Application of feedback principles to marking proformas increases student efficacy, perceived utility of feedback, and likelihood of use

Pedagogical and psychological literature identifies numerous factors contributing to feedback effectiveness, including type, frequency, and specificity. Despite this wealth of research, feedback practice at universities is often reported as problematic or poor by students despite lecturers perceiving their feedback as useful. The present research employed a quantitative counterbalanced experimental design to compare the perceived utility of a pedagogically informed feedback proforma, designed to provide detailed, timely, and constructive feedback, to standard practice. Results suggest that the presentation of feedback is important to students; more functional and comprehensible feedback increases the likelihood of students using the feedback provided, and can reduce likely marking time per script without compromising perceived feedback quality. Further to this, post-submission feedback proformas increase students’ confidence in their ability to complete the assignment when provided alongside the assignment title. In summary, the research supports the application of principles of feedback in the provision of summative feedback to enhance students’ likelihood of use, perceived value of the feedback received, and confidence

A ‘new life’ story or ‘delaying the inevitable’? Exploring older people's narratives during exercise uptake

Objectives: The purpose of this study was to examine narratives of ageing in a clinical population embarking on a physical activity/exercise programme, exploring if and how their narratives changed throughout their experiences. Design: The study employed a longitudinal narrative approach. Method: Participants were six sedentary individuals aged between 78 and 89 years who were enrolled on an exercise programme for older adults. During the course of the 32-week programme participants took part in multiple interviews focused on their attitudes towards physical activity and their physical self-perceptions and identity. A structural narrative analysis was used to focus on the progression of the plot outlined in each participant's story. Results: Our results suggested the emergence of two comparative narratives, with each demonstrated in the stories told by three participants. The first narrative is one of decelerated decline, in which the exercise programme is assimilated or fitted into the existing life narrative, but little is made of the personal meaning of being active. In the second narrative, participation in exercise prompted participants to re-story their ageing narratives, changing from initially accepting the decline they associated with an ageing body, to the prospect of gaining some control. While this increased sense of control may intuitively seem positive, participants initially described a number of existential challenges and dilemmas as well as their resolution of these. Conclusion: Participants' emergent stories highlighted that while older adults may perceive exercise positively, their existing narratives of decline may be resistant to change. Where changes do occur, it is important for health professionals to recognize the associated difficulties with gaining increased responsibility for health

Inequalities and inclusion in exercise referral schemes: a mixed-method multi-scheme analysis

Physical activity prescription, commonly through exercise referral schemes, is an established disease prevention and management pathway. There is considerable heterogeneity in terms of uptake, adherence, and outcomes, but because within-scheme analyses dominate previous research, there is limited contextual understanding of this variance. Both the impact of schemes on health inequalities and best practices for inclusion of at-risk groups are unclear. To address this, we modelled secondary data from the multi-scheme National Referral Database, comprising 23,782 individuals across 14 referral schemes, using a multilevel Bayesian inference approach. Scheme-level local demographics identified over-sampling in uptake; on the basis of uptake and completion data, more inclusive schemes (n = 4) were identified. Scheme coordinators were interviewed, and data were analyzed using a grounded theory approach. Inequalities presented in a nuanced way. Schemes showed promise for engaging populations at greater risk of poor health (e.g., those from more deprived areas or of an ethnic minority background). However, the completion odds were lower for those with a range of complex circumstances (e.g., a mental health-related referral). We identified creative best practices for widening access (e.g., partnership building), maintaining engagement (e.g., workforce diversity), and tailoring support, but recommend changes to wider operational contexts to ensure such approaches are viable

Should we ‘hug a hoodie’? Protocol for a systematic review and meta-analysis of interventions with young people not in employment, education or training (so-called NEETs)

Background: Whilst the majority of young people succeed in education and make a positive transition to the world of work and adult life, recent statistics identify that youth comprise 40% of the world's unemployed, equating to nearly 75 million individuals. These numbers are associated with both decreased economic activity and adverse well-being, with accompanying social, health and financial costs. As a result, a wide range of providers have implemented interventions targeting this population; however, their relative effectiveness is unknown. This is exacerbated by a diverse literature base, the delivery of provision and policy across multiple sectors and disparate approaches to programme evaluation. Methods and design: We will undertake a systematic review of interventions targeting youth not in employment, education or training (NEET) populations. Only randomised and non-randomised controlled trials will be included. The objectives of the review will be to: (i) systematically review, synthesise and quality appraise experimental evidence on the effects of interventions with NEET young people, (ii) estimate effects on current NEET status, well-being and other relevant psychological and behavioural outcomes, (iii) investigate potential variation in intervention effects among sub-groups stratified by pre-trial duration of current status, socioeconomic status, gender, sub-classifications of NEET individuals and intervention components (e.g. type, frequency, duration, provider and setting) and (iv) assess the robustness of results in separate sensitivity analyses that exclude studies with higher risk of bias (e.g. in terms of study quality) or follow-up length. A rigorous literature search of English language publications post-1990 will be conducted using the following electronic databases: Medline, Embase, PsycINFO, ERIC, EPPI-Centre (Bibliomap), Social Science Citation Index, British Education Index, Conference Proceedings Index, Dissertation Abstracts, Popline and grey literature collections (e.g. GLADNET). These database searches will be supplemented with hand searching, requests for unpublished literature and website searches. Discussion: A report and executive summary will be developed by the research team with input from consultant stakeholders to aid translation of the findings into practice. The research will be disseminated at national and international conferences and submitted for peer-reviewed publication. Systematic review registration: PROSPERO CRD4201400753

A review of automated sleep stage scoring based on physiological signals for the new millennia

Background and Objective: Sleep is an important part of our life. That importance is highlighted by the multitude of health problems which result from sleep disorders. Detecting these sleep disorders requires an accurate interpretation of physiological signals. Prerequisite for this interpretation is an understanding of the way in which sleep stage changes manifest themselves in the signal waveform. With that understanding it is possible to build automated sleep stage scoring systems. Apart from their practical relevance for automating sleep disorder diagnosis, these systems provide a good indication of the amount of sleep stage related information communicated by a specific physiological signal. Methods: This article provides a comprehensive review of automated sleep stage scoring systems, which were created since the year 2000. The systems were developed for Electrocardiogram (ECG), Electroencephalogram (EEG), Electrooculogram (EOG), and a combination of signals. Results: Our review shows that all of these signals contain information for sleep stage scoring. Conclusions: The result is important, because it allows us to shift our research focus away from information extraction methods to systemic improvements, such as patient comfort, redundancy, safety and cost

Application of nonlinear methods to discriminate fractionated electrograms in paroxysmal versus persistent atrial fibrillation

Background and Objective: Complex fractionated atrial electrograms (CFAE) may contain information concerning the electrophysiological substrate of atrial fibrillation (AF); therefore they are of interest to guide catheter ablation treatment of AF. Electrogram signals are shaped by activation events, which are dynamical in nature. This makes it difficult to establish those signal properties that can provide insight into the ablation site location. Nonlinear measures may improve information. To test this hypothesis, we used nonlinear measures to analyze CFAE. Methods: CFAE from several atrial sites, recorded for a duration of 16 s, were acquired from 10 patients with persistent and 9 patients with paroxysmal AF. These signals were appraised using non-overlapping windows of 1-, 2- and 4-s durations. The resulting data sets were analyzed with Recurrence Plots (RP) and Recurrence Quantification Analysis (RQA). The data was also quantified via entropy measures. Results: RQA exhibited unique plots for persistent versus paroxysmal AF. Similar patterns were observed to be repeated throughout the RPs. Trends were consistent for signal segments of 1 and 2 s as well as 4 s in duration. This was suggestive that the underlying signal generation process is also repetitive, and that repetitiveness can be detected even in 1-s sequences. The results also showed that most entropy metrics exhibited higher measurement values (closer to equilibrium) for persistent AF data. It was also found that Determinism (DET), Trapping Time (TT), and Modified Multiscale Entropy (MMSE), extracted from signals that were acquired from locations at the posterior atrial free wall, are highly discriminative of persistent versus paroxysmal AF data. Conclusions: Short data sequences are sufficient to provide information to discern persistent versus paroxysmal AF data with a significant difference, and can be useful to detect repeating patterns of atrial activation

Comparing adaptive and fixed bandwidth-based kernel density estimates in spatial cancer epidemiology

Background: Monitoring spatial disease risk (e.g. identifying risk areas) is of great relevance in public health research, especially in cancer epidemiology. A common strategy uses case-control studies and estimates a spatial relative risk function (sRRF) via kernel density estimation (KDE). This study was set up to evaluate the sRRF estimation methods, comparing fixed with adaptive bandwidth-based KDE, and how they were able to detect ‘risk areas’ with case data from a population-based cancer registry. Methods: The sRRF were estimated within a defined area, using locational information on incident cancer cases and on a spatial sample of controls, drawn from a high-resolution population grid recognized as underestimating the resident population in urban centers. The spatial extensions of these areas with underestimated resident population were quantified with population reference data and used in this study as ‘true risk areas’. Sensitivity and specificity analyses were conducted by spatial overlay of the ‘true risk areas’ and the significant (α=.05) p-contour lines obtained from the sRRF. Results: We observed that the fixed bandwidth-based sRRF was distinguished by a conservative behavior in identifying these urban ‘risk areas’, that is, a reduced sensitivity but increased specificity due to oversmoothing as compared to the adaptive risk estimator. In contrast, the latter appeared more competitive through variance stabilization, resulting in a higher sensitivity, while the specificity was equal as compared to the fixed risk estimator. Halving the originally determined bandwidths led to a simultaneous improvement of sensitivity and specificity of the adaptive sRRF, while the specificity was reduced for the fixed estimator. Conclusion: The fixed risk estimator contrasts with an oversmoothing tendency in urban areas, while overestimating the risk in rural areas. The use of an adaptive bandwidth regime attenuated this pattern, but led in general to a higher false positive rate, because, in our study design, the majority of true risk areas were located in urban areas. However, there is a strong need for further optimizing the bandwidth selection methods, especially for the adaptive sRRF.<br

Evaluation of linear and quadratic modal analysis for a partitioned FSI solver

In this paper, linear and quadratic modal approximations of elastodynamic solid deformation in FSI problems are considered. Firstly, the theory of quadratic exten- sion of modal analysis presented in [1] is laid out. The quadratic and linear approximations are then benchmarked against full FEM analysis in various test cases. These are chosen to be representative of flutter considerations in the aerospace field. The quadratic ap- proximation is shown to produce a markedly better prediciton of solid deformation for small to medium deflections

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

Background: There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods: Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results: With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion: High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage.<br