Cost-effectiveness of dexamphetamine and methylphenidate for the treatment of childhood attention deficit hyperactivity disorder

Objective: To analyze from a health sector perspective the cost-effectiveness of dexamphetamine (DEX) and methylphenidate (MPH) interventions to treat childhood attention deficit hyperactivity disorder (ADHD), compared to current practice. Method: Children eligible for the interventions are those aged between 4 and 17 years in 2000, who had ADHD and were seeking care for emotional or behavioural problems, but were not receiving stimulant medication. To determine health benefit, a meta-analysis of randomized controlled trials was performed for DEX and MPH, and the effect sizes were translated into utility values. An assessment on second stage filter criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Simulation modelling techniques are used to present a 95% uncertainty interval (UI) around the incremental cost-effectiveness ratio (ICER), which is calculated in cost (in A$) per DALY averted. Results: The ICER for DEX is A$4100/DALY saved (95% UI: negative to A$14 000) and for MPH is A$15 000/DALY saved (95% UI: A$9100-22 000). DEX is more costly than MPH for the government, but much less costly for the patient. Conclusions: MPH and DEX are cost-effective interventions for childhood ADHD. DEX is more cost-effective than MPH, although if MPH were listed at a lower price on the Pharmaceutical Benefits Scheme it would become more cost-effective. Increased uptake of stimulants for ADHD would require policy change. However, the medication of children and wider availability of stimulants may concern parents and the community.

Cost-effectiveness of psychological and pharmacological interventions for generalized anxiety disorder and panic disorder

Objective: To assess from a health sector perspective the incremental cost-effectiveness of interventions for generalized anxiety disorder (cognitive behavioural therapy [CBT] and serotonin and noradrenaline reuptake inhibitors [SNRIs]) and panic disorder (CBT, selective serotonin reuptake inhibitors [SSRIs] and tricyclic antidepressants [TCAs]). Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analyses of randomised controlled trials. An assessment on second stage filters ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are calculated for a period of one year for the eligible population (prevalent cases of generalized anxiety disorder/panic disorder identified in the National Survey of Mental Health and Wellbeing, extrapolated to the Australian population in the year 2000 for those aged 18 years and older). Simulation modelling techniques are used to present 95% uncertainty intervals (UI) around the incremental cost-effectiveness ratios (ICERs). Results: Compared to current practice, CBT by a psychologist on a public salary is the most cost-effective intervention for both generalized anxiety disorder (A$6900/DALY saved; 95% UI A$4000 to A$12 000) and panic disorder (A$6800/DALY saved; 95% UI A$2900 to A$15 000). Cognitive behavioural therapy results in a greater total health benefit than the drug interventions for both anxiety disorders, although equity and feasibility concerns for CBT interventions are also greater. Conclusions: Cognitive behavioural therapy is the most effective and cost-effective intervention for generalized anxiety disorder and panic disorder. However, its implementation would require policy change to enable more widespread access to a sufficient number of trained therapists for the treatment of anxiety disorders.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

Darwinian grandparenting: Preferential investment in more certain kin

Studies on grandparental investment have revealed that mothers fathers are emotionally closer to their grandchildren than are fathers' mothers. In the current study, it was hypothesized that this difference is caused by the fact that fathers' mothers often have the potential to invest in genetically more certain kin (children through their daughters). To test this hypothesis, 787 participants rated their emotional closeness and exposure to their grandparents and indicated whether they had cousins through paternal and maternal aunts and uncles. Results indicated that participants felt closer to mothers' fathers than fathers' mothers only when alternate investment outlets for fathers' mothers were available. Closeness ratings to fathers fathers also were reduced when they had grandchildren through their daughters. Exposure to grandparents revealed a similar pattern of findings but did not show the same sensitivity to the presence of more certain kin and did not appear to account for the closeness ratings.

Implications of current ecological thinking for biodiversity conservation: A review of the salient issues

Given escalating concern worldwide about the loss of biodiversity, and given biodiversity's centrality to quality of life, it is imperative that current ecological knowledge fully informs societal decision making. Over the past two decades, ecological science has undergone many significant shifts in emphasis and perspective, which have important implications for how we manage ecosystems and species. In particular, a shift has occurred from the equilibrium paradigm to one that recognizes the dynamic, non-equilibrium nature of ecosystems. Revised thinking about the spatial and temporal dynamics of ecological systems has important implications for management. Thus, it is of growing concern to ecologists and others that these recent developments have not been translated into information useful to managers and policy makers. Many conservation policies and plans are still based on equilibrium assumptions. A fundamental difficulty with integrating current ecological thinking into biodiversity policy and management planning is that field observations have yet to provide compelling evidence for many of the relationships suggested by non-equilibrium ecology. Yet despite this scientific uncertainty, management and policy decisions must still be made. This paper was motivated by the need for considered scientific debate on the significance of current ideas in theoretical ecology for biodiversity conservation. This paper aims to provide a platform for such discussion by presenting a critical synthesis of recent ecological literature that (1) identifies core issues in ecological theory, and (2) explores the implications of current ecological thinking for biodiversity conservation.

Separation and hedging results with state-contingent production

A state-contingent model of production under uncertainty is developed and compared with more traditional models of production under uncertainty. Producer behaviour with both production and price risk, in the presence and in the absence of futures and forward markets, is analysed in this state-contingent framework. Conditions for the optimal hedge to be positive or negative are derived. We also show that, under plausible conditions, a risk-averse producer facing price uncertainty and the ability to hedge price risk will never willingly adopt a nonstochastic technology. New separation results, which hold in the presence of both price and production risk, are then developed. These separation results generalize Townsend's spanning results by reducing the number of necessary forward markets by one.

Optimal quantum measurements for phase-shift estimation in optical interferometry

Quantum information theory, applied to optical interferometry, yields a 1/n scaling of phase uncertainty Delta phi independent of the applied phase shift phi, where n is the number of photons in the interferometer. This 1/n scaling is achieved provided that the output state is subjected to an optimal phase measurement. We establish this scaling law for both passive (linear) and active (nonlinear) interferometers and identify the coefficient of proportionality. Whereas a highly nonclassical state is required to achieve optimal scaling for passive interferometry, a classical input state yields a 1/n scaling of phase uncertainty for active interferometry.

Evaluating SVM and MLDA in the extraction of discriminant regions for mental state prediction

Pattern recognition methods have been successfully applied in several functional neuroimaging studies. These methods can be used to infer cognitive states, so-called brain decoding. Using such approaches, it is possible to predict the mental state of a subject or a stimulus class by analyzing the spatial distribution of neural responses. In addition it is possible to identify the regions of the brain containing the information that underlies the classification. The Support Vector Machine (SVM) is one of the most popular methods used to carry out this type of analysis. The aim of the current study is the evaluation of SVM and Maximum uncertainty Linear Discrimination Analysis (MLDA) in extracting the voxels containing discriminative information for the prediction of mental states. The comparison has been carried out using fMRI data from 41 healthy control subjects who participated in two experiments, one involving visual-auditory stimulation and the other based on bimanual fingertapping sequences. The results suggest that MLDA uses significantly more voxels containing discriminative information (related to different experimental conditions) to classify the data. On the other hand, SVM is more parsimonious and uses less voxels to achieve similar classification accuracies. In conclusion, MLDA is mostly focused on extracting all discriminative information available, while SVM extracts the information which is sufficient for classification. (C) 2009 Elsevier Inc. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

PTCH1 gene mutations in exon 17 and loss of heterozygosity on D9S180 microsatellite in sporadic and inherited human basal cell carcinomas

Background Basal cell carcinomas (BCCs) are the most frequent human cancer that results from malignant transformation of basal cells in the epidermis. Gorlin syndrome is a rare inherited autosomal dominant disease that predisposes with multiple BCCs and other birth defects. Both sporadic and inherited BCCs are associated with mutations in the tumor suppressor gene PTCH1, but there is still uncertainty on the role of its homolog PTCH2. Objectives To search for mutations and genomic instability in sporadic and inherited BCCs. Methods DNA obtained from leukocytes and tumor cells was amplified by polymerase chain reaction regarding five exons of PTCH1 and PTCH2 and neighboring microsatellites. Exons were sequenced and compared with the GenBank database. Results Only D9S180, of six microsatellites, showed loss of heterozygosity in three BCCs (two sporadic and one inherited). One sporadic BCC presented the mutation g. 2885G>C in exon 17 of PTCH1, which predicts the substitution p.R962T in an external domain of the protein. In addition, the leukocytes and tumor cells of one patient with Gorlin syndrome showed the mutation g. 2839T>G in the same exon and gene, which predicts a p.E947stop and truncated protein. All control and tumor samples presented IVS9 + 217T in intron 9 of PTCH1. Conclusion Mutations found in the PTCH1 gene and neighboring repetitive sequences may have contributed to the development of the studied BCCs.

Characterizing QALYs under a general rank dependent utility model

This paper provides a characterization of QALYs, the most important outcome measure in medical decision making, in the context of a general rank dependent utility model. We show that both for chronic and for nonchronic health states the characterization of QALYs depends on intuitive conditions. This facilitates the assessment of the validity of QALYs in rank dependent non-expected utility theories and a comparison with other utility based measures of health.

A social identity theory of leadership

A social identity theory of leadership is described that views leadership as a group process generated by social categorization and prototype-based depersonalization processes associated with social identity. Group identification, as self-categorization, constructs an intragroup prototypicality gradient that invests the most prototypical member with the appearance of having influence; the appearance arises because members cognitively and behaviorally conform to the prototype. The appearance of influence becomes a reality through depersonalized social attraction processes that make followers agree and comply with the leader's ideas and suggestions. Consensual social attraction also imbues the leader with apparent status and creates a status-based structural differentiation within the group into leader(s) and followers, which has characteristics of unequal status intergroup relations. In addition, a fundamental attribution process constructs a charismatic leadership personality for the leader, which further empowers the leader and sharpens the leader-follower status differential. Empirical support for the theory is reviewed and a range of implications discussed, including intergroup dimensions, uncertainty reduction and extremism, power, and pitfalls of prototype-based leadership.

Model-based procedure for scale-up of wet, overflow ball mills - Part III: Validation and discussion

A new ball mill scale-up procedure is developed. This procedure has been validated using seven sets of Ml-scale ball mil data. The largest ball mills in these data have diameters (inside liners) of 6.58m. The procedure can predict the 80% passing size of the circuit product to within +/-6% of the measured value, with a precision of +/-11% (one standard deviation); the re-circulating load to within +/-33% of the mass-balanced value (this error margin is within the uncertainty associated with the determination of the re-circulating load); and the mill power to within +/-5% of the measured value. This procedure is applicable for the design of ball mills which are preceded by autogenous (AG) mills, semi-autogenous (SAG) mills, crushers and flotation circuits. The new procedure is more precise and more accurate than Bond's method for ball mill scale-up. This procedure contains no efficiency correction which relates to the mill diameter. This suggests that, within the range of mill diameter studied, milling efficiency does not vary with mill diameter. This is in contrast with Bond's equation-Bond claimed that milling efficiency increases with mill diameter. (C) 2001 Elsevier Science Ltd. All rights reserved.

Neural adaptations to resistance training - Implications for movement control

It has long been believed that resistance training is accompanied by changes within the nervous system that play an important role in the development of strength. Many elements of the nervous system exhibit the potential for adaptation in response to resistance training, including supraspinal centres, descending neural tracts, spinal circuitry and the motor end plate connections between motoneurons and muscle fibres. Yet the specific sites of adaptation along the neuraxis have seldom been identified experimentally, and much of the evidence for neural adaptations following resistance training remains indirect. As a consequence of this current lack of knowledge, there exists uncertainty regarding the manner in which resistance training impacts upon the control and execution of functional movements. We aim to demonstrate that resistance training is likely to cause adaptations to many neural elements that are involved in the control of movement, and is therefore likely to affect movement execution during a wide range of tasks. We review a small number of experiments that provide evidence that resistance training affects the way in which muscles that have been engaged during training are recruited during related movement tasks. The concepts addressed in this article represent an important new approach to research on the effects of resistance training. They are also of considerable practical importance, since most individuals perform resistance training in the expectation that it will enhance their performance in-related functional tasks.

The effects of time delays in adaptive phase measurements

It is not possible to make measurements of the phase of an optical mode using linear optics without introducing an extra phase uncertainty. This extra phase variance is quite large for heterodyne measurements, however it is possible to reduce it to the theoretical limit of log (n) over bar (4 (n) over bar (2)) using adaptive measurements. These measurements are quite sensitive to experimental inaccuracies, especially time delays and inefficient detectors. Here it is shown that the minimum introduced phase variance when there is a time delay of tau is tau/(8 (n) over bar). This result is verified numerically, showing that the phase variance introduced approaches this limit for most of the adaptive schemes using the best final phase estimate. The main exception is the adaptive mark II scheme with simplified feedback, which is extremely sensitive to time delays. The extra phase variance due to time delays is considered for the mark I case with simplified feedback, verifying the tau /2 result obtained by Wiseman and Killip both by a more rigorous analytic technique and numerically.