To what extent do politeness expectations shape risk perception? Even numerical probabilities are under their spell!

Severity influences categorical likelihood communications: A case study with Southeast Asian weather forecasters

Risk assessments are common in multiple domains, from finance to medicine. They require evaluating an event's potential severity and likelihood. We investigate the possible dependence of likelihood and severity within the domain of impact-based weather forecasting (IBF), following predictions derived from considering asymmetric loss functions. In a collaboration between UK psychologists and partners from four meteorological organisations in Southeast Asia, we conducted two studies (N = 363) eliciting weather warnings from forecasters. Forecasters provided warnings denoting higher likelihoods for high severity impacts than low severity impacts, despite these impacts being described as having the same explicit numerical likelihood of occurrence. This 'Severity effect' is pervasive, and we find it can have a continued influence even for an updated forecast. It is additionally observed when translating warnings made on a risk matrix to numerical probabilities.

Eye-tracking evidence for fixation asymmetries in verbal and numerical quantifier processing

When people are given quantified information (e.g., ‘there is a 60% chance of rain’), the format of quantifiers (i.e., numerical: ‘a 60% chance’ vs. verbal: ‘it is likely’) might affect their decisions. Previous studies with indirect cues of judgements and decisions (e.g., response times, decision outcomes) give inconsistent findings that could support either a more intuitive process for verbal than numerical quantifiers or a greater focus on the context (e.g., rain) for verbal than numerical quantifiers. We used two pre-registered eye-tracking experiments (n(1) = 148, n(2) = 133) to investigate decision-making processes with verbal and numerical quantifiers. Participants evaluated multiple verbally or numerically quantified nutrition labels (Experiment 1) and weather forecasts (Experiment 2) with different context valence (positive or negative), and quantities (‘low’, ‘medium’, or ‘high’ in Experiment 1 and ‘possible’, ‘likely’, or ‘very likely’ in Experiment 2) presented in a fully within-subjects design. Participants looked longer at verbal than numerical quantifiers, and longer at the contextual information with verbal quantifiers. Quantifier format also affected judgements and decisions: in Experiment 1, participants judged positive labels to be better in the verbal compared to the equivalent numerical condition (and to be worse for negative labels). In Experiment 2, participants decided on rain protection more for a verbal forecast of rain than the equivalent numerical forecast. The results fit the explanation that verbal quantifiers put more focus on the informational context than do numerical quantifiers, rather than prompting more intuitive decisions.

Do people really prefer verbal probabilities?

When people communicate uncertainty, do they prefer to use words (e.g., "a chance", "possible") or numbers (e.g., "20%", "a 1 in 2 chance")? To answer this question, past research drew from a range of methodologies, yet failed to provide a clear-cut answer. Building on a review of existing methodologies, theoretical accounts and empirical findings, we tested the hypothesis that the preference for a particular format is driven by the variant of uncertainty that people experience. We expected that epistemic uncertainty would be more often communicated in words, whereas distributional uncertainty would be more often communicated in numbers; for the dispositional uncertainty, we expected that an individual's disposition would be more often communicated in words, whereas dispositions from the world would be more often communicated numerically. In three experiments (one oral, two written), participants communicated their uncertainty regarding two outcomes per variants of uncertainty: epistemic, dispositional and distributional. Overall, participants communicated their uncertainty more often in words, but this preference depended on the variants of uncertainty. Participants conveyed their epistemic and dispositional uncertainties more often in words and their distributional uncertainty in numbers (Experiments 1 and 2) but this effect was greatly reduced when the precision of uncertainty was held constant (Experiment 3), pointing out the key role of uncertainty vagueness. We have reviewed the implications of our findings for the existing accounts of format preferences.

Development of the Multi-Dimensional Analysis of Patient Outcome Predictions (MD.POP) during medical encounters

OBJECTIVE

Our first objective was to develop the Multi-Dimensional analysis of Patient Outcome Predictions (MD.POP), an interaction analysis system that assesses how HCPs discuss precisely and exclusively patient outcomes during medical encounters. The second objective was to study its interrater reliability.

METHOD

The MD.POP was developed by consensus meetings. Forty simulated medical encounters between physicians and an actress portraying a patient were analysed. Interrater reliability analysis was conducted on 20 of those simulated encounters.

RESULTS

The MD.POP includes six dimensions: object, framing, value, domain, probability and form of POP. The coding method includes four steps: 1) transcription of the encounter, 2) POP identification, 3) POP dimension coding and 4) POP scoring. Descriptive analyses show that the MD.POP is able to describe verbal expressions addressing the patient's outcomes. Statistical analyses show excellent interrater reliability (Cohen's Kappa ranging from 0.92 to 0.94).

CONCLUSION

The MD.POP is a reliable interaction analysis system that assesses how HCPs discuss patient medical, psychological or social outcomes during medical encounters.

PRACTICAL IMPLICATION

The MD.POP provides a measure for researchers to study how HCPs communicate with patients about potential outcomes. Results of such studies will allow to provide recommendations to improve HCP's communication about patients' outcomes.

A direct and comprehensive test of two postulates of politeness theory applied to uncertainty communication

Applied to uncertainty communication, politeness theory postulates that when announcing bad news (1) speakers may intend not only to inform, but also to manage (e.g., save) the hearers’ or speakers’ own faces (i.e., face-managing intentions), and (2) speakers may perform face-managing intentions by altering the explicitly communicated probability. Previous research has assumed these two core postulates when explaining various reasoning and judgment phenomena in hearers, but has failed to test them empirically in a comprehensive and direct way: jointly in relation to speakers. To provide this critical evidence, we asked subjects to communicate a predefined numerical probability of two negative outcomes, using a verbal probability scale. Subjects reported their communication intentions afterwards. In line with the first politeness theory postulate, speakers intended not only to be informative but also to tactfully announce bad news or to avoid being blamed in case they made inaccurate (too low or too high) prediction. In line with the second politeness theory postulate, speakers altered their explicitly communicated probability more often and more substantially when adopting face-managing intentions than when adopting informative intentions. We discuss how this evidence corroborates the politeness theory and validates the previous research that focused on hearers.

Do people really say it is "likely" when they believe it is only "possible"? Effect of politeness on risk communication

Politeness theory posits that speakers can use verbal probabilities (e.g., there is a chance, it is likely) to hedge bad news. So far, only indirect evidence supports that claim: From the hearer's standpoint, verbal probabilities are interpreted either as plain likelihood-communication devices or as face-management devices, resulting in different risk perceptions. The present research aims to test more directly the postulate of politeness theory by focusing on the effects of speakers' intentions on risk communication. In three experiments, participants communicated a probability by choosing an expression from a list of verbal probabilities. Results consistently showed that polite speakers communicated a different risk magnitude than informative speakers. Further findings indicate that the effect of the speakers' intention depends on the valence of the uncertain outcome. The theoretical and applied implications of these findings are discussed.

Top scores are possible, bottom scores are certain (and middle scores are not worth mentioning): A pragmatic view of verbal probabilities

In most previous studies of verbal probabilities, participants are asked to translate expressions such as possible and not certain into numeric probability values. This probabilistic translation approach can be contrasted with a novel which-outcome (WO) approach that focuses on the outcomes that people naturally associate with probability terms. The WO approach has revealed that, when given bell-shaped distributions of quantitative outcomes, people tend to associate certainty with minimum (unlikely) outcome magnitudes and possibility with (unlikely) maximal ones. The purpose of the present paper is to test the factors that foster these effects and the conditions in which they apply. Experiment 1 showed that the association of probability term and outcome was related to the association of scalar modifiers (i.e., it is certain that the battery will last at least…, it is possible that the battery will last up to…). Further, we tested whether this pattern was dependent on the frequency (e.g., increasing vs. decreasing distribution) or the nature of the outcomes presented (i.e., categorical vs. continuous). Results showed that despite being slightly affected by the shape of the distribution, participants continue to prefer to associate possible with maximum outcomes and certain with minimum outcomes. The final experiment provided a boundary condition to the effect, showing that it applies to verbal but not numerical probabilities.