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The national implementation of competency-based medical education (CBME) has prompted an increased interest in identifying and tracking clinical and educational outcomes for emergency medicine training programs. For the 2019 Canadian Association of Emergency Physicians (CAEP) Academic Symposium, we developed recommendations for measuring outcomes in emergency medicine training in the context of CBME to assist educational leaders and systems designers in program evaluation.
We conducted a three-phase study to generate educational and clinical outcomes for emergency medicine (EM) education in Canada. First, we elicited expert and community perspectives on the best educational and clinical outcomes through a structured consultation process using a targeted online survey. We then qualitatively analyzed these responses to generate a list of suggested outcomes. Last, we presented these outcomes to a diverse assembly of educators, trainees, and clinicians at the CAEP Academic Symposium for feedback and endorsement through a voting process.
Academic Symposium attendees endorsed the measurement and linkage of CBME educational and clinical outcomes. Twenty-five outcomes (15 educational, 10 clinical) were derived from the qualitative analysis of the survey results and the most important short- and long-term outcomes (both educational and clinical) were identified. These outcomes can be used to help measure the impact of CBME on the practice of Emergency Medicine in Canada to ensure that it meets both trainee and patient needs.
Self-reported activity restriction is an established correlate of depression in dementia caregivers (dCGs). It is plausible that the daily distribution of objectively measured activity is also altered in dCGs with depression symptoms; if so, such activity characteristics could provide a passively measurable marker of depression or specific times to target preventive interventions. We therefore investigated how levels of activity throughout the day differed in dCGs with and without depression symptoms, then tested whether any such differences predicted changes in symptoms 6 months later.
Design, setting, participants, and measurements:
We examined 56 dCGs (mean age = 71, standard deviation (SD) = 6.7; 68% female) and used clustering to identify subgroups which had distinct depression symptom levels, leveraging baseline Center for Epidemiologic Studies of Depression Scale–Revised Edition and Patient Health Questionnaire-9 (PHQ-9) measures, as well as a PHQ-9 score from 6 months later. Using wrist activity (mean recording length = 12.9 days, minimum = 6 days), we calculated average hourly activity levels and then assessed when activity levels relate to depression symptoms and changes in symptoms 6 months later.
Clustering identified subgroups characterized by: (1) no/minimal symptoms (36%) and (2) depression symptoms (64%). After multiple comparison correction, the group of dCGs with depression symptoms was less active from 8 to 10 AM (Cohen’s d ≤ −0.9). These morning activity levels predicted the degree of symptom change on the PHQ-9 6 months later (per SD unit β = −0.8, 95% confidence interval: −1.6, −0.1, p = 0.03) independent of self-reported activity restriction and other key factors.
These novel findings suggest that morning activity may protect dCGs from depression symptoms. Future studies should test whether helping dCGs get active in the morning influences the other features of depression in this population (i.e. insomnia, intrusive thoughts, and perceived activity restriction).
We describe the design and performance of the Engineering Development Array, which is a low-frequency radio telescope comprising 256 dual-polarisation dipole antennas working as a phased array. The Engineering Development Array was conceived of, developed, and deployed in just 18 months via re-use of Square Kilometre Array precursor technology and expertise, specifically from the Murchison Widefield Array radio telescope. Using drift scans and a model for the sky brightness temperature at low frequencies, we have derived the Engineering Development Array’s receiver temperature as a function of frequency. The Engineering Development Array is shown to be sky-noise limited over most of the frequency range measured between 60 and 240 MHz. By using the Engineering Development Array in interferometric mode with the Murchison Widefield Array, we used calibrated visibilities to measure the absolute sensitivity of the array. The measured array sensitivity matches very well with a model based on the array layout and measured receiver temperature. The results demonstrate the practicality and feasibility of using Murchison Widefield Array-style precursor technology for Square Kilometre Array-scale stations. The modular architecture of the Engineering Development Array allows upgrades to the array to be rolled out in a staged approach. Future improvements to the Engineering Development Array include replacing the second stage beamformer with a fully digital system, and to transition to using RF-over-fibre for the signal output from first stage beamformers.
Efficient natural dispersal of herbicide-resistance alleles via seed and pollen can markedly accelerate the incidence of herbicide-resistant weed populations across an agroecoregion. Studies were conducted in western Canada in 2014 and 2015 to investigate pollen- and seed-mediated gene flow in kochia. Pollen-mediated gene flow (PMGF) from glyphosate-resistant (GR) to non-GR kochia was quantified in a field trial (hub and spoke design) at Saskatoon, Saskatchewan. Seed-mediated gene flow of acetolactate synthase (ALS) inhibitor-resistant kochia as a function of tumbleweed speed and distance was estimated in cereal stubble fields at Lethbridge, Alberta and Scott, Saskatchewan. Regression analysis indicated that outcrossing from GR to adjacent non-GR kochia ranged from 5.3 to 7.5%, declining exponentially to 0.1 to 0.4% at 96 m distance. However, PMGF was significantly influenced by prevailing wind direction during pollination (maximum of 11 to 17% outcrossing down-wind). Seed dropped by tumbleweeds varied with distance and plant speed, approaching 90% or more (ca. 100,000 seeds or more) at distances of up to 1,000 m and plant speeds of up to 300 cm s–1. This study highlights the efficient proximal (pollen) and distal (seed) gene movement of this important GR weed.
In western Canada, more money is spent on wild oat herbicides than on any
other weed species, and wild oat resistance to herbicides is the most
widespread resistance issue. A direct-seeded field experiment was conducted
from 2010 to 2014 at eight Canadian sites to determine crop life cycle, crop
species, crop seeding rate, crop usage, and herbicide rate combination
effects on wild oat management and canola yield. Combining 2× seeding rates
of early-cut barley silage with 2× seeding rates of winter cereals and
excluding wild oat herbicides for 3 of 5 yr (2011 to 2013) often led to
similar wild oat density, aboveground wild oat biomass, wild oat seed
density in the soil, and canola yield as a repeated canola–wheat rotation
under a full wild oat herbicide rate regime. Wild oat was similarly well
managed after 3 yr of perennial alfalfa without wild oat herbicides.
Forgoing wild oat herbicides in only 2 of 5 yr from exclusively summer
annual crop rotations resulted in higher wild oat density, biomass, and seed
banks. Management systems that effectively combine diverse and optimal
cultural practices against weeds, and limit herbicide use, reduce selection
pressure for weed resistance to herbicides and prolong the utility of
threatened herbicide tools.
Infrastructure forms the economic backbone of modern society. It is a key determinant of economic competitiveness, social well-being and environmental sustainability. Yet infrastructure systems (energy, transport, water, waste and ICT) in advanced economies globally face serious challenges. For the first time, a leading team of researchers sets out a systematic approach to making long-term choices about national infrastructure systems. Great Britain is used as a case study to demonstrate how the methodologies and accompanying models can be effectively applied in a national infrastructure assessment. Lessons and insights for other industrialised nations and emerging economies are highlighted, demonstrating practical scenarios for delivering infrastructure services in a wide range of future socio-economic and environmental conditions. The Future of National Infrastructure provides practitioners, policy-makers, and academics with the concepts, models and tools needed to identify and test robust, sustainable, and resilient strategies for the provision of national infrastructure.
The redshifted 21cm line of neutral hydrogen (Hi), potentially observable at low radio frequencies (~50–200 MHz), should be a powerful probe of the physical conditions of the inter-galactic medium during Cosmic Dawn and the Epoch of Reionisation (EoR). The sky-averaged Hi signal is expected to be extremely weak (~100 mK) in comparison to the foreground of up to 104 K at the lowest frequencies of interest. The detection of such a weak signal requires an extremely stable, well characterised system and a good understanding of the foregrounds. Development of a nearly perfectly (~mK accuracy) calibrated total power radiometer system is essential for this type of experiment. We present the BIGHORNS (Broadband Instrument for Global HydrOgen ReioNisation Signal) experiment which was designed and built to detect the sky-averaged Hi signal from the EoR at low radio frequencies. The BIGHORNS system is a mobile total power radiometer, which can be deployed in any remote location in order to collect radio frequency interference (RFI) free data. The system was deployed in remote, radio quiet locations in Western Australia and low RFI sky data have been collected. We present a description of the system, its characteristics, details of data analysis, and calibration. We have identified multiple challenges to achieving the required measurement precision, which triggered two major improvements for the future system.
Two broad aims drive weed science research: improved management and improved
understanding of weed biology and ecology. In recent years, agricultural
weed research addressing these two aims has effectively split into separate
subdisciplines despite repeated calls for greater integration. Although some
excellent work is being done, agricultural weed research has developed a
very high level of repetitiveness, a preponderance of purely descriptive
studies, and has failed to clearly articulate novel hypotheses linked to
established bodies of ecological and evolutionary theory. In contrast,
invasive plant research attracts a diverse cadre of nonweed scientists using
invasions to explore broader and more integrated biological questions
grounded in theory. We propose that although studies focused on weed
management remain vitally important, agricultural weed research would
benefit from deeper theoretical justification, a broader vision, and
increased collaboration across diverse disciplines. To initiate change in
this direction, we call for more emphasis on interdisciplinary training for
weed scientists, and for focused workshops and working groups to develop
specific areas of research and promote interactions among weed scientists
and with the wider scientific community.