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PubMed2005

Finding more meaning: the antecedents of uncertainty revisited.

AIMS AND OBJECTIVES: The objective of this study was to explore the extent to which several antecedents explained the uncertainty of men who were undergoing the watchful waiting management option for prostate cancer. BACKGROUND: Uncertainty plays a significant role in explaining various outcomes in the chronically ill. However, little is known about the factors that accompany and modify uncertainty. For uncertainty to predict the outcomes of individuals coping with illness, it is imperative to understand its accompanying antecedents. DESIGN: The study used a correlational single group non-experimental design. METHODS: The convenience sample completed a one-time mailed questionnaire aimed at measuring the antecedents of uncertainty. RESULTS: A total of 19 participants completed questionnaires. The results revealed significant relationships between level of education and length of time with illness and uncertainty. Stepwise multiple regression indicated that education explained 52% of the variance in uncertainty. CONCLUSIONS: This study strengthens the relationship between both education and length of time with illness, and uncertainty. It further supports the Uncertainty in Illness Model and enhances the understanding of the factors that influence uncertainty in the sample. RELEVANCE TO CLINICAL PRACTICE: This study assisted in the identification of factors that influence uncertainty in men undergoing the watchful waiting management option for prostate cancer. Future study should examine the role of antecedents in explaining uncertainty in additional populations and using alternative measures, when necessary.

Aged↗

PubMed2002

Evaluation of accuracy and uncertainty of ELISA assays for the determination of interleukin-4, interleukin-5, interferon-gamma and tumor necrosis factor-alpha.

The comparison of analytical results calls for validation of the assays used, i.e. for the documentation of accuracy (trueness and precision), linearity and specificity. In addition, there is a growing demand for evaluation and documentation of traceability and uncertainty of analytical results. However, models for establishing the traceability and uncertainty of immunoassay results are lacking. Sandwich enzyme-linked immunosorbent assays (ELISAs) were developed for determination of the human cytokines interleukin-4 (IL-4), interleukin-5 (IL-5), interferon-y (IFN-gamma) and tumor necrosis factor-alpha (TNF-alpha). The accuracy of each of the assays was evaluated in the ranges of 1-15 microg/l (IL-4), 0.001-1 microg/l (IL-5), 0.5-2.5 microg/l (IFN-T) and 0.14-2.2 microg/l (TNF-alpha). Other evaluated performance characteristics were the limit of detection (LOD), immunological specificity, and robustness. Traceability was ensured by the use of World Health Organization International Standards (WHO IS). An uncertainty budget, which combined the contribution from all known uncertainty components, was established for each cytokine ELISA. The between-run relative analytical standard deviation (RSDA) of the assessed ELISAs was found to be in the range of 11-18%, except for IL-5 where RSDA increased at decreasing concentrations. The LOD was 0.12 microg/l, 0.0077 microg/l, 0.0069 microg/l and 0.0063 microg/l for IL-4, IL-5, IFN-gamma and TNF-alpha, respectively. Traceability to the WHO IS was established for each of the cytokines. The combined relative standard uncertainty (U(result)/C(result)) was 28%, 22-62%, 28% and 24% for the IL-4, IL-5, IFN-gamma and TNF-alpha results, respectively. The major contributions to uncertainty came from the relative analytical standard deviation and from the uncertainty of the mass concentration of the WHO IS. The uncertainty of the WHO IS was not stated in the accompanying certificate and was evaluated by other means. The largest sources of uncertainty were located outside our laboratory. This means that the possibilities to improve the reliability of the results produced by the ELISAs are very limited. The task of evaluating measurement uncertainty would be much easier if producers of international reference standards reported the uncertainty of the value of standards. The model for evaluating uncertainty presented in this paper is applicable to other types of assays and to most analytical methods.

Bias↗

PubMed2006

Parameter sensitivity and uncertainty of the forest carbon flux model FORUG: a Monte Carlo analysis.

The Monte Carlo technique can be used to propagate input variable uncertainty and parameter uncertainty through a model to determine output uncertainty. However, to carry out Monte Carlo simulations, the uncertainty distributions or the probability density functions (PDFs) of the model parameters and input variables must be known. This remains one of the bottlenecks in current uncertainty research in forest carbon flux modeling. Because forest carbon flux models involve many parameters, we questioned whether it is necessary to take into account all parameters in the uncertainty analysis. A sensitivity analysis can determine the parameters contributing most to the overall model output uncertainty. This paper illustrates the usefulness of the Monte Carlo simulation technique for ranking parameters for sensitivity and uncertainty in process-based forest flux models. The uncertainty of the output (net ecosystem exchange, NEE) of the FORUG model was estimated for the Hesse beech forest (1997). Based on the arbitrary uncertainty of ten key parameters, a standard deviation of 0.88 Mg C ha(-1) year(-1) NEE was found which is equal to 24% of the mean value of NEE. Sensitivity analysis showed that the overall output uncertainty of the FORUG model can largely be determined by accounting for the uncertainty of only a few key parameters. The results led to the identification of the key FORUG parameters and to the recommendation for a process-based description of the soil respiration process in the FORUG model.

Carbon↗

PubMed2000

Tolerance of uncertainty of medical students and practicing physicians.

BACKGROUND: Tolerance of uncertainty is believed to be an important attribute of practicing physicians. This study attempts to (1) estimate how medical students perceive physicians' tolerance of uncertainty and (2) measure the tolerance of uncertainty of practicing physicians. RESEARCH DESIGN: Cross-sectional. SETTING AND SUBJECTS: Medical students (n = 113) and practicing physicians (n = 151) at the Faculty of Health Sciences, Ben-Gurion University, Israel. MEASURES: A self-administered, Hebrew version of an instrument developed in the United States. INDEPENDENT VARIABLES: Age, gender, seniority (year of study for students or years in practice for physicians), country of birth for students or of graduation for physicians, and physicians' specialty. DEPENDENT VARIABLES: Two dimensions, which were identified by factor analysis: reluctance to disclose uncertainty and stress from uncertainty. RESULTS: The estimates of physicians' stress from uncertainty by first-year students aged <22 years were higher than those by first-year students aged > or =22 years. There were no significant differences in the way junior and senior medical students perceived physicians' tolerance of uncertainty. Stress from uncertainty was higher in female physicians (P = 0.028) and in graduates of the former Soviet Union (P = 0.044) than among male physicians and Israeli graduates, respectively. Reluctance to disclose uncertainty was higher among graduates of the former Soviet Union (P = 0.003) and among psychiatrists (P = 0.021) than among Israeli graduates and other specialties, respectively. CONCLUSIONS: The reliability and factor structure of the instrument were replicated. The previously reported differences in tolerance of uncertainty between women and men and between local and foreign graduates were confirmed. Physicians' tolerance of uncertainty appeared to be higher than that attributed to them by students. The expected age-related differences in perception of clinical uncertainty were not detected between junior and senior medical students.

Adult↗

PubMed2004

Determination of the reference air kerma rate for 192Ir brachytherapy sources and the related uncertainty.

Different methods exist to determine the air kerma calibration factor of an ionization chamber for the spectrum of a 192Ir high-dose-rate (HDR) or pulsed-dose-rate (PDR) source. An analysis of two methods to obtain such a calibration factor was performed: (i) the method recommended by [Goetsch et al., Med. Phys. 18, 462-467 (1991)] and (ii) the method employed by the Dutch national standards institute NMi [Petersen et al., Report S-EI-94.01 (NMi, Delft, The Netherlands, 1994)]. This analysis showed a systematic difference on the order of 1% in the determination of the strength of 192Ir HDR and PDR sources depending on the method used for determining the air kerma calibration factor. The definitive significance of the difference between these methods can only be addressed after performing an accurate analysis of the associated uncertainties. For an NE 2561 (or equivalent) ionization chamber and an in-air jig, a typical uncertainty budget of 0.94% was found with the NMi method. The largest contribution in the type-B uncertainty is the uncertainty in the air kerma calibration factor for isotope i, N(i)k, as determined by the primary or secondary standards laboratories. This uncertainty is dominated by the uncertainties in the physical constants for the average mass-energy absorption coefficient ratio and the stopping power ratios. This means that it is not foreseeable that the standards laboratories can decrease the uncertainty in the air kerma calibration factors for ionization chambers in the short term. When the results of the determination of the 192Ir reference air kerma rates in, e.g., different institutes are compared, the uncertainties in the physical constants are the same. To compare the applied techniques, the ratio of the results can be judged by leaving out the uncertainties due to these physical constants. In that case an uncertainty budget of 0.40% (coverage factor=2) should be taken into account. Due to the differences in approach between the method used by NMi and the method recommended by Goetsch et al., an extra type-B uncertainty of 0.9% (k= 1) has to be taken into account when the method of Goetsch et al. is applied. Compared to the uncertainty of 1% (k= 2) found for the air calibration of 192Ir, the difference of 0.9% found is significant.

Air↗

PubMedDate not supplied

Effects of uncertainty on perceived health status in patients with atrial fibrillation.

The nursing discipline has focused on uncertainty as a main theme of research as well as an area needing assessment in clinical practice because the concept of uncertainty can be applied across diagnostic categories and may be worthwhile in explaining responses to illness. This study aimed to examine the effects of uncertainty on perceived health status including physical health, mental health, and general health within the theoretical framework of uncertainty in illness. This descriptive correlational and cross-sectional survey study included 81 subjects with atrial fibrillation using a face-to-face interview method. Individuals with greater symptom severity perceived more uncertainty and uncertainty was appraised as a danger rather than opportunity, thus those with greater uncertainty appraised a greater danger. While there was no relationship between danger appraisal and physical health, the significant relationships were shown between danger appraisal and mental health (r = -0.68) and between danger appraisal and general health (r = -0.39) respectively. The symptom severity had a significant direct effect on general health rather than having indirect effects through uncertainty and appraisal. Uncertainty had a significant impact on the perception of mental health through danger appraisal, identifying an area for nursing interventions. The mediating model of uncertainty with mental health as an outcome variable was supported by the empirical data of this study. In order to expand the present body of knowledge on uncertainty in illness model, recommendations for the future nursing studies and nursing practice were included.

Adult↗

PubMed2000

RESEARCH: Assessing Uncertainty in Estimates of Nitrogen Loading to Estuaries for Research, Planning, and Risk Assessment.

/ There can be considerable uncertainty associated with calculations of nutrient loading to estuaries from their watersheds, arising from uncertainty in the variables used in the calculation. Analysis of uncertainty is particularly important in the context of planning and management, where such information can be useful in helping make decisions about development in the coastal zone and in risk assessment, where probability of worse-case extremes may be relevant. This fact has been largely ignored when loading calculations have been made, presumably because both uncertainty estimates for the input variables and a standard method were lacking. Parametric (propagation for normal error estimates) and nonparametric methods (bootstrap and enumeration of combinations) to assess the uncertainty in calculated rates of nitrogen loading were compared, based on the propagation of uncertainty observed in the variables used in the calculation. In addition, since such calculations are often based on literature surveys rather than random replicate measurements for the site in question, error propagation was also compared using the uncertainty of the sampled population (e.g., standard deviation) as well as the uncertainty of the mean (e.g., standard error of the mean). Calculations for the predicted nitrogen loading to a shallow estuary (Waquoit Bay, MA) were used as an example. The previously estimated mean loading from the watershed (5,400 ha) to Waquoit Bay (600 ha) was 23,000 kg N yr(-1). The mode of a nonparametric estimate of the probability distribution differed dramatically, equaling only 70% of this mean. Repeated observations were available for only 8 of the 16 variables used in our calculation. We estimated uncertainty in model predictions by treating these as sample replicates. Parametric and nonparametric estimates of the standard error of the mean loading rate were 12-14%. However, since the available data include site-to-site variability, as is often the case, standard error may be an inappropriate measure of confidence. The standard deviations were around 38% of the loading rate. Further, 95% confidence intervals differed between the nonparametric and parametric methods, with those of the nonparametric method arranged asymmetrically around the predicted loading rate. The disparity in magnitude and symmetry of calculated confidence limits argue for careful consideration of the nature of the uncertainty of variables used in chained calculations. This analysis also suggests that a nonparametric method of calculating loading rates using most frequently observed values for variables used in loading calculations may be more appropriate than using mean values. These findings reinforce the importance of including assessment of uncertainty when evaluating nutrient loading rates in research and planning. Risk assessment, which may need to consider relative probability of extreme events in worst-case scenarios, will be in serious error using normal estimates, or even the nonparametric bootstrap. A method such as our enumeration of combinations produces a more reliable distribution of risk.

Journal Article↗

PubMed2001

Reliability of the ICRP's dose coefficients for members of the public, II. Uncertainties in the absorption of ingested radionuclides and the effect on dose estimates. International Comission on Radiological Protection.

Data on the gastrointestinal absorption of 12 elements have been reviewed. In each case, absorption is expressed as the fraction of the ingested element absorbed to blood, referred to as the f1 value, applying to intakes of unspecified chemical form by average population groups. The level of confidence in individual absorption values has been estimated in terms of lower and upper bounds, A and B, such that there is judged to be roughly a 90% probability that the true central value is no less than A and no greater than B. Ranges are proposed for intakes by adults, 10-year-old children and 3-month-old infants. Uncertainty in f1 values (B/A) ranged from 10% to factors of 100-400. The lowest uncertainties were for the well absorbed elements, H, I and Cs, for which there are good data, and the greatest uncertainties were for less well absorbed elements for which few data are available, particularly Zr and Sb. Ranges were generally wider for children and infants than for adults because of the need to allow for the likelihood of increased absorption with only limited data in support of the proposed values. The largest ranges were for 3-month-old infants, reflective lack of knowledge on the time-course and magnitude of possible increased absorption in the first few months of life. For each age group, ICRP values of absorption tend towards the upper bound of the ranges, indicating a degree of conservatism in th calculation of ingestion dose coefficients. Examination of the effect of the proposed confidence intervals for f1 values on uncertainties in dose coefficients for ingested radionuclides showed that there was no direct relationship. For some radionuclides, uncertainties in effective dose were small despite large uncertainties in f1 values while for others the uncertainties in effective doses approached the corresponding values for uncertainty in f1 values. These differences reflect the relative contributions to effective dose from cumulative activity in the contents of the alimentary tract, which in many cases is insensitive to uncertainties in f1, and cumulative activity of the absorbed radionuclide in systemic tissues, which is proportional to f1. In general, uncertainties in effective close for children and infants exceeded those in adults as a result of greater uncertainties in f1 values for the younger age groups. However, this effect was reduced in some cases by shorter retention times of absorbed nuclides in body tissues and organs.

Adult↗

PubMed2005

[Evaluation of measurement uncertainty for the determination of ginsenosides in Radix ginseng by HPLC].

AIM: To set out the procedure for estimation of measurement uncertainty for the determination of ginsenosides R(g1), Re and R(b1) in Radix ginseng by HPLC. METHODS: To facilitate the identification and analysis of the uncertainty sources arising from the procedure of analysis, a cause and effect diagram was constructed and simplified. Each uncertainty component whether associated with individual sources or with the combined effects of several sources, was evaluated with respect to the significance of its contribution to the overall measurement uncertainty and was expressed as standard uncertainty. All the standard uncertainties were then combined according to the appropriate rules to give a combined standard uncertainty and an expanded standard uncertainty. Results The expanded standard uncertainties for the HPLC determination of ginsenoside R(g1), Re, and R(b1), are 0.12c, 0.14c and 0.13c, respectively. CONCLUSION: Measurement uncertainty is applicable to set the limit of the ginsenosides in Radix ginseng. The establishment of the methodology for the evaluation of measurement uncertainty is important to the studies of Chinese materia medica standards.

Chromatography, High Pressure Liquid↗

PubMed2006

Reporting and analyzing statistical uncertainties in Monte Carlo-based treatment planning.

PURPOSE: To investigate methods of reporting and analyzing statistical uncertainties in doses to targets and normal tissues in Monte Carlo (MC)-based treatment planning. METHODS AND MATERIALS: Methods for quantifying statistical uncertainties in dose, such as uncertainty specification to specific dose points, or to volume-based regions, were analyzed in MC-based treatment planning for 5 lung cancer patients. The effect of statistical uncertainties on target and normal tissue dose indices was evaluated. The concept of uncertainty volume histograms for targets and organs at risk was examined, along with its utility, in conjunction with dose volume histograms, in assessing the acceptability of the statistical precision in dose distributions. The uncertainty evaluation tools were extended to four-dimensional planning for application on multiple instances of the patient geometry. All calculations were performed using the Dose Planning Method MC code. RESULTS: For targets, generalized equivalent uniform doses and mean target doses converged at 150 million simulated histories, corresponding to relative uncertainties of less than 2% in the mean target doses. For the normal lung tissue (a volume-effect organ), mean lung dose and normal tissue complication probability converged at 150 million histories despite the large range in the relative organ uncertainty volume histograms. For "serial" normal tissues such as the spinal cord, large fluctuations exist in point dose relative uncertainties. CONCLUSIONS: The tools presented here provide useful means for evaluating statistical precision in MC-based dose distributions. Tradeoffs between uncertainties in doses to targets, volume-effect organs, and "serial" normal tissues must be considered carefully in determining acceptable levels of statistical precision in MC-computed dose distributions.

Esophagus↗

PubMed2005

Monitoring groundwater contamination and delineating source zones at industrial sites: uncertainty analyses using integral pumping tests.

Field-scale characterisations of contaminant plumes in groundwater, as well as source zone delineations, are associated with uncertainties that can be considerable. A major source of uncertainty in environmental datasets is due to variability of sampling results, as a direct consequence of the heterogeneity of environmental matrices. We develop a methodology for quantifying uncertainties in field-scale mass flow and average concentration estimations, using integral pumping tests (IPTs), where the contaminant concentration is measured as a function of time in a pumping well. This procedure increases the sampling volume and reduces the effect of small-scale variability that may bias point-scale measurements. In particular, using IPTs, the interpolation uncertainty of conventional point-scale measurements is transformed to a quantifiable uncertainty related to the (unknown) plume position relative to the pumping well. We show that this plume position uncertainty generally influenced the predicted mass flows and average concentrations (of acenapthene, benzene and CHCs) to a greater extent than a boundary condition uncertainty related to the local water balance, considering 19 control planes at a highly heterogeneous industrial site in southwest Germany. Furthermore, large (order of magnitude) uncertainties only occurred if the conditions were strongly heterogeneous in the nearest vicinity of the well. We also develop a consistent methodology for an assessment of the combined effect of uncertainty in hydraulic conditions and uncertainty in reactive transport parameters for delimiting of both contaminant source zones and zones absent of source, based on (downgradient) IPTs.

Benzene↗

PubMed2006

Methods to quantify and identify the sources of uncertainty for river basin water quality models.

Worldwide, the application of river basin water quality models is increasing, often imposed by law. It is, thus, important to know the degree of uncertainty associated with these models and their application to a specific watershed. These uncertainties lead to errors that are revealed when model outputs are compared to observations. Such uncertainty is typically described by calculating the residuals. However, residuals should not be seen as an estimate of total uncertainty, since through the calibration process, the residuals may be reduced by over-adjustment to the data, which is typically the case for over-parameterised models. Over-adjustment during a calibration period can also lead to highly biased results when the model is applied to other periods or environmental conditions. The total model uncertainties are, therefore, assessed by four components: the sum of the squares of the residuals (SSQ), parameter uncertainties (that can be ignored when their error is much smaller than SSQ), input data uncertainties, and an additional predictive uncertainty that is expressed when the model appears to be biased when it is applied for data other than the data used for calibration. The sources are ranked according to a quantification criterion (magnitude) as well as an identification criterion that depends on the number of observations that are covered by the confidence region. This approach is illustrated with SWAT2003 simulations for flow and sediment of Honey Creek, a tributary of the Sandusky River basin (Ohio). The results show the dominance of the model uncertainty. The input data uncertainty is less important.

Calibration↗

PubMed2004

Why am I unsure? Internal and external attributions of uncertainty dissociated by fMRI.

Behavioral evidence suggests that the perceived reason of uncertainty causes different coping strategies to be implemented, particularly frequency ratings with externally attributed uncertainty and memory search with internally attributed uncertainty. We used functional magnetic resonance imaging (fMRI) to investigate whether processes related to these different attributions of uncertainty differ also in their neural substrates. Participants had to predict events that were uncertain due to internal factors, that is, insufficient knowledge. Data were compared with a preceding study in which event prediction was uncertain due to external factors, that is, event probabilities. Parametric analyses revealed the posterior frontomedian cortex, that is, mesial Brodmann Area 8 (BA 8) as the common cortical substrate mediating processes related to uncertainty no matter what the cause of uncertainty. However, processes related to the two differently attributed types of uncertainty differed significantly in relation to the brain network that was coactivated. Only processes related to internally attributed uncertainty elicited activation within the mid-dorsolateral and posterior parietal areas known to underlie working memory (WM) functions. Together, findings from both experiments suggest that there is a common cerebral correlate for uncertain predictions but different correlates for coping strategies of uncertainty. Concluding, BA 8 reflects that we are uncertain, coactivated networks what we do to resolve uncertainty.

Adaptation, Psychological↗

PubMed2003

Effect of non-significant proportional bias in the final measurement uncertainty.

The trueness of an analytical method can be assessed by calculating the proportional bias of the method in terms of apparent recovery. If the apparent recovery does not differ significantly from one, the analytical method has not a significant bias. If this is the case, the bias is neglected and the uncertainty associated with this bias is included in the uncertainty budget of results. However, when assessing trueness there is always a probability of incorrectly concluding that the proportional bias is not significant. Therefore, the uncertainty of results may be underestimated. In this paper, we study how non-significant bias affects the uncertainty of analytical results. Moreover, we study how to avoid the underestimation of uncertainty by including the non-significant bias calculated in the uncertainty budget. To answer these questions, we have used the Monte-Carlo method to simulate the process of estimating the apparent recovery of a biased analytical method and, subsequently, the future results this method provides. The results of the simulation show that non-significant bias may underestimate the uncertainty of analytical results when bias contributes in more than 20% to the overall uncertainty. Uncertainty is specially underestimated when bias contributes in more than 50% to the overall uncertainty.

Journal Article↗

PubMed2003

Influences of parameter uncertainties within the ICRP-66 respiratory tract model: particle clearance.

Quantifying radiological risk following the inhalation of radioactive aerosols entails not only an assessment of particle deposition within respiratory tract regions but a full accounting of clearance mechanisms whereby particles may be translocated to adjacent respiratory tissue regions, absorbed to blood, or released to the gastrointestinal tract. The model outlined in ICRP Publication 66 represents to date one of the most complete overall descriptions of particle deposition and clearance, as well as localized radiation dosimetry, within the respiratory tract. In this study, a previous review of the ICRP-66 deposition model is extended to the study of the subsequent clearance model. A systematic review of the clearance component within the ICRP 66 respiratory tract model was conducted in which probability density functions were assigned to all input parameters for both 239PuO2 and 238UO2/238U3O8. These distributions were subsequently incorporated within a computer code LUDUC (Lung Dose Uncertainty Code) in which Latin hypercube sampling techniques are used to generate multiple (e.g., 1,000) sets of input vectors (i.e., trials) for all model parameters needed to assess mechanical clearance and particle dissolution/absorption. Integral numbers of nuclear disintegrations, U(s), in various lung regions were shown to be well-described by lognormal probability distributions. Of the four extrathoracic clearance compartments of the respiratory tract, uncertainties in U(s), expressed as the ratio of its 95% to 5% confidence levels, were highest within the LN(ET) tissues for 239PuO2 (ratio of 50 to 130) and within the ET(seq) tissues for 238UO2/238U3O8 (ratio of 12 to 50). Peak uncertainties in U(s) in these respiratory regions occurred at particle sizes of approximately 0.5-0.6 microm where uncertainties in ET2 particle deposition fractions accounted for only approximately 10% of the total U(s) uncertainty for 239PuO2, and only approximately 30% of the total U(s) uncertainty for 238UO2/238U3O8 (the remainder is attributed to the clearance model alone). Of the eight clearance compartments within the thoracic regions of the respiratory tract, and for particle sizes below approximately 5 microm, uncertainties in U(s) were highest within the LN(TH) tissues for 239PuO2 (ratio of 60 to 80) and within the BB(seq) tissues for 238UO2/238U3O8 (ratio of 20 and 60). At particle sizes exceeding approximately 5 microm in aerodynamic diameter, peak uncertainties in U(s) are noted for the AI, bb(seq), and bb1 clearance compartments. As the particle size approaches 10 microm in size, uncertainties in U(s) within these three thoracic tissue regions approach a factor of 1,000 and are dominated by corresponding uncertainties in particle deposition.

Aerosols↗

PubMed1999

Characterization of uncertainty and variability in residential radon cancer risks.

Radon, a naturally occurring gas found at some level in most homes, is an established risk factor for human lung cancer. The U.S. National Research Council has recently completed a comprehensive evaluation of the health risks of residential exposure to radon and developed models for projecting radon lung cancer risks to the general population. This analysis suggests that radon may play a role in the etiology of 10-15% of all lung cancer cases in the United States, although these estimates are subject to considerable uncertainty. In this article, we present a detailed analysis of uncertainty and variability in estimates of lung cancer risk due to residential exposure to radon. We use a general framework for the analysis of uncertainty and variability that we developed previously. Specifically, we focus on estimates of the age-specific excess relative risk (ERR) and lifetime relative risk (LRR), both of which vary substantially among individuals. We also consider estimates of the population attributable risk (PAR), which reflects the proportion of the lung cancer burden attributable to radon. Variability in the ERR and LRR is largely determined by variability in residential exposure levels and in the dosimetric K-factor used to extrapolate from occupational to environmental settings. Uncertainty in the ERR and LRR is due to uncertainty in the model parameters, notably those reflecting the carcinogenic potency of radon and the modifying effect of attained age. Uncertainty in the PAR is determined by uncertainty about the values of the parameters in the risk models used to estimate the PAR. Uncertainty in radon levels in homes and the dosimetric K-factor contribute comparatively little to uncertainty in the PAR. These results suggest that reduction in uncertainty about the PAR for radon induced lung cancer can only be achieved if more reliable risk projection models can be developed.

Air Pollutants, Radioactive↗

PubMed2005

Decisions under uncertainty: probabilistic context influences activation of prefrontal and parietal cortices.

Many decisions are made under uncertainty; that is, with limited information about their potential consequences. Previous neuroimaging studies of decision making have implicated regions of the medial frontal lobe in processes related to the resolution of uncertainty. However, a different set of regions in dorsal prefrontal and posterior parietal cortices has been reported to be critical for selection of actions to unexpected or unpredicted stimuli within a sequence. In the current study, we induced uncertainty using a novel task that required subjects to base their decisions on a binary sequence of eight stimuli so that uncertainty changed dynamically over time (from 20 to 50%), depending on which stimuli were presented. Activation within prefrontal, parietal, and insular cortices increased with increasing uncertainty. In contrast, within medial frontal regions, as well as motor and visual cortices, activation did not increase with increasing uncertainty. We conclude that the brain response to uncertainty depends on the demands of the experimental task. When uncertainty depends on learned associations between stimuli and responses, as in previous studies, it modulates activation in the medial frontal lobes. However, when uncertainty develops over short time scales as information is accumulated toward a decision, dorsal prefrontal and posterior parietal contributions are critical for its resolution. The distinction between neural mechanisms subserving different forms of uncertainty resolution provides an important constraint for neuroeconomic models of decision making.

Adult↗

PubMed2003

Testing the mediating effect of appraisal in the model of uncertainty in illness study.

BACKGROUND: Although there have been a great number of research studies based on the model of uncertainty in illness, few studies have considered the appraisal portion of model. PURPOSE: The purpose of this study was to test the mediating effect of appraisal in the model of uncertainty in illness. Additionally, this study aimed to examine the relationships among uncertainty, symptom severity, appraisal, and anxiety in patients newly diagnosed with atrial fibrillation. METHODS: This study employed a descriptive correlational and cross-sectional survey design using a face-to-face interview method. Patients diagnosed with atrial fibrillation within the previous 6 months prior to data collection were interviewed by Mishel Uncertainty in Illness Scale-Community Form, appraisal scale, Symptom Checklist-Severity V.3, and State Anxiety Inventory. RESULTS: A total of 81 patients with atrial fibrillation were recruited from two large urban medical centers in Cleveland, Ohio, U.S.A. Symptom severity was the significant variable in explaining uncertainty (beta=0.34). Individuals with greater symptom severity perceived more uncertainty. Uncertainty was appraised as a danger rather than opportunity, and those with greater uncertainty appraised a greater danger (p<.01). While the appraisal of opportunity had the negative relationship with anxiety (r=-0.25), the appraisal of danger was positively associated with anxiety (r=0.78). The measure of goodness of fit (Q) of the model was.7863, and the significant test (chi(2)) for the Q was statistically significant (df =3, p<.001). Accordingly, the overall mediating model of uncertainty in illness was proven not to be fit to the empirical data of patients with atrial fibrillation. Consequently, the mediating effect of appraisal was not supported by the empirical data of this study. CONCLUSION: The findings of this study were discussed in terms of their relevance compared with those of previous studies or theoretical framework and the plausible explanations on study findings. Lastly, in order to expand the present body of knowledge on uncertainty in illness model, recommendations for the future nursing studies were included.

Journal Article↗