Libertarian paternalism: Policy and everyday translations of the rational and the affective

Following the financial collapse in 2008 many commentators went onto pronounce the end of neoliberalism as a credible system for managing welfare state capitalism. The narrow economic belief in individuals as rational utility maximizers (the linchpin of neoliberal governance) was proved to be uncomfortably inaccurate. In light of these claims, British governments and think tanks have published various research and pol-icy documents promoting the use of soft forms of state power to ‘nudge’ citizens into behaving responsibly and rationally. Through an analysis of key policy documents and academic texts, I examine the repertoires and formulations informing this emerging governmental rationality (‘libertarian paternalism’) and draw together these perspectives to explore their effects in terms of framing policy understandings of the rational and the emotional. I conclude the article by utilizing a discursive psychology approach with the aim to problematize existing policy (mis)understandings of emotion as automated and unreflexive

Current use of aminoglycosides: indications, pharmacokinetics and monitoring for toxicity

The new Australian Therapeutic Guidelines: Antibiotic, version 14 have revised the recommendations for the use and monitoring of aminoglycosides. The guidelines have clear distinctions between empirical and directed therapy as well as revised recommendations about the monitoring of aminoglycosides. This has led many clinicians to review their current practice with regard to the use of aminoglycosides. This review summarizes why aminoglycosides are still a valid treatment option and discusses the rationale for current dosing regimens in Gram-negative infections. In particular it focuses on the various methods for monitoring aminoglycosides that are currently being used. The aminoglycoside monitoring methods can be categorized into three groups: linear regression analysis (one compartment model), population methods and Bayesian estimation procedures. Although the population methods are easy to use and require minimal resources they can recommend clinically inappropriate doses as they have constant pharmacokinetic parameters and are not valid in special population groups, that is, renal impairment. The linear regression and Bayesian methods recommend more accurate dosage regimens; however, they require additional resources, such as information technology and healthcare personnel with background training in pharmacokinetics. The Bayesian methods offer additional advantages, such as calculation of doses based on a single serum concentration and optimization of the patient's previous pharmacokinetic data, in order to determine subsequent dosage regimens. We recommend the Bayesian estimation procedures be used, wherever feasible. However, they require the expertise of healthcare practitioners with a good understanding of pharmacokinetic principles, such as clinical pharmacists/clinical pharmacologists, in order to make appropriate recommendations

Vancomycin therapeutics and monitoring: a contemporary approach

Vancomycin remains a clinically useful antibiotic despite the advent of several alternative drugs. Optimising vancomycin therapy with therapeutic drug monitoring is widely recommended. The aim of therapeutic drug monitoring is to help the clinician to achieve target pharmacodynamic parameters in the case of vancomycin, an area under the concentration time curve/minimum inhibitory concentration ratio of ≥400. Vancomycin monitoring methods can be categorised into four categories: empiric trough concentrations; linear regression analysis (one-compartment model), population methods and Bayesian estimation procedures. Although the empiric trough concentrations and population methods are easy to use and require minimal resources, there are large differences in the published vancomycin model parameters. This demonstrates that there is great variance in pharmacokinetic parameters between the models and a single vancomycin model cannot be applied to all patient populations. The linear regression and Bayesian methods recommended more accurate dosage regimens; however, they require additional resources such as information technology and healthcare personnel with background training in pharmacokinetics. The Bayesian methods offered additional advantages such as calculation of doses based on a single-serum concentration and optimisation of the patient's previous pharmacokinetic data to determine subsequent dosage regimens. Computerised programs, utilising the Bayesian estimation procedures, are able to achieve target concentrations in a greater percentage of patients earlier in the course of therapy than the empiric trough concentrations and population methods. We recommend the use of these programs providing there is appropriate expertise available to make appropriate recommendations