Quantitative meanings of verbal probability expressions.

Reagan, Robert Timothy; Mosteller, Frederick; Youtz, Cleo

doi:10.1037/0021-9010.74.3.433

Cited by 162 publications

(87 citation statements)

References 7 publications

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“…Several studies of physicians show similar large interindividual differences in the interpretation of verbal or descriptive terms, even among experienced physicians. 1,2,19,24 We used a rank-ordered list to help decrease interindividual variability and allow better discrimination among terms, compared with random-order lists. 13,14 Even then, when ordered according to assigned percentages (Table 2), only the 1st and last 4 terms remained in their original positions, and the central 10 terms were nearly indistinguishable statistically, similar to the results we obtained for pathologists.…”

Section: Discussionmentioning

confidence: 99%

Interpretation by Clinicians of Probability Expressions in Cytology Reports and Effect on Clinical Decision-Making

Christopher

Hotz

Shelly³

et al. 2010

Journal of Veterinary Internal Medicine

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Background: Cytology often is used to obtain a diagnosis, such as that of malignant neoplasia. When a diagnosis is uncertain, pathologists often express probability using qualitative terms, such as “probable,” that have imprecise meanings. Hypothesis: Terms expressing probability are interpreted variably by veterinary practitioners and affect decisions regarding treatment and euthanasia. Animals: None. Methods: An online survey of members of the Veterinary Information Network was conducted. Veterinarians were asked to assign percentage probabilities to 18 modifiers of a diagnosis of lymphoma. They also were asked to select their most likely clinical action based on a diagnosis of lymphoma qualified one of 4 modifiers. Results were analyzed using descriptive and nonparametric methods. Percentage probabilities were analyzed by ANOVA after variance stabilization. Results: For 871 valid surveys, probabilities assigned to the 18 modifiers overlapped substantially, with medians (interquartile range) of 50% (50–70%) for “possible,” 66% (66–85%) for “probable,” and 70% (70–90%) for “consistent with.” More (P < .001) veterinarians (50.4%) chose to initiate treatment with a diagnosis of “consistent with lymphoma” as compared with “probable” (14.6%) or “possible” (1.6%) lymphoma. For clients considering euthanasia if the diagnosis was cancer, more (P < .001) veterinarians recommended euthanasia with a diagnosis of “consistent with lymphoma” (62.5%) as compared with “probable” (35.3%), or “possible” (2.0%) lymphoma. Conclusions and Clinical Importance: Probability expressions are interpreted variably yet have a major impact on clinical decision‐making, including the decision to recommend euthanasia. Standardized terminology could improve decision‐making and enhance clinical outcome.

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Section: Discussionmentioning

confidence: 99%

Interpretation by Clinicians of Probability Expressions in Cytology Reports and Effect on Clinical Decision-Making

Christopher

Hotz

Shelly³

et al. 2010

Journal of Veterinary Internal Medicine

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“…The CMAH uses the terms 'unlikely,' 'possible,' 'likely,' 'very likely' and 'almost certain' on an ordinal scale to express the likelihood of avalanche(s). Although many studies of quantified verbal probability expressions have identified consistent probability ranges for these terms (e.g., Kent 1964;Reagan et al 1989;Mosteller and Youtz 1990;Mastrandea et al 2010), the scale dependence of probability values and the scale independence of this likelihood terminology rule out associating probability values for this multi-scale approach. When a single slope that is possible to trigger is treated in isolation, it might be considered an unacceptably high risk.…”

Section: Likelihood Of Avalanche(s)mentioning

confidence: 99%

A conceptual model of avalanche hazard

Statham

Haegeli

Greene³

et al. 2017

Nat Hazards

114

112

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This conceptual model of avalanche hazard identifies the key components of avalanche hazard and structures them into a systematic, consistent workflow for hazard and risk assessments. The method is applicable to all types of avalanche forecasting operations, and the underlying principles can be applied at any scale in space or time. The concept of an avalanche problem is introduced, describing how different types of avalanche problems directly influence the assessment and management of the risk. Four sequential questions are shown to structure the assessment of avalanche hazard, namely: (1) What type of avalanche problem(s) exists? (2) Where are these problems located in the terrain? (3) How likely is it that an avalanche will occur? and (4) How big will the avalanche be? Our objective was to develop an underpinning for qualitative hazard and risk assessments and address this knowledge gap in the avalanche forecasting literature. We used judgmental decomposition to elicit the avalanche forecasting process from forecasters and then described it within a risk-based framework that is consistent with other natural hazards disciplines.

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“…Although it does not appear in the IPCC-recommended probability lexicon, "possible" is often used to convey uncertainty in the IPCC reports (Intergovernmental Panel on Climate Change, 2014). "Possible" means, on average, a probability range between 35 and 60%, (Budescu & Wallsten, 1985;Juanchich, Sirota, & Butler, 2012;Reagan, Mosteller, & Youtz, 1989). It should therefore be used for outcomes that have a similar frequency of 35-60%.…”

Section: How Likely Are Extreme Outcomes?mentioning

confidence: 99%

How much will the sea level rise? Outcome selection and subjective probability in climate change predictions.

Juanchich¹,

Sirota²

2017

Journal of Experimental Psychology: Applied

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We tested whether people focus on extreme outcomes to predict climate change and assessed the gap between the frequency of the predicted outcome and its perceived probability while controlling for climate change beliefs. We also tested two cost-effective interventions to reduce the preference for extreme outcomes and the frequency-probability gap by manipulating the probabilistic format: numerical or dual-verbal-numerical. In four experiments, participants read a scenario featuring a distribution of sea level rises, selected a sea rise to complete a prediction (e.g., "It is 'unlikely' that the sea level will rise … inches") and judged the likelihood of this sea rise occurring. Results showed that people have a preference for predicting extreme climate change outcomes in verbal predictions (59% in Experiments 1-4) and that this preference was not predicted by climate change beliefs.Results also showed an important gap between the predicted outcome frequency and participants' perception of the probability that it would occur. The dual-format reduced the preference for extreme outcomes for low and medium probability predictions but not for high ones and none of the formats consistently reduced the frequency-probability gap.Key words: Uncertainty, prediction, probability, frequency, climate change. Public Significance Statement:Four experiments advance our knowledge of the way people predict climate change based on a distribution of sea rise projections. People tend to predict extreme outcomes and to over-estimate their chance of occurrence. To reduce miscommunications, forecasters should state whether they predict a minimal or maximal outcome and should express their predictions in such a way that the probability of the outcome matches its frequency of occurrence in the projections.

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Quantitative meanings of verbal probability expressions.

Cited by 162 publications

References 7 publications

Interpretation by Clinicians of Probability Expressions in Cytology Reports and Effect on Clinical Decision-Making

Interpretation by Clinicians of Probability Expressions in Cytology Reports and Effect on Clinical Decision-Making

A conceptual model of avalanche hazard

How much will the sea level rise? Outcome selection and subjective probability in climate change predictions.

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