Available evidence does not support routine administration of antipyretics to reduce duration of fever or illness

Commentary on : Carey JV. Literature review : should antipyretic therapies routinely be administered to patients with [corrected] fever? J Clin Nurs 2010;19:2377–93.

Elicitator : a user-friendly, interactive tool to support scenario-based elicitation of expert knowledge

Expert elicitation is the process of determining what expert knowledge is relevant to support a quantitative analysis and then eliciting this information in a form that supports analysis or decision-making. The credibility of the overall analysis, therefore, relies on the credibility of the elicited knowledge. This, in turn, is determined by the rigor of the design and execution of the elicitation methodology, as well as by its clear communication to ensure transparency and repeatability. It is difficult to establish rigor when the elicitation methods are not documented, as often occurs in ecological research. In this chapter, we describe software that can be combined with a well-structured elicitation process to improve the rigor of expert elicitation and documentation of the results

Focusing on patients : differences between the practice of expert and non-expert nephrology nurses

Specialisation in nursing enables a nurse to focus, in much greater depth, on the requisite knowledge and skills for providing patients with the best possible care. Nephrology nursing is one such area where specialisation has evolved. The characteristic focus of practice emerged as an important feature during a study into the process of expertise acquisition in nephrology nursing practice. Using grounded theory methodology, this study involved 6 non-expert and 11 expert nurses and took place in one renal unit in New South Wales. Nephrology nursing practice was observed for 103 hours, and this was immediately followed by semi-structured interviews. The characteristic of focus was conceptualised as the nurses' centre of attention or concentration while they were undertaking nursing activities. Focus ranged from inexperienced non-expert nurses concentrating predominantly on the immediate task at hand, experienced non-expert nurses who focussed on the medium term to expert nurses who viewed actions (and their possible consequences) more broadly and in the longer term. Of significance to nursing, is how nephrology nurses alter their focus of practice as they acquire and exercise their developing expertise in this specialty.

Backpackers and sustainable tourism : exploring the potential

There is conflicting evidence in the literature with respect to backpackers as contributors to sustainable travel. This paper explores this market with respect to sustainable travel attitudes, behaviours and preferences. More specifically it examined the motivations of backpacker visitors to Australia, their preferences for environmentally friendly and volunteer tourism experiences, and explored attitudes towards the influence of environmental impacts on the future of travel. The resultsindicate that not all backpackers necessarily have a strong focus on the sustainability of their travel, but that those interested in community and environmental volunteering have the greatest potential to make meaningful contributions.

Multitask learning with expert advice

We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the “ideal” algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.

Multitask learning with expert advice

We consider the problem of prediction with expert advice in the setting where a forecaster is presented with several online prediction tasks. Instead of competing against the best expert separately on each task, we assume the tasks are related, and thus we expect that a few experts will perform well on the entire set of tasks. That is, our forecaster would like, on each task, to compete against the best expert chosen from a small set of experts. While we describe the "ideal" algorithm and its performance bound, we show that the computation required for this algorithm is as hard as computation of a matrix permanent. We present an efficient algorithm based on mixing priors, and prove a bound that is nearly as good for the sequential task presentation case. We also consider a harder case where the task may change arbitrarily from round to round, and we develop an efficient approximate randomized algorithm based on Markov chain Monte Carlo techniques.

The Relative Efficiency of International, Domestic, and Budget Airlines : Nonparametric Evidence

This study determines whether the inclusion of low-cost airlines in a dataset of international and domestic airlines has an impact on the efficiency scores of so-called ‘prestigious’ purportedly ‘efficient’ airlines. This is because while many airline studies concern efficiency, none has truly included a combination of international, domestic and budget airlines. The present study employs the nonparametric technique of data envelopment analysis (DEA) to investigate the technical efficiency of 53 airlines in 2006. The findings reveal that the majority of budget airlines are efficient relative to their more prestigious counterparts. Moreover, most airlines identified as inefficient are so largely because of the overutilization of non-flight assets.

Functional heterogeneity as a two-dimensional concept : empirical evidence for new venture teams

Previous research on entrepreneurial teams has failed to settle the controversy over whether team heterogeneity helps or hinders new venture performance. Reconciling this inconsistency, this paper suggests a new conceptual approach to disentangle differential effects of team heterogeneity by modeling two separate heterogeneity dimensions, namely knowledge scope and knowledge disparity. Analyzing unique data on functional experiences of the members of 337 start-up teams, we find support for our contention of team heterogeneity as a two-dimensional concept. Results suggest that knowledge disparity negatively relates to both start-ups’ entrepreneurial and innovative performance. In contrast, we find knowledge scope to positively affect entrepreneurial performance, while it shows an inverse U-shaped relationship to innovative start-up performance.