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A disproportionate number of people with mental ill-health experience social exclusion. Appropriate measurement tools are required to progress opportunities to improve social inclusion. We have developed a novel measure, the Filia Social Inclusion Measure (F-SIM). Here we aimed to present a more concise, easy-to-use form, while retaining its measurement integrity by (i) refining the F-SIM using traditional and contemporary item-reduction techniques; and (ii) testing the psychometric properties of the reduced measure.
Five hundred and six participants completed the F-SIM, younger and older groups of people with serious mental illness (including psychosis, mood, anxiety disorders) and same-aged community counterparts. The F-SIM was completed at baseline and 2-week follow-up, alongside other measures (including social inclusion, loneliness). The F-SIM was refined using multidimensional scaling network analysis, confirmatory factor analysis and item response theory. The psychometric evaluation included assessment of dimensionality, internal consistency, test–retest reliability, discriminant ability and construct validity.
The F-SIM was reduced from 135-items to 16; with 4-items in each domain of housing and neighbourhood, finances, employment and education and social participation and relationships. Psychometric properties were sound, including strong internal consistency within domains (all α > 0.85) and excellent overall (α = 0.92). Test–retest reliability was also high (γ = 0.90). Differences between groups were observed; clinical subgroups consistently reported lower levels of social inclusion compared to community counterparts.
The F-SIM16 is a sound, reliable, brief self-report measure of social inclusion suitable for use in clinical and research settings. It has the potential to evaluate the effectiveness of interventions, and aid in fostering targeted and personalised needs-based care.
One of the main capabilities of atom probe tomography (APT) is the ability to not only identify but also characterize early stages of precipitation at length scales that are not achievable by other techniques. One of the most popular methods to identify nanoscale clustering in APT data, based on the density-based spatial clustering of applications with noise (DBSCAN), is used extensively in many branches of research. However, it is common that not all of the steps leading to the selection of certain parameters used in the analysis are reported. Without knowing the rationale behind parameter selection, it may be difficult to compare cluster parameters obtained by different researchers. In this work, a simple open-source tool, PosgenPy, is used to justify cluster search parameter selection via providing a systematic sweep through parameter values with multiple randomizations to minimize a false-positive cluster ratio. The tool is applied to several different microstructures: a simulated material system and two experimental datasets from a low-alloy steel . The analyses show how values for the various parameters can be selected to ensure that the calculated cluster number density and cluster composition are accurate.
Posthumanism is a growing field of interdisciplinary study that has emerged, principally in the last 20 years, as a broad church which seeks to reconceptualize human beings’ relationships with the world. At its heart, Posthumanism seeks to destabilize and question the category of ‘human’, which it sees as having previously been treated as transcendent and ahistorical. In its place, the figure of the posthuman aims to capture the complex and situated nature of our species’ existence, outside traditional dichotomies like culture and nature, mind and body, person and environment, and so on. From animal studies (e.g. Despret 2016; Wolfe 2009), via a rekindled attention to the material world (Coole & Frost 2010) to the cutting edge of quantum physics (Barad 2007), Posthumanism draws on a diverse range of inspiration (Ferrando 2019). This diversity also covers a significant internal dissonance and difference, with some posthumanists taking relational approaches, others arguing for the essential qualities of things, some focusing primarily on material things without humans and others calling for explicitly feminist investigations.
Is the ‘material’ or ‘ontological’ turn a major new paradigm in archaeological theory? Or is it another iteration of the cycle of piecemeal innovation which has created a very fragmented discipline? While there are insights from recent scholarship in this vein which are certainly important, this paper will err toward the latter view. Even though ‘symmetrical’ and other object-agency approaches are still growing in mainstream archaeological debate, much of the source literature upon which they draw has been around for several decades, and accumulated a fair amount of critique. At the very least, therefore, we need to learn from the way the materiality debate is playing out in other sub-fields. Beyond that, I will argue, we should go back to the turn before this one—the practice turn—and explore that road a bit more thoroughly, if we are to find the most useful approaches to develop in the future.
The aims of anaesthesia for cardiac surgery are: prevention of perioperative cardiac ischaemia and arrhythmias, tight haemodynamic control, avoidance of non-cardiac complications and early tracheal extubation. This chapter deals with the management of low-risk patients undergoing elective CABG surgery.
To address the increasing demand for the use of simulation for assessment, our objective was to review the literature pertaining to simulation-based assessment and develop a set of consensus-based expert-informed recommendations on the use of simulation-based assessment as presented at the 2019 Canadian Association of Emergency Physicians (CAEP) Academic Symposium on Education.
A panel of Emergency Medicine (EM) physicians from across Canada, with leadership roles in simulation and/or assessment, was formed to develop the recommendations. An initial scoping literature review was conducted to extract principles of simulation-based assessment. These principles were refined via thematic analysis, and then used to derive a set of recommendations for the use of simulation-based assessment, organized by the Consensus Framework for Good Assessment. This was reviewed and revised via a national stakeholder survey, and then the recommendations were presented and revised at the consensus conference to generate a final set of recommendations on the use of simulation-based assessment in EM.
We developed a set of recommendations for simulation-based assessment, using consensus-based expert-informed methods, across the domains of validity, reproducibility, feasibility, educational and catalytic effects, acceptability, and programmatic assessment. While the precise role of simulation-based assessment will be a subject of continued debate, we propose that these recommendations be used to assist educators and program leaders as they incorporate simulation-based assessment into their programs of assessment.
In this paper, we seek to explore the ways in which landscapes become venues not only for manipulations of the past in a present, but also for shaping possible futures. Considerations of temporality and being in the landscape have been more strongly focused on the past and social memory than the future, anticipation and projectivity, but these are vital considerations if we are to preserve the possibility that past people imagined alternative futures. A fruitful archaeological context for an exploration of past futures can be found in the choices people made during the late Iron Age and Roman period in Britain, which has an increasingly rich and high-resolution material record for complex changes and continuities during a period of cultural interactions and imperial power dynamics. More specifically, recent research into the architectural and material practices evident on rural settlement sites and across landscapes forces us to challenge preconceptions about the reactive/reactionary culture of rural societies. Case-studies from Kent and the West Country will be deployed to develop the argument that in the materializing of time, the future has a very significant part to play.
Vulnerability to depression can be measured in different ways. We here examine how genetic risk factors are inter-related for lifetime major depression (MD), self-report current depressive symptoms and the personality trait Neuroticism.
We obtained data from three population-based adult twin samples (Virginia n = 4672, Australia #1 n = 3598 and Australia #2 n = 1878) to which we fitted a common factor model where risk for ‘broadly defined depression’ was indexed by (i) lifetime MD assessed at personal interview, (ii) depressive symptoms, and (iii) neuroticism. We examined the proportion of genetic risk for MD deriving from the common factor v. specific to MD in each sample and then analyzed them jointly. Structural equation modeling was conducted in Mx.
The best fit models in all samples included additive genetic and unique environmental effects. The proportion of genetic effects unique to lifetime MD and not shared with the broad depression common factor in the three samples were estimated as 77, 61, and 65%, respectively. A cross-sample mega-analysis model fit well and estimated that 65% of the genetic risk for MD was unique.
A large proportion of genetic risk factors for lifetime MD was not, in the samples studied, captured by a common factor for broadly defined depression utilizing MD and self-report measures of current depressive symptoms and Neuroticism. The genetic substrate for MD may reflect neurobiological processes underlying the episodic nature of its cognitive, motor and neurovegetative manifestations, which are not well indexed by current depressive symptom and neuroticism.
The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the ~198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999–2010 provided most of the outlines. Their total extent is estimated as 726 800 ± 34 000 km2. The uncertainty, about ±5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be combined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.