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Adult Age Differences in Hindsight Bias: The Role of Recall Ability

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Julia Groß at University of Mannheim
Julia Groß
Ute J Bayen at Heinrich Heine University Düsseldorf
Ute J Bayen
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Abstract

Hindsight bias, that is, the overestimation of one's prior knowledge of outcomes after the actual outcomes are known, is stronger in older than young adults (e.g., Bayen, Erdfelder, Bearden, & Lozito, 2006). The authors investigated whether age differences in the recall of original judgments account for this difference. Multinomial model-based analyses of data from a hindsight memory task revealed that biased reconstruction of original judgments was equally likely in both age groups when recall of original judgments was lowered in young adults via a manipulation of retention interval. These results support a recall-based explanation of age differences in hindsight bias. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
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BRIEF REPORT
Adult Age Differences in Hindsight Bias: The Role of Recall Ability
Julia Groß and Ute J. Bayen
Heinrich-Heine-Universität Düsseldorf
Hindsight bias, that is, the overestimation of one’s prior knowledge of outcomes after the actual outcomes
are known, is stronger in older than young adults (e.g., Bayen, Erdfelder, Bearden, & Lozito, 2006). The
authors investigated whether age differences in the recall of original judgments account for this
difference. Multinomial model-based analyses of data from a hindsight memory task revealed that biased
reconstruction of original judgments was equally likely in both age groups when recall of original
judgments was lowered in young adults via a manipulation of retention interval. These results support a
recall-based explanation of age differences in hindsight bias.
Keywords: aging, hindsight bias, recall, multinomial model
Given the growing proportion of older adults in the world’s
population (United Nations, 2013), understanding effects of aging
on memory and judgment is increasingly relevant. A hard-to-avoid
and ubiquitous bias in memory and judgment is hindsight bias:
After learning about facts or outcomes of events, people tend to
overestimate what they knew about these facts or events before-
hand. Hindsight bias may therefore narrow the search for potential
explanations for an event. This may, for instance, lead to prema-
ture assignment of guilt, in legal decision making (e.g., Berlin,
2000;Harley, 2007).
Typically, in studies of hindsight bias, participants are asked to
provide original judgments (OJs) to difficult questions (e.g., “How
many African nations are there?”) and must later recall the OJs
(recall of original judgment, ROJ). For experimental items, as
opposed to control items, the correct judgment (CJ) is provided
before recall. In this case, participants typically recall their OJs
with lower probability (recollection bias) and/or, when the OJ is
not recalled, OJ reconstruction is biased toward the CJ (recon-
struction bias). Both biases constitute hindsight bias.
Hindsight bias is well researched and robust (cf. Blank, Musch,
& Pohl, 2007). However, only a handful of studies have examined
its occurrence in old age (Bayen et al., 2006;Bernstein, Erdfelder,
Meltzoff, Peria, & Loftus, 2011;Coolin, Bernstein, Thornton, &
Thornton, 2014;Groß & Bayen, 2015). These indicate larger
hindsight bias in older compared to young adults; yet the sources
of this age difference still need to be clarified.
One possible explanation is that older adults’ deficits in inhib-
itory control (e.g., Hasher & Zacks, 1988;Lustig, Hasher, &
Zacks, 2007) may increase the biasing effect of the CJ on OJ
recollection and/or on OJ reconstruction (cf. Bayen, Pohl, Erd-
felder, & Auer, 2007). Both Coolin, Erdfelder, Bernstein, Thorn-
ton, & Thornton (2014) and Groß and Bayen (2015) found evi-
dence in support of this explanation; however, age differences in
inhibitory function could not fully account for age differences in
hindsight bias.
Another possible explanation for age differences in hindsight
bias are age differences in recall ability. It is well established that
the average ability to recall information from episodic memory is
lower in older than in young adults (e.g., Verhaeghen, Marcoen, &
Goossens, 1993). Accordingly, in hindsight studies, young adults
recalled more of their OJs than older adults (Bayen et al., 2006;
Bernstein et al., 2011;Groß & Bayen, 2015). Since perfectly
recalling one’s OJ precludes the occurrence of hindsight bias (cf.
Pohl, 2007), lower OJ recall increases the number of items that
remain for hindsight bias to occur, thereby increasing its proba-
bility.
Bayen et al. (2006) used Erdfelder and Buchner’s (1998) multi-
nomial processing tree (MPT) model to estimate separate contri-
butions of overall recollection, recollection bias, and reconstruc-
tion bias to age differences in hindsight bias. They found that both
lower overall recollection and larger probability of reconstruction
bias underlay age differences in hindsight bias, whereas age dif-
ferences in recollection bias contributed only little. In both Bern-
stein et al.’s (2011) and Coolin, Erdfelder, et al.’s (2014) studies,
older adults showed lower overall recollection and descriptively
higher probability of reconstruction bias; however, the latter dif-
ference did not reach statistical significance. Coolin, Erdfelder, et
al. (2014) found a significant (yet small) recollection bias in older,
This article was published Online First April 20, 2015.
Julia Groß and Ute J. Bayen, Institute for Experimental Psychology,
Heinrich-Heine-Universität Düsseldorf.
This work was in part supported by Grant BA 3539/4-1 from the
Deutsche Forschungsgemeinschaft and the Research Initiative “Age(ing):
Cultural Concepts and Practical Realisations” of the Heinrich-Heine-
Universität Düsseldorf. We thank Siegmund Switala for technical assis-
tance and Marie Bernadette Bette, Anne Hagen, Diana Kuhl, and Claudia
Roth for help with data collection. We thank Morten Moshagen for his help
with modeling interactions with the MPT model.
Correspondence concerning this article should be addressed to Julia Groß,
Heinrich-Heine-Universität Düsseldorf, Institute for Experimental Psychol-
ogy, Building 23.02., Universitätsstr. 1, D-40225 Germany. E-mail: gross@
hhu.de
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Psychology and Aging © 2015 American Psychological Association
2015, Vol. 30, No. 2, 253–258 0882-7974/15/$12.00 http://dx.doi.org/10.1037/pag0000017
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... This well-established phenomenon is known as hindsight bias (e.g., Christensen-Szalanski & Willham, 1991;Groß & Pachur, 2019;Hawkins & Hastie, 1990), and was initially introduced by Fischhoff (1975). It has been shown for estimates of realworld quantities (e.g., lengths of rivers, heights of towers; see Bayen et al., 2006;Bernstein et al., 2011;Erdfelder & Buchner, 1998;Groß & Bayen, 2015;Pohl & Hell, 1996), but also for two-alternative-choice tasks, judgments of event outcomes (e.g., historical and medical), and other tasks and materials (see Pohl, 2007, for an overview). Traditionally, hindsight bias has been viewed as a manifestation of the limitations of human information processing and as an impediment to accurate judgment (e.g., Arkes, 1981). ...
... Hindsight bias is a multifaceted phenomenon (manifested in inevitability and foreseeability impressions as well as distorted memory; for overviews, see Blank et al., 2007Blank et al., , 2008Roese & Vohs, 2012). In tasks that require participants to estimate real-world quantities such as historical dates, heights of buildings, lengths of rivers, or the population of cities (e.g., Bayen et al., 2006;Bernstein et al., 2011;Erdfelder & Buchner, 1998;Groß & Bayen, 2015), hindsight bias has often been investigated in the so-called memory paradigm (Pohl, 2007), where it manifests as distorted memory. In this paradigm, participants are first presented with questions whose quantitative answers they are unlikely to know exactly, but can estimate (e.g., "How long is the Amazon river [in km]?"). ...
... To test this possibility and to better understand the nature and consequences of knowledge updating in real-world quantitative estimation-one of the most frequently studied contexts of hindsight bias (e.g., Bayen et al., 2006;Bernstein et al., 2011;Coolin et al., 2016;Erdfelder & Buchner, 1998;Groß & Bayen, 2015;Pohl et al., 2018Pohl et al., , 2010Pohl & Hell, 1996)-we connect the investigation of hindsight bias with research on seeding effects (Brown & Siegler, 1993). 3 Our integrative framework allows for a more differentiated conceptualization of the processes of knowledge updating and its downstream consequences. ...
Knowledge Updating in Real-World Estimation: Connecting Hindsight Bias and Seeding Effects
Article
Full-text available
  • Aug 2023
When people estimate the quantities of objects (e.g., country populations), are then presented with the objects’ actual quantities, and subsequently asked to remember their initial estimates, responses are often distorted towards the actual quantities. This hindsight bias—traditionally considered to reflect a cognitive error—has more recently been proposed to result from adaptive knowledge updating. But how to conceptualize such knowledge-updating processes and their potentially beneficial consequences? Here, we provide a framework that conceptualizes knowledge updating in the context of hindsight bias in real-world estimation by connecting it with research on seeding effects—improvements in people’s estimation accuracy after exposure to numerical facts. This integrative perspective highlights a previously neglected facet of knowledge updating, namely, recalibration of metric domain knowledge, which can be expected to lead to transfer learning and thus improve estimation for objects from a domain more generally. We develop an experimental paradigm to investigate the association of hindsight bias with improved estimation accuracy. In Experiment 1, we demonstrate that the classical approach to induce hindsight bias indeed produces transfer learning. In Experiment 2, we provide evidence for the novel prediction that hindsight bias can be triggered via transfer learning; this establishes a direct link from knowledge updating to hindsight bias. Our work integrates two prominent but previously unconnected research programs on the effects of knowledge updating in real-world estimation and supports the notion that hindsight bias is driven by adaptive learning processes.
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... Hindsight bias occurs when recalled judgments are shifted toward presented correct answers. We will refer to the bias measured in the memory paradigm as the memory component of hindsight bias. 1 Research has repeatedly demonstrated that in such numerical-estimation tasks, older adults are more prone to the described memory distortion (e.g., Bayen et al., 2006;Bernstein et al., 2011;Coolin et al., 2015;Groß & Bayen, 2015). In a recent meta-analysis, Groß and Pachur (2019) found that older adults show worse memory for their own original judgments than young adults do, and-as a consequence-must reconstruct their judgments more often. ...
... In this reconstruction, older adults are more prone to be biased by the correct answer than younger adults are. This could be due to older adults' worse memory for their own original judgments (e.g., Groß & Bayen, 2015), and/or to their larger difficulties in inhibiting the correct answer in the reconstruction of original judgments (e.g., Coolin et al., 2015). ...
... The memory component of hindsight bias is mainly governed by variables that affect memory in general, such as the depth of encoding, the length of the retention interval, and the amount of interference (Erdfelder et al., 2007;Groß & Bayen, 2015;Hell et al., 1988). It has been suggested that this memory component of hindsight bias is a by-product of an adaptive knowledge-updating process (Hoffrage et al., 2000). ...
Older and Younger Adults’ Hindsight Bias after Positive and Negative Outcomes
Article
Full-text available
  • May 2021
  • MEM COGNITION
After learning about facts or outcomes of events, people overestimate in hindsight what they knew in foresight. Prior research has shown that this hindsight bias is more pronounced in older than in younger adults. However, this robust finding is based primarily on a specific paradigm that requires generating and recalling numerical judgments to general knowledge questions that deal with emotionally neutral content. As older and younger adults tend to process positive and negative information differently, they might also show differences in hindsight bias after positive and negative outcomes. Furthermore, hindsight bias can manifest itself as a bias in memory for prior given judgments, but also as retrospective impressions of inevitability and foreseeability. Currently, there is no research on age differences in all three manifestations of hindsight bias. In this study, younger (N = 46, 18 – 30 years) and older adults (N = 45, 64 – 90 years) listened to everyday-life scenarios that ended positively or negatively, recalled the expectation they previously held about the outcome (to measure the memory component of hindsight bias), and rated each outcome’s foreseeability and inevitability. Compared to younger adults, older adults recalled their prior expectations as closer to the actual outcomes (i.e., they showed a larger memory component of hindsight bias), and this age difference was more pronounced for negative than for positive outcomes. Inevitability and foreseeability impressions, however, did not differ between the age groups. Thus, there are age differences in hindsight bias after positive and negative outcomes, but only with regard to memory for prior judgments.
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... 2 In a series of experiments, Erdfelder and Buchner (1998) demonstrated parameter validity by means of selective-influence manipulations. Like the source-monitoring model, the hindsightbias model has been applied to study young adults (e.g., Dehn & Erdfelder, 1998;Erdfelder, Brandt, & Bröder, 2007), older adults and children (Coolin et al., 2015;Groß & Bayen, 2015;Groß & Pachur, 2019;Pohl, Bayen, Arnold, Auer, & Martin, 2018;Pohl et al., 2010), as well as clinical populations (Groß & Bayen, 2017b;Ruoß & Becker, 2001). In Sections 4 and 5, we describe the parameter recovery simulations for the two models. ...
... r E = .36; e.g., Bayen, Erdfelder, Bearden, & Lozito, 2006;Groß & Bayen, 2015, 2017b. For these simulations, we used variances and covariances from a data set by Groß and Bayen (2017a); see Appendix A for a list of all 13 generating parameter values, variances, and covariances. ...
... With a typical level of heterogeneity and a typical number of participants (∼50) and items (∼50), the PP-B approach produces the most accurate estimates-independent of whether core parameter values are high or low. The latter aspect is particularly important if the goal is to examine group differences in parameters (e.g., age-group differences) or differences between experimental conditions (Bayen et al., 2006;Erdfelder & Buchner, 1998;Groß & Bayen, 2015, 2017bPohl et al., 2018Pohl et al., , 2010. ...
Parameter estimation approaches for multinomial processing tree models: A comparison for models of memory and judgment
Article
  • Sep 2020
  • J MATH PSYCHOL
Multinomial processing tree (MPT) models are commonly used in cognitive psychology to disentangle and measure the psychological processes underlying behavior. Various estimation approaches can be used to estimate the parameters of MPT models for a group of participants. These approaches are implemented in various programs (e.g., MPTinR, TreeBUGS) and differ with regard to how data are pooled across participants (no pooling, complete pooling, or partial pooling). The partial-pooling approaches differ with regard to whether correlations between parameters are explicitly modeled (latent-trait MPT) or not (beta-MPT). However, it is currently unclear whether the theoretical advantages of the partial-pooling approaches actually yield the best results in standard practice (i.e., with typical parameter values and amounts of data). We conducted parameter recovery analyses comparing the accuracy and precision of four estimation approaches for two MPT models: the source-monitoring model and the hindsight-bias model. For essential (“core”) parameters of the two models, the partial-pooling approaches yielded the best results overall. Importantly, there were also model-specific differences between the approaches. For the source-monitoring model, the latent-trait approach achieved the best results; for the more complex hindsight-bias model, the latent-trait approach appeared to be overparameterized for typical amounts of data; here, the beta-MPT approach was better. We derive recommendations for applications of the two MPT models.
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... Presentation of the correct answer may therefore have a stronger impact on older adults' recall of their original judgments than on young adults' (leading to a larger recollection bias), as well as on their reconstruction of their original judgment (leading to a larger reconstruction bias). Some of the studies on age differences in hindsight bias have indeed established a link between age differences in reconstruction bias and recollection bias, on the one hand, and agerelated declines in episodic memory (Coolin, Erdfelder, Bernstein, Thornton, & Thornton, 2015;Groß & Bayen, 2015a) and inhibitory control (e.g., Coolin et al., 2015;Groß & Bayen, 2015b), on the other. ...
... On the one hand, some studies have found age differences in one or both of the underlying processes: specifically, a larger reconstruction bias in older than in young adults ( Bayen et al., 2006;Groß, 2013, Exp. 2;Groß & Bayen, 2015a, 2015b and/or a contribution of recollection bias in older but not in young adults ( Coolin et al., 2015;Groß, 2013, Exp. 2;Groß & Bayen, 2015b). ...
... As both conditions implemented the standard paradigm, we collapsed the data of both conditions for our analyses. One study (Groß, 2013, Exp. 2) included a third item type in addition to control and experimental items ("choice items"); another study (Groß & Bayen, 2015a) included a group of young adults with a 46-hr retention interval. We did not consider these conditions in our analyses. ...
Age Differences in Hindsight Bias: A Meta-Analysis
Article
Full-text available
  • Jan 2019
After people have learned a fact or the outcome of an event, they often overestimate their ability to have known the correct answer beforehand. This hindsight bias has two sources: an impairment in direct recall of the original (i.e., uninformed) judgment after presentation of the correct answer (recollection bias) and a reconstruction of the original judgment that is biased towards the correct answer (reconstruction bias). Research on how cognitive aging affects the sources of hindsight bias has produced mixed results. To synthesize the available findings, we conducted a meta-analysis of nine studies (N = 366 young, N = 368 older adults). We isolated the probabilities of recollection, recollection bias, and reconstruction bias with a Bayesian, three-level hierarchical implementation of the multinomial processing tree model of hindsight bias (Erdfelder & Buchner, 1998). Additionally, we quantified the magnitude of bias in the reconstructed judgment. Overall, older adults were less likely to recollect their original judgment than young adults, and thus had to reconstruct it more frequently. Importantly, outcome knowledge impaired recollection of the original judgment (i.e., recollection bias) to a similar extent in both age groups, but outcome knowledge was more likely to distort reconstruction of the original judgment (i.e., reconstruction bias) in older adults. In addition, the magnitude of bias in the reconstructed judgments was slightly larger in older than in young adults. Our results provide the basis for a targeted investigation of the mechanisms driving these age differences.
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... Reconstruction bias occurs when, upon failure to recall one's original judgment, they use outcome information to help them reconstruct their judgment. This HB13 model has been used to measure recollection and reconstruction processes underlying verbal hindsight bias in different age groups (see Bayen et al., 2006;Bernstein et al., 2011;Coolin et al., 2015Coolin et al., , 2016Dehn & Erdfelder, 1998;Erdfelder et al., 2007;Groß & Bayen, 2015;Groß & Pachur, 2019;Pohl et al., 2018). ...
Hindsight Bias for Emotional Faces
Article
Full-text available
  • Feb 2022
People who learn the outcome to a situation or problem tend to overestimate what was known in the past-this is hindsight bias. Whereas previous research has revealed robust hindsight bias in the visual domain, little is known about how outcome information affects our memory of others' emotional expressions. The goal of the current work was to test whether participants exhibited hindsight bias for emotional faces and whether this varied as a function of emotion. Across five experiments, participants saw images of faces displaying different emotions. In the foresight phase, participants watched several emotional faces gradually clarify from blurry to clear. Once participants believed they knew what emotion the face was exhibiting, they identified the emotion from several options (e.g., angry, disgusted, happy, scared, surprised). In the hindsight phase, participants saw clear versions of each face before stopping the clarification at the point at which they previously identified the emotional expression. On average, participants exhibited hindsight bias for all emotions except happy faces (i.e., they indicated that they identified the emotional expressions at a blurrier point in hindsight than they had in foresight). A multinomial processing tree model of our data revealed that this was not due to participants' better recollection of foresight judgments for happy faces compared to the other emotions. Additionally, participants showed a smaller reconstruction bias for happy faces than the other emotions. We discuss the social implications of these findings as well as the potential for this paradigm to be used across cultures and ages. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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... Given that the model fits the data (which can be statistically test ed), the estimated probabilities can be statistically compared to each other or to fixed val ues (such as zero) by running appropriate tests. In this way, many hindsight-bias studies have provided further insights into the underlying cognitive processes (see Bayen, Erd felder, Bearden, & Lozito, 2006;Bernstein, Erdfelder, Meltzoff, Peria, & Loftus, 2011;Groß & Bayen, 2015A;Groß & Pachur, 2019;Pohl, Bayen, Arnold, Auer, & Martin, 2018;Pohl, Bayen, & Martin, 2010). ...
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Evaluating the Robustness of Parameter Estimates in Cognitive Models: A Meta-Analytic Review of Multinomial Processing Tree Models Across the Multiverse of Estimation Methods
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  • Jun 2024
Researchers have become increasingly aware that data-analysis decisions affect results. Here, we examine this issue systematically for multinomial processing tree (MPT) models, a popular class of cognitive models for categorical data. Specifically, we examine the robustness of MPT model parameter estimates that arise from two important decisions: the level of data aggregation (complete-pooling, no-pooling, or partial-pooling) and the statistical framework (frequentist or Bayesian). These decisions span a multiverse of estimation methods. We synthesized the data from 13,956 participants (164 published data sets) with a meta-analytic strategy and analyzed the magnitude of divergence between estimation methods for the parameters of nine popular MPT models in psychology (e.g., process-dissociation, source monitoring). We further examined moderators as potential sources of divergence. We found that the absolute divergence between estimation methods was small on average (<.04; with MPT parameters ranging between 0 and 1); in some cases, however, divergence amounted to nearly the maximum possible range (.97). Divergence was partly explained by few moderators (e.g., the specific MPT model parameter, uncertainty in parameter estimation), but not by other plausible candidate moderators (e.g., parameter trade-offs, parameter correlations) or their interactions. Partial-pooling methods showed the smallest divergence within and across levels of pooling and thus seem to be an appropriate default method. Using MPT models as an example, we show how transparency and robustness can be increased in the field of cognitive modeling.
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Evaluating the Robustness of Parameter Estimates in Cognitive Models: A Meta-Analytic Review of Multinomial Processing Tree Models Across the Multiverse of Estimation Methods
Preprint
  • Mar 2024
Researchers have become increasingly aware that data-analysis decisions affect results. Here, we examine this issue systematically for multinomial processing tree (MPT) models, a popular class of cognitive models for categorical data. Specifically, we examine the robustness of MPT model parameter estimates that arise from two important decisions: the level of data aggregation (complete pooling, no pooling, or partial pooling) and the statistical framework (frequentist or Bayesian). These decisions span a multiverse of estimation methods. We synthesized the data from 13,956 participants (164 published data sets) with a meta-analytic strategy and analyzed the magnitude of divergence between estimation methods for the parameters of nine popular multinomial processing tree (MPT) models in psychology (e.g., process dissociation, source monitoring). We further examined moderators as potential sources of divergence. We found that the absolute divergence between estimation methods was small on average (< .04; with MPT parameters ranging between 0 and 1); in some cases, however, divergence amounted to nearly the maximum possible range (.97). Divergence was partly explained by few moderators (e.g., the specific MPT model parameter, uncertainty in parameter estimation), but not by other plausible candidate moderators (e.g., parameter trade-offs, parameter correlations) or their interactions. Partial-pooling methods showed the smallest divergence within and across levels of pooling and thus seem to be an appropriate default method. Using MPT models as an example, we show how transparency and robustness can be increased in the field of cognitive modeling.
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Retrospective and prospective hindsight bias: Replications and extensions of Fischhoff (1975) and Slovic and Fischhoff (1977)
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  • J EXP SOC PSYCHOL
Hindsight bias refers to the tendency to perceive an event outcome as more probable after being informed of that outcome. We conducted very close replications of two classic experiments of hindsight bias and a conceptual replication testing hindsight bias regarding the perceived replicability of hindsight bias. In Study 1 (N = 890), we replicated Experiment 2 in Fischhoff (1975), and found support for hindsight bias in retrospective judgments (dmean = 0.60). In Study 2 (N = 608), we replicated Experiment 1 in Slovic and Fischhoff (1977), and found support for hindsight bias in prospective judgments (dmean = 0.40). In Study 3 (N = 520) we found strong support for hindsight bias regarding perceived likelihood of our replication of hindsight bias (d = 0.43–1.03). We also included extensions examining surprise, confidence, and task difficulty, yet found mixed evidence with weak to no effects. We concluded support for hindsight bias in both retrospective and prospective judgments, and in evaluations of replication findings, and therefore call for establishing measures to address hindsight bias in valuations of replication work and interpreting research outcomes. All materials, data, and code, were shared on: https://osf.io/nrwpv/.
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Explaining individual differences in cognitive processes underlying hindsight bias
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Full-text available
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After learning an event's outcome, people's recollection of their former prediction of that event typically shifts toward the actual outcome. Erdfelder and Buchner (Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 387-414, 1998) developed a multinomial processing tree (MPT) model to identify the underlying processes contributing to this hindsight bias (HB) phenomenon. More recent applications of this model have revealed that, in comparison to younger adults, older adults are more susceptible to two underlying HB processes: recollection bias and reconstruction bias. However, the impact of cognitive functioning on these processes remains unclear. In this article, we extend the MPT model for HB by incorporating individual variation in cognitive functioning into the estimation of the model's core parameters in older and younger adults. In older adults, our findings revealed that (1) better episodic memory was associated with higher recollection ability in the absence of outcome knowledge, (2) better episodic memory and inhibitory control and higher working memory capacity were associated with higher recollection ability in the presence of outcome knowledge, and (3) better inhibitory control was associated with less reconstruction bias. Although the pattern of effects was similar in younger adults, the cognitive covariates did not significantly predict the underlying HB processes in this age group. In sum, we present a novel approach to modeling individual variability in MPT models. We applied this approach to the HB paradigm to identify the cognitive mechanisms contributing to the underlying HB processes. Our results show that working memory capacity and inhibitory control, respectively, drive individual differences in recollection bias and reconstruction bias, particularly in older adults.
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Age Differences in Hindsight Bias: The Role of Episodic Memory and Inhibition
Article
Full-text available
  • May 2014
  • EXP AGING RES
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Full-text available
  • Mar 2014
  • AGING NEUROPSYCHOL C
Hindsight bias is the overestimation of one's earlier knowledge about facts or one's prediction of events after learning about the actual facts or events. The authors examined age differences in hindsight bias and their relation to visual access control. Younger and older adults recalled their numerical answers to general-knowledge questions. For half of the items, the correct judgment (CJ) was shown during recall. To indicate whether the distracting CJ was visually accessed, the authors measured fixations to the CJ. An instructional manipulation to ignore the CJ affected fixations and hindsight bias. Older adults showed stronger hindsight bias and more fixations to the task-irrelevant CJ, indicating an age-related deficit in access control. However, evidence for the effect of CJ access on hindsight bias was weak and more pronounced in younger than in older adults.
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Publisher Summary This chapter discusses the theoretical and empirical literature that addresses aging and discourse comprehension. A series of five studies guided by a particular working memory viewpoint regarding the formation of inferences during discourse processing is described in the chapter. Compensatory strategies may be used with different degrees of likelihood across the life span largely as a function of efficiency with which inhibitory mechanisms function because these largely determine the facility with which memory can be searched. The consequences for discourse comprehension in particular may be profound because the establishment of a coherent representation of a message hinges on the timely retrieval of information necessary to establish coreference among certain critical ideas. Discourse comprehension is an ideal domain for assessing limited capacity frameworks because most models of discourse processing assume that multiple components, demanding substantially different levels of cognitive resources, are involved. For example, access to a lexical representation from either a visual array or an auditory message is virtually capacity free.
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Memory Aging
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  • Dec 2006
This chapter provides an overview of the current status of description and explanation of age trends for various forms of memory. Strong evidence suggests that age-related dissociations in memory functions and findings are consistent with the recollection-familiarity distinction and with multiple systems models of memory. This general pattern implicates the importance of examining age-memory relationships in terms of the neural substrates most affected by aging, especially regions of the prefrontal cortex and the medial temporal lobe, and their mappings to regions engaged by the task domain and response requirements. At the macro-level, a large portion of the age variance observed in memory performance is attributable to task-general effects of slowing, which add overhead to any speeded measures of responding. At a more micro-level, questions arise regarding the aging of specific cognitive processes and specific neurocognitive mechanisms that reliably account for behavioral data on memory aging.
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Hindsight Bias In Legal Decision Making
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  • Feb 2007
  • SOC COGNITION
jurors in the U.S. legal system face a difficult challenge; they must ignore negative outcomes, and judge the defendant's pre-outcome actions in a fairway. This method of rejudging the pastwhile trying to ignore certain information, makes jurors vulnerable to hindsight bias. In this article I review a growing body of research that demonstrates the detrimental effects of hindsight bias on legal decision making. Topics examined include: effects of hindsight bias on judgments of legal liability and medical malpractice litigation, the relationship between the severity of the outcome and the size of the hindsight bias effect, the role of visual hindsight bias in the courtroom, and hindsight bias in experts. I end with a review of studies that have attempted to reduce or eliminate hindsight bias in the courtroom.
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Hindsight Bias: On Being Wise After the Event
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  • Feb 2007
  • SOC COGNITION
Since Baruch Fischhoff's (1975) groundbreaking paper opened up a whole new research field, more than 150 journal articles and book chapters, two meta-analyses (Christensen-Szalanski & Willham, 1991; Guilbault, Bryant, Brockway & Posavac, 2004), and one special issue (Memory, 2003, edited by Ulrich Hoffrage & Rodiger Pohl) have addressed hindsight phenomena. The current editorial aims to provide a rough roadmap to the hindsight bias research landscape. It highlights some important Iandmarks and developments of the last 30 years and puts the 13 articles of the present special issue into a historical and systematic perspective.
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Hindsight Bias Across the Life Span
Article
  • Feb 2007
  • SOC COGNITION
The authors review the current state of developmental research on hindsight bias. In research on cognitive development in children as well as in cognitive-aging research, studies on hindsight bias are rare. The few existing studies indicate that children and older adults show stronger hindsight bias than young adults. The authors show commonalities and differences in hindsight bias studies in the child development and aging literatures, and suggest venues for future research toward a life span perspective on the development of hindsight bias. Special emphasis is given to the potential of theories developed for other retroactive-interference paradigms to help explain age differences in hindsight bias. Methodological challenges in investigating the development of hindsight bias are also discussed.
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