Facilitating personal development for public involvement in health-care education and research: a co-produced pilot study in one UK higher education institute

BACKGROUND: Public involvement in the education of students enrolled on higher education programmes has gained impetus. For students enrolled on professional health-care programmes and health-related modules in the UK, there is also a requirement by professional bodies to include "service user" involvement in preparation for entry to a professional health-care register and continuing professional development. Actively involving patients and members of the public in research is also a requirement by many research funders. In this article, the term Patient and Public Involvement (PPI) will be used throughout to include lay members, volunteers, user and carers. OBJECTIVES: A unique pilot study was introduced across a health faculty to integrate PPI in a deliberate way. It aimed to provide an educational, focused programme of events that was meaningful to develop and inform peoples' knowledge, skills and confidence for their involvement in the health faculty. DESIGN: PPI members volunteered to sit on a steering group to determine the educational journey; the outcomes of three focus groups with PPI members (N = 32) and academics informed the programme content which included a range of workshops covering the exploration of public roles and barriers to involvement, introduction to research and interviewing skills. RESULTS: The workshops were well attended, and outcomes indicated the importance of co-production when designing, delivering and evaluating programmes. DISCUSSION: Co-production underpinned this pilot study, resulting in a programme which was meaningfully received by public contributors. RECOMMENDATIONS: Co-production was seen as integral to this research to ensure that outcomes were indeed "fit for purpose"

Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

<p>Abstract</p> <p>Background</p> <p>Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks.</p> <p>Methods</p> <p>Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008.</p> <p>Results</p> <p>NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley.</p> <p>Conclusions</p> <p>We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years.</p

A possible signature of the influence of tidal perturbations in dwarf galaxy scaling relations

Dwarf galaxies are excellent cosmological probes, because their shallow potential wells make them very sensitive to the key processes that drive galaxy evolution, including baryonic feedback, tidal interactions, and ram pressure stripping. However, some of the key parameters of dwarf galaxies, which help trace the effects of these processes, are still debated, including the relationship between their sizes and masses. We re-examine the Fornax Cluster dwarf population from the point of view of isomass-radius–stellar mass relations (IRSMRs) using the Fornax Deep Survey Dwarf galaxy Catalogue, with the centrally located (among dwarfs) 3.63M☉ pc-2 isodensity radius defining our fiducial relation. This relation is a powerful diagnostic tool for identifying dwarfs with unusual structure, as dwarf galaxies’ remarkable monotonicity in light profile shapes, as a function of stellar mass, reduces the relation’s scatter tremendously. By examining how different dwarf properties (colour, 10th nearest neighbour distance, etc.) correlate with distance from our fiducial relation, we find a significant population of structural outliers with comparatively lower central mass surface density and larger half-light-radii, residing in locally denser regions in the cluster, albeit with similar red colours. We propose that these faint, extended outliers likely formed through tidal disturbances, which make the dwarfs more diffuse, but with little mass-loss. Comparing these outliers with ultra-diffuse galaxies (UDGs), we find that the term UDG lacks discriminatory power; UDGs in the Fornax Cluster lie both on and off of IRSMRs defined at small radii, while IRSMR outliers with masses below ∼ 107.5M☉ are excluded from the UDG classification due to their small effective radii

Carbon related defects in irradiated silicon revisited

Electronic structure calculations employing hybrid functionals are used to gain insight into the interaction of carbon (C) atoms, oxygen (O) interstitials, and self-interstitials in silicon (Si). We calculate the formation energies of the C related defects C(i)(Si(I)), C(i)O(i), C(i)C(s), and C(i)O(i)(Si(I)) with respect to the Fermi energy for all possible charge states. The C(i)(Si(I))(2+) state dominates in almost the whole Fermi energy range. The unpaired electron in the C(i)O(i)(+) state is mainly localized on the C interstitial so that spin polarization is able to lower the total energy. The three known atomic configurations of the C(i)C(s) pair are reproduced and it is demonstrated that hybrid functionals yield an improved energetic order for both the A and B-types as compared to previous theoretical studies. Different structures of the C(i)O(i)(Si(I)) cluster result for positive charge states in dramatically distinct electronic states around the Fermi energy and formation energies

Why is it difficult to implement e-health initiatives? A qualitative study

&lt;b&gt;Background&lt;/b&gt; The use of information and communication technologies in healthcare is seen as essential for high quality and cost-effective healthcare. However, implementation of e-health initiatives has often been problematic, with many failing to demonstrate predicted benefits. This study aimed to explore and understand the experiences of implementers - the senior managers and other staff charged with implementing e-health initiatives and their assessment of factors which promote or inhibit the successful implementation, embedding, and integration of e-health initiatives.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methods&lt;/b&gt; We used a case study methodology, using semi-structured interviews with implementers for data collection. Case studies were selected to provide a range of healthcare contexts (primary, secondary, community care), e-health initiatives, and degrees of normalization. The initiatives studied were Picture Archiving and Communication System (PACS) in secondary care, a Community Nurse Information System (CNIS) in community care, and Choose and Book (C&#38;B) across the primary-secondary care interface. Implementers were selected to provide a range of seniority, including chief executive officers, middle managers, and staff with 'on the ground' experience. Interview data were analyzed using a framework derived from Normalization Process Theory (NPT).&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt; Twenty-three interviews were completed across the three case studies. There were wide differences in experiences of implementation and embedding across these case studies; these differences were well explained by collective action components of NPT. New technology was most likely to 'normalize' where implementers perceived that it had a positive impact on interactions between professionals and patients and between different professional groups, and fit well with the organisational goals and skill sets of existing staff. However, where implementers perceived problems in one or more of these areas, they also perceived a lower level of normalization.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt; Implementers had rich understandings of barriers and facilitators to successful implementation of e-health initiatives, and their views should continue to be sought in future research. NPT can be used to explain observed variations in implementation processes, and may be useful in drawing planners' attention to potential problems with a view to addressing them during implementation planning

Approaches to the evaluation of outbreak detection methods

BACKGROUND: An increasing number of methods are being developed for the early detection of infectious disease outbreaks which could be naturally occurring or as a result of bioterrorism; however, no standardised framework for examining the usefulness of various outbreak detection methods exists. To promote comparability between studies, it is essential that standardised methods are developed for the evaluation of outbreak detection methods. METHODS: This analysis aims to review approaches used to evaluate outbreak detection methods and provide a conceptual framework upon which recommendations for standardised evaluation methods can be based. We reviewed the recently published literature for reports which evaluated methods for the detection of infectious disease outbreaks in public health surveillance data. Evaluation methods identified in the recent literature were categorised according to the presence of common features to provide a conceptual basis within which to understand current approaches to evaluation. RESULTS: There was considerable variation in the approaches used for the evaluation of methods for the detection of outbreaks in public health surveillance data, and appeared to be no single approach of choice. Four main approaches were used to evaluate performance, and these were labelled the Descriptive, Derived, Epidemiological and Simulation approaches. Based on the approaches identified, we propose a basic framework for evaluation and recommend the use of multiple approaches to evaluation to enable a comprehensive and contextualised description of outbreak detection performance. CONCLUSION: The varied nature of performance evaluation demonstrated in this review supports the need for further development of evaluation methods to improve comparability between studies. Our findings indicate that no single approach can fulfil all evaluation requirements. We propose that the cornerstone approaches to evaluation identified provide key contributions to support internal and external validity and comparability of study findings, and suggest these be incorporated into future recommendations for performance assessment