Is a sigh “just a sigh”? Sighs as emotional signals and responses to a difficult task

Sighing and the interpretation of sighs in everyday life seem never to have been the subject of psychological research. A questionnaire study of sighing showed that people associate sighing mainly with negative, low-intensity and deactivated emotional states. A second study investigated self/other differences in the interpretation of sighs in four hypothetical situations, revealing that sighs in other people are primarily perceived as signs of sadness, whereas own sighs are more often believed to express a state of "giving up" something or somebody. In a third experimental study participants worked on difficult (insoluble) puzzles, which generated many futile solution attempts, often accompanied by sighs. It is concluded that sighs are often unintentional expressions of an activity, plan or desire that has to be discarded, creating a pause before it can be replaced by a novel initiative.     

When 90% confidence intervals are 50% certain: on the credibility of credible intervals

Estimated confidence intervals for general knowledge items are usually too narrow. We report five experiments showing that people have much less confidence in these intervals than dictated by the assigned level of confidence. For instance, 90% intervals can be associated with an estimated confidence of 50% or less (and still lower hit rates). Moreover, interval width appears to remain stable over a wide range of instructions (high and low numeric and verbal confidence levels). This leads to a high degree of overconfidence for 90% intervals, but less for 50% intervals or for free choice intervals (without an assigned degree of confidence). To increase interval width one may have to ask exclusion rather than inclusion questions, for instance by soliciting ‘improbable’ upper and lower values (Experiment 4), or by asking separate ‘more than’ and ‘less than’ questions (Experiment 5). We conclude that interval width and degree of confidence have different determinants, and cannot be regarded as equivalent ways of expressing uncertainty. Copyright © 2005 John Wiley & Sons, Ltd.     

Why is p = .90 better than p = .70? Preference for definitive predictions by lay consumers of probability judgements

What do people regard as an informative and valuable probability statement? This article reports four experiments that show participants to have a clear preference for more extreme and higher probabilities over less extreme and lower ones. This pattern emerged in Experiment 1, in which no context was provided, and was further explored in Experiment 2 within a positive and a negative context. The findings were further confirmed in Experiment 3, which employed a Bayesian framework with revisions of opinions. Finally, Experiment 4 showed how preference for high probabilities can lead people to prefer an overconfident to a more well-calibrated (accurate) forecaster. The results are interpreted as manifestations of a search for definitive predictions principle, which asserts that high probabilities are preferred to medium ones and often favored over the corresponding complementary low probabilities on the basis of their capacity to predict the occurrence of single outcomes.     

More than 50% or Less than 70% Chance: Pragmatic Implications of Single‐Bound Probability Estimates

Probability estimates can be given as ranges or uncertainty intervals, where often only one of the interval bounds (lower or upper) is specified. For instance, a climate forecast can describe La Niña as having “more than 70% chance” or “less than 90% chance” of occurring. In three experiments, we studied how research participants perceived climate‐related forecasts expressed with lower‐bound (“over X% chance”) or upper‐bound (“under Y% chance”) probability statements. Results indicate that such single‐bound statements give pragmatic information in addition to the numeric probabilities they convey. First, the studies show that these statements are directional, leading the listeners' attention in opposite directions. “Over” statements guide attention towards the possible occurrence of the event and are explained by reasons for why it might happen, while “under” statements direct attention to its possible non‐occurrence and are more often explained by reasons for why the target event might not appear, corresponding to positive (it is possible) versus negative (it is uncertain) verbal probabilities. Second, boundaries were found to reveal the forecaster's beliefs and could be perceived as indicative of an increasing or a decreasing trend. Single‐bound probability estimates are therefore not neutral communications of probability level but might “leak” information about the speaker's expectations and about past and future developments of the forecast. Copyright © 2017 John Wiley & Sons, Ltd.     

There is a 60% probability,but I am 70% certain: communicative consequences of external and internal expressions of uncertainty

Current theories of probability recognise a distinction between external (un)certainty (frequentistic probabilities) and internal (un)certainty (degrees of belief). The present studies investigated this distinction in lay people's judgements of probability statements formulated to suggest either an internal (“I am X% certain”) or an external (“It is X% certain” or “There is an X% probability”) interpretation. These subtle differences in wording influenced participants' perceptions and endorsements of such statements, and their impressions of the speaker. External expressions were seen to signal more reliable task duration estimates, and a lower degree of external than internal certainty was deemed necessary to advise a course of action. In conversations about football, internal expressions were perceived as signalling more personal interest, and were expected to be on the average 10% higher than corresponding external probabilities. Finally, people who reported their outcome expectations for two major sports events let their degree of interest in these events influence their internal but not their external certainty. These results have implications for the communication of uncertainty and probability.     

Good luck and bad luck: how to tell the difference

Good luck implies comparison with a worse counterfactual outcome, whereas bad luck implies upward comparisons. People will accordingly describe themselves as particularly lucky after recollecting situations where they avoided something negative, and as particularly unlucky after recollecting episodes in which they missed something positive (Study 1). Upward and downward comparisons can be created by the way a situation develops, and are accentuated by the way a story is told. Good luck stories typically change for the better only in the last stage, whereas bad luck stories show a more steady downward progression (Study 2). This is also reflected in phrases believed to be characteristic of good luck versus bad luck stories, with good luck stories involving surprise and reference to close counterfactuals, whereas bad luck stories focus on initial normal events (Study 3). Good and bad luck imply different orders of events (negative–positive versus positive–negative), so by rearranging the narrative sequence, the same set of outcomes can form the basis for a good luck story as well as a bad luck story (Study 4). The final experiment (Study 5) shows that negative outcome expectations are typical for chance‐determined and uncontrolled situations. Under such circumstances, factual outcomes do not have to be exceptionally good to be considered as lucky. Copyright © 1999 John Wiley & Sons, Ltd.     

Waiting for the bus: when base-rates refuse to be neglected

The paper reports the results from 16 versions of a simple probability estimation task, where probability estimates derived from base-rate information have to be modified by case knowledge. In the bus problem [adapted from Falk, R., Lipson, A., & Konold, C. (1994). The ups and downs of the hope function in a fruitless search. In G. Wright & P. Ayton (Eds.), Subjective probability (pp. 353-377). Chichester, UK: Wiley], a passenger waits for a bus that departs before schedule in 10% of the cases, and is more than 10 min delayed in another 10%. What are Fred's chances of catching the bus on a day when he arrives on time and waits for 10 min? Most respondents think his probability is 10%, or 90%, instead of 50%, which is the correct answer. The experiments demonstrate the difficulties people have in replacing the original three-category 1/8/1 partitioning with a normalized, binary partitioning, where the middle category is discarded. In contrast with typical studies of "base-rate neglect", or under-weighing of base-rates, this task demonstrates a reversed base-rate fallacy, where frequentistic information is overextended and case information ignored. Possible explanations for this robust phenomenon are briefly discussed.     

Being responsible versus acting responsibly: Effects of agency and risk taking on responsibility judgments

In three experimental studies, with managers and students as participants, we explore in this paper the relation between two kinds of responsibility judgments, called Responsibility 1 (R1) and Responsibility 2 (R2). Decision makers can be viewed as being more or less responsible for their choice and its consequences (R1). Their actions can also be evaluated, from a normative point of view, as instances of more or less responsible behavior (R2). Experiment 1 showed that managers who depart from the default or “normal” course of action, by choosing a new (versus familiar) alternative, changing (versus sticking to) an initial decision, or going against (versus following) the advice of a management team, are rated as more responsible (R1) for the outcomes of their decision. At the same time, they are perceived to act in a less responsible way (R2). Experiment 2 compared decision makers choosing between more or less risky options. High risk takers were held more responsible (R1) for their choice and for its consequences, but were again viewed as behaving in a less responsible way (R2) than low risk takers. In Experiment 3, participants judged decision makers who followed or opposed others' advice by choosing either a high or a low risk option. Opposing others' advice led to higher R1 and lower R2 scores, especially when choosing the high risk option, moderated by outcome (successful decisions appearing more responsible than those that went wrong). Thus R1 and R2 judgments should be distinguished as having different and sometimes even opposite determinants.     

Pre‐outcome regret: Widespread and overlooked

Many real‐life decisions (e.g. promises, plans and agreements) involve a time interval between when the decision is made and the main outcome is revealed. Nearly all regret studies focus on anticipated or experienced post‐outcome regret. We argue that regret is also frequently experienced in the pre‐outcome period, and that this ‘pre‐outcome regret’ has other sources than regret experienced after the outcome is known. Regret experienced in the pre‐outcome period has an important function post‐outcome regret (usually) cannot have, namely to motivate the decision maker to reconsider the ongoing decision process and reverse the initial decision. Pre‐outcome regret should for these reasons be distinguished from post‐outcome regret, and studied separately. In two scenario studies, participants were asked to imagine their regret after agreeing to perform an inconvenient task. In both, more regret was reported before than after the event, even when they had imagined a ‘worst case’ outcome. In the third study, participants described a difficult choice from their own life. Again, regret was perceived as higher in the pre‐outcome period than afterwards. In a fourth study, participants reported regret ‘online’ during an economic game (a version of the ultimatum game). They regretted their decisions more before than after they knew the outcome. We conclude that experienced pre‐outcome regret is often stronger than post‐outcome regret, and typically increases during the pre‐outcome period. We suspect that the absence of JDM studies of pre‐outcome regret is a legacy of the dominant gambling metaphor within decision research. Copyright © 2010 John Wiley & Sons, Ltd.