A practice-centered intervention to increase screening for domestic violence in primary care practices

BACKGROUND: Interventions to change practice patterns among health care professionals have had mixed success. We tested the effectiveness of a practice centered intervention to increase screening for domestic violence in primary care practices. METHODS: A multifaceted intervention was conducted among primary care practice in North Carolina. All practices designated two individuals to serve as domestic violence resources persons, underwent initial training on screening for domestic violence, and participated in 3 lunch and learn sessions. Within this framework, practices selected the screening instrument, patient educational material, and content best suited for their environment. Effectiveness was evaluated using a pre/post cross-sectional telephone survey of a random selection of female patients from each practice. RESULTS: Seventeen practices were recruited and fifteen completed the study. Baseline screening for domestic violence was 16% with a range of 2% to 49%. An absolute increase in screening of 10% was achieved (range of increase 0 to 22%). After controlling for clustering by practice and other patient characteristics, female patients were 79% more likely to have been screened after the intervention (OR 1.79, 95% CI 1.43–2.23). CONCLUSION: An intervention that allowed practices to tailor certain aspects to fit their needs increased screening for domestic violence. Further studies testing this technique using other outcomes are needed

Do primary care medical homes facilitate care transitions after psychiatric discharge for patients with multiple chronic conditions?

Primary-care-based medical homes may facilitate care transitions for persons with multiple chronic conditions (MCC) including serious mental illness. The purpose of this manuscript is to assess outpatient follow-up rates with primary care and mental health providers following psychiatric discharge by medical home enrollment and medical complexity

Demographic trade-offs predict tropical forest dynamics

Understanding tropical forest dynamics and planning for their sustainable management require efficient, yet accurate, predictions of the joint dynamics of hundreds of tree species. With increasing information on tropical tree life histories, our predictive understanding is no longer limited by species data but by the ability of existing models to make use of it. Using a demographic forest model, we show that the basal area and compositional changes during forest succession in a neotropical forest can be accurately predicted by representing tropical tree diversity (hundreds of species) with only five functional groups spanning two essential trade-offs—the growth-survival and stature-recruitment trade-offs. This data-driven modeling framework substantially improves our ability to predict consequences of anthropogenic impacts on tropical forests

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness

Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition

The long-term and large-scale dynamics of ecosystems are in large part determined by the performances of individual plants in competition with one another for light, water, and nutrients. Woody biomass, a pool of carbon (C) larger than 50% of atmospheric CO2, exists because of height-structured competition for light. However, most of the current Earth system models that predict climate change and C cycle feedbacks lack both a mechanistic formulation for height-structured competition for light and an explicit scaling from individual plants to the globe. In this study, we incorporate height-structured competition for light, competition for water, and explicit scaling from individuals to ecosystems into the land model version 3 (LM3) currently used in the Earth system models developed by the Geophysical Fluid Dynamics Laboratory (GFDL). The height-structured formulation is based on the perfect plasticity approximation (PPA), which has been shown to accurately scale from individual-level plant competition for light, water, and nutrients to the dynamics of whole communities. Because of the tractability of the PPA, the coupled LM3-PPA model is able to include a large number of phenomena across a range of spatial and temporal scales and still retain computational tractability, as well as close linkages to mathematically tractable forms of the model. We test a range of predictions against data from temperate broadleaved forests in the northern USA. The results show the model predictions agree with diurnal and annual C fluxes, growth rates of individual trees in the canopy and understory, tree size distributions, and species-level population dynamics during succession. We also show how the competitively optimal allocation strategy - the strategy that can competitively exclude all others - shifts as a function of the atmospheric CO2 concentration. This strategy is referred to as an evolutionarily stable strategy (ESS) in the ecological literature and is typically not the same as a productivity-or growth-maximizing strategy. Model simulations predict that C sinks caused by CO2 fertilization in forests limited by light and water will be down-regulated if allocation tracks changes in the competitive optimum. The implementation of the model in this paper is for temperate broadleaved forest trees, but the formulation of the model is general. It can be expanded to include other growth forms and physiologies simply by altering parameter values

Ecologic Factors Associated with West Nile Virus Transmission, Northeastern United States

Risk for disease was 4 times greater in the least forested counties

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Arousal frequency is associated with increased fatigue in obstructive sleep apnea

Fatigue is an important and often underemphasized symptom in patients with obstructive sleep apnea (OSA). Sleep fragmentation, i.e., arousals and disruptions in sleep architecture, is common in patients with OSA and may potentially contribute to their fatigue. We hypothesized that arousal frequency and changes in sleep architecture contribute to the fatigue experienced by patients with OSA. Seventy-three patients with diagnosed but untreated OSA (AHI ≥ 15) were enrolled in this study. A baseline polysomnogram was obtained, and fatigue was measured with the Multidimensional Fatigue Symptom Inventory-short form (MFSI-sf). We evaluated the association between fatigue and arousals and various polysomongraphic variables, including sleep stages and sleep efficiency. Significant correlations between MFSI-sf subscale scores and various arousal indices were noted. Emotional fatigue scores were associated with total arousal index (r = 0.416, p = .021), respiratory movement arousal index (r = 0.346, p = .025), and spontaneous movement arousal index (r = 0.378, p = .025). Physical fatigue scores were associated with total arousal index (r = 0.360, p = .033) and respiratory movement arousal index (r = 0.304, p = .040). Percent of stage 1 sleep and REM sleep were also associated with physical and emotional fatigue scores. Hierarchal linear regression analysis demonstrated that emotional fatigue scores were independently associated with spontaneous movement arousals after controlling for age, body mass index, depression, and sleep apnea severity. These findings suggest that arousals may contribute to the fatigue seen in patients with OSA

Chronicity of sleep problems in children with chronic illness: a longitudinal population-based study

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to examine the chronicity of sleep problems in children with chronic illness, and potential predictors of sleep problems.</p> <p>Methods</p> <p>Using data from a longitudinal total population study in Norway, The Bergen Child Study, data on sleep problems, chronic illness and potential confounders were assessed at ages 79 and 1113.</p> <p>Results</p> <p>295 of 4025 (7.3%) children had a chronic illness, and the prevalence of chronic sleep problems was significantly higher in this group compared to children without chronic illness (6.8% versus 3.6%). Sleep problems at the first wave increased the risk of sleep problems at the second wave, also when adjusting for potential confounders (odds-ratio = 5.41). Hyperactivity and emotional problems were also independent risk factors for later sleep problems.</p> <p>Conclusion</p> <p>These findings call for increased awareness and development of treatment strategies of sleep problems in children with chronic illness.</p