5,992 research outputs found
Social networks, social capital and end-of-life care for people with dementia: a realist review
OBJECTIVES (1) To develop an understanding of how social
capital may be conceptualised within the context of endof-life care and how it can influence outcomes for people
with dementia and their families with specific reference
to the context and mechanisms that explain observed
outcomes. (2) To produce guidance for healthcare systems
and researchers to better structure and design a public
health approach to end-of-life care for people with
dementia.
DESIGN A realist review.
Data sources MEDLINE, EMBASE, CINAHL and grey
literature.
ANALYSIS We conceptualised social capital as a complex
intervention and, in order to understand how change is
generated, used realist evaluation methods to create
different configurations of context, mechanism and
outcomes. We conducted an iterative search focusing
on social capital, social networks and end-of-life care in
dementia. All study designs and outcomes were screened
and analysed to elicit explanations for a range of outcomes
identified. Explanations were consolidated into an
overarching programme theory that drew on substantive
theory from the social sciences and a public health
approach to palliative care.
RESULTS We identified 118 articles from 16 countries
ranging from 1992 to 2018. A total of 40 contextmechanism-outcome configurations help explain how
social capital may influence end-of-life care for people
with dementia. Such influence was identified within five
key areas. These included: (1) socially orientating a person
with dementia following diagnosis; (2) transitions in the
physical environment of care; (3) how the caregiving
experience is viewed by those directly involved with it; (4)
transition of a person with dementia into the fourth age;
(5) the decision making processes underpinning such
processes.
CONCLUSION This review contributes to the dispassionate
understanding of how complex systems such as
community and social capital might be viewed as a tool to
improve end-of-life care for people with dementia.
PROSPERO REGISTRATION NUMBER CRD42018084524
'She's a F**king ticket':the pragmatics of f**k in Irish English - an age and gender perspective
The ROTSE-III Robotic Telescope System
The observation of a prompt optical flash from GRB990123 convincingly
demonstrated the value of autonomous robotic telescope systems. Pursuing a
program of rapid follow-up observations of gamma-ray bursts, the Robotic
Optical Transient Search Experiment (ROTSE) has developed a next-generation
instrument, ROTSE-III, that will continue the search for fast optical
transients. The entire system was designed as an economical robotic facility to
be installed at remote sites throughout the world. There are seven major system
components: optics, optical tube assembly, CCD camera, telescope mount,
enclosure, environmental sensing & protection and data acquisition. Each is
described in turn in the hope that the techniques developed here will be useful
in similar contexts elsewhere.Comment: 19 pages, including 4 figures. To be published in PASP in January,
2003. PASP Number IP02-11
Awareness in severe Alzheimer’s disease: a systematic review
OBJECTIVE: There is limited understanding about how people in the severe stages of Alzheimer’s disease (AD) experience and demonstrate awareness. We synthesised all available evidence with the aim of understanding how awareness is preserved or impaired in severe AD and what evidence there is for different levels of awareness according to the levels of awareness framework.
METHOD: A systematic search of the following databases: Embase, PsycINFO, MEDLINE and Web of Science was carried out. A narrative synthesis and analysis was conducted of all included studies. All studies were assessed for quality using the AXIS and CASP tools.
RESULTS: Our findings suggest that lower level sensory awareness is relatively maintained in severe AD. Findings for higher level awareness are variable and this may be related to the diversity of methods that have been used to explore awareness in these circumstances.
CONCLUSION: Awareness is complex, heterogeneous and varies significantly between individuals. Environmental and contextual factors have a significant impact on whether awareness is observed in people with severe AD. Adaptation of the environment has the potential to facilitate the expression of awareness while education of caregivers may increase understanding of people with severe AD and potentially improve the quality of care that is received
Utilización de modelos de reflectancia como nexo entre muestras foliares y la cobertura forestal: aplicación a datos hiperespectrales
[ES] El presente trabajo demuestra la utilización de
modelos de simulación de la cobertura forestal
mediante su aplicación a datos hiperespectrales
del sensor aerotransportado CASI. Los modelos
SAIL y Kuusk permiten ser utilizados como
nexo de unión entre los niveles de hoja y de
cobertura: las relaciones a nivel de hoja
obtenidas entre índices ópticos y bioindicadores
de estrés, como contenido clorofílico o
fluorescencia clorofílica, pueden ser
transformadas a un nivel superior de cobertura
mediante la utilización de dichos modelos.
Finalmente se realiza una demostración de la
utilización de modelos de cobertura a través de
los resultados obtenidos en el proyecto
Bioindicators of Forest Sustainability,
desarrollado en 12 zonas de Acer saccharum M.
localizadas en Ontario (Canadá) donde se
obtuvieron medidas de campo de muestras
foliares, así como datos hiperespectrales del
sensor aerotransportado CASI en 1997, 1998 y
1999. Los indices ópticos desarrollados a nivel
de hoja fueron aplicados, a través de modelos de
cobertura, a los datos de reflectancia obtenidos
por CASI de 2 m de resolución espacial y 72
bandas[EN] This paper demonstrates the use and
applications of Canopy Reflectance Models
(CR) with airborne hyperspectral CASI data.
SAIL and Kuusk canopy reflectance models are
the link between the leaf and canopy levels:
leaf-level relationships obtained between optical
indices and stress bioindicators, such as
chlorophyll content and chlorophyll
fluorescence can be scaled-up to the canopy
level using canopy reflectance models. The
application of canopy reflectance models is
demonstrated with the results obtained in the
Bioindicators of Forest Sustainability Project.
The work was carried out in 12 study areas of
Acer saccharum M. in the Algoma Region,
Ontario (Canada), where field measurements
and hyperspectral CASI imagery have been
collected in 1997, 1998 and 1999 deployments.
Single leaf reflectance and transmittance,
chlorophyll and carotenoid content, and
chlorophyll fluorescence of broad leaves were
measured. The physiological indices and
derivative analysis indices extracted from leaf
spectral reflectance were tested at canopy level
using CASI data of 72 channels and 2 m spatial
resolution.Peer reviewe
Muscle Activated 3D Printed Prosthetic Arm
Due to the rapid growth of children and the cost of myoelectric technology, children are not given the same opportunities to use myoelectric prosthetics as adults. The Muscle Activated Prosthesis (MAP) team seeks to reconcile this by creating an affordable, trans-radial, myoelectric prosthesis that utilizes the flexibility of 3D printing technology for a fourteen-year-old congenital amputee named Lily. The MAP team has completed the design and prototype of a myoelectric prosthesis with a material cost of approximately 10,000-$20,000 cost of clinically accepted myoelectric prosthetic upper limbs. The 3D printed prosthetic arm prototype incorporates electromyography (EMG) electrodes, a motor and tendon system, an open-source prosthetic hand design, a custom printed circuit board (PCB), and lithium-ion battery power. The opening and closing of the prosthetic hand is controlled by the myoelectric signals from the user’s forearm contractions which can be tested by the team using our adaptive prosthetic attachment. All these components result in an affordable prosthetic that has the potential for customization and adaptation to different sized limbs.
Funding for this work provided by The Collaboratory for Strategic Partnerships and Applied Research.https://mosaic.messiah.edu/engr2022/1009/thumbnail.jp
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The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model
Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed
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Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).
The 2013 US Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are not known to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male nondeployed Regular US Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naive Bayes, random forests, support vector regression and elastic net penalized regression) were explored. Of the Army suicides in 2004-2009, 41.5% occurred among 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100 000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded
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