126 research outputs found
Healthy People 2020 Structured Evidence Queries for PubMed: Practice Informed by Research
Objective: Healthy People 2020 is a set of objectives with 10-year targets to guide national health promotion and disease prevention efforts. Public health professionals may have limited time to identify relevant research articles on public health strategies. NLM recognized the need to reduce the time and increase the precision of finding research to support evidence-based actions to achieve HP2020 objectives.
Methods: NLM collaborated with the HHS Office of Disease Prevention and Health Promotion to develop pre-formulated search strategies â structured evidence queries (SEQs) â of PubMed to make research evidence related to HP2020 objectives easier to find. The queries were developed by librarians, working in consultation with subject matter experts in public health. The PubMed search strategies are organized by HP2020 topic areas on the HP2020 SEQ website that is supported by NLM with assistance of the collaboration, Partners in Information Access for the Public Health Workforce. The website also provides search queries for the Healthy People 2020 Leading Health Indicators, a subset of high-priority health issues that represent significant threats to the publicâs health. Information to help users learn more about PubMed, obtain full-text copies of articles, and find additional resources for public health practice are provided on the site.
Results: The Healthy People 2020 Structured Evidence Queries website, http://phpartners.org/hp2020, launched in June 2011. As of the end of 2012, structured evidence queries were formulated for 268 health objectives in 24 Healthy People 2020 topic areas, with the expectation of full coverage by May 2013. The SEQs are also integrated with the HHS HealthyPeople.gov website. The PubMed search strategies were designed to return a manageable number of relevant citations for busy public health professionals to review. Users retrieve the most recent research articles indexed for MEDLINE on Healthy People objectives each time a SEQ is selected and run in PubMed. The search strategies can be modified to address particular practice and research needs. The website includes FAQs on how to modify and save searches, obtain copies of articles, and receive assistance from the National Network of Libraries of Medicine. Additional resources on public health topics are available from the Partners in Information Access for the Public Health Workforce website, http://PHPartners.org.
Conclusions: The HP2020 SEQs provide peer-reviewed research evidence to support national objectives for improving the health of all Americans. The resource is the outcome of an effective partnership between librarians, public health professionals, and subject experts
Spiritual Struggles among Atheists: Links to Psychological Distress and Well-Being
Religious and spiritual struggles (R/S struggles)âtension or conflicts regarding religious or spiritual mattersâhave been robustly linked to greater psychological distress and lower well-being. Most research in this area has relied on samples consisting predominantly of participants who believe in god(s). Limited research has examined R/S struggles among atheists, generally conflating them with agnostics and other nontheists. This study investigated the prevalence of R/S struggles among atheists and compared atheists to theists in two samples (3978 undergraduates, 1048 Internet workers). Results of a multilevel model showed that atheists experience less demonic, doubt, divine, moral, and overall R/S struggles than theists, but similar levels of interpersonal and ultimate meaning struggles. Correlation and regression analyses among atheists demonstrated links between moral, ultimate meaning, and overall R/S struggles and greater distress (depression and anxiety symptoms) as well as lower well-being (life satisfaction and meaning in life). Even after controlling neuroticism, ultimate meaning struggles continued to predict lower well-being and higher distress across samples; moral struggles also predicted distress independently. This study demonstrates the relevance of R/S struggles to atheists and reinforces the applicability of previous results to atheist samples, but also highlights substantial differences between atheists and theists in certain R/S struggles
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Select strengths and biases of models in representing the Arctic winter boundary layer over sea ice: the Larcform 1 single column model intercomparison
Weather and climate models struggle to represent lower tropospheric temperature and moisture profiles and surface fluxes in Arctic winter, partly because they lack or misrepresent physical processes that are specific to high latitudes. Observations have revealed two preferred states of the Arctic winter boundary layer. In the cloudy state, cloud liquid water limits surface radiative cooling, and temperature inversions are weak and elevated. In the radiatively clear state, strong surface radiative cooling leads to the build-up of surface-based temperature inversions. Many large-scale models lack the cloudy state, and some substantially underestimate inversion strength in the clear state. Here, the transformation from a moist to a cold dry air mass is modeled using an idealized Lagrangian perspective. The trajectory includes both boundary layer states, and the single-column experiment is the first Lagrangian Arctic air formation experiment (Larcform 1) organized within GEWEX GASS (Global atmospheric system studies). The intercomparison reproduces the typical biases of large-scale models: some models lack the cloudy state of the boundary layer due to the representation of mixed-phase microphysics or to the interaction between micro- and macrophysics. In some models, high emissivities of ice clouds or the lack of an insulating snow layer prevent the build-up of surface-based inversions in the radiatively clear state. Models substantially disagree on the amount of cloud liquid water in the cloudy state and on turbulent heat fluxes under clear skies. Observations of air mass transformations including both boundary layer states would allow for a tighter constraint of model behavior
Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge.
Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods
Connecting LandâAtmosphere Interactions to Surface Heterogeneity in CHEESEHEAD19
The Chequamegon Heterogeneous Ecosystem Energy-Balance Study Enabled by a High-Density Extensive Array of Detectors 2019 (CHEESEHEAD19) is an ongoing National Science Foundation project based on an intensive field campaign that occurred from June to October 2019. The purpose of the study is to examine how the atmospheric boundary layer (ABL) responds to spatial heterogeneity in surface energy fluxes. One of the main objectives is to test whether lack of energy balance closure measured by eddy covariance (EC) towers is related to mesoscale atmospheric processes. Finally, the project evaluates data-driven methods for scaling surface energy fluxes, with the aim to improve modelâdata comparison and integration. To address these questions, an extensive suite of ground, tower, profiling, and airborne instrumentation was deployed over a 10 km Ă 10 km domain of a heterogeneous forest ecosystem in the ChequamegonâNicolet National Forest in northern Wisconsin, United States, centered on an existing 447-m tower that anchors an AmeriFlux/NOAA supersite (US-PFa/WLEF). The project deployed one of the worldâs highest-density networks of above-canopy EC measurements of surface energy fluxes. This tower EC network was coupled with spatial measurements of EC fluxes from aircraft; maps of leaf and canopy properties derived from airborne spectroscopy, ground-based measurements of plant productivity, phenology, and physiology; and atmospheric profiles of wind, water vapor, and temperature using radar, sodar, lidar, microwave radiometers, infrared interferometers, and radiosondes. These observations are being used with large-eddy simulation and scaling experiments to better understand submesoscale processes and improve formulations of subgrid-scale processes in numerical weather and climate models
The Arctic Summer Cloud Ocean Study (ASCOS): overview and experimental design
The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol-cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007-2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21âČ N, 01°29âČ W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets
Framework for strategic wind farm site prioritisation based on modelled wolf reproduction habitat in Croatia
In order to meet carbon reduction targets, many nations are greatly expanding their wind power capacity. However, wind farm infrastructure potentially harms wildlife, and we must therefore find ways to balance clean energy demands with the need to protect wildlife. Wide-ranging carnivores live at low density and are particularly susceptible to disturbance from infrastructure development, so are a particular concern in this respect. We focused on Croatia, which holds an important population of wolves and is currently planning to construct many new wind farms. Specifically, we sought to identify an optimal subset of planned wind farms that would meet energy targets while minimising potential impact on wolves. A suitability model for wolf breeding habitat was carried out using Maxent, based on six environmental variables and 31 reproduction site locations collected between 1997 and 2015. Wind farms were prioritised using Marxan to find the optimal trade-off between energy capacity and overlap with critical wolf reproduction habitat. The habitat suitability model predictions were consistent with the current knowledge: probability of wolf breeding site presence increased with distance to settlements, distance to farmland and distance to roads and decreased with distance to forest. Spatial optimisation showed that it would be possible to meet current energy targets with only 31% of currently proposed wind farms, selected in a way that reduces the potential ecological cost (overall predicted wolf breeding site presence within wind farm sites) by 91%. This is a highly efficient outcome, demonstrating the value of this approach for prioritising infrastructure development based on its potential impact on wide-ranging wildlife species
Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science
It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the âSeattle Implementation Research Conferenceâ; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRCâs membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRCâs primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term âEBP championsâ for these groups) â and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleaguesâ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations
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