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PubMed2026

Patient experiences of diagnostic uncertainty in musculoskeletal care: a systematic review of qualitative studies.

BACKGROUND: Diagnosis plays a central role in musculoskeletal care. However, establishing a clear diagnosis is often challenging, and diagnostic uncertainty is common. OBJECTIVES: To explore patient experiences of diagnostic uncertainty in musculoskeletal care. METHODS: Five databases (CINAHL, Embase, MEDLINE, AMED, Web of Science) were searched from inception to October 2025. Qualitative studies involving semi-structured interviews with adults receiving care for MSK conditions were included. Methodological quality was appraised using the Joanna Briggs Institute Qualitative Checklist. Data were synthesised using thematic synthesis, and confidence in findings was assessed using the Grading of Recommendations Assessment, Development, and Evaluation Confidence in the Evidence from Reviews of Qualitative Research approach (GRADE-CERQual). RESULTS: Twenty-six studies involving 462 participants were included. Critical appraisal identified 23 studies with varying methodological limitations; all studies were included in the synthesis. Nine descriptive themes were synthesised into three analytical themes: (1) patient expectations and perceived meanings of a diagnosis and interpretations of diagnostic uncertainty; (2) the multi-dimensional experience of diagnostic uncertainty; and (3) the role of contextual factors, particularly communication and the therapeutic relationship, in shaping experiences of diagnostic uncertainty. Using GRADE-CERQual, confidence in these themes was rated as low, moderate and very low, respectively. CONCLUSION: Diagnostic uncertainty is a subjective and multi-dimensional experience shaped in part by patients' expectations and the meanings attributed to diagnosis. Its impact spans predominantly cognitive and affective domains and may influence clinical presentation. Patient-centred communication and strong therapeutic relationships may support patients in navigating diagnostic uncertainty in musculoskeletal care.

Adult↗

PubMed2004

Indicators of uncertainty in chemical risk assessments.

For most of the chemical substances that are subject to regulatory and industrial decision making, important toxicological data are missing. The available dataset is often difficult to interpret, and the differences between alternative, scientifically reasonable interpretations may have major impact on decision making. Since such uncertainties are an important factor in decision making it is essential that they be reported in a transparent and understandable way. In order to clarify how toxicologists report uncertainties, 30 risk assessments for one and the same substance (trichloroethylene) from the years 1973-2001 were searched for phrases indicating uncertainty. These phrases can be divided between four categories: contentual, epistemic, conditionalising, and inferential uncertainty indicators. A typology of uncertainty indicators, based on these categories, is proposed. It is concluded that the use of uncertainty indicators in these texts is not transparent and that the development of standardised uncertainty indicators should significantly improve communications both within the scientific community and between scientists and policymakers.

Animals↗

PubMedDate not supplied

Doctors expressions of uncertainty and patient confidence.

Although recent work has encouraged doctors to express their uncertainty to patients as a means to improve communication the potential impact of this on patients remains unclear. The present study first explored the impact of the way in which uncertainty was expressed (behaviourally versus verbally) on doctor's and patient's beliefs about patient confidence. Second the study examined the role of the patient's personal characteristics and knowledge of their doctor as a means to address the broader context. Matched questionnaires were completed by GPs (n=66, response rate=92%) and patients (n=550, response rate=88%) from practices in the south-east of England. The results showed that the majority of GPs and patients viewed verbal expressions of uncertainty such as 'Let's see what happens' as the most potentially damaging to patient confidence and both GPs and patients believed that asking a nurse for advice would have a detrimental effect. In contrast, behaviours such as using a book or computer were seen as benign or even beneficial activities. When compared directly, GPs and patients agreed about behavioural expressions of uncertainty, but the patients rated the verbal expressions as more detrimental to their confidence than anticipated by the doctors. In terms of the context, patients who indicated that both verbal and behavioural expressions of uncertainty would have the most detrimental impact upon their confidence were younger, lower class and had known their GP for less time. To conclude, patients' reactions to uncertainty occur within the context of the patient's own background and experience, however, some consistent responses can be found. In particular, whilst behavioural expressions of uncertainty may have a positive impact upon patient confidence, verbal expressions have a consistently detrimental effect which is underestimated by GPs.

Adult↗

PubMed2003

Random and systematic measurement uncertainties considered in the evaluation of parameters derived from the course of the tabletting process.

The uncertainty of some characteristic parameters describing the course of the tabletting process, namely the area quotient according to Emschermann and Müller, the apparent net work, the slope of the Heckel-plot, and the parameters of the modified Weibull function, was calculated according to the German norm DIN 1319-4 1999. The method allows to consider random and systematic uncertainties in a consistent way as variances of normal and rectangular probability distributions, respectively, or other suitable probability distributions based on Bayesian statistics and the principle of maximum entropy. So, random and systematic uncertainties known from a calibration and validation study of the measurement of force and displacement, and the uncertainty of the true density were included meaningfully into the uncertainty of the resulting tabletting parameters using the propagation of uncertainties according to the Gauss method. The standard uncertainty for the results calculated this way seems to be suitable for a critical evaluation of the tabletting data.

Bayes Theorem↗

PubMed2005

Uncertainty in NAPL volume estimates due to random measurement errors during partitioning tracer tests.

The uncertainty in NAPL volume estimates obtained through partitioning tracers can be quantified as a function of random errors in volume and concentration measurements when moments are calculated from experimentally measured breakthrough curves using the trapezoidal rule for numerical integration. The methodology is based upon standard stochastic methods for random error propagation. Monte Carlo simulations using a synthetic data set derived from the one-dimensional solution of the advective-dispersive equation serve to verify the process. It is shown that the uncertainty in NAPL volume predictions nonlinearly increases as the retardation factor decreases. An important result of this observation is that there is a large degree of uncertainty in using partitioning tracers to conclude NAPL is absent from the swept zone. Under the conditions investigated, random errors in concentration measurements are shown to have a greater impact on NAPL volume uncertainty than random errors in volume measurements, and it is also shown that uncertainty in NAPL volume decreases as the resolution of the breakthrough curves increases. The impact of uncertainty in background retardation (i.e., sorption of partitioning tracers in the absence of NAPL) was also investigated, and it likewise indicated that the relative uncertainty in NAPL volume estimates increases as the retardation factor decreases.

Computer Simulation↗

PubMed2006

A stochastic regression approach to analyzing thermodynamic uncertainty in chemical speciation modeling.

Chemical speciation modeling is a vital tool for assessing the bioavailability of inorganic species, yet significant uncertainties in thermodynamic parameters and model form limit its potential for decision-making. In this paper we present a novel method for the quantification of thermodynamic parameter uncertainty and ionic strength correction model uncertainty using Bayesian Markov Chain Monte Carlo (MCMC) estimation methods. These methods allow for the inclusion of correlation modeling, which has not been present in previous work. The MCMC simulations are used to model a natural river water to determine the uncertainty in the calculated environmental speciation of ethylenediamenetetraacetate, a chelating agent that has attracted considerable environmental interest. The results indicate that incorporating correlation among related thermodynamic parameters into the uncertainty model is necessary to correctly quantify the overall system uncertainty. This result indicates the superiority of MCMC estimation methods overtraditional Monte Carlo methods when available data are used to estimate parameter uncertainty in systems with closely related model parameters.

Bayes Theorem↗

PubMed2003

Measurement uncertainty from physical sample preparation: estimation including systematic error.

A methodology is proposed, which employs duplicated primary sampling and subsequent duplicated physical preparation coupled with duplicated chemical analyses. Sample preparation duplicates should be prepared under conditions that represent normal variability in routine laboratory practice. The proposed methodology requires duplicated chemical analysis on a minimum of two of the sample preparation duplicates. Data produced from the hierarchical design is treated with robust analysis of variance (ANOVA) to generate uncertainty estimates, as standard uncertainties ('u' expressed as standard deviation), for primary sampling (ssamp), physical sample preparation (sprep) and chemical analysis (sanal). The ANOVA results allow the contribution of the sample preparation process to the overall uncertainty to be assessed. This methodology has been applied for the first time to a case study of pesticide residues in retail strawberry samples. Duplicated sample preparation was performed under ambient conditions on two consecutive days. Multi-residue analysis (quantification by GC-MS) was undertaken for a range of incurred pesticide residues including those suspected of being susceptible to loss during sample preparation procedures. Sampling and analytical uncertainties dominated at low analyte concentrations. The sample preparation process contributed up to 20% to the total variability and had a relative uncertainty (Uprep%) of up to 66% (for bupirimate at 95% confidence). Estimates of systematic errors during physical sample preparation were also made using spike recovery experiments. Four options for the estimation of measurement uncertainty are discussed, which both include and exclude systematic error arising from sample preparation and chemical analysis. A holistic approach to the combination and subsequent expression of uncertainty is advised.

Calibration↗

PubMed2005

Two-stage application of the optimised uncertainty method: a practical assessment.

Uncertainty estimates from routine sampling and analytical procedures can be assessed as being fit for purpose using the optimised uncertainty (OU) method. The OU method recommends an optimal level of uncertainty that should be reached in order to minimise the expected financial loss, given a misclassification of a batch as a result of the uncertainty. Sampling theory can used as a predictive tool when a change in sampling uncertainty is recommended by the OU method. The OU methodology has been applied iteratively for the first time using a case study of wholesale butter and the determination of five quality indicators (moisture, fat, solids-not-fat (SNF), peroxide value (PV) and free fatty acid (FFA)). The sampling uncertainty (s(samp)) was found to be sub-optimal for moisture and PV determination, for 3-fold composite samples. A revised sampling protocol was devised using Gy's sampling theory. It was predicted that an increase in sample mass would reduce the sampling uncertainty to the optimal level, resulting in a saving in expectation of loss of over pounds 2000 per 20 tonne batch, when compared to current methods. Application of the optimal protocol did not however, achieve the desired reduction in s(samp) due to limitations in sampling theory. The OU methodology proved to be a useful tool in identifying broad weaknesses within a routine protocol and assessing fitness for purpose. However, the successful routine application of sampling theory, as part of the optimisation process, requires substantial prior knowledge of the sampling target.

Animals↗

PubMed2006

Task uncertainty and rationality in medical problem solving.

QUALITY ISSUE: Medical problem-solving situations are characterized by various degrees of 'task uncertainty'--i.e. uncertainty related to the definition of a problem, the effect of a technology, the value of a solution, and so on. The need for professional discretion varies and depends on the degree of perceived task uncertainty. SUGGESTED SOLUTION: In this report it is argued that, in order to obtain rationality in problem-solving processes, differences in the degree of task uncertainty need to be met by variation in the structure of the health care organization. IMPLICATIONS: The main implications of this view are that (under norms of rationality) problem-solving processes with low task uncertainty must be organized in one way and processes with high task uncertainty in another. Furthermore, processes with high and low task uncertainty also need to be evaluated according to different standards. Some hypotheses regarding the different organizational requirements are presented.

Humans↗

PubMed2005

Uncertainty in eddy covariance measurements and its application to physiological models.

Flux data are noisy, and this uncertainty is largely due to random measurement error. Knowledge of uncertainty is essential for the statistical evaluation of modeled and measured fluxes, for comparison of parameters derived by fitting models to measured fluxes and in formal data-assimilation efforts. We used the difference between simultaneous measurements from two towers located less than 1 km apart to quantify the distributional characteristics of the measurement error in fluxes of carbon dioxide (CO2) and sensible and latent heat (H and LE, respectively). Flux measurement error more closely follows a double exponential than a normal distribution. The CO2 flux uncertainty is negatively correlated with mean wind speed, whereas uncertainty in H and LE is positively correlated with net radiation flux. Measurements from a single tower made 24 h apart under similar environmental conditions can also be used to characterize flux uncertainty. Uncertainty calculated by this method is somewhat higher than that derived from the two-tower approach. We demonstrate the use of flux uncertainty in maximum likelihood parameter estimates for simple physiological models of daytime net carbon exchange. We show that inferred model parameters are highly correlated, and that hypothesis testing is therefore possible only when the joint distribution of the model parameters is taken into account.

Carbon Dioxide↗

PubMedDate not supplied

Impact of uncertainty, social support, and prenatal coping on the psychological well-being of high-risk pregnant women.

BACKGROUND: The effects of uncertainty and social support on the psychological well-being of high-risk pregnant women may be influenced by their prenatal coping strategies. OBJECTIVE: The purpose of this study was to investigate whether prenatal coping strategies (preparation for motherhood, avoidance, positive interpretation of events, and prayer) mediate the effects of uncertainty and social support on the psychological well-being of high-risk pregnant women. METHODS: A cross-sectional, descriptive, correlational design was used. The convenience sample consisted of 105 high-risk pregnant women 18-34 years of age and at 24-36 weeks gestation. The main measures were Mishel Uncertainty in Illness Scale, Medical Outcomes Study Social Support Survey, Prenatal Coping Inventory, and Psychological General Well-Being Index. Data analysis included descriptive statistics, correlational techniques, and path analyses. RESULTS: The women reported low levels of uncertainty, moderate levels of distress, and high levels of social support. Prayer was the most frequently used prenatal coping strategy, whereas avoidance was used least often. Women who reported higher levels of uncertainty also reported less social support (r = -.45, p < .01), less psychological well-being (r = -.48, p < .01), less positive interpretation (r = -.30, p < .01), and more use of avoidance (r = .43, p < .01). The modified path analysis showed good fit with the data. Avoidance significantly mediated the effects of uncertainty on psychological well-being (z = -2.74, p < .01). Social support had a significant direct effect on preparation for motherhood (beta = .43, z = 3.94, p < .001). DISCUSSION: Avoidance mediated the effect of uncertainty on psychological well-being for the high-risk pregnant women in this sample. The results of the study may help perinatal nurses to better understand how high-risk pregnancy affects these women.

Adaptation, Psychological↗

PubMed2006

The relationships between uncertainty and posttraumatic stress in survivors of childhood cancer.

The purposes of this study were to understand the levels of uncertainty and posttraumatic stress and to examine their relationships in young adult survivors of childhood cancer. A cross-sectional correlational design was used in this study. Mailed survey was the data collection method. The Mishel Uncertainty in Illness Scale-Community Form was the measure of uncertainty. The University of California at Los Angeles Post Traumatic Stress Disorder Index was the measure of posttraumatic stress. A total of 46 (51.1%) survivors responded to the survey and the analysis was based on data from 45. Participants reported a mean 51.3 (SD = 14.5, range = 23 to 90) level of uncertainty; and a mean 15.7 (SD = 11.0, range = 0 to 43) level of posttraumatic stress. Uncertainty was positively correlated with posttraumatic stress (r = .40, p = .039). The re- conceptualization of the Uncertainty in Illness Theory (UIT) and developmental perspectives can explain the relationships between uncertainty and posttraumatic stress in the young adult survivors of childhood cancer. The re-conceptualization of UIT can serve as a guide for future studies.

Adaptation, Psychological↗

PubMed2006

Effect of uncertainty on depression in patients with newly diagnosed atrial fibrillation.

This cross-sectional survey study aimed to determine the effects of uncertainty on depression through the appraisal within the "uncertainty in illness" model. In 81 subjects with atrial fibrillation, individuals with greater symptom severity perceived more uncertainty. Uncertainty was appraised as a danger rather than an opportunity. While the appraisal of opportunity had a negative relationship with depression, the appraisal of danger was positively associated with depression. The indirect effect of uncertainty on depression through appraisal was supported by the empirical data on patients with atrial fibrillation. Helping patients to correctly interpret symptoms and to understand the effectiveness of treatment may modify and reduce their uncertainty so that uncertainty leading to worse health outcomes may be reduced.

Adaptation, Psychological↗

PubMed2006

Uncertainties of exposure-related quantities in mammographic x-ray unit quality control.

Breast screening programs operate in many countries with mammographic x-ray units subject to stringent quality control tests. These tests include the evaluation of quantities based on exposure measurements, such as half value layer, automatic exposure control reproducibility, average glandular dose, and radiation output rate. There are numerous error sources that contribute to the uncertainty of these exposure-related quantities, some of which are unique to the low energy x-ray spectrum produced by mammographic x-ray units. For each of these exposure-related quantities, the applicable error sources and their magnitudes vary, depending on the test equipment used to make the measurement, and whether or not relevant corrections have been applied. This study has identified and quantified a range of error sources that may be used to estimate the combined uncertainty of these exposure-related quantities, given the test equipment used and corrections applied. The uncertainty analysis uses methods described by the International Standards Organization's Guide to the Expression of Uncertainty in Measurement. Examples of how these error sources combine to give the uncertainty of the exposure-related quantities are presented. Using the best test equipment evaluated in this study, uncertainties of the four exposure-related quantities at the 95% confidence interval were found to be +/-1.6% (half value layer), +/-0.0008 (automatic exposure control reproducibility), +/-2.3% (average glandular dose), and +/-2.1% (radiation output rate). In some cases, using less precise test equipment or failing to apply corrections, resulted in uncertainties more than double in magnitude.

Breast↗

PubMed2006

Classification images with uncertainty.

Classification image and other similar noise-driven linear methods have found increasingly wider applications in revealing psychophysical receptive field structures or perceptual templates. These techniques are relatively easy to deploy, and the results are simple to interpret. However, being a linear technique, the utility of the classification-image method is believed to be limited. Uncertainty about the target stimuli on the part of an observer will result in a classification image that is the superposition of all possible templates for all the possible signals. In the context of a well-established uncertainty model, which pools the outputs of a large set of linear frontends with a max operator, we show analytically, in simulations, and with human experiments that the effect of intrinsic uncertainty can be limited or even eliminated by presenting a signal at a relatively high contrast in a classification-image experiment. We further argue that the subimages from different stimulus-response categories should not be combined, as is conventionally done. We show that when the signal contrast is high, the subimages from the error trials contain a clear high-contrast image that is negatively correlated with the perceptual template associated with the presented signal, relatively unaffected by uncertainty. The subimages also contain a "haze" that is of a much lower contrast and is positively correlated with the superposition of all the templates associated with the erroneous response. In the case of spatial uncertainty, we show that the spatial extent of the uncertainty can be estimated from the classification subimages. We link intrinsic uncertainty to invariance and suggest that this signal-clamped classification-image method will find general applications in uncovering the underlying representations of high-level neural and psychophysical mechanisms.

Adult↗

PubMedDate not supplied

Radiologist uncertainty and the interpretation of screening.

OBJECTIVE: To determine radiologists' reactions to uncertainty when interpreting mammography and the extent to which radiologist uncertainty explains variability in interpretive performance. METHODS: The authors used a mailed survey to assess demographic and clinical characteristics of radiologists and reactions to uncertainty associated with practice. Responses were linked to radiologists' actual interpretive performance data obtained from 3 regionally located mammography registries. RESULTS: More than 180 radiologists were eligible to participate, and 139 consented for a response rate of 76.8%. Radiologist gender, more years interpreting, and higher volume were associated with lower uncertainty scores. Positive predictive value, recall rates, and specificity were more affected by reactions to uncertainty than sensitivity or negative predictive value; however, none of these relationships was statistically significant. CONCLUSION: Certain practice factors, such as gender and years of interpretive experience, affect uncertainty scores. Radiologists' reactions to uncertainty do not appear to affect interpretive performance.

Colorado↗

PubMed2003

Embracing uncertainty: an exploration of the experiences of childhood cancer survivors.

Uncertainty is a central theme in the cancer survivorship and coping literature. Existing research on cancer-related uncertainty has primarily documented the adverse effects of existential uncertainty on survivors' well-being and located uncertainty within the stress and coping paradigm. Using in-depth qualitative interviews, the authors explores the paradoxical meanings and impact of uncertainty in the lives of long-term survivors of childhood cancer. The findings suggest that although uncertainty can be a source of distress, it can also be a catalyst for growth, a deepened appreciation for life, greater awareness of life purpose, development of confidence and resilience, and optimism. The results suggest that uncertainty is a dialectic phenomenon located within larger contexts of both stress and coping, and psychospiritual growth.

Adaptation, Psychological↗

PubMed2006

Application of uncertainty and sensitivity analysis in river basin management.

Considering uncertainty in the decision-making process in river basin management is important because uncertainty is regarded as one of the main obstacles to sound decision-making. In case of high uncertainty, the risks of making a wrong decision could be quite high, which may have severe consequences. This paper applies a screening sensitivity analysis method, the Morris method, to investigate the propagation of uncertainty from factors in a flood damage model into the model outputs and explores the importance of factors based on the sensitivity analysis. Uncertainty reduction in the most influential factors identified by the Morris method is proposed as a means to reduce the uncertainty in model outputs. In this way the risks of making a wrong decision could be reduced. The results in this paper show that the Morris method is an efficient approach to help reduce the uncertainty in model outputs.

Conservation of Natural Resources↗