In 2 experiments, we attempted to reduce belief-consistent biases in interpretations of a polarized problem by making information easier to interpret. In the experiments, participants solved numerical problems that were either framed in a politically polarized (the effects of Muslim prayer rooms on support for Islamic extremism) or a neutral setting (the effects of a skin cream on skin rash). In both studies, the problems were presented twice, with the second presentation accompanied with an aid to facilitate problem-solving. In Experiment 1, this aid came in the form of an informative text on how to calculate the numbers to solve the problem. In Experiment 2, the aid provided participants with the first calculus necessary to solve the problem: transforming frequencies to percentages. Overall, results demonstrated belief-consistent responses in the polarized scenario when participants attempted to solve the first problem (higher accuracy when the correct conclusion was in line with participants’ ideology). Information on how to calculate the problem (Experiment 1) only slightly reduced the biased responses, whereas the added percentages (Experiment 2) led to a substantial reduction of the bias. Thus, we demonstrate that the facilitation of complex information on a polarized topic reduces biases in favor of rational reasoning.

One way of controlling global warming is to substitute fuel driven cars with electric cars. Electric vehicles need to be charged. For maximal efficiency the charging times should be as short as possible. In the US charging stations are classified as Level 1 charging 5-10 miles/h, Level 2 25 miles/h and Fast DCFC stations 150-1000 miles/h. We asked participants to select one of two upgrades of charging stations that would save most charging time for a vehicle. The alternatives were upgrading L1 (5miles/h) to L2 (25 miles/h) or L2 (25miles/h) to Fast (250 miles/h). In all, 86% of the participants wanted to upgrade to a Fast station, which objectively saves less time than L1 to L2. The second study replicated the first study and 91% of the participants wanted to upgrade to the Fast (250) station. The third study offered alternatives with smaller objective efficiency differences than the earlier studies: upgrading L2 (30) to Fast (150) and Fast (150) to Fast (600) and 68% of the participants preferred the second incorrect alternative. Verbal justifications showed that many participants seemed to assume that differences in charging time are proportional to charging time saved. The results have practical implications and illustrate the difficulty to process reciprocal variables leading to incorrect decisions. Finally, we suggest two strategies for counteracting biased intuitive decision making when charging efficiencies are compared.

Participants judged the risk of an infection during a face to face conversation at different interpersonal distances from a SARS-CoV-2 infected person who wore a face mask or not, and in the same questionnaire answered questions about Corona related issues. Keeping a distance to an infected person serves as a protective measure against an infection. When an infected person moves closer, risk of infection increases. Participants were aware of this fact, but underestimated the rate at which the risk of infection increases when getting closer to an infected person, e.g., from 1.5 to 0.5 m (perceived risk increase = 3.33 times higher, objective = 9.00 times higher). This is alarming because it means that people can take risks of infection that they are not aware of or want to take, when they approach another possibly virus infected person. Correspondingly, when an infected person moves away the speed of risk decrease was underestimated, meaning that people are not aware of how much safer they will be if they move away from an infected person. The perceived risk reducing effects of a face mask were approximately correct. Judgments of infection risk at different interpersonal distances (with or without a mask) were unrelated to how often a person used a mask, avoided others or canceled meetings during the COVID-19 pandemic. Greater worry in general and in particular over COVID-19, correlated positively with more protective behavior during the pandemic, but not with judgments of infection risk at different interpersonal distances. Participants with higher scores on a cognitive numeracy test judged mask efficiency more correctly, and women were more worried and risk avoiding than men. The results have implications for understanding behavior in a pandemic, and are relevant for risk communications about the steep increase in risk when approaching a person who may be infected with an airborne virus.

In a questionnaire, participants judged the increase in SARS-CoV-2 virus exposure when moving closer to an infected person. Earlier studies have shown that the actual increase in virus exposure is underestimated and the present study replicated and extended these studies. The primary purpose was to investigate to what extent questionnaire judgments about hypothetical situations can predict judgments and actual behavior in real physical space. Participants responded to a questionnaire and the same participants also took part in a parallel study that was conducted in a room with a mannequin representing a virus infected person. The earlier reported bias in the perception of exposure as a function of distance to a virus source was replicated in the questionnaire and the physical laboratory study. A linear function connected median exposure judgments at the same distances from a virus source in the questionnaire and in the laboratory, R2 = 0.99. When asked to move to a distance that would give a prescribed exposure level, a linear function described the relationship between questionnaire distance judgments and moves to distances in the physical space, R2 = 0.95. We concluded that questionnaire data about perceived virus exposures are reliable indicators of real behavior. For health reasons, the significant underestimations of the steep increase of virus exposure during an approach to a virus source need to be stressed in communications to policy makers, the public, professionals working close to clients, nursing staff, and other care providers.

The resource saving bias is a cognitive bias describing how resource savings from improvements of high-productivity units are overestimated compared to improvements of less productive units. Motivational reasoning describes how attitudes, here towards private/public health care, distort decisions based on numerical facts. Participants made a choice between two productivity increase options with the goal of saving doctor resources. The options described productivity increases in low-/high-productivity private/public emergency rooms. Jointly, the biases produced 78% incorrect decisions. The cognitive bias was stronger than the motivational bias. Verbal justifications of the decisions revealed elaborations of the problem beyond the information provided, biased integration of quantitative information, change of goal of decision, and motivational attitude biases. Most (83%) of the incorrect decisions were based on (incorrect) mathematical justifications illustrating the resource saving bias. Participants who had better scores on a cognitive test made poorer decisions. Women who gave qualitative justifications to a greater extent than men made more correct decision. After a first decision, participants were informed about the correct decision with a mathematical explanation. Only 6.3% of the participants corrected their decisions after information illustrating facts resistance. This could be explained by psychological sunk cost and coherence theories. Those who made the wrong choice remembered the facts of the problem better than those who made a correct choice.

Background During the COVID-19 pandemic people were asked to keep interpersonal distance, wash their hands and avoid gatherings of people. But, do people understand how much a change of the distance to a virus infected person means for the exposure to that person’s virus? To answer this question, we studied how people perceive virus exposure from an infected person at different distances and lengths of a conversation. Method An online questionnaire was distributed to 101 participants drawn from the general US population. Participants judged perceived virus exposure at different interpersonal distances to an infected person in a face to face conversation of different lengths of time. A model based on empirical and theoretical studies of dispersion of particles in the air was used to estimate a person’s objective virus exposure during different times and distances from a virus source. The model and empirical data show that exposure changes with the square of the distance and linearly with time. Results A majority (78%) of the participants underestimated the effects on virus exposure following a change of interpersonal distance. The dominating bias was assuming that exposure varies linearly with distance. To illustrate, an approach to a virus source from 6 to 2 feet was judged to give a 3 times higher exposure but, objectively it is 9 times. By way of contrast, perceptions of exposure as a function of the duration of a conversation were unbiased. The COVID-19 pandemic caused by the SARS-CoV2 virus is likely to be followed by other pandemics also caused by airborne Corona or other viruses. Therefore, the results are important for administrators when designing risk communications to the general public and workers in the health care sector about social distancing and infection risks. Conclusions People quite drastically underestimate the increase in virus exposure following an approach to a virus infected person. They also overestimate exposure after a move away from an infected person. For public health reasons, the correct function connecting distance with virus exposure should be communicated to the general public to avoid deliberate violations of recommended interpersonal distances.

Measurements of human attitudes and perceptions have traditionally used numerical point judgments. In the present study, we compared conventional point estimates of weight with an interval judgment method. Participants were allowed to make step by step judgments, successively converging towards their best estimate. Participants estimated, in grams, the weight of differently sized boxes, estimates thus susceptible to the size-weight illusion. The illusion makes the smaller of two objects of the same weight, differing only in size, to be perceived as heavier. The self-selected interval method entails participants judging a highest and lowest reasonable value for the true weight. This is followed by a splitting procedure, consecutive choices of selecting the upper or lower half of the interval the individual estimates most likely to include the true value. Compared to point estimates, interval midpoints showed less variability and reduced the size-weight illusion, but only to a limited extent. Accuracy improvements from the interval method were limited, but the between participant variation suggests that the method has merit.

Participants judged airborne Corona virus exposure following a change of inter-personal distance and time of a conversation with an infected person with and without a face mask. About 75% of the participants underestimated how much virus exposure changes when the distance to an infected person changed. The smallest average face to face distance from an infected person without a mask that a participant judged as sufficiently safe was about 12 feet (3.67 m). Correlations showed that the more a person underestimated the effects of change of distance on exposure the shorter was that persons own safety distance. On average the effects of different lengths of a conversation on exposure were correct, but those who judged the effects of time as smaller tended to select longer safety distances. Worry of own COVID-19 infection correlated with protective behaviors: keeping longer safety distances, avoiding public gatherings, postponement of meetings with friends. The results showed that the protective effects of both distancing and wearing a face mask were under-estimated by a majority of the participants. Implications of these results were discussed last.

The chief purpose of the present study was to identify and describe cognitive judgment rules that lead to the same bias in a traffic context. A judgment is biased if it deviates systematically from physical, statistical or other scientific facts. Another purpose was to introduce Spectral analysis to traffic judgment research. Spectral analysis (Svenson, Gonzalez & Eriksson, 2018) of judgment distributions were used in the data analyses because this method can identify different judgment rules. The following biases will be investigated: the time saving bias (Svenson 1970, 2008), the miles per gallon, the MPG illusion The main purpose of this study was to identify different cognitive rules that lead to a particular judgment bias. To fulfill this purpose, a new method Spectral analysis was introduced and applied. Participants judged time saved by driving faster, fuel saved by replacing a car and braking capacity at different speeds. These problems invite the time saving bias (e.g., time saved from speed increases at higher speeds overestimated), the miles per gallon, MPG illusion (misjudgment of fuel saved by replacing a car) and the braking capacity bias (overestimation of braking capacity after speed increase). The average results replicated the biases. Spectral analysis of individual participants and problems showed that a speed difference rule explained about half of the time saving judgments and about three fourth of the MPG judgments. A difference between speeds rule described about one third of the biased braking judgments and a ratio/proportion rule about one fifth of the time saving and MPG judgments. All rules give biased judgments in all three domains. The paper ends with a discussion of hierarchies of cognitive rules, applications of the results, and how to mitigate or avoid the biases and the risks associated with the biases. (c) 2021 Elsevier Ltd. All rights reserved.

The time loss bias describes overestimation of time lost after speed decreases from high speeds and underestimations after decreases from low driving speeds. Participants judged the speed decrease from one speed (e.g. 130 km/h) that would give the same time loss as a decrease from another speed (e.g. from 40 to 30 km/h). We carried out descriptive spectral analyses of distributions of judgments for each problem. Each distribution peak was associated with a judgment rule. The first study found two different judgment processes both leading to the time loss bias: a Difference process rule used for 20% and a Ratio rule used for 31% of the judgments. The correct rule applied to 10% of the judgments. The second study added verbal protocols. The results showed that the Ratio rule was most common (41%) followed by the Difference (12%) and correct (8%) rules. Verbal reports supported these results.

In order to minimize the risk of infection during the Covid-19 pandemic, people are recommended to keep interpersonal distance (e.g., 1 m, 2 m, 6 feet), wash their hands frequently, limit social contacts and sometimes to wear a face mask. We investigated how people judge the protective effect of interpersonal distance against the Corona virus. The REM model, based on earlier empirical studies, describes how a person’s virus exposure decreases with the square of the distance to another person emitting a virus in a face to face situation. In a comparison with model predictions, most participants underestimated the protective effect of moving further away from another person. Correspondingly, most participants were not aware of how much their exposure would increase if they moved closer to the other person. Spectral analysis of judgments showed that a linear ratio model with the independent variable = (initial distance)/(distance to which a person moves) was the most frequently used judgment rule. It leads to insensitivity to change in exposure compared with the REM model. The present study indicated a need for information about the effects of keeping interpersonal distance and about the importance of virus carrying aerosols in environments with insufficient air ventilation. Longer conversations emitting aerosols in a closed environment may lead to ambient concentrations of aerosols in the air that no distance can compensate for. The results of the study are important for risk communications in countries where people do not wear a mask and when authorities consider removal of a recommendation or a requirement to wear a face mask.

This chapter begins by drawing together from the case studies the generic empirical characteristics of the practice in corporate management of hazards. As the burden of hazard management has escalated, so too has the view of safety, waste reduction, and environmental protection. Commitment of high-level management to health and safety appears to be an important, if somewhat elusive, contributor to effective hazard management. Patric Lagadec notes the importance of top-level management's ensuring that hazard problems are not covered up at lower levels and insisting on an effective system of upward flow of information. Modern hazard management employs a wide variety of technological and behavioral controls designed to prevent or reduce hazard. Comparative studies of hazard management in industrialized countries have suggested a greater reliance on corporations and trade unions in hazard management and more confidence in regulatory discretion outside the United States.

PHARMACHEM is an international corporation that manufactures, among other products, pharmaceuticals for people and animals. The analysis of hazard controls in PHARMACHEM and the plant is a sequential but iterative process. PHARMACHEM is a highly profitable corporation with a very large investment in research and development, so that its manufacturing costs are proportionately lower than those in other industries. PHARMACHEM uses a wide variety of measures to control the hazards of manufacturing PRODUCT-A. The occupational health and safety hazards of PRODUCT-A fall into two types: those that are common to manufacturing processes in general and to chemical plants in particular, and those that are specific to the synthesis and manufacturing of PRODUCT-A. Prior to the production of PRODUCT-A at the plant, the standard operating procedures developed in pilot runs in the laboratory and other plants included detailed safety and health cautions.

This chapter examines Volvo's hazard-management structure and process within a broad societal context. The first Volvo automobile made its debut in 1927 and through the early 1930s the company made only a couple of hundred cars each year. Volvo is particularly noteworthy as a leader in automobile safety. The organizational structure of the Volvo Car Corporation, with an emphasis on hazard management. Within Volvo, the Safety and Environment Department is responsible for establishing and maintaining the required posture for product liability and for coordinating the overall product-liability prevention and reduction program. Whereas the Safety and Environment Department mainly analyzes information in documents, reports, and journals, the Volvo Safety Center also generates a great deal of research data bearing upon hazard identification and assessment. In fact, Volvo uses a well-articulated system of extensive feedback for improving the safety of its cars.

We used correlation and spectral analyses to investigate the cognitive structures and processes producing biased judgments. We used 5 different sets of driving problems to exemplify problems that trigger biases, specifically: (1) underestimation of the impact of occasional slow speeds on mean speed judgments, (2) overestimation of braking capacity after a speed increase, (3) the time saving bias (overestimation of the time saved by increasing a high speed further, and underestimation of time saved when increasing a low speed), (4) underestimation of increase of fatal accident risk when speed is increased, and (5) underestimation of the increase of stopping distance when speed is increased. The results verified the predicted biases. A correlation analysis found no strong links between biases; only accident risk and stopping distance biases were correlated significantly. Spectral analysis of judgments was used to identify different decision rules. Most participants were consistent in their use of a single rule within a problem set with the same bias. The participants used difference, average, weighed average and ratio rules, all producing biased judgments. Among the rules, difference rules were used most frequently across the different biases. We found no personal consistency in the rules used across problem sets. The complexity of rules varied across problem sets for most participants.