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PubMed2005

Residential radon in Canada: an uncertainty analysis of population and individual lung cancer risk.

Following a comprehensive evaluation of the health risks of radon, the U.S. National Research Council (US-NRC) concluded that the radon inside the homes of U.S. residents is an important cause of lung cancer. To assess lung cancer risks associated with radon exposure in Canadian homes, we apply the new (US-NRC) techniques, tailoring assumptions to the Canadian context. A two-dimensional uncertainty analysis is used to provide both population-based (population attributable risk, PAR; excess lifetime risk ratio, ELRR; and life-years lost, LYL) and individual-based (ELRR and LYL) estimates. Our primary results obtained for the Canadian population reveal mean estimates for ELRR, PAR, and LYL are 0.08, 8%, and 0.10 years, respectively. Results are also available and stratified by smoking status (ever versus never). Conveniently, the three indices (ELRR, PAR, and LYL) reveal similar output uncertainty (geometric standard deviation, GSD approximately 1.3), and in the case of ELRR and LYL, comparable variability and uncertainty combined (GSD approximately 4.2). Simplifying relationships are identified between ELRR, LYL, PAR, and the age-specific excess rate ratio (ERR), which suggest a way to scale results from one population to another. This insight is applied in scaling our baseline results to obtain gender-specific estimates, as well as in simplifying and illuminating sensitivity analysis.

Age Factors↗
PubMed2006

Measuring uncertainty importance: investigation and comparison of alternative approaches.

Uncertainty importance measures are quantitative tools aiming at identifying the contribution of uncertain inputs to output uncertainty. Their application ranges from food safety (Frey & Patil (2002)) to hurricane losses (Iman et al. (2005a, 2005b)). Results and indications an analyst derives depend on the method selected for the study. In this work, we investigate the assumptions at the basis of various indicator families to discuss the information they convey to the analyst/decisionmaker. We start with nonparametric techniques, and then present variance-based methods. By means of an example we show that output variance does not always reflect a decisionmaker state of knowledge of the inputs. We then examine the use of moment-independent approaches to global sensitivity analysis, i.e., techniques that look at the entire output distribution without a specific reference to its moments. Numerical results demonstrate that both moment-independent and variance-based indicators agree in identifying noninfluential parameters. However, differences in the ranking of the most relevant factors show that inputs that influence variance the most are not necessarily the ones that influence the output uncertainty distribution the most.

Analysis of Variance↗
PubMed2003

Discrete coding of reward probability and uncertainty by dopamine neurons.

Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.

Animals↗
PubMed2004

Human midbrain sensitivity to cognitive feedback and uncertainty during classification learning.

Mesencephalic dopaminergic system (MDS) neurons may participate in learning by providing a prediction error signal to their targets, which include ventral striatal, orbital, and medial frontal regions, as well as by showing sensitivity to the degree of uncertainty associated with individual stimuli. We investigated the mechanisms of probabilistic classification learning in humans using functional magnetic resonance imaging to examine the effects of feedback and uncertainty. The design was optimized for separating neural responses to stimulus, delay, and negative and positive feedback components. Compared with fixation, stimulus and feedback activated brain regions consistent with the MDS, whereas the delay period did not. Midbrain activity was significantly different for negative versus positive feedback (consistent with coding of the "prediction error") and was reliably correlated with the degree of uncertainty as well as with activity in MDS target regions. Purely cognitive feedback apparently engages the same regions as rewarding stimuli, consistent with a broader characterization of this network.

Adult↗
PubMed2006

Collinear facilitation is largely uncertainty reduction.

When flanked by collinear Gabor patches, detection thresholds for a target Gabor patch improve by up to a factor of 2. This result has been interpreted as evidence for collinear facilitation. However, facilitation has been observed only for targets near detection threshold, where observers seem uncertain about the location and other properties of the stimulus. So the effect of the flankers may be to reduce this uncertainty. If this is true, then other cues to target location should produce a similar improvement in thresholds. To test this hypothesis, we measured contrast detection thresholds for a Gabor target alone, and in the presence of either a faint circle surrounding the target location, or two high-energy flanking Gabor patches. We also used an adaptive procedure to measure the slope of the psychometric function to determine whether the slopes were considerably lower in the presence of location cues or flanking Gabors, as predicted by signal detection theory when uncertainty is reduced. As observed previously, the presence of collinear flankers improved detection thresholds by a factor of two. Yet, on average, the circle alone accounted for the most of the facilitation; for three of our five observers, it improved thresholds as much as the collinear flankers. Other cues that specified target location produced similar improvements in detection thresholds. The slopes of the psychometric functions were much shallower in the presence of these location cues or the collinear flankers compared to the target-alone condition. This change in the slopes indicates that the threshold improvement is largely due to a significant reduction in uncertainty.

Contrast Sensitivity↗
PubMed2005

How children and adults produce and perceive uncertainty in audiovisual speech.

We describe two experiments on signaling and detecting uncertainty in audiovisual speech by adults and children. In the first study, utterances from adult speakers and child speakers (aged 7-8) were elicited and annotated with a set of six audiovisual features. It was found that when adult speakers were uncertain they were more likely to produce fillers, delays, high intonation, eyebrow movements, and "funny faces." The basic picture for the child speakers was somewhat similar, in that the presence of certain audiovisual cues correlated with uncertainty, but the differences were relatively small and less often significant. In the second study both adult and child judges watched responses from adult and child speakers selected from the first study to find out whether they were able to correctly estimate a speakers' level of uncertainty. It was found that both child and adult judges gave more accurate scores for answers from adult speakers than from child speakers and that child judges overall provided less accurate scores than adult judges.

Adult↗
PubMed2005

Uncertainty principle of genetic information in a living cell.

BACKGROUND: Formal description of a cell's genetic information should provide the number of DNA molecules in that cell and their complete nucleotide sequences. We pose the formal problem: can the genome sequence forming the genotype of a given living cell be known with absolute certainty so that the cell's behaviour (phenotype) can be correlated to that genetic information? To answer this question, we propose a series of thought experiments. RESULTS: We show that the genome sequence of any actual living cell cannot physically be known with absolute certainty, independently of the method used. There is an associated uncertainty, in terms of base pairs, equal to or greater than micros (where micro is the mutation rate of the cell type and s is the cell's genome size). CONCLUSION: This finding establishes an "uncertainty principle" in genetics for the first time, and its analogy with the Heisenberg uncertainty principle in physics is discussed. The genetic information that makes living cells work is thus better represented by a probabilistic model rather than as a completely defined object.

Animals↗
PubMed2006

Benefits of the uncertainty management intervention for African American and White older breast cancer survivors: 20-month outcomes.

In a 2 x 2 randomized block repeated measure design, this study evaluated the follow-up efficacy of the uncertainty management intervention at 20 months. The sample included 483 recurrence-free women (342 White, 141 African American women; mean age = 64 years) who were 5-9 years posttreatment for breast cancer. Women were randomly assigned to either the intervention or usual care control condition. The intervention was delivered during 4 weekly telephone sessions in which survivors were guided in the use of audiotaped cognitive-behavioral strategies and a self-help manual. Repeated measures MANOVAs evaluating treatment group, ethnic group, and treatment by ethnic interaction effects at 20 months indicated that training in uncertainty management resulted in improvements in cognitive reframing, cancer knowledge, and a variety of coping skills. Importantly, the 20-month outcomes also demonstrated benefits for women in the intervention condition in terms of declines in illness uncertainty and stable effects in personal growth over time.

Adaptation, Psychological↗
PubMed2003

Coping with uncertainty: a call for a new science-policy forum.

The scientific and policy worlds have different goals, which can lead to different standards for what constitutes "proof" of a change or phenomena, and different approaches for characterizing and conveying uncertainty and risk. These differences can compromise effective communication among scientists, policymakers, and the public, and constrain the types of socially compelling questions scientists are willing to address. In this paper, we review a set of approaches for dealing with uncertainty, and illustrate some of the errors that arise when science and policy fail to coordinate correctly. We offer a set of recommendations, including restructuring of science curricula and establishment of science-policy forums populated by leaders in both arenas, and specifically constituted to address problems of uncertainty.

Curriculum↗
PubMed2006

Integrated urban water modelling with uncertainty analysis.

In the last twenty years, the scientific world has paid particular care towards the problems that involve the environment. Accordingly, several researches were developed to describe phenomena that take place during both wet and dry periods and to increase the knowledge in this field. In particular, attention was addressed towards the problems linked with receiving water body pollution because of the impact of rain water in the urban environment. In order to obtain a good description of the problem, it is important to analyse both quantity and quality aspects connected with all the transformation phases that characterise the urban water cycle. Today, according to this point, integrated modelling approach is spreading, aiming to find solutions to improve the quality characteristics of the receiving water body. Because several models are connected together for analysing the fate of pollutants from the sources on the urban catchment to the final recipient, classical problems connected with the selection and calibration of parameters are amplified by the complexity of the modelling approach increasing the uncertainty and reducing the reliability connected with a model's application. For this reason, a parsimonious integrated modelling approach has been developed and its uncertainty has been evaluated adopting the well known GLUE framework. For the purpose of the study, the uncertainty analysis has been applied to a "semi-hypothetic" case study obtained connecting Fossolo catchment (Bologna-Italy) to the Oreto river near Palermo (Italy).

Cities↗
PubMed2003

Use of Monte Carlo simulation to investigate uncertainty in exposure modeling.

OBJECTIVES: This study used Monte Carlo (MC) simulation to examine the influence of uncertainty on an exposure model and to determine whether a difference exists between two worker groups in a ceramic fiber manufacturing plant. METHODS: Data on work practices and conditions were gathered in interviews with long-serving employees. With the use of previously developed deterministic modeling techniques and likely distributions for model parameters, MC simulations generated exposure profiles for the two job titles. RESULTS: The exposure profiles overlapped considerably, although the average estimated exposure for one job was approximately double that of the other. However, when the correlation between the model parameters in the two jobs was considered, it was concluded that there was a significant difference in the two estimates. CONCLUSIONS: Models are increasingly being used to estimate exposure. Different work situations inevitably result in different exposure estimates. However, it is difficult to determine whether such differences in estimated exposure between worker groups are simply the result of uncertainty with respect to the model parameters or whether they reflect real differences between occupational groups. This study demonstrates the value of MC simulation in helping define the uncertainty in deterministic model estimates.

Ceramics↗
PubMed2002

Validation of pesticide root zone model 3.12: employing uncertainty analysis.

Computer models are being increasingly used to provide an efficient cost-effective means of evaluating the fate and behavior of chemicals in the environment. These models can be used in lieu of or in conjunction with field studies. Because of the increasing reliance on models for critical regulatory decision making, the need arose to assess the validity of regulatory models via an analysis of the correlation of model response estimates with measured data. In conjunction with the evaluation of the correlation of model response estimates and measured field data, a rigorous statistically based validation was also warranted. Because of the unique nature of the correlative exercise using modeled and measured data, standard statistical analyses, while informative, failed to encompass factors associated with the uncertainty of measured environmental fate data and potential model inputs. In an effort to evaluate this uncertainty, an initial sensitivity analysis was performed where key model input parameters for runoff and leaching simulations were identified. Once the sensitive input parameters were identified, a Monte Carlo-based preprocessor was developed whereby the sampling distributions of these parameters were used to propagate uncertainty in the input parameters into error in model predictions. Importantly, assumptions about parameter distributions for input into the Monte Carlo tool were made only after a formal detailed site-specific analysis of measured field data. Employing the functionality of the Crystal Ball Pro development environment, the pesticide root zone model (PRZM) 3.12 was run iteratively for 500 trials, and model output was collated and analyzed. The model predictions were considered reasonably accurate for most regulatory requirements, and the model prediction error was considered acceptable.

Decision Making↗
PubMed2002

Understanding laboratory testing in diagnostic uncertainty: a qualitative study in general practice.

BACKGROUND: Better knowledge of the professional's motives for ordering laboratory tests in the case of diagnostic uncertainty may lead to interventions directed at reducing unnecessary testing. AIM: To gain insight into the general practitioner's (GP's) motives for ordering laboratory tests for patients presenting with unexplained complaints. DESIGN OF STUDY: Semi-structured interviews based on surgery observations. SETTING: Twenty-one general practices in rural and urban areas of The Netherlands. METHOD: Investigation of the GP's perception of determinants of test-ordering behaviour in the situation of diagnostic uncertainty. The interviews were structured by evaluating the consultations and test-ordering performance of that day. RESULTS: Dutch GPs vary considerably in their motives for ordering tests. Numerous motives emerged from the data. Some examples of important themes include: personal routines; tolerance of diagnostic uncertainty; time pressure; and tactical motives for test ordering. Complying with the perceived needs of the patient for reassurance through testing is seen as an easy, cost- and time-effective strategy. A clear hierarchy in the determinants was not found. CONCLUSION: The decision to request laboratory testing is the result of a complex interaction of considerations that are often conflicting. Designers of interventions meant to improve the ordering of tests should be aware of the numerous determinants, and take contextual variables into account.

Adult↗
PubMed2003

[The handling of uncertainty in economic evaluations of health care strategies].

BACKGROUND: The recent development of prospective economic evaluations in association with randomized controlled clinical trials has provided clinical and economic data allowing a statistical analysis of uncertainty. Pertinent comparison of alternative medical strategies in the cost-effectiveness analysis requires analysis of the incremental cost-effectiveness ratio. In this work, we were interested in developing confidence regions of the cost-effectiveness ratio in order to take into consideration its uncertainty which creates a certain number of problems when the denominator approaches zero. Our objectives were to conduct a critical analysis of the different estimations used and examine their application in the decision making process. METHODS: There are two kinds of methods: those based on the density of the estimated ratio (Taylor method, parametric and non-parametric bootstrap methods such as percentile, percentile-t and bias-corrected and accelerated methods) and those based on the bivariate density of the variable pair: difference of average costs, difference of average effects (box method, ellipse method, and Fieller method). RESULTS: We showed that methods based on the density of the ratio become unstable and inapplicable when the statistical difference of average effects tends towards zero. In practice however, data often take on such a pattern. We give an example of an economic evaluation as an illustration. Bivariate density methods do not have this drawback. Moreover, the "mirror decision" phenomenon requires that the region of confidence be a directed single confidence sector for valid decision making. CONCLUSIONS: Uncertainty must be taken into account for all economic evaluations but the use of undirected confidence regions is inappropriate as a decision-making tool.

Analysis of Variance↗
PubMedDate not supplied

Statistical distributions of uncertainty and variability in activated sludge model parameters.

All models used in activated sludge design and analysis use parameters to characterize process performance. The values of these parameters are often assumed based on default values recommended in the literature, but to date, no quantitative estimates of the parameter uncertainties have been published. Similarly, little attention has been given to quantifying site-specific parameter variability, even though its occurrence has been observed several times in the literature. In this paper, universal uncertainty distributions of the model parameters from Activated Sludge Model No. 1 are developed from a database of parameter values reported in the literature using Bayesian statistics. Site-specific distributions of parameter variability were developed using the same techniques. All parameter distributions developed demonstrated that significant uncertainty and variability exist, which could lead to overdesign or plant failure if not considered during the design process.

Bayes Theorem↗
PubMed2005

Uncertainty and precaution in environmental management.

In this paper, two different visions of the relationship between science and policy are contrasted with one another: the "modern" vision and the "precautionary" vision. Conditions which must apply in order to invoke the Precautionary Principle are presented, as are some of the main challenges posed by the principle. The following central question remains: If scientific certainty cannot be provided, what may then justify regulatory interventions, and what degree of intervention is justifiable? The notion of "quality of information" is explored, and it is emphasized that there can be no absolute definition of good or bad quality. Collective judgments of quality are only possible through deliberation on the characteristics of the information, and on the relevance of the information to the policy context. Reference to a relative criterion therefore seems inevitable and legal complexities are to be expected. Uncertainty is presented as a multidimensional concept, reaching far beyond the conventional statistical interpretation of the concept. Of critical importance is the development of methods for assessing qualitative categories of uncertainty. Model quality assessment should observe the following rationale: identify a model that is suited to the purpose, yet bears some reasonable resemblance to the "real" phenomena. In this context, "purpose" relates to the policy and societal contexts in which the assessment results are to be used. It is therefore increasingly agreed that judgment of the quality of assessments necessarily involves the participation of non-modellers and non-scientists. A challenging final question is: How to use uncertainty information in policy contexts? More research is required in order to answer this question.

Decision Making↗
PubMed2005

The precautionary principle in times of intermingled uncertainty and risk: some regulatory complexities.

This article explores the use of the precautionary principle in situations of intermingled uncertainty and risk. It analyses how the so-called uncertainty paradox works out by examining the Pfizer case. It reveals regulatory complexities that result from contradictions in precautionary thinking. In conclusion, a plea is made for embedment of uncertainty information, while stressing the need to rethink regulatory reform in the broader sense.

Animal Feed↗
PubMed2005

Uncertainty as a monster in the science-policy interface: four coping strategies.

Using the metaphor of monsters, an analysis is made of the different ways in which the scientific community responds to uncertainties that are hard to tame. A monster is understood as a phenomenon that at the same moment fits into two categories that were considered to be mutually excluding, such as knowledge versus ignorance, objective versus subjective, facts versus values, prediction versus speculation, science versus policy. Four styles of coping with monsters in the science-policy interface can be distinguished with different degrees of tolerance towards the abnormal: monster-exorcism, monster-adaptation, monster-embracement, and monster-assimilation. Each of these responses can be observed in the learning process over the past decades and current practices of coping with uncertainties in the science policy interface on complex environmental problems. We might see this ongoing learning process of the scientific community of coping with complex systems as a dialectic process where one strategy tends to dominate the field until its limitations and shortcomings are recognized, followed by a rise of one of the other strategies. We now seem to find ourselves in a phase with growing focus on monster assimilation placing uncertainty at the heart of the science-policy and science-society interfaces.

Environment↗