularly important for understanding and improving community integration in recently-housed Veterans across psychiatric diagnoses.
Reconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales.
The National Institutes of Health requires data and safety monitoring boards (DSMBs) for all phase III clinical trials. The National Heart, Lung and Blood Institute requires DSMBs for all clinical trials involving more than one site and those involving cooperative agreements and contracts. These policies have resulted in the establishment of DSMBs for many implementation trials, with little consideration regarding the appropriateness of DSMBs and/or key adaptations needed by DSMBs to monitor data quality and participant safety. In this perspective, we review the unique features of implementation trials and reflect on key questions regarding the justification for DSMBs and their potential role and monitoring targets within implementation trials.
When 2017 Hurricane Harvey struck the coastline of Texas on August 25, 2017, it resulted in 88 fatalities and more than US $125 billion in damage to infrastructure. The floods associated with the storm created a toxic mix of chemicals, sewage and other biohazards, and over 6 million cubic meters of garbage in Houston alone. The level of biohazard exposure and injuries from trauma among persons residing in affected areas was widespread and likely contributed to increases in emergency department (ED) visits in Houston and cities receiving hurricane evacuees. We investigated medical surge resulting from these evacuations in Dallas–Fort Worth (DFW) metroplex EDs.
We used data sourced from the North Texas Syndromic Surveillance Region 2/3 in ESSENCE to investigate ED visit surge following the storm in DFW hospitals because this area received evacuees from the 60 counties with disaster declarations due to the storm. We used the interrupted time series (ITS) analysis to estimate the magnitude and duration of the ED surge. ITS was applied to all ED visits in DFW and visits made by patients residing in any of the 60 counties with disaster declarations due to the storm. The DFW metropolitan statistical area included 55 hospitals. Time series analyses examined data from March 1, 2017–January 6, 2018 with focus on the storm impact period, August 14–September 15, 2017. Data from before, during, and after the storm were visualized spatially and temporally to characterize magnitude, duration, and spatial variation of medical surge attributable to Hurricane Harvey.
During the study period overall, ED visits in the DFW area rose immediately by about 11% (95% CI: 9%, 13%), amounting to ~16 500 excess total visits before returning to the baseline on September 21, 2017. Visits by patients identified as residing in disaster declaration counties to DFW hospitals rose immediately by 127% (95% CI: 125%, 129%), amounting to 654 excess visits by September 29, 2017, when visits returned to the baseline. A spatial analysis revealed that evacuated patients were strongly clustered (Moran’s I = 0.35, P < 0.0001) among 5 of the counties with disaster declarations in the 11-day window during the storm surge.
The observed increase in ED visits in DFW due to Hurricane Harvey and ensuing evacuation was significant. Anticipating medical surge following large-scale hurricanes is critical for community preparedness planning. Coordinated planning across stakeholders is necessary to safeguard the population and for a skillful response to medical surge needs. Plans that address hurricane response, in particular, should have contingencies for support beyond the expected disaster areas.
The political atmosphere on US college campuses is overwhelmingly left-leaning and liberal, with the vast majority of faculty self-identifying as socially progressive. Considerable research on cognitive biases has demonstrated the pervasive role of people’s attitudes, which act as filters during thinking and reasoning – particularly about politically-valenced topics. The prevalence of faculty from one side of the political spectrum coupled with the omnipresence of cognitive biases means that college campuses and the research done by their faculty runs the risk of favoring one side during what should, scientifically-speaking, be a process of fair and open inquiry. We discuss these phenomena and document numerous examples in which lack of genuine viewpoint diversity has spelled trouble for sound science. We advocate a more ideologically-diverse scientific workforce to better enable true diversity of thinking on key issues of our time.
There are large between-country differences in measures of economic and noneconomic well-being. Many researchers view increasing the stock of human capital as the key to raising economic development, promoting democratization, and improving health, and hence improving overall societal well-being. The single most studied aspect of human capital concerns cognitive competence. Differences in population cognitive competence might explain these societal differences. Evidence suggests that education builds cognitive competence, and education and cognitive competence promote better social outcomes, in terms of both economic and noneconomic factors. However, measuring population cognitive competence for countries requires representative samples, culture-fair tests, equivalency in the relationship between test measures and other cognitive attributes, and comparability in testing situations. In most cases, none of this has been achieved.
The Minnesota Center for Twin and Family Research (MCTFR) comprises multiple longitudinal, community-representative investigations of twin and adoptive families that focus on psychological adjustment, personality, cognitive ability and brain function, with a special emphasis on substance use and related psychopathology. The MCTFR includes the Minnesota Twin Registry (MTR), a cohort of twins who have completed assessments in middle and older adulthood; the Minnesota Twin Family Study (MTFS) of twins assessed from childhood and adolescence into middle adulthood; the Enrichment Study (ES) of twins oversampled for high risk for substance-use disorders assessed from childhood into young adulthood; the Adolescent Brain (AdBrain) study, a neuroimaging study of adolescent twins; and the Siblings Interaction and Behavior Study (SIBS), a study of adoptive and nonadoptive families assessed from adolescence into young adulthood. Here we provide a brief overview of key features of these established studies and describe new MCTFR investigations that follow up and expand upon existing studies or recruit and assess new samples, including the MTR Study of Relationships, Personality, and Health (MTR-RPH); the Colorado-Minnesota (COMN) Marijuana Study; the Adolescent Brain Cognitive Development (ABCD) study; the Colorado Online Twins (CoTwins) study and the Children of Twins (CoT) study.
Subclinical adolescent alcohol use is highly prevalent and may have deleterious effects on important psychosocial and brain outcomes. Prior research has focused on identifying endophenotypes of pathological drinking, and the predictors of normative drinking remain understudied. This study investigated the incremental predictive value of two potential psychophysiological endophenotypes, P3 amplitude (an index of decision making) and midfrontal theta power (a correlate of attentional control), for prospectively predicting the expression and initiation of alcohol use emerging in adolescence.
A large (N = 594) epidemiological sample was prospectively assessed at ages 11/14/17. Alcohol/substance use was assessed at all ages via a computerized self-report inventory. EEG was recorded at age-14 during a visual oddball task to elicit P3 and theta.
Reduced target-related P3 and theta at age-14 prospectively predicted drinking at age-17 independent of one another. Among alcohol-naive individuals at age-14, attenuated P3 and theta increased the odds of new-onset alcohol behaviors 3 years later. Importantly, the endophenotypes provided significant incremental predictive power of future non-clinical alcohol use beyond relevant risk factors (prior alcohol use; tobacco/illicit drug initiation; parental alcohol use disorder).
The current report is the first of our knowledge to demonstrate that deviations in parietal P3 and midfrontal theta prospectively predict the emergence of normative/non-pathological drinking. P3 and theta provide modest yet significant explanatory variance beyond prominent self-report and familial risk measures. Findings offer strong evidence supporting the predictive utility of P3 and theta as candidate endophenotypes for adolescent drinking.