Using evidence to inform health policy: case study

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mirt: A Multidimensional Item Response Theory Package for the R Environment

Item response theory (IRT) is widely used in assessment and evaluation research to explain how participants respond to item level stimuli. Several R packages can be used to estimate the parameters in various IRT models, the most flexible being the ltm (Rizopoulos 2006), eRm (Mair and Hatzinger 2007), and MCMCpack (Martin, Quinn, and Park 2011) packages. However these packages have limitations in that ltm and eRm can only analyze unidimensional IRT models effectively and the exploratory multidimensional extensions available in MCMCpack requires prior understanding of Bayesian estimation convergence diagnostics and are computationally intensive. Most importantly, multidimensional confirmatory item factor analysis methods have not been implemented in any R package. The mirt package was created for estimating multidimensional item response theory parameters for exploratory and confirmatory models by using maximum-likelihood meth- ods. The Gauss-Hermite quadrature method used in traditional EM estimation (e.g., Bock and Aitkin 1981) is presented for exploratory item response models as well as for confirmatory bifactor models (Gibbons and Hedeker 1992). Exploratory and confirmatory models are estimated by a stochastic algorithm described by Cai (2010a,b). Various program comparisons are presented and future directions for the package are discussed

Generating Adaptive and Non-Adaptive Test Interfaces for Multidimensional Item Response Theory Applications

Computerized adaptive testing (CAT) is a powerful technique to help improve measurement precision and reduce the total number of items required in educational, psychological, and medical tests. In CATs, tailored test forms are progressively constructed by capitalizing on information available from responses to previous items. CAT applications primarily have relied on unidimensional item response theory (IRT) to help select which items should be administered during the session. However, multidimensional CATs may be constructed to improve measurement precision and further reduce the number of items required to measure multiple traits simultaneously. A small selection of CAT simulation packages exist for the R environment; namely, catR (Magis and Raîche 2012), catIrt (Nydick 2014), and MAT (Choi and King 2014). However, the ability to generate graphical user interfaces for administering CATs in realtime has not been implemented in R to date, support for multidimensional CATs have been limited to the multidimensional three-parameter logistic model, and CAT designs were required to contain IRT models from the same modeling family. This article describes a new R package for implementing unidimensional and multidimensional CATs using a wide variety of IRT models, which can be unique for each respective test item, and demonstrates how graphical user interfaces and Monte Carlo simulation designs can be constructed with the mirtCAT package

Multi-locus analysis of human infective Cryptosporidium species and subtypes using ten novel genetic loci

Background: Cryptosporidium is a protozoan parasite that causes diarrheal illness in a wide range of hosts including humans. Two species, C. parvum and C. hominis are of primary public health relevance. Genome sequences of these two species are available and show only 3-5% sequence divergence. We investigated this sequence variability, which could correspond either to sequence gaps in the published genome sequences or to the presence of species-specific genes. Comparative genomic tools were used to identify putative species-specific genes and a subset of these genes was tested by PCR in a collection of Cryptosporidium clinical isolates and reference strains. Results: The majority of the putative species-specific genes examined were in fact common to C. parvum and C. hominis. PCR product sequence analysis revealed interesting SNPs, the majority of which were species-specific. These genetic loci allowed us to construct a robust and multi-locus analysis. The Neighbour-Joining phylogenetic tree constructed clearly discriminated the previously described lineages of Cryptosporidium species and subtypes. Conclusions: Most of the genes identified as being species specific during bioinformatics in Cryptosporidium sp. are in fact present in multiple species and only appear species specific because of gaps in published genome sequences. Nevertheless SNPs may offer a promising approach to studying the taxonomy of closely related species of Cryptosporidia

Two-dimensional colloidal fluids exhibiting pattern formation

Fluids with competing short range attraction and long range repulsive interactions between the particles can exhibit a variety of microphase separated structures. We develop a lattice-gas (generalised Ising) model and analyse the phase diagram using Monte Carlo computer simulations and also with density functional theory (DFT). The DFT predictions for the structures formed are in good agreement with the results from the simulations, which occur in the portion of the phase diagram where the theory predicts the uniform fluid to be linearly unstable. However, the mean-field DFT does not correctly describe the transitions between the different morphologies, which the simulations show to be analogous to micelle formation. We determine how the heat capacity varies as the model parameters are changed. There are peaks in the heat capacity at state points where the morphology changes occur. We also map the lattice model onto a continuum DFT that facilitates a simplification of the stability analysis of the uniform fluid.Comment: 13 pages, 15 figure

Is the Scottish population living dangerously? Prevalence of multiple risk factors: the Scottish Health Survey 2003

<b>Background:</b> Risk factors are often considered individually, we aimed to investigate the prevalence of combinations of multiple behavioural risk factors and their association with socioeconomic determinants.<p></p> <b>Methods:</b> Multinomial logistic regression was used to model the associations between socioeconomic factors and multiple risk factors from data in the Scottish Health Survey 2003. Prevalence of five main behavioural risk factors - smoking alcohol, diet, overweight/obesity, and physical inactivity, and the odds in relation to demographic, individual and area socioeconomic factors.<p></p> <b>Results:</b> Full data were available on 6,574 subjects (80.7% of the survey sample). Nearly the whole adult population (97.5%) reported to have at least one behavioural risk factor; while 55% have three or more risk factors; and nearly 20% have four or all five risk factors. The most important determinants for having four or five multiple risk factors were low educational attainment which conferred around a 3-fold increased odds compared to high education; and residence in the most deprived communities (relative to least deprived) which had greater than 3-fold increased odds.<p></p> <b>Conclusions:</b> The prevalence of multiple behavioural risk factors was high and the prevalence of absence of all risk factors very low. These behavioural patterns were socioeconomically determined. Policy to address factors needs to be joined up and better consider underlying socioeconomic circumstances.<p></p&gt

The needs of young carers and the role of the school nurse

Young carers provide a significant contribution to society in their caring role, which is in line with the UK Government’s Big Society agenda. In contrast with their contribution to society, young carers have huge associated costs related to poor outcomes and the numbers that end up not in employment, education or training (NEET). Missing school due to caring responsibilities is likely to have an effect on future education and job prospects. Understanding the impact of the caring role on the school experience of young carers will enable school nurses to provide appropriate support for young carers, improving their school experience and subsequent outcomes

Aspirated capacitor measurements of air conductivity and ion mobility spectra

Measurements of ions in atmospheric air are used to investigate atmospheric electricity and particulate pollution. Commonly studied ion parameters are (1) air conductivity, related to the total ion number concentration, and (2) the ion mobility spectrum, which varies with atmospheric composition. The physical principles of air ion instrumentation are long-established. A recent development is the computerised aspirated capacitor, which measures ions from (a) the current of charged particles at a sensing electrode, and (b) the rate of charge exchange with an electrode at a known initial potential, relaxing to a lower potential. As the voltage decays, only ions of higher and higher mobility are collected by the central electrode and contribute to the further decay of the voltage. This enables extension of the classical theory to calculate ion mobility spectra by inverting voltage decay time series. In indoor air, ion mobility spectra determined from both the novel voltage decay inversion, and an established voltage switching technique, were compared and shown to be of similar shape. Air conductivities calculated by integration were: 5.3 +- 2.5 fS/m and 2.7 +- 1.1 fS/m respectively, with conductivity determined to be 3 fS/m by direct measurement at a constant voltage. Applications of the new Relaxation Potential Inversion Method (RPIM) include air ion mobility spectrum retrieval from historical data, and computation of ion mobility spectra in planetary atmospheres.Comment: To be published in Review of Scientific Instrument