Detecting and measuring deprivation in primary care: development, validity and reliability of a self-reported questionnaire - the DiPCare-Q

Background: General practitioners play a central role in taking deprivation into consideration when caring for patients in primary care. Validated questions to identify deprivation in primary-care practices are still lacking. For both clinical and research purposes, this study therefore aims to develop and validate a standardized instrument measuring both material and social deprivation at an individual level. Methods: The Deprivation in Primary Care Questionnaire (DiPCare-Q) was developed using qualitative and quantitative approaches between 2008 and 2011. A systematic review identified 199 questions related to deprivation. Using judgmental item quality, these were reduced to 38 questions. Two focus groups (primary-care physicians, and primary-care researchers), structured interviews (10 laymen), and think aloud interviews (eight cleaning staff) assured face validity. Item response theory analysis was then used to derive the DiPCare-Q index using data obtained from a random sample of 200 patients who were to complete the questionnaire a second time over the phone. For construct and criterion validity, the final 16 questions were administered to a random sample of 1,898 patients attending one of 47 different private primary-care practices in western Switzerland (validation set) along with questions on subjective social status (subjective SES ladder), education, source of income, welfare status, and subjective poverty. Results: Deprivation was defined in three distinct dimensions (table); material deprivation (eight items), social deprivation (five items) and health deprivation (three items). Item consistency was high in both the derivation (KR20 = 0.827) and the validation set (KR20 = 0.778). The DiPCare-Q index was reliable (ICC = 0.847). For construct validity, we showed the DiPCare-Q index to be correlated to patients' estimation of their position on the subjective SES ladder (rs = 0.539). This position was correlated to both material and social deprivation independently suggesting two separate mechanisms enhancing the feeling of deprivation. Conclusion: The DiPCare-Q is a rapid, reliable and validated instrument useful for measuring both material and social deprivation in primary care. Questions from the DiPCare-Q are easy to use when investigating patients' social history and could improve clinicians' ability to detect underlying social distress related to deprivation.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Estimation of the noisy component of anatomical backgrounds.

The knowledge of the relationship that links radiation dose and image quality is a prerequisite to any optimization of medical diagnostic radiology. Image quality depends, on the one hand, on the physical parameters such as contrast, resolution, and noise, and on the other hand, on characteristics of the observer that assesses the image. While the role of contrast and resolution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging uniform test objects, even though real images contain anatomical backgrounds whose statistical nature is much different from test objects used to assess system noise. The goal of this study was to demonstrate the importance of variations in background anatomy by quantifying its effect on a series of detection tasks. Several types of mammographic backgrounds and signals were examined by psychophysical experiments in a two-alternative forced-choice detection task. According to hypotheses concerning the strategy used by the human observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision theory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed that the observer's behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. This dual nature of the anatomy is quantified. It is shown that its effect varies according to its amplitude and the profile of the object being detected. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by increasing the dose will not improve task performance. This observation indicates that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, more contrast, or less dose.

Lag-one autocorrelation in short series: Estimation and hypothesis testing

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is studied. The performance of the ten lag-one autocorrelation estimators is compared in terms of Mean Square Error (combining bias and variance) using data series generated by Monte Carlo simulation. The results show that there is not a single optimal estimator for all conditions, suggesting that the estimator ought to be chosen according to sample size and to the information available of the possible direction of the serial dependence. Additionally, the probability of labelling an actually existing autocorrelation as statistically significant is explored using Monte Carlo sampling. The power estimates obtained are quite similar among the tests associated with the different estimators. These estimates evidence the small probability of detecting autocorrelation in series with less than 20 measurement times.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

Comparison of methods for estimation of needle losses in Scots pine following defoliation by Bupalus piniaria

Abstract

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

Visibility and Speed Estimation of Iowa State Highway Commission Snowplows, HR-174, 1975

Many accidents involving Iowa snowplows have happened in recent years. This study investigated the influence of time of day, sex of subject, type of snowplow sign and snowplow speed on the criteria of oncoming driver reaction time and his estimate of snowplow speed. Film strips were made of a car passing a snow-Plow under various experimental conditions. These experimental movie strips were viewed in the laboratory by college student drivers who were asked to indicate their reaction time to slow down and to estimate the speed of the snowplow being passed. The generally best sign condition for the snowplow was to have a striped rear sign and a speed-proportional flashing light in addition to the standard rotating beacon on top of the truck. Several recommendations were made.

Remsen source water protection project : agreement no. 8025-015 between the Iowa Watershed Improvement Review Board and the City of Remsen final report.

This final report to the Iowa Watershed Improvement Review Board by the City of Remsen Utilities consists of accomplishments made by the Remsen Utilities as per this agreement. The City of Remsen Utilities did in fact purchase approximately 27 acres of land lying upstream of the city’s water well field. The land was purchased from Mr. Larry Rodesch and Mr. Rich Harpenau for the purpose of removing nitrates from Remsen’s water source and establishing native prairie grasses to assist in this removal.

Reconfigurable Architecture To Estimate The Motion Of An Underwater Vehicle

This work proposes a parallel architecture for a motion estimation algorithm. It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great numbers of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. Due to its regular processing scheme, parallel implementation of correspondence problem can be an adequate approach to reduce the computation time. This work introduces parallel and real-time implementation of such low-level tasks to be carried out from the moment that the current image is acquired by the camera until the pairs of point-matchings are detected

Owl pellets as a source of DNA for genetic studies of small mammals.

Owl pellets contain a good skeletal record of the small mammals consumed, and correspond to the undigested portions of prey which are regurgitated. These pellets are easy to find at the roosting site of owls. As it has been demonstrated that amplifiable DNA can be isolated from ancient bone remains, the possibility of using owl pellets as a source of DNA for small mammal genetics studies via the polymerase chain reaction has been investigated. The main uncertainties when isolating DNA from such a material are firstly the possibility that the extracted DNA would be too degraded during the digestion in the stomach of the owl, and secondly that extensive cross-contaminations could occur among the different prey consumed. The results obtained clearly demonstrate that cross-contamination does not occur, and that mitochondrial and nuclear DNA can be amplified using skulls of small mammals found in owl pellets as a source of DNA. The relative efficiency of two methods of DNA extraction is estimated and discussed. Thus, owl pellets represent a non-invasive sampling technique which provides a valuable source of DNA for studying population genetics of small mammals.

Cellular source and mechanisms of high transcriptome complexity in the Mammalian testis.

Understanding the extent of genomic transcription and its functional relevance is a central goal in genomics research. However, detailed genome-wide investigations of transcriptome complexity in major mammalian organs have been scarce. Here, using extensive RNA-seq data, we show that transcription of the genome is substantially more widespread in the testis than in other organs across representative mammals. Furthermore, we reveal that meiotic spermatocytes and especially postmeiotic round spermatids have remarkably diverse transcriptomes, which explains the high transcriptome complexity of the testis as a whole. The widespread transcriptional activity in spermatocytes and spermatids encompasses protein-coding and long noncoding RNA genes but also poorly conserves intergenic sequences, suggesting that it may not be of immediate functional relevance. Rather, our analyses of genome-wide epigenetic data suggest that this prevalent transcription, which most likely promoted the birth of new genes during evolution, is facilitated by an overall permissive chromatin in these germ cells that results from extensive chromatin remodeling.