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PubMed1996

Relationships among illness uncertainty, stress, coping, and emotional well-being at entry into a clinical drug trial.

The purpose of this cross-sectional study was to examine the relationships among illness uncertainty, stress, coping, and emotional well-being at the time of entry into a clinical drug trial. Hopefulness and mood state were included as indicators of emotional well-being. The sample included 59 clients who participated in a 2-year trial using methotrexate for progressive multiple sclerosis. Results indicated that ambulation status, education, perceived stress, and illness uncertainty were the best correlates of emotional well-being. The results suggest that clients entering a drug trial with high levels of illness uncertainty and stress are likely to experience mood disturbances and feel less hopeful about treatment effectiveness. This information may be used as a foundation for developing nursing interventions designed to foster emotional well-being at the time of entry into drug trials.

Adaptation, Psychological↗
PubMed1999

Reasoning under uncertainty in deluded schizophrenic patients: a longitudinal study.

Several current hypotheses consider the process of attribution of importance to stimuli and the integration of actually perceived reality with experience as a cognitive base for the genesis of delusions. We tested these models by a comparison of deluded schizophrenics, healthy controls, and anxious patients on reasoning under uncertainty. Reasoning under uncertainty was examined in currently deluded schizophrenics (n = 29), in 16 of them also in remission, in normal control groups (n = 35), and in anxious patients (n = 31) using a probabilistic inference task. Acutely psychotic schizophrenics were less ready than normal subjects, anxious patients, and schizophrenics, in remission to modify their judgement in probabilistic situation confronted with potentially disconfirmatory data. They were also less prone than anxious patients and schizophrenics in remission to correct their estimate confronted with confirmatory data. The data support the hypothesis of a weaker influence of incoming stimuli on reasoning under uncertainty as a cognitive base of the maintenance of delusions.

Acute Disease↗
PubMed2002

Uncertainties in alanine dosimetry in the therapeutic dose range.

A method for evaluating the overall uncertainty of alanine EPR transfer dosimetry in the therapeutic dose range is described. The method uses experimental data on EPR signal reproducibility from replicate dosimeters irradiated to low doses (1-5 Gy), estimates of Type B uncertainties, and Monte Carlo simulations of heteroscedastic orthogonal linear regression. A Bruker ECS106 spectrometer and Bruker alanine dosimeters have been used for this evaluation. The results demonstrate that alanine dosimetry can be used for transfer dosimetry in that range with the overall uncertainty 1.5-4% (1sigma) depending on the dose, the number of replicate dosimeters. and the duration of the calibration session (the session should not exceed one working day).

Alanine↗
PubMed2000

Importance of covariances for uncertainty estimates in measurement of radionuclide mixtures by multichannel counting.

Multichannel counting is often used when samples containing a mixture of known radionuclides are measured. Solutions to this method have been presented but to our knowledge, none of them took into account the covariances for evaluating the uncertainty of measurement. This paper presents new solutions for estimating uncertainties in measurement of radionuclide mixtures by multichannel counting and shows that covariances may contribute significantly to uncertainty of measurement so that they must be evaluated.

Alpha Particles↗
PubMedDate not supplied

Gaining a new perspective on life as a consequence of uncertainty in HIV infection.

HIV infection affects the lives of hundreds of thousands of North Americans. The experience of those infected is one of enormous upheaval. An HIV diagnosis can disrupt both daily life and the ability to plan for the future. Central to this experience is the uncertainty of a disease with vague symptomatology, changing medical management, and social stigma. This qualitative study explores the experience and consequences of uncertainty in the lives of 10 people with HIV infection. In-depth focused interviews were conducted to explore uncertainty after HIV diagnosis. Findings reveal that individuals living with HIV infection form a new perspective on life, which is maintained through five core experiences: surviving the HIV diagnosis, taking care, living in the present, seeking support, and appreciating the positive. Each core experience is comprised of a number of actions used by the individual to formulate and maintain the new perspective on life.

Adaptation, Psychological↗
PubMed2001

Analysis of uncertainties in estimates of components of variance in multivariate ROC analysis.

RATIONALE AND OBJECTIVES: Solutions have previously been presented to the problem of estimating the components of variance in the general linear model used for multivariate receiver operating characteristic (ROC) analysis. The case where the variance components do not change across the modalities under comparison was first treated, followed by the case where they are permitted to change. No analysis of uncertainties in these estimates has been presented previously. MATERIALS AND METHODS: For the case where the variance components do not change across modalities, the "jackknife-after-bootstrap" resampling procedure can be used together with conventional linear propagation of variance to solve for the uncertainties in estimates of the components. For the case where the components are permitted to change across modalities, a slight elaboration of this procedure is presented. RESULTS: The approach was validated by Monte Carlo simulations, where uncertainties in estimates of the variance components calculated by the jackknife-after-bootstrap procedure were found to converge in the mean to the Monte Carlo results over many independent trials. The method is exemplified with data from a study of readers-with and without the aid of a computer-assist modality-given the task of discriminating benign from malignant masses in mammography. CONCLUSION: The present approach is relevant to a broad class of problems where estimates of multiple contributions to the variance observed in ROC assessment of diagnostic modalities are desired, in particular, for the assessment of multiple-reader studies of computer-aided diagnosis in radiology where the variance components may change across reading modalities (eg, unaided vs computer-aided reading).

Analysis of Variance↗
PubMed2000

CNV and temporal uncertainty with 'ageing' and 'non-ageing' S1-S2 intervals.

OBJECTIVES: Uncertainty about the timing of a known external event is an everyday phenomenon but has been rarely investigated with electrophysiological methods. We studied how the amplitude of the contingent negative variation (CNV) is affected by temporal variation of S2 presentation. Competing hypotheses about the development of CNV during the foreperiod until S2 presentation were that CNV either would follow a monotonic trend, be it increasing or decreasing, or alternatively that the time-course of CNV would be affected by the probability with which S2 was presented at each time-point in a given task. METHODS: The interval between cueing stimulus and imperative stimulus was randomly chosen from 3 different values between 1.3 and 2.6 s, using 3 different probability distributions in separate blocks: an 'ageing', a 'non-ageing' and a 'Gaussian' distribution. RESULTS: As previously shown, reaction times were determined by the probability of the imperative stimulus at the given length of the foreperiod. The same was found for CNV amplitude: the effects of temporal uncertainty on CNV mainly depended on the particular distribution of temporal probabilities used in a block. The relevant parameter was the a posteriori probability of event occurrence, very similar to the effects of this parameter on response times. In fact, the major part of the effect of a posteriori probability on CNV was common variation of CNV and response times. CONCLUSIONS: Thus, under temporal uncertainty the amplitude of CNV reflects the subjective expectancies for the occurrence of a given event, with this variation being related to variations in response times.

Adult↗
PubMed1997

Healthy years equivalents versus time trade-off. Ambiguity on certainty and uncertainty.

Preference assessment literature has debated the equivalence of the healthy years equivalents (HYE) and time trade-off (TTO) methods. The central issue is whether the HYE measures preferences under uncertainty. This work shows that the two stages of the HYE first add and then remove the element of uncertainty so that ultimately the technique doses not measure preferences under uncertainty. This makes the HYE, at best, a cumbersome equivalent of the TTO.

Decision Support Techniques↗
PubMed2000

An ICP-OES method with 0.2% expanded uncertainties for the characterization of LiA1O2

An improved inductively coupled plasma-optical emission spectrometry (ICP-OES) method has been applied to the determination of Li and A1 mass fractions and the Li/A1 amount-of-substance ratio in representative samples of LiA1O2. This ICP-OES method has uncertainty on the order of 0.2%,(2,3) comparable to the best analytical methods. This method is based on several strategies, which are detailed in this work. The mean measured mass fractions of Li and A1 in eight samples were 0.10151 +/- 0.00016 (+/-0.16%) and 0.41068 +/- 0.00056 (+/-0.14%), and the mean Li/A1 amount-of-substance ratio was 0.9793 +/- 0.0017 (+/-0.17%). The uncertainty is dominated by sample handling and heterogeneity-about a factor of 2 larger than the ICP-OES instrumental uncertainties, which were 0.04% for A1 and 0.07% for Li.

Journal Article↗
PubMed2001

Sources of uncertainty in isotope ratio measurements by inductively coupled plasma mass spectrometry.

A model is presented describing the effects of dead time and mass bias correction factor uncertainties, flicker noise, and counting statistics on isotope ratio measurement precision using inductively coupled plasma mass spectrometry (ICPMS) with a single collector. Noise spectral analysis is exploited to enable estimation of the flicker noise parameters. For the instrument used, the flicker noise component exhibited a fairly weak frequency (t) dependence (is proportional to f -0.33+/-0.12), but was directly proportional to the total number of counts, Q. As white noise, determined by counting statistics, is given by Q0.5, the isotope ratio measurement uncertainties will actually cease to improve when Q exceeds a certain threshold. This would suggest that flicker noise could become the limiting factor for the precision with which isotope ratios can be determined by ICPMS. However, under most experimental conditions, uncertainties associated with mass discrimination and dead time correction factors are decisive. For ratios up to approximately 22 (115In/113In), optimum major isotope count rates are generally below 0.3 MHz, for which precision in the mass discrimination factor is limiting. The model derived could be used as a starting point for determining optimum conditions and understanding the limitations of single-collector ICPMS for precise isotope ratio measurements.

Journal Article↗
PubMedDate not supplied

Application of a decision-support tool to assess pooling strategies in perfusion culture processes under uncertainty.

Biopharmaceutical manufacture is subject to numerous risk factors that may affect operational costs and throughput. This paper discusses the need for incorporating such uncertainties in decision-making tools in order to reflect the inherent variability of process parameters during the operation of a biopharmaceutical plant. The functionalities of a risk-based prototype tool to model cost summation, perform mass balance calculations, simulate resource handling, and incorporate uncertainties in order to evaluate the potential risk associated with different manufacturing strategies are demonstrated via a case study. The case study is based upon the assessment of pooling strategies in the perfusion culture of mammalian cells to deliver a therapeutic protein for commercial use. Monte Carlo simulations, which generate random sample behaviors for probabilistic factors so as to imitate the uncertainties inherent in any process, have been applied. This provides an indication of the range of possible output values and hence enables trends or anomalies in the expected performance of a process to be determined.

Animals↗
PubMedDate not supplied

Decision-support tool for assessing biomanufacturing strategies under uncertainty: stainless steel versus disposable equipment for clinical trial material preparation.

This paper presents the application of a decision-support tool, SIMBIOPHARMA, for assessing different manufacturing strategies under uncertainty for the production of biopharmaceuticals. SIMBIOPHARMA captures both the technical and business aspects of biopharmaceutical manufacture within a single tool that permits manufacturing alternatives to be evaluated in terms of cost, time, yield, project throughput, resource utilization, and risk. Its use for risk analysis is demonstrated through a hypothetical case study that uses the Monte Carlo simulation technique to imitate the randomness inherent in manufacturing subject to technical and market uncertainties. The case study addresses whether start-up companies should invest in a stainless steel pilot plant or use disposable equipment for the production of early phase clinical trial material. The effects of fluctuating product demands and titers on the performance of a biopharmaceutical company manufacturing clinical trial material are analyzed. The analysis highlights the impact of different manufacturing options on the range in possible outcomes for the project throughput and cost of goods and the likelihood that these metrics exceed a critical threshold. The simulation studies highlight the benefits of incorporating uncertainties when evaluating manufacturing strategies. Methods of presenting and analyzing information generated by the simulations are suggested. These are used to help determine the ranking of alternatives under different scenarios. The example illustrates the benefits to companies of using such a tool to improve management of their R&D portfolios so as to control the cost of goods.

Clinical Trials as Topic↗
PubMed2001

Geostatistical assessment and validation of uncertainty for three-dimensional dioxin data from sediments in an estuarine river.

Contaminated sediment management is an urgent environmental and regulatory issue worldwide. Because remediation is expensive, sound quantitative assessments of uncertainty aboutthe spatial distribution of contaminants are critical, butthey are hampered bythe physical complexity of sediment environments. This paper describes the use of geostatistical modeling approaches to quantify uncertainty of 2,3,7,8-tetrachlorodibenzo-p-dioxin concentrations in Passaic River (New Jersey) sediments and to incorporate this information in decision-making processes, such as delineation of contaminated areas and additional sampling needs. First, coordinate transformation and analysis of three-dimensional semivariograms were used to describe and modelthe directional variability accounting forthe meandering course of the river. Then, indicator kriging was employed to provide models of local uncertainty at unsampled locations without requiring a prior transform (e.g. log-normal) of concentrations. Cross-validation results show that the use of probability thresholds leads to more efficient delineation of contaminated areas than a classification based on the exceedence of regulatory thresholds by concentration estimates. Depending on whether additional sampling aims at reducing prediction errors or misclassification rates, the variance of local probability distributions or a measure of the expected closeness to the regulatory threshold can be used to locate candidate locations.

Decision Making↗
PubMed2005

Illustrating sensitivity and uncertainty in environmental fate models using partitioning maps.

Variations of model predictions of the environmental fate of organic contaminants are usually analyzed for only one or at most a few selected chemicals, even though parameter sensitivity and contribution to uncertainty are widely different for different chemicals. A graphical method is introduced that allows for the comprehensive investigation of model sensitivity and uncertainty for all persistent organic nonelectrolytes at the same time. This is achieved by defining a two-dimensional hypothetical "chemical space" as a function of the equilibrium partition coefficients between air, water, and octanol (KOW, KAW, KOA), and plotting sensitivity and/or uncertainty of a specific model result to each input parameter as a function of this chemical space. The approach is illustrated for the bulk phase concentrations in air, water, soil, and sediment calculated by a level III model. Colored contour maps facilitate the identification of those input parameters that cause a high output variation of hypothetical and real chemicals. They also allow for the easy categorization of chemicals in terms of common parameter sensitivities, and thus comparable environmental behavior. Sensitivity varies with the mode of emission and the degradability of the chemicals, making it necessary to develop multiple sets of contour maps. Comparison of these sets of maps in turn allows the investigation of how parameter sensitivities change as a result of changes in mode of emission and persistence. The presented method can be used for investigating the sensitivity of any prediction obtained with any linear fate model that characterizes the partitioning behavior of organic chemicals with KAW, KoW, and KOA. Once the sensitivity maps have been constructed for a given environmental scenario, it is possible to perform a sensitivity analysis for a specific chemical by simple. placement of the substances' partitioning combinations within the chemical space. The maps can further contribute to the mechanistic understanding of a model's behavior, can aid in explaining observations of divergent environmental behavior of related substances, and can provide a rationale for grouping chemicals with similar model behavior, or for selecting representative example chemicals for a model investigation. They can also help in deciding when accurate and precise knowledge of physical chemical property data is crucial and when approximate numbers suffice to conduct a model investigation.

Air↗
PubMed2005

Uncertainty of air pollution cost estimates: to what extent does it matter?

How large is the social cost penalty if one makes the wrong choice because of uncertainties in the estimates of the costs and benefits of environmental policy measures? For discrete choices there is no general rule other than the recommendation to always carefully compare costs and benefits when introducing policies for environmental protection. For continuous choices (e.g., the ceiling for the total emissions of a pollutant by an entire sector or region), it is instructive to look at the cost penalty as a function of the error in the incremental damage cost estimate. Using abatement cost curves for NOx, SO2, dioxins, and CO2, this paper evaluates the cost penalty for errors in the following: national emission ceilings for NOx and SO2 in each of 12 countries of Europe, an emission ceiling for dioxins in the UK, and limits for the emission of CO2 in Europe. The cost penalty turns out to be remarkably insensitive to errors. An error by a factor of 3 due to uncertainties in the damage estimates for NOx and SO2 increases the total social cost by at most 20% and in most cases much less. For dioxins, the total social cost is increased by at most 10%. For CO2, several different possible cost curves are examined: for some the sensitivity to uncertainties is greater than for the other pollutants, but even here the penalty is less than 30% and in most cases much less if the true damage costs are twice as high as the ones estimated. The paper also quantifies the benefit of improving the accuracy of damage cost estimates by further research.

Air Pollutants↗
PubMed2001

Determination of sulfamethazine and trimethoprim in liquid feed premixes by HPLC and diode array detection, with an analysis of the uncertainty of the analytical results.

Sulfamethazine (SMZ) and trimethoprim (TMP) are antibacterials used in veterinary practice. This paper describes a method for their determination in veterinary liquid feed premixes that is based on liquid chromatography with diode array detection. Gradient elution with methanol and ammonium acetate achieved excellent separation of the two analytes within 15 min without any interference from the matrix. Absorbance of the column effluent was monitored at 264 nm for SMZ and at 230 nm for TMP. Detailed analyses of the uncertainties of determinations afford estimated expanded uncertainties of, respectively, 0.2 and 0.1 w/v % for typical SMZ and TMP concentrations of 10.7 and 2.1 w/v %, respectively. At the lower end of the calibrated range of the method, the dominant source of uncertainty is the preparation of standards and the construction of the calibration line.

Animal Feed↗
PubMed2004

Simplified enzymatic high-performance anion exchange chromatographic determination of total fructans in food and pet food-limitations and measurement uncertainty.

A simplified method to determine total fructans in food and pet food has been developed and validated. It follows the principle of AOAC method 997.08, i.e., high-performance anion exchange chromatographic (HPAEC) determination of total fructose released from fructans (F(f)) and total glucose released from fructans (G(f)) after enzymatic fructan hydrolysis. Unlike AOAC method 997.08, calculation of total fructans is based on the determination of F(f) alone. This is motivated by the inherent difficulty to accurately determine low amounts of G(f) since many food and pet food products contain other sources of total glucose (e.g., starch and sucrose). In this case, a correction factor g can be used (1.05 by default) to take into account the theoretical contribution of G(f). At levels >5% of total fructans and in commercial fructan ingredients, both F(f) and G(f) can and should be accurately determined; hence, no correction factor g is required. The method is suitable to quantify total fructans in various food and pet food products at concentrations >or=0.2% providing that the product does not contain other significant sources of total fructose such as free fructose or sucrose. Recovery rates in commercial fructan ingredients and in selected food and pet food ranged from 97 to 102%. As part of a measurement uncertainty estimation study, individual contributions to the total uncertainty (u) of the total fructan content were identified and quantified by using the validation data available. As a result, a correlation between the sucrose content and the total uncertainty of the total fructan content was established allowing us to define a limit of quantitation as a function of the sucrose content. One can conclude that this method is limited to food products where the sucrose content does not exceed about three times the total fructan content. Despite this limitation, which is inherent to any total fructan method based on the same approach, this procedure represents an excellent compromise with regard to accuracy, applicability, and convenience.

Animals↗
PubMed1999

Conditional uncertainty analysis and implications for decision making: the case of WIPP.

Uncertainty analyses and the reporting of their results can be misinterpreted when these analyses are conditional on a set of assumptions generally intended to bring some conservatism in the decisions. In this paper, two cases of conditional uncertainty analysis are examined. The first case includes studies that result, for instance, in a family of risk curves representing percentiles of the probability distribution of the future frequency of exceeding specified consequence levels conditional on a set of hypotheses. The second case involves analyses that result in an interval of outcomes estimated on the basis of conservative assumptions. Both types of results are difficult to use because they are sometimes misinterpreted as if they represented the output of a full uncertainty analysis. In the first case, the percentiles shown on each risk curve may be taken at face value when in reality (in marginal terms) they are lower if the chosen hypotheses are conservative. In the second case, the fact that some segments of the resulting interval are highly unlikely--or that some more benign segments outside the range of results are quite possible--does not appear. Also, these results are difficult to compare to those of analyses of other risks, possibly competing for the same risk management resources, and the decision criteria have to be adapted to the conservatism of the hypotheses. In this paper, the focus is on the first type (conditional risk curves) more than on the second and the discussion is illustrated by the case of the performance assessment of the Waste Isolation Pilot Plant in New Mexico. For policy-making purposes, however, the problems of interpretation, comparison, and use of the results are similar.

Confidence Intervals↗