Quantitative evaluation of recall and precision of CAT Crawler, a search engine specialized on retrieval of Critically Appraised Topics

BACKGROUND: Critically Appraised Topics (CATs) are a useful tool that helps physicians to make clinical decisions as the healthcare moves towards the practice of Evidence-Based Medicine (EBM). The fast growing World Wide Web has provided a place for physicians to share their appraised topics online, but an increasing amount of time is needed to find a particular topic within such a rich repository. METHODS: A web-based application, namely the CAT Crawler, was developed by Singapore's Bioinformatics Institute to allow physicians to adequately access available appraised topics on the Internet. A meta-search engine, as the core component of the application, finds relevant topics following keyword input. The primary objective of the work presented here is to evaluate the quantity and quality of search results obtained from the meta-search engine of the CAT Crawler by comparing them with those obtained from two individual CAT search engines. From the CAT libraries at these two sites, all possible keywords were extracted using a keyword extractor. Of those common to both libraries, ten were randomly chosen for evaluation. All ten were submitted to the two search engines individually, and through the meta-search engine of the CAT Crawler. Search results were evaluated for relevance both by medical amateurs and professionals, and the respective recall and precision were calculated. RESULTS: While achieving an identical recall, the meta-search engine showed a precision of 77.26% (±14.45) compared to the individual search engines' 52.65% (±12.0) (p < 0.001). CONCLUSION: The results demonstrate the validity of the CAT Crawler meta-search engine approach. The improved precision due to inherent filters underlines the practical usefulness of this tool for clinicians

Evaluating the Combined Effectiveness of Influenza Control Strategies and Human Preventive Behavior

Control strategies enforced by health agencies are a major type of practice to contain influenza outbreaks. Another type of practice is the voluntary preventive behavior of individuals, such as receiving vaccination, taking antiviral drugs, and wearing face masks. These two types of practices take effects concurrently in influenza containment, but little attention has been paid to their combined effectiveness. This article estimates this combined effectiveness using established simulation models in the urbanized area of Buffalo, NY, USA. Three control strategies are investigated, including: Targeted Antiviral Prophylaxis (TAP), workplace/school closure, community travel restriction, as well as the combination of the three. All control strategies are simulated with and without regard to individual preventive behavior, and the resulting effectiveness are compared. The simulation outcomes suggest that weaker control strategies could suffice to contain influenza epidemics, because individuals voluntarily adopt preventive behavior, rendering these weaker strategies more effective than would otherwise have been expected. The preventive behavior of individuals could save medical resources for control strategies and avoid unnecessary socio-economic interruptions. This research adds a human behavioral dimension into the simulation of control strategies and offers new insights into disease containment. Health policy makers are recommended to review current control strategies and comprehend preventive behavior patterns of local populations before making decisions on influenza containment

Rate accelerations in nuclear 18S rDNA of mycoheterotrophic and parasitic angiosperms

Rate variation in genes from all three genomes has been observed frequently in plant lineages with a parasitic and mycoheterotrophic mode of life. While the loss of photosynthetic ability leads to a relaxation of evolutionary constraints in genes involved in the photosynthetic apparatus, it remains to be determined how prevalent increased substitution rates are in nuclear DNA of non-photosynthetic angiosperms. In this study we infer rates of molecular evolution of 18S rDNA of all parasitic and mycoheterotorphic plant families (except Lauraceae and Polygalaceae) using relative rate tests. In several holoparasitic and mycoheterotrophic plant lineages extremely high substitution rates are observed compared to other photosynthetic angiosperms. The position and frequency of these substitutions have been identified to understand the mutation dynamics of 18S rRNA in achlorophyllous plants. Despite the presence of significantly elevated substitution rates, very few mutations occur in major functional and structural regions of the small ribosomal molecule, providing evidence that the efficiency of the translational apparatus in non-photosynthetic plants has not been affected

Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

Evolutionary Game Theory and Social Learning Can Determine How Vaccine Scares Unfold

Immunization programs have often been impeded by vaccine scares, as evidenced by the measles-mumps-rubella (MMR) autism vaccine scare in Britain. A “free rider” effect may be partly responsible: vaccine-generated herd immunity can reduce disease incidence to such low levels that real or imagined vaccine risks appear large in comparison, causing individuals to cease vaccinating. This implies a feedback loop between disease prevalence and strategic individual vaccinating behavior. Here, we analyze a model based on evolutionary game theory that captures this feedback in the context of vaccine scares, and that also includes social learning. Vaccine risk perception evolves over time according to an exogenously imposed curve. We test the model against vaccine coverage data and disease incidence data from two vaccine scares in England & Wales: the whole cell pertussis vaccine scare and the MMR vaccine scare. The model fits vaccine coverage data from both vaccine scares relatively well. Moreover, the model can explain the vaccine coverage data more parsimoniously than most competing models without social learning and/or feedback (hence, adding social learning and feedback to a vaccine scare model improves model fit with little or no parsimony penalty). Under some circumstances, the model can predict future vaccine coverage and disease incidence—up to 10 years in advance in the case of pertussis—including specific qualitative features of the dynamics, such as future incidence peaks and undulations in vaccine coverage due to the population's response to changing disease incidence. Vaccine scares could become more common as eradication goals are approached for more vaccine-preventable diseases. Such models could help us predict how vaccine scares might unfold and assist mitigation efforts

Bridging the gaps among research, policy and practice in ten low- and middle-income countries: Development and testing of a questionnaire for health-care providers

<p>Abstract</p> <p>Background</p> <p>The reliability and validity of instruments used to survey health-care providers' views about and experiences with research evidence have seldom been examined.</p> <p>Methods</p> <p>Country teams from ten low- and middle-income countries (China, Ghana, India, Iran, Kazakhstan, Laos, Mexico, Pakistan, Senegal and Tanzania) participated in the development, translation, pilot-testing and administration of a questionnaire designed to measure health-care providers' views and activities related to improving their clinical practice and their awareness of, access to and use of research evidence, as well as changes in their clinical practice that they attribute to particular sources of research evidence that they have used. We use internal consistency as a measure of the questionnaire's reliability and, whenever possible, we use explanatory factor analyses to assess the degree to which questions that pertain to a single domain actually address common themes. We assess the questionnaire's face validity and content validity and, to a lesser extent, we also explore its criterion validity.</p> <p>Results</p> <p>The questionnaire has high internal consistency, with Cronbach's alphas between 0.7 and 0.9 for 16 of 20 domains and sub-domains (identified by factor analyses). Cronbach's alphas are greater than 0.9 for two domains, suggesting some item redundancy. Pre- and post-field work assessments indicate the questionnaire has good face validity and content validity. Our limited assessment of criterion validity shows weak but statistically significant associations between the general influence of research evidence among providers and more specific measures of providers' change in approach to preventing or treating a clinical condition.</p> <p>Conclusion</p> <p>Our analysis points to a number of strengths of the questionnaire - high internal consistency (reliability) and good face and content validity - but also to areas where it can be shortened without losing important conceptual domains.</p

Towards a characterization of behavior-disease models

The last decade saw the advent of increasingly realistic epidemic models that leverage on the availability of highly detailed census and human mobility data. Data-driven models aim at a granularity down to the level of households or single individuals. However, relatively little systematic work has been done to provide coupled behavior-disease models able to close the feedback loop between behavioral changes triggered in the population by an individual's perception of the disease spread and the actual disease spread itself. While models lacking this coupling can be extremely successful in mild epidemics, they obviously will be of limited use in situations where social disruption or behavioral alterations are induced in the population by knowledge of the disease. Here we propose a characterization of a set of prototypical mechanisms for self-initiated social distancing induced by local and non-local prevalence-based information available to individuals in the population. We characterize the effects of these mechanisms in the framework of a compartmental scheme that enlarges the basic SIR model by considering separate behavioral classes within the population. The transition of individuals in/out of behavioral classes is coupled with the spreading of the disease and provides a rich phase space with multiple epidemic peaks and tipping points. The class of models presented here can be used in the case of data-driven computational approaches to analyze scenarios of social adaptation and behavioral change.Comment: 24 pages, 15 figure

Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health

Proportions of Convective and Stratiform Precipitation Revealed in Water Isotope Ratios

Tropical and midlatitude precipitation is fundamentally of two types, spatially-limited and high-intensity convective or widespread and lower-intensity stratiform, owing to differences in vertical air motions and microphysical processes governing rain formation. These processes are difficult to observe or model and precipitation partitioning into rain types is critical for understanding how the water cycle responds to climate changes. Here, we combine two independent data sets – convective and stratiform precipitation fractions, derived from the Tropical Rainfall Measuring Mission satellite or synoptic cloud observations, and stable isotope and tritium compositions of surface precipitation, derived from a global network – to show that isotope ratios reflect rain type proportions and are negatively correlated with stratiform fractions. Condensation and riming associated with boundary layer moisture produces higher isotope ratios in convective rain, along with higher tritium when riming in deep convection occurs with entrained air at higher altitudes. Based on our data, stable isotope ratios can be used to monitor changes in the character of precipitation in response to periodic variability or changes in climate. Our results also provide observational constraints for an improved simulation of convection in climate models and a better understanding of isotope variations in proxy archives, such as speleothems and tropical ice

Exploring the role of organizational policies and procedures in promoting research utilization in registered nurses

<p>Abstract</p> <p>Background</p> <p>Policies and procedures (P&Ps) have been suggested as one possible strategy for moving research evidence into practice among nursing staff in hospitals. Research in the area of P&Ps is limited, however. This paper explores: 1) nurses' use of eight specific research-based practices (RBPs) and RBP overall, 2) nurses' use and understanding of P&Ps, and 3) the role of P&Ps in promoting research utilization.</p> <p>Methods</p> <p>Staff nurses from the eight health regions governing acute care services across the Canadian province of Newfoundland and Labrador completed an anonymous questionnaire regarding their use of eight RBPs and associated P&Ps. Data were also obtained from authorities in six of the eight regions about existing relevant P&Ps. We used descriptive statistics and multivariate regression analysis to assess the relationship between key independent variables and self-reported use of RBP.</p> <p>Results</p> <p>Use of the eight RBPs ranged from 7.8% to 88.6%, depending on the practice. Nurses ranked P&P manuals as their number one source of practice knowledge. Most respondents (84.8%) reported that the main reason they consult the P&P manual is to confirm they are practicing according to agency rules. Multivariate regression analysis identified three significant predictors of being a user versus non-user of RBP overall: awareness, awareness by regular use, and persuasion. Six significant predictors of being a consistent versus less consistent user of RBP overall were also identified: perception of P&P existence, unit, nursing experience, personal experience as a source of practice knowledge, number of existing research-based P&Ps, and lack of time as a barrier to consulting P&P manuals.</p> <p>Conclusion</p> <p>Findings suggest that nurses use P&Ps to guide their practice. However, the mere existence of P&Ps is not sufficient to translate research into nursing practice. Individual and organizational factors related to nurses' understanding and use of P&Ps also play key roles. Thus, moving research evidence into practice will require careful interplay between the organization and the individual. P&Ps may be the interface through which this occurs.</p