P. Howe, Andrew Perfors, B. Walker, Y. Kashima, N. Fay
Bayesian statistics offers a normative description for how a person should combine their original beliefs (i.e., their priors) in light of new evidence (i.e., the likelihood). Previous research suggests that people tend to under-weight both their prior (base rate neglect) and the likelihood (conservatism), although this varies by individual and situation. Yet this work generally elicits people's knowledge as single point estimates (e.g., x has 5% probability of occurring) rather than as a full distribution. Here we demonstrate the utility of eliciting and fitting full distributions when studying these questions. Across three experiments, we found substantial variation in the extent to which people showed base rate neglect and conservatism, which our method allowed us to measure for the first time simultaneously at the level of the individual. We found that while most people tended to disregard the base rate, they did so less when the prior was made explicit. Although many individuals were conservative, there was no apparent systematic relationship between base rate neglect and conservatism within individuals. We suggest that this method shows great potential for studying human probabilistic reasoning.
{"title":"Base rate neglect and conservatism in probabilistic reasoning: Insights from eliciting full distributions","authors":"P. Howe, Andrew Perfors, B. Walker, Y. Kashima, N. Fay","doi":"10.31234/osf.io/q7znk","DOIUrl":"https://doi.org/10.31234/osf.io/q7znk","url":null,"abstract":"Bayesian statistics offers a normative description for how a person should combine their original beliefs (i.e., their priors) in light of new evidence (i.e., the likelihood). Previous research suggests that people tend to under-weight both their prior (base rate neglect) and the likelihood (conservatism), although this varies by individual and situation. Yet this work generally elicits people's knowledge as single point estimates (e.g., x has 5% probability of occurring) rather than as a full distribution. Here we demonstrate the utility of eliciting and fitting full distributions when studying these questions. Across three experiments, we found substantial variation in the extent to which people showed base rate neglect and conservatism, which our method allowed us to measure for the first time simultaneously at the level of the individual. We found that while most people tended to disregard the base rate, they did so less when the prior was made explicit. Although many individuals were conservative, there was no apparent systematic relationship between base rate neglect and conservatism within individuals. We suggest that this method shows great potential for studying human probabilistic reasoning.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43304326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1017/s193029750000838x
M. Birnbaum
This paper illustrates how to apply the RECIPE design to evaluate multiattribute judgment, reporting an experiment in which participants judged intentions to receive a new vaccine against COVID-19. The attributes varied were Price of the vaccine, Risks of side effects as reported in trials, and Effectiveness of the vaccine in preventing COVID. The RECIPE design is a union of factorial designs in which each of three attributes is presented alone, in pairs with each of the other attributes, and in a complete factorial with all other information. Consistent with previous research with analogous judgment tasks, the additive and relative weight averaging models with constant weights could be rejected in favor of a configural weight averaging model in which the lowest-valued attribute receives additional weight. That is, people are unlikely to accept vaccination if Price is too high, Risk is too high, or Effectiveness is too low. The attribute with the greatest weight was Effectiveness, followed by Risk of side-effects, and Price carried the least weight.
{"title":"Multiattribute judgment: Acceptance of a new COVID-19 vaccine as a function of price, risk, and effectiveness","authors":"M. Birnbaum","doi":"10.1017/s193029750000838x","DOIUrl":"https://doi.org/10.1017/s193029750000838x","url":null,"abstract":"This paper illustrates how to apply the RECIPE design to evaluate multiattribute judgment, reporting an experiment in which participants judged intentions to receive a new vaccine against COVID-19. The attributes varied were Price of the vaccine, Risks of side effects as reported in trials, and Effectiveness of the vaccine in preventing COVID. The RECIPE design is a union of factorial designs in which each of three attributes is presented alone, in pairs with each of the other attributes, and in a complete factorial with all other information. Consistent with previous research with analogous judgment tasks, the additive and relative weight averaging models with constant weights could be rejected in favor of a configural weight averaging model in which the lowest-valued attribute receives additional weight. That is, people are unlikely to accept vaccination if Price is too high, Risk is too high, or Effectiveness is too low. The attribute with the greatest weight was Effectiveness, followed by Risk of side-effects, and Price carried the least weight.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41654708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1017/s1930297500008378
Arvid Erlandsson
In ten studies (N = 9187), I systematically investigated the direction and size of seven helping effects (the identifiable-victim effect, proportion dominance effect, ingroup effect, existence effect, innocence effect, age effect and gender effect). All effects were tested in three decision modes (separate evaluation, joint evaluation and forced choice), and in their weak form (equal efficiency), or strong form (unequal efficiency). Participants read about one, or two, medical help projects and rated the attractiveness of and allocated resources to the project/projects, or choose which project to implement. The results show that the included help-situation attributes vary in their: (1) Evaluability – e.g., rescue proportion is the easiest to evaluate in separate evaluation. (2) Justifiability – e.g., people prefer to save fewer lives now rather than more lives in the future, but not fewer identified lives rather than more statistical lives. (3) Prominence – e.g., people express a preference to help females, but only when forced to choose.
{"title":"Seven (weak and strong) helping effects systematically tested in separate evaluation, joint evaluation and forced choice","authors":"Arvid Erlandsson","doi":"10.1017/s1930297500008378","DOIUrl":"https://doi.org/10.1017/s1930297500008378","url":null,"abstract":"In ten studies (N = 9187), I systematically investigated the direction and size of seven helping effects (the identifiable-victim effect, proportion dominance effect, ingroup effect, existence effect, innocence effect, age effect and gender effect). All effects were tested in three decision modes (separate evaluation, joint evaluation and forced choice), and in their weak form (equal efficiency), or strong form (unequal efficiency). Participants read about one, or two, medical help projects and rated the attractiveness of and allocated resources to the project/projects, or choose which project to implement. The results show that the included help-situation attributes vary in their: (1) Evaluability – e.g., rescue proportion is the easiest to evaluate in separate evaluation. (2) Justifiability – e.g., people prefer to save fewer lives now rather than more lives in the future, but not fewer identified lives rather than more statistical lives. (3) Prominence – e.g., people express a preference to help females, but only when forced to choose.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41622627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1017/s1930297500008391
P. Lunn, Jason Somerville
Previous research in multiple judgment domains has found that nonlinear functions are typically processed less accurately than linear ones. This empirical regularity has potential implications for consumer choice, given that nonlinear functions (e.g., diminishing returns) are commonplace. In two experimental studies we measured precision and bias in consumers’ ability to identify surpluses when returns to product attributes were nonlinear. We hypothesized that nonlinear functions would reduce precision and induce bias toward linearization of nonlinear relationships. Neither hypothesis was supported for monotonic nonlinearities. However, precision was greatly reduced for products with nonmonotonic attributes. Moreover, assessments of surplus were systematically and strongly biased, regardless of the shape of returns and despite feedback and incentives. The findings imply that consumers use a flexible but coarse mechanism to compare attributes against prices, with implications for the prevalence of costly mistakes.
{"title":"Consumers’ ability to identify a surplus when returns to attributes are nonlinear","authors":"P. Lunn, Jason Somerville","doi":"10.1017/s1930297500008391","DOIUrl":"https://doi.org/10.1017/s1930297500008391","url":null,"abstract":"Previous research in multiple judgment domains has found that nonlinear functions are typically processed less accurately than linear ones. This empirical regularity has potential implications for consumer choice, given that nonlinear functions (e.g., diminishing returns) are commonplace. In two experimental studies we measured precision and bias in consumers’ ability to identify surpluses when returns to product attributes were nonlinear. We hypothesized that nonlinear functions would reduce precision and induce bias toward linearization of nonlinear relationships. Neither hypothesis was supported for monotonic nonlinearities. However, precision was greatly reduced for products with nonmonotonic attributes. Moreover, assessments of surplus were systematically and strongly biased, regardless of the shape of returns and despite feedback and incentives. The findings imply that consumers use a flexible but coarse mechanism to compare attributes against prices, with implications for the prevalence of costly mistakes.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48723354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1017/s1930297500008408
Angelo Pirrone, A. Reina, F. Gobet
Recent work has derived the optimal policy for two-alternative value-based decisions, in which decision-makers compare the subjective expected reward of two alternatives. Under specific task assumptions — such as linear utility, linear cost of time and constant processing noise — the optimal policy is implemented by a diffusion process in which parallel decision thresholds collapse over time as a function of prior knowledge about average reward across trials. This policy predicts that the decision dynamics of each trial are dominated by the difference in value between alternatives and are insensitive to the magnitude of the alternatives (i.e., their summed values). This prediction clashes with empirical evidence showing magnitude-sensitivity even in the case of equal alternatives, and with ecologically plausible accounts of decision making. Previous work has shown that relaxing assumptions about linear utility or linear time cost can give rise to optimal magnitude-sensitive policies. Here we question the assumption of constant processing noise, in favour of input-dependent noise. The neurally plausible assumption of input-dependent noise during evidence accumulation has received strong support from previous experimental and modelling work. We show that including input-dependent noise in the evidence accumulation process results in a magnitude-sensitive optimal policy for value-based decision-making, even in the case of a linear utility function and a linear cost of time, for both single (i.e., isolated) choices and sequences of choices in which decision-makers maximise reward rate. Compared to explanations that rely on non-linear utility functions and/or non-linear cost of time, our proposed account of magnitude-sensitive optimal decision-making provides a parsimonious explanation that bridges the gap between various task assumptions and between various types of decision making.
{"title":"Input-dependent noise can explain magnitude-sensitivity in optimal value-based decision-making","authors":"Angelo Pirrone, A. Reina, F. Gobet","doi":"10.1017/s1930297500008408","DOIUrl":"https://doi.org/10.1017/s1930297500008408","url":null,"abstract":"Recent work has derived the optimal policy for two-alternative value-based decisions, in which decision-makers compare the subjective expected reward of two alternatives. Under specific task assumptions — such as linear utility, linear cost of time and constant processing noise — the optimal policy is implemented by a diffusion process in which parallel decision thresholds collapse over time as a function of prior knowledge about average reward across trials. This policy predicts that the decision dynamics of each trial are dominated by the difference in value between alternatives and are insensitive to the magnitude of the alternatives (i.e., their summed values). This prediction clashes with empirical evidence showing magnitude-sensitivity even in the case of equal alternatives, and with ecologically plausible accounts of decision making. Previous work has shown that relaxing assumptions about linear utility or linear time cost can give rise to optimal magnitude-sensitive policies. Here we question the assumption of constant processing noise, in favour of input-dependent noise. The neurally plausible assumption of input-dependent noise during evidence accumulation has received strong support from previous experimental and modelling work. We show that including input-dependent noise in the evidence accumulation process results in a magnitude-sensitive optimal policy for value-based decision-making, even in the case of a linear utility function and a linear cost of time, for both single (i.e., isolated) choices and sequences of choices in which decision-makers maximise reward rate. Compared to explanations that rely on non-linear utility functions and/or non-linear cost of time, our proposed account of magnitude-sensitive optimal decision-making provides a parsimonious explanation that bridges the gap between various task assumptions and between various types of decision making.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49403485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-09-01DOI: 10.1017/s1930297500008445
A. Kühberger
In classic research on judgment and decision making under risk, risk is described by providing participants with the respective outcomes and probabilities in a summary format. Recent research has introduced a different paradigm – decisions-by-experience – where participants learn about risk by sampling from the outcomes, rather than by summary descriptions. This latter research reports a description-experience gap, indicating that some of the classic patterns of risk attitude reverse when people experience the risk. Recent research has attempted to investigate risky choice framing in the decisions-by-experience paradigm. I discuss how this research runs into problems in properly manipulating framing in decisions by experience. Drawing from framing research with animals, I argue that framing effects also exist in experience tasks. The classic Asian Disease task, however, awaits proper translation into an experience paradigm.
{"title":"Risky choice framing by experience: A methodological note","authors":"A. Kühberger","doi":"10.1017/s1930297500008445","DOIUrl":"https://doi.org/10.1017/s1930297500008445","url":null,"abstract":"In classic research on judgment and decision making under risk, risk is described by providing participants with the respective outcomes and probabilities in a summary format. Recent research has introduced a different paradigm – decisions-by-experience – where participants learn about risk by sampling from the outcomes, rather than by summary descriptions. This latter research reports a description-experience gap, indicating that some of the classic patterns of risk attitude reverse when people experience the risk. Recent research has attempted to investigate risky choice framing in the decisions-by-experience paradigm. I discuss how this research runs into problems in properly manipulating framing in decisions by experience. Drawing from framing research with animals, I argue that framing effects also exist in experience tasks. The classic Asian Disease task, however, awaits proper translation into an experience paradigm.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44942008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Survey respondents over-forecast inflation: they expect it to be higher than it turns out to be. Furthermore, people are generally overconfident in their forecasts. In two experiments, we show that providing outcome feedback that informs people of the actual level of the inflation that they have forecast reduces both over-forecasting and overconfidence in forecasts. These improvements were preserved even after feedback had been withdrawn, a finding that indicates that they were not produced because feedback had a temporary incentive effect but because it had a more permanent learning effect. However, providing forecasters with more outcome feedback did not have a greater effect. Feedback appears to provide people with information about biases in their judgments and, once they have received that information, no additional advantage is obtained by giving it to them again. Reducing over-forecasting also had no clear effect on overall error. This was because providing outcome feedback after every judgment also affected the noise or random error in forecasts, increasing it by a sufficient amount to cancel out the benefits provided by the reduction in over-forecasting.
{"title":"Outcome feedback reduces over-forecasting of inflation and overconfidence\u0000 in forecasts","authors":"Xiaoxiao Niu, N. Harvey","doi":"10.17632/ZRM9PZPRFD.1","DOIUrl":"https://doi.org/10.17632/ZRM9PZPRFD.1","url":null,"abstract":"\u0000 Survey respondents over-forecast inflation: they expect it to be higher\u0000 than it turns out to be. Furthermore, people are generally overconfident in\u0000 their forecasts. In two experiments, we show that providing outcome feedback\u0000 that informs people of the actual level of the inflation that they have\u0000 forecast reduces both over-forecasting and overconfidence in forecasts.\u0000 These improvements were preserved even after feedback had been withdrawn, a\u0000 finding that indicates that they were not produced because feedback had a\u0000 temporary incentive effect but because it had a more permanent learning\u0000 effect. However, providing forecasters with more outcome feedback did not\u0000 have a greater effect. Feedback appears to provide people with information\u0000 about biases in their judgments and, once they have received that\u0000 information, no additional advantage is obtained by giving it to them again.\u0000 Reducing over-forecasting also had no clear effect on overall error. This\u0000 was because providing outcome feedback after every judgment also affected\u0000 the noise or random error in forecasts, increasing it by a sufficient amount\u0000 to cancel out the benefits provided by the reduction in\u0000 over-forecasting.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44249734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Gretton, E. Meyers, A. C. Walker, Jonathan A. Fugelsang, Derek J. Koehler
During the COVID-19 pandemic, public health messaging, including guidance regarding protective health behavior (e.g., use of non-medical masks), changed over time. Although many revisions were a result of gains in scientific understanding, we nonetheless hypothesized that making changes in guidance salient would negatively impact evaluations of experts and health-protective intentions. In Study 1 (N = 300), we demonstrate that describing COVID-19 guidance in terms of inconsistency (versus consistency) leads people to perceive scientists and public health authorities less favorably (e.g., as less expert). Among a Canadian subsample, making guidance change salient also reduced intentions to download the COVID Alert contact tracing app. In Study 2 (N = 1399), we show that a brief forewarning intervention mitigates detrimental effects of changes in guidance. In the absence of forewarning, emphasizing inconsistency harmed judgments of public health authorities and reduced health-protective intentions, but forewarning eliminated this effect.
{"title":"A Brief Forewarning Intervention Overcomes Negative Effects of Salient Changes in COVID-19 Guidance","authors":"J. Gretton, E. Meyers, A. C. Walker, Jonathan A. Fugelsang, Derek J. Koehler","doi":"10.31234/osf.io/gbqw3","DOIUrl":"https://doi.org/10.31234/osf.io/gbqw3","url":null,"abstract":"During the COVID-19 pandemic, public health messaging, including guidance regarding protective health behavior (e.g., use of non-medical masks), changed over time. Although many revisions were a result of gains in scientific understanding, we nonetheless hypothesized that making changes in guidance salient would negatively impact evaluations of experts and health-protective intentions. In Study 1 (N = 300), we demonstrate that describing COVID-19 guidance in terms of inconsistency (versus consistency) leads people to perceive scientists and public health authorities less favorably (e.g., as less expert). Among a Canadian subsample, making guidance change salient also reduced intentions to download the COVID Alert contact tracing app. In Study 2 (N = 1399), we show that a brief forewarning intervention mitigates detrimental effects of changes in guidance. In the absence of forewarning, emphasizing inconsistency harmed judgments of public health authorities and reduced health-protective intentions, but forewarning eliminated this effect.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44889607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1017/s1930297500008044
Barış Sevi, Natalie J. Shook
Disgust is a cross-culturally recognized emotion that is characterized by avoidant or cautious tendencies. Accordingly, greater sensitivity to disgust may be related to less willingness to take risks. Relatively little research has examined the association between disgust sensitivity and risk-taking propensity. Further, no research to date has taken a domain specific approach to understanding the association between these constructs. Across two studies (N1=98, N2=390) and a mini-meta analysis utilizing two additional datasets (total N=1981), we assessed the extent to which domain specific disgust sensitivity (i.e., Pathogen, Sexual, and Moral) were related to domain specific risk-taking propensity (i.e., Social, Recreational, Health/Safety, Ethical, and Financial). We conducted two cross-sectional studies, with a community and a student sample. Participants completed surveys that included measures of disgust sensitivity and risk-taking propensity. Bivariate correlations across the two studies indicated that greater disgust sensitivity was related to lower risk-taking propensity across almost all domains. However, when controlling for covariance among the disgust sensitivity domains, regression analyses suggested variability in the association between disgust sensitivity and risk-taking propensity depending on domains. Based on mini meta-analysis, sexual disgust sensitivity had the strongest relationships with social risk-taking propensity and health/safety risk-taking propensity, and moral disgust sensitivity had the strongest relationship with ethical risk-taking propensity. These findings suggest the presence of domain specific relations between disgust sensitivity and risk-taking propensity. The domain specific focus may help in utilizing disgust as a factor to decrease certain risky behaviors (e.g., moral disgust for decreasing plagiarism).
{"title":"The relation between disgust sensitivity and risk-taking propensity: A domain specific approach","authors":"Barış Sevi, Natalie J. Shook","doi":"10.1017/s1930297500008044","DOIUrl":"https://doi.org/10.1017/s1930297500008044","url":null,"abstract":"Disgust is a cross-culturally recognized emotion that is characterized by avoidant or cautious tendencies. Accordingly, greater sensitivity to disgust may be related to less willingness to take risks. Relatively little research has examined the association between disgust sensitivity and risk-taking propensity. Further, no research to date has taken a domain specific approach to understanding the association between these constructs. Across two studies (N1=98, N2=390) and a mini-meta analysis utilizing two additional datasets (total N=1981), we assessed the extent to which domain specific disgust sensitivity (i.e., Pathogen, Sexual, and Moral) were related to domain specific risk-taking propensity (i.e., Social, Recreational, Health/Safety, Ethical, and Financial). We conducted two cross-sectional studies, with a community and a student sample. Participants completed surveys that included measures of disgust sensitivity and risk-taking propensity. Bivariate correlations across the two studies indicated that greater disgust sensitivity was related to lower risk-taking propensity across almost all domains. However, when controlling for covariance among the disgust sensitivity domains, regression analyses suggested variability in the association between disgust sensitivity and risk-taking propensity depending on domains. Based on mini meta-analysis, sexual disgust sensitivity had the strongest relationships with social risk-taking propensity and health/safety risk-taking propensity, and moral disgust sensitivity had the strongest relationship with ethical risk-taking propensity. These findings suggest the presence of domain specific relations between disgust sensitivity and risk-taking propensity. The domain specific focus may help in utilizing disgust as a factor to decrease certain risky behaviors (e.g., moral disgust for decreasing plagiarism).","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49467659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-01DOI: 10.1017/s1930297500008093
David A. Comerford
A standard way to elicit expectations asks for the percentage chance an event will occur. Previous research demonstrates noise in reported percentages. The current research models a bias; a five percentage point change in reported probabilities implies a larger change in beliefs at certain points in the probability distribution. One contribution of my model is that it can parse bias in beliefs from biases in reports. I reconsider age and gender differences in Subjective Survival Probabilities (SSPs). These are generally interpreted as differences in survival beliefs, e.g., that males are more optimistic than females and older respondents are more optimistic than younger respondents. These demographic differences (in the English Longitudinal Study of Ageing) can be entirely explained by reporting bias. Older respondents are no more optimistic than younger respondents and males are no more optimistic than females. Similarly, in forecasting, information is obscured by taking reported percentages at face value. Accounting for reporting bias thus better exploits the private information contained in reports. Relative to a face-value specification, a specification that does this delivers improved forecasts of mortality events, raising the pseudo R-squared from less than 3 percent to over 6 percent.
{"title":"Apparent age and gender differences in survival optimism: To what extent are they a bias in the translation of beliefs onto a percentage scale?","authors":"David A. Comerford","doi":"10.1017/s1930297500008093","DOIUrl":"https://doi.org/10.1017/s1930297500008093","url":null,"abstract":"A standard way to elicit expectations asks for the percentage chance an event will occur. Previous research demonstrates noise in reported percentages. The current research models a bias; a five percentage point change in reported probabilities implies a larger change in beliefs at certain points in the probability distribution. One contribution of my model is that it can parse bias in beliefs from biases in reports. I reconsider age and gender differences in Subjective Survival Probabilities (SSPs). These are generally interpreted as differences in survival beliefs, e.g., that males are more optimistic than females and older respondents are more optimistic than younger respondents. These demographic differences (in the English Longitudinal Study of Ageing) can be entirely explained by reporting bias. Older respondents are no more optimistic than younger respondents and males are no more optimistic than females. Similarly, in forecasting, information is obscured by taking reported percentages at face value. Accounting for reporting bias thus better exploits the private information contained in reports. Relative to a face-value specification, a specification that does this delivers improved forecasts of mortality events, raising the pseudo R-squared from less than 3 percent to over 6 percent.","PeriodicalId":48045,"journal":{"name":"Judgment and Decision Making","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43949874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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