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Summary Background Presentations to emergency departments (EDs) and patient acuity continue to increase. Whilst strategies to deliver safe patient care in the ED are evolving, emergency nurses need to be well educated through specialist qualifications to enable delivery of advanced patient care. This paper presents a comparative analysis of available international practice and competency standards for nurses graduating from emergency nursing courses in Australia, Canada, New Zealand, the United Kingdom, and the United States. Methods CINAHL, Scopus, Ovid MEDLINE, and Embase were searched for papers, published in English, using the terms: ‘emergency’, ‘accident and emergency’, ‘nursing’, ‘competency’, ‘practice standards’, ‘scope of practice’, ‘regulation’, and ‘specialist standards’. Secondary sources from relevant reference lists and professional websites were also searched. Results The standards from the five countries were common across five domains: clinical expertise, communication, teamwork, resources and environment, and legal. None of the standards were specific to the emergency nursing graduate, and there was variability in the level of expertise required for which the standards apply. Conclusions The available practice standards demonstrated some commonality. Consideration of the utility of a universal framework for informing the development of emergency nursing practice standards and emergency nursing curriculum for nurses wishing to specialise is needed. [ABSTRACT FROM AUTHOR]

Most of the stock assessments conducted in the USA and in New Zealand are based on packages that have been developed for generic use, are well documented, and have been tested using simulation. However, this is not the case for assessments conducted in Australia and many other countries. This paper reviews all of the model-based stock assessments for Australian fisheries to evaluate how many of these assessments could have been conducted using the publicly-available stock assessment packages used widely in the USA and New Zealand. The 76 model-based assessments reflect 37% of the 2013 catch recorded in Australia's Status for Key Australian Fish Stocks Reports (or 34% of the total catch in 2013). All but 18 (or 24 if full rather than approximate age-size-structured models need to be used) of the stock assessments could have been conducted using stock assessment packages used in the United States and New Zealand. Adoption and use of packages for more stocks in Australia should increase the likelihood that results are based on correctly-coded models whose estimation performance is widely understood, reduce the time needed to conduct assessments, and speed up the peer-review process. The availability of training, manuals, and example data sets for stock assessment packages should partially address their additional complexity. Additional benefits, in terms of numbers of assessed stocks, could occur if Australian stock assessment scientists develop a forum to collaborate and share methods. These results are applicable to many other jurisdictions that undertake stock assessments. [ABSTRACT FROM AUTHOR]

Objectives: This paper provides a quantitative review that estimates exposure rates by type of violence, setting, source, and world region. Design: A quantitative review of the nursing violence literature was summarized. Data sources: A literature search was conducted using the CINAHL, Medline and PsycInfo data bases. Studies included had to report empirical results using a nursing sample, and include data on bullying, sexual harassment, and/or violence exposure rates. A total of 136 articles provided data on 151,347 nurses from 160 samples. Procedure: Articles were identified through a database search and by consulting reference lists of review articles that were located. Relevant data were coded by the three authors. Categories depended on the availability of at least five studies. Exposure rates were coded as percentages of nurses in the sample who reported a given type of violence. Five types of violence were physical, nonphysical, bullying, sexual harassment, and combined (type of violence was not indicated). Setting, timeframe, country, and source of violence were coded. Results: Overall violence exposure rates were 36.4% for physical violence, 66.9% for nonphysical violence, 39.7% for bullying, and 25% for sexual harassment, with 32.7% of nurses reporting having been physically injured in an assault. Rates of exposure varied by world region (Anglo, Asia, Europe and Middle East), with the highest rates for physical violence and sexual harassment in the Anglo region, and the highest rates of nonphysical violence and bullying in the Middle East. Regions also varied in the source of violence, with patients accounting for most of it in Anglo and European regions, whereas patents' families/friends were the most common source in the Middle East. Conclusions: About a third of nurses worldwide indicated exposure to physical violence and bullying, about a third reported injury, about a quarter experienced sexual harassment, and about two-thirds indicated nonphysical violence. Physical violence was most prevalent in emergency departments, geriatric, and psychiatric facilities. Physical violence and sexual harassment were most prevalent in Anglo countries, and nonphysical violence and bullying were most prevalent in the Middle East. Patients accounted for most physical violence in the Anglo region and Europe, and patient family and friends accounted for the most in the Middle East. [ABSTRACT FROM AUTHOR]

Abstract: Falls and their injury outcomes have count distributions that are highly skewed toward the right with clumping at zero, posing analytical challenges. Different modelling approaches have been used in the published literature to describe falls count distributions, often without consideration of the underlying statistical and modelling assumptions. This paper compares the use of modified Poisson and negative binomial (NB) models as alternatives to Poisson (P) regression, for the analysis of fall outcome counts. Four different count-based regression models (P, NB, zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB)) were each individually fitted to four separate fall count datasets from Australia, New Zealand and United States. The finite mixtures of P and NB regression models were also compared to the standard NB model. Both analytical (F, Vuong and bootstrap tests) and graphical approaches were used to select and compare models. Simulation studies assessed the size and power of each model fit. This study confirms that falls count distributions are over-dispersed, but not dispersed due to excess zero counts or heterogeneous population. Accordingly, the P model generally provided the poorest fit to all datasets. The fit improved significantly with NB and both zero-inflated models. The fit was also improved with the NB model, compared to finite mixtures of both P and NB regression models. Although there was little difference in fit between NB and ZINB models, in the interests of parsimony it is recommended that future studies involving modelling of falls count data routinely use the NB models in preference to the P or ZINB or finite mixture distribution. The fact that these conclusions apply across four separate datasets from four different samples of older people participating in studies of different methodology, adds strength to this general guiding principle. [Copyright &y& Elsevier]