Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Uncertainty”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47Linked to original sources
PubMed2006

Reliability of the ICRP'S dose coefficients for members of the public: IV. basis of the human alimentary tract model and uncertainties in model predictions.

The biokinetic and dosimetric model of the gastrointestinal (GI) tract applied in current documents of the International Commission on Radiological Protection (ICRP) was developed in the mid-1960s. The model was based on features of a reference adult male and was first used by the ICRP in Publication 30, Limits for Intakes of Radionuclides by Workers (Part 1, 1979). In the late 1990s an ICRP task group was appointed to develop a biokinetic and dosimetric model of the alimentary tract that reflects updated information and addresses current needs in radiation protection. The new age-specific and gender-specific model, called the Human Alimentary Tract Model (HATM), has been completed and will replace the GI model of Publication 30 in upcoming ICRP documents. This paper discusses the basis for the structure and parameter values of the HATM, summarises the uncertainties associated with selected features and types of predictions of the HATM and examines the sensitivity of dose estimates to these uncertainties for selected radionuclides. Emphasis is on generic biokinetic features of the HATM, particularly transit times through the lumen of the alimentary tract, but key dosimetric features of the model are outlined, and the sensitivity of tissue dose estimates to uncertainties in dosimetric as well as biokinetic features of the HATM are examined for selected radionuclides.

Dose-Response Relationship, Radiation↗
PubMed2007

Uncertainties in doses calculated according to ICRP recommendations after inhalation of 239PUO2 and early chest monitoring.

This study estimates uncertainties in Pu biokinetics and effective doses calculated after an acute inhalation exposure to 239PuO2 according to ICRP recommendations (default values for aerosols size and PuO2 dissolution parameters). This was performed using the most recently reported variations in model parameters and simulations after a Monte Carlo approach. Without chest monitoring, uncertainties in thoracic retention and plutonium excretion was 8-10 (95% confidence interval as the ratio between 97.5 and 2.5 percentiles of the lognormal distributions) up to 900 d after exposure. Early chest monitoring reduces significantly the uncertainties in plutonium biokinetics and doses which remain within a 95% confidence interval of 2.3 as compared with 6.6, without monitoring. Analysis of bioassay data previously reported shows that the dose delivered to some individuals can be out of the confidence interval, which was mostly due to an inhibition of the late mechanical clearance of the alveolar interstitium.

Administration, Inhalation↗
PubMed1989

Uncertainty in predictions of fallout radionuclides in foods and of subsequent ingestion.

Uncertainty in predictions from the PATHWAY food-chain model was estimated using Monte Carlo simulation. Uncertainty estimates, measured by the geometric standard deviation (GSD), were obtained for median values of time-integrated concentrations of 131I, 136Cs, and 137Cs in foods and for the corresponding time-integrated intakes resulting from ingestion of all foods. The GSDs associated with a given food for the two short-lived radionuclides, 131I and 136Cs, were not significantly different, but they differed from the GSDs for the longer-lived radionuclide. The GSDs for integrated concentrations of radionuclides in milk varied with the time of year fallout was deposited, but uncertainty for nondairy products was relatively independent of the date of fallout deposition. The estimated GSDs were applied to other radionuclides of interest based on physical half-life and ranged from 1.7 to 2.7 for time-integrated intake across all foods for radionuclides with physical half-lives less than 30 d, from 1.8 to 2.3 for half-lives ranging from 30 to 500 d, and from 1.9 to 2.1 when half-lives were greater than 500 d.

Animal Feed↗
PubMed1996

An approach to evaluating bias and uncertainty in estimates of external dose obtained from personal dosimeters.

This paper describes an approach to quantifying errors in recorded estimates of external radiation dose obtained from personal dosimeters and applies the approach to dose estimates of workers at the Hanford site. Because a major objective of this evaluation is to provide the information needed for adjusting epidemiologic dose-response analyses of worker data for errors in dose estimates, the paper addresses the extent that errors for different workers are correlated, focuses on recorded doses as estimates of organ doses, and focuses on recorded doses as estimates of organ doses, and gives consideration to both annual and cumulative doses. The evaluation emphasizes errors resulting from the fact that dosimeters are limited in their ability to respond accurately to all radiation energies to which workers are exposed or to radiation coming from all directions. For each of several sources of error, systematic bias factors are estimated for two energy ranges (100--300 keV and 300--1,000 keV), two geometries (anterior-posterior and rotational), and four calendar year periods. These are then combined using information provided by health physicists on energies and geometries in Hanford exposure environments. Except for the period before 1958, deep dose, the objective of modern dosimetry systems, was found to be fairly accurately estimated. Lung dose was found to be overestimated by about 10%, and bone marrow dose was found to be overestimated by about 50%. However, many aspects of this evaluation relied heavily on subjective judgments, and, thus, these factors are subject to considerable uncertainty. Estimates of uncertainty in the bias factors and uncertainty reflecting random error are provided.

Bias↗
PubMed2001

Risks of fatal cancer from inhalation of 239,240plutonium by humans: a combined four-method approach with uncertainty evaluation.

The risk per unit dose to the four primary cancer sites for plutonium inhalation exposure (lung, liver, bone, bone marrow) is estimated by combining the risk estimates that are derived from four independent approaches. Each approach represents a fundamentally different source of data from which plutonium risk estimates can be derived. These are: (1) epidemiologic studies of workers exposed to plutonium; (2) epidemiologic studies of persons exposed to low-LET radiation combined with a factor for the relative biological effectiveness (RBE) of plutonium alpha particles appropriate for each cancer site of concern; (3) epidemiologic studies of persons exposed to alpha-emitting radionuclides other than plutonium; and (4) controlled studies of animals exposed to plutonium and other alpha-emitting radionuclides extrapolated to humans. This procedure yielded the following organ-specific estimates of the distribution of mortality risk per unit dose from exposure to plutonium expressed as the median estimate with the 5th to 95th percentiles of the distribution in parentheses: lung 0.13 Gy(-1) (0.022-0.53 Gy(-1)); liver 0.057 Gy(-1) (0.011-0.47 Gy(-1)); bone 0.0013 Gy(-1) (0.000060-0.025 Gy(-1)); bone marrow (leukemia), 0.013 Gy(-1) (0.00061-0.05 Gy(-1)). Because the different tissues do not receive the same dose following an inhalation exposure, the mortality risk per unit intake of activity via inhalation of a 1-microm AMAD plutonium aerosol also was determined. To do this, inhalation dose coefficients based on the most recent ICRP models and accounting for input parameter uncertainties were combined with the risk coefficients described above. The following estimates of the distribution of mortality risk per unit intake were determined for a 1-microm AMAD plutonium aerosol with a geometric standard deviation of 2.5: lung 5.3 x 10(-7) Bq(-1) (0.65-35 x 10(-7) Bq(-1)), liver 1.2 x 10(-7) Bq(-1) (0.091-20 x 10(-7) Bq(-1)), bone 0.11 x 10(-7) Bq(-1) (0.0030-4.3 x 10(-7) Bq(-1)), bone marrow (leukemia) 0.049 x 10(-7) Bq(-1) (0.0017-0.59 x 10(-7) Bq(-1)). The cancer mortality risk for all sites was estimated to be 10 x 10(-7) Bq(-1) (2.1-55 x 10(-7) Bq(-1))--a result that agrees very well with other recent estimates. The large uncertainties in the risks per unit intake of activity reflect the combined uncertainty in the dose and risk coefficients.

Administration, Inhalation↗
PubMed2002

Dealing with uncertainty in formulating occupational and public exposure limits.

Scientists are forced to address many sources of uncertainty in the setting of exposure limits. This paper discusses the rationale for some of the approaches that have been used for many years to address uncertainties encountered in the setting of occupational and public exposure limits to protect against non-cancer effects of chemicals. These approaches are quite different from the methodology that has been adopted for the setting of exposure limits to power-frequency electric and magnetic fields to avoid adverse effects of induced electric fields and currents. The limitations of the non-standard electric and magnetic fields guideline methodology are described. To address these limitations, a probabilistic approach to developing exposure limits for electric and magnetic fields has been proposed. As a demonstration, this approach has been applied to the estimation of magnetic field exposures that would not pose significant risks of cardiac stimulation from electric fields induced in the torso. The results of this probabilistic analysis demonstrate the importance of explicitly characterizing potential sources of uncertainty and variability. Furthermore, the use of fixed, single point estimates of dosimetric parameters by electric and magnetic fields guideline-setting organizations provides more than adequate protection to individuals from the risk of cardiac stimulation. The mean magnetic field level that would increase the risk of cardiac stimulation is shown by this approach to be about three times higher than is predicted by dosimetric formulas used by the ACGIH and ICNIRP. If input data for parameters affecting the risk of adverse effects with lower thresholds, i.e., nerve stimulation, are developed and validated, this method could be used in the setting of electric and magnetic fields standards based more strongly on quantitative assessments of experimental data.

Electromagnetic Fields↗
PubMedDate not supplied

The effects of uncertainty in families with children who are chronically ill.

This study examined the experiences, stresses, support networks, and needs of four families with chronically ill children receiving home care. Chronic uncertainty appeared to be the major psychosocial stressor confronting each family. Parents experienced uncertainty when dealing with the child's illness, treatments, other family members, and healthcare professionals. Home care nurses had a great impact on minimizing the burden of uncertainty by providing consistent support and understanding, and normalizing the home environment.

Adaptation, Psychological↗
PubMed2003

Quantifying and reporting uncertainty from systematic errors.

Optimal use of epidemiologic findings in decision making requires more information than standard analyses provide. It requires calculating and reporting the total uncertainty in the results, which in turn requires methods for quantifying the uncertainty introduced by systematic error. Quantified uncertainty can improve policy and clinical decisions, better direct further research, and aid public understanding, and thus enhance the contributions of epidemiology. The error quantification approach proposed here is based on estimating a probability distribution for a bias-corrected effect measure based on externally-derived distributions of bias levels. Using Monte Carlo simulation, corrections for multiple biases are combined by identifying the steps through which true causal effects become data, and (in reverse order) correcting for the errors introduced by each step. The bias-correction calculations are the same as those used in sensitivity analysis, but the resulting distribution of possible true values is more than a sensitivity analysis; it is a more complete reporting of the actual study results. The approach is illustrated with an application to a recent study that resulted in the drug, phenylpropanolamine, being removed from the market.

Appetite Depressants↗
PubMed2003

Longitudinal analysis of illness uncertainty, coping, hopefulness, and mood during participation in a clinical drug trial.

The purpose of this longitudinal study was to examine the relationships among illness uncertainty, coping effectiveness, hopefulness, and mood in persons with chronic, progressive multiple sclerosis (MS) during participation in a double-blind clinical drug trial. The similarities and differences in the pattern of relationships among variables were investigated within each of four data collection time frames and across time. The convenience sample comprised 52 participants with clinically definite MS who participated in a 2-year trial using methotrexate to treat progressive MS. Participants with more severe disability were found to be less hopeful and more emotionally distressed. Participants with higher levels of hopefulness used more effective coping strategies and had more positive moods, and those with greater uncertainty about their MS were likely to experience less hopefulness and more negative moods. The pattern of relationships among uncertainty, coping, hopefulness, and mood did not change throughout participation in the drug trial. The findings may be used as a foundation for planning nursing interventions with patients involved in drug studies.

Adaptation, Psychological↗
PubMed2001

The influence of experimental and model uncertainties on EXAFS results.

We analyze EXAFS oscillations in k-space with the FEFF code to obtain main-shell distances Rv and mean-square displacement parameters sigma2i for all single and multiple scattering paths i in the shells v up to a maximum shell radius Rmax. To quantify the uncertainty in the determination of these model parameters we take into account experimental errors and uncertainties connected with background subtraction, with the approximate handling of the electronic many-body problem in FEFF, and with the truncation of the multiple scattering series. The impact of these uncertainties on the Rv and sigma2i is investigated in the framework of Bayesian methods. We introduce an a priori guess of these model parameters and consider two alternative strategies to control the weight of the a priori input relative to that of the experimental data. We can take a model parameter space of up to 250 dimensions. Optionally we can also fit the coordination numbers Nj (j < or = v) and the skewness of the distribution of the Rv besides the Rv and sigma2i. The method is applied to 10K Cu K-edge and 300K Au L3-edge data to obtain model parameters and their a posteriori error correlation matrices.

Journal Article↗
PubMed2006

Uncertainty estimation by convolution using spatial statistics.

Kriging has proven to be a useful tool in image processing since it behaves, under regular sampling, as a convolution. Convolution kernels obtained with kriging allow noise filtering and include the effects of the random fluctuations of the experimental data and the resolution of the measuring devices. The uncertainty at each location of the image can also be determined using kriging. However, this procedure is slow since, currently, only matrix methods are available. In this work, we compare the way kriging performs the uncertainty estimation with the standard statistical technique for magnitudes without spatial dependence. As a result, we propose a much faster technique, based on the variogram, to determine the uncertainty using a convolutional procedure. We check the validity of this approach by applying it to one-dimensional images obtained in diffractometry and two-dimensional images obtained by shadow moire.

Algorithms↗
PubMed2002

Risk and uncertainty analysis in government safety decisions.

Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of "conservatism" for the ranking of risk mitigation measures.

Journal Article↗
PubMed2002

Uncertainty in measurements of dermal absorption of pesticides.

Dermal absorption experiments form an important component in the assessment of risk from exposure to pesticides and other substances. Much dermal absorption data is gathered in rat experiments carried out using a certain standard protocol. Uncertainties in these data arise from many sources and can be quite large. For example, measurements of the systemic absorption of hexaconazole differed by more than an order of magnitude within a single experiment. Two diniconazole studies produced quite different results, due to minor differences in protocol and in chemical formulation. Limits of detection can also prevent accurate measurement when the amounts absorbed are small. These examples illustrate the need for measuring and reporting uncertainties in estimates that are based on these data. The most direct way to estimate uncertainty is to compute the sample standard deviations of replicate measurements. By pooling these estimates across dose and duration groups for which they are similar, the number of degrees of freedom is increased, and more precise confidence intervals can be obtained. In particular, the ratio of upper to lower 95% confidence limits was reduced by as much as ten-fold for hexaconazole, seven-fold for uniconazole, and nearly four-fold for propiconazole.

Absorption↗
PubMed2003

Joint persistence of transformation products in chemicals assessment: case studies and uncertainty analysis.

The joint persistence (JP) quantifies the environmental persistence of a parent compound and a selection of relevant transformation products. Here, the importance as well as the uncertainty of the JP in comparison to the persistence of the parent compound alone (primary persistence, PP) are investigated. To demonstrate the effect of transformation products on the environmental persistence of organic chemicals, three case studies of parent compounds (nonylphenol ethoxylates, perchloroethylene, atrazine) and transformation products are investigated in detail with a multimedia fate model. Comparison of the PP and JP values shows that transformation products can significantly increase the persistence. In addition to the point estimates of PP and JP, the associated uncertainties are investigated. For each of the case studies, the chemical-specific input parameters of all compounds are varied and the corresponding variance of the PP and JP is determined by Monte Carlo simulations. Interestingly, the higher number of input parameters required for the JP does not necessarily increase the uncertainty of the JP as compared to that of the PP alone. An exact mathematical expression specifying the contribution of each transformation product to the JP is given. When transformation products are grouped in different generations, it becomes discernible that the first generation increases the JP most; the later generations are of decreasing importance. Finally, the effect of incomplete knowledge of the transformation products and their properties on the JP results is discussed. For reliable JP estimates, knowledge of the first generation transformation products and their degradation rate constants is required.

Journal Article↗
PubMed2003

Further notes on public response to uncertainty in risks and science.

Given the prevalence of uncertainty and variability in estimates of environmental health risks, it is important to know how citizens interpret information representing uncertainty in risk estimates. Ranges of risk estimates from a hypothetical industry source elicited divergent evaluations of risk assessors' honesty and competence among New Jersey residents within one mile of one or more factories. A plurality saw ranges of risk estimates as both honest and competent, but with most judging such ranges as deficient on one or both dimensions. They wanted definitive conclusions about safety, tended to believe the high end of the range was more likely to be an accurate estimate of the risk, and believed that institutions only discuss risks when they are "high." Acknowledgment of scientific, as opposed to self-interested, reasons for uncertainty and disputes among experts was low. Attitude toward local industry seemed associated with, if not a cause of, attitudes about ranges of risk estimates. These reactions by industry neighbors appear to replicate the findings of Johnson and Slovic (1995, 1998), despite the hypothetical producer of risk estimates being industry instead of government. Respondents were older and less educated on average than were the earlier samples, but more diverse. Regression analyses suggested attitude toward industry was a major factor in these reactions, although other explanations (e.g., level of scientific understanding independent of general education) were not tested in this study.

Adolescent↗
PubMed2003

Correlations between parameters in risk models: estimation and propagation of uncertainty by Markov Chain Monte Carlo.

Monte Carlo simulation has become the accepted method for propagating parameter uncertainty through risk models. It is widely appreciated, however, that correlations between input variables must be taken into account if models are to deliver correct assessments of uncertainty in risk. Various two-stage methods have been proposed that first estimate a correlation structure and then generate Monte Carlo simulations, which incorporate this structure while leaving marginal distributions of parameters unchanged. Here we propose a one-stage alternative, in which the correlation structure is estimated from the data directly by Bayesian Markov Chain Monte Carlo methods. Samples from the posterior distribution of the outputs then correctly reflect the correlation between parameters, given the data and the model. Besides its computational simplicity, this approach utilizes the available evidence from a wide variety of structures, including incomplete data and correlated and uncorrelated repeat observations. The major advantage of a Bayesian approach is that, rather than assuming the correlation structure is fixed and known, it captures the joint uncertainty induced by the data in all parameters, including variances and covariances, and correctly propagates this through the decision or risk model. These features are illustrated with examples on emissions of dioxin congeners from solid waste incinerators.

Journal Article↗
PubMed2005

Integration of stochastic effects and data uncertainties into the design of process equipment.

Stochastic effects and data uncertainties are present in any engineering calculation. Their impact may be particularly important if they concern the design of process equipment. A calculation model for the dynamic behavior of a heat exchanger and procedures to deal with the related uncertainties are presented. Their propagation through the calculation by means of a Monte Carlo approach is shown. The temperature at the heat exchanger outlet and the step response of a sudden variation in the heat exchanger inlet temperature are simulated and evaluated by way of example. It is demonstrated that the inclusion of stochastic effects and uncertainties provides a more reliable basis for design decisions and hence reduces the probability of errors.

Journal Article↗
PubMed1988

Sources of maternal confidence and uncertainty and perceptions of problem-solving competence.

Although a mother's perception of her competence in problem-solving issues of infant care may affect her sensitivity to her infant's cues, little is known about factors that contribute to this perception. This study explored the type of information on which maternal confidence is based and examined its relationship to perceived competence in problem-solving issues of infant care. The 49 mothers of healthy newborns who participated in this study were interviewed 30 and 90 days after the infant's birth to learn about sources of confidence or uncertainty. The interview protocol also included scaled items to assess perceived problem-solving competence. The infant's mood was most frequently reported as either a source of confidence or uncertainty at both 30 and 90 days. The infant's response to care as a source of confidence or uncertainty was positively related to perceived competence, suggesting that strengthening mothers' attention to this source of information about their performance may be clinically useful. Direct study of the type of information used to evaluate competence in problem-solving is recommended, since it may differ from the type of information on which mothers base their confidence in caring for their infants.

Adult↗