Dual-processes in learning and judgment: Evidence from the multiple cue probability learning paradigm

Rolison, Jonathan J.; Evans, Jonathan St. B. T.; Dennis, Ian; Walsh, Clare R.

doi:10.1016/j.obhdp.2012.03.003

Cited by 15 publications

(29 citation statements)

References 35 publications

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“…The most prominent model concerning the interplay between these systems is the “Default Interventionist” model, which suggests that Type 2 processes can intervene and override intuitive Type 1 responses when feelings as to the correctness of the intuitive answer are troublesome (Thompson et al, 2013 )—see also alternative models such as those of Handley and Trippas ( 2015 ) and Pennycook et al ( 2015 ). Further, the engagement of Type 2 explicit processes, which determine information use, depends on task characteristics (Rolison et al, 2011 , 2012 ). We speculate that high emotional arousal associated with the CCT Hot version decreases the chance of Type 2 process usage compared to the CCT Cold version.…”

Section: Introductionmentioning

confidence: 99%

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

Markiewicz

Kubińska

2015

Front. Psychol.

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Objective: This paper aims to provide insight into information processing differences between hot and cold risk taking decision tasks within a single domain. Decision theory defines risky situations using at least three parameters: outcome one (often a gain) with its probability and outcome two (often a loss) with a complementary probability. Although a rational agent should consider all of the parameters, s/he could potentially narrow their focus to only some of them, particularly when explicit Type 2 processes do not have the resources to override implicit Type 1 processes. Here we investigate differences in risky situation parameters' influence on hot and cold decisions. Although previous studies show lower information use in hot than in cold processes, they do not provide decision weight changes and therefore do not explain whether this difference results from worse concentration on each parameter of a risky situation (probability, gain amount, and loss amount) or from ignoring some parameters.Methods: Two studies were conducted, with participants performing the Columbia Card Task (CCT) in either its Cold or Hot version. In the first study, participants also performed the Cognitive Reflection Test (CRT) to monitor their ability to override Type 1 processing cues (implicit processes) with Type 2 explicit processes. Because hypothesis testing required comparison of the relative importance of risky situation decision weights (gain, loss, probability), we developed a novel way of measuring information use in the CCT by employing a conjoint analysis methodology.Results: Across the two studies, results indicated that in the CCT Cold condition decision makers concentrate on each information type (gain, loss, probability), but in the CCT Hot condition they concentrate mostly on a single parameter: probability of gain/loss. We also show that an individual's CRT score correlates with information use propensity in cold but not hot tasks. Thus, the affective dimension of hot tasks inhibits correct information processing, probably because it is difficult to engage Type 2 processes in such circumstances. Individuals' Type 2 processing abilities (measured by the CRT) assist greater use of information in cold tasks but do not help in hot tasks.

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Section: Introductionmentioning

confidence: 99%

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

Markiewicz

Kubińska

2015

Front. Psychol.

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“…16 Furthermore, in studies of judgment analysis, individuals have a tendency to use all the information provided to them, even when some of it is irrelevant. 17,18 Our study has some limitations. We presented psychiatrists with hypothetical patient outcomes, rather than using real patients, in order to ensure an adequate range of patient outcomes.…”

Section: Discussionmentioning

confidence: 93%

How Do Psychiatrists Apply the Minimum Clinically Important Difference to Assess Patient Responses to Treatment?

McMichael

Rolison

Boeri

et al. 2016

MDM Policy & Practice

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Symptom report scales are used in clinical practice to monitor patient outcomes. Using them permits the definition of a minimum clinically important difference (MCID) beyond which a patient may be judged as having responded to treatment. Despite recommendations that clinicians routinely use MCIDs in clinical practice, statisticians disagree about how MCIDs should be used to evaluate individual patient outcomes and responses to treatment. To address this issue, we asked how clinicians actually use MCIDs to evaluate patient outcomes in response to treatment. Sixty-eight psychiatrists made judgments about whether hypothetical patients had responded to treatment based on their pre- and posttreatment change scores on the widely used Positive and Negative Syndrome Scale. Psychiatrists were provided with the scale’s MCID on which to base their judgments. Our secondary objective was to assess whether knowledge of the patient’s genotype influenced psychiatrists’ responder judgments. Thus, psychiatrists were also informed of whether patients possessed a genotype indicating hyperresponsiveness to treatment. While many psychiatrists appropriately used the MCID, others accepted a far lower posttreatment change as indicative of a response to treatment. When psychiatrists accepted a lower posttreatment change than the MCID, they were less confident in such judgments compared to when a patient’s posttreatment change exceeded the scale’s MCID. Psychiatrists were also less likely to identify patients as responders to treatment if they possessed a hyperresponsiveness genotype. Clinicians should recognize that when judging patient responses to treatment, they often tolerate lower response thresholds than warranted. At least some conflate their judgments with information, such as the patient’s genotype, that is irrelevant to a post hoc response-to-treatment assessment. Consequently, clinicians may be at risk of persisting with treatments that have failed to demonstrate patient benefits.

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“…Although the Mapping Model is adapted to continuous judgment, the model is confined to tasks with binary cue dimensions where the knowledge of cue directions is used with a simple adding strategy of the binary cue dimensions to infer the criterion. Knowledge of cue directions can thus be used for an additive integration of cue information, as the Mapping Model assumes, to facilitate a piecemeal integration of abstracted cue weights, as the CAM assumes (Juslin, Jones, et al, 2003Newell et al, 2009;Rolison et al, 2012;von Helversen et al, 2013), or to form extreme prototypes as statistically valid reference points for fast and accurate similarity-based assessments, as the PBM assumes.…”

Section: Discussionmentioning

confidence: 99%

“…This research paradigm, MPCL, has often emphasised the role of trial-anderror feedback and there has been a more or less implicit assumption that learning from feedback is a controlled hypothesis testing and summing of cue weights. Externally provided feedback is assumed to adjust faulty beliefs about which cues to attend, weigh, and integrate in order to correctly infer the distal criteria, usually varying on a continuous dimension as in estimation tasks (Juslin, Karlsson, & Olsson, 2008;Klayman, 1988;Lindell, 1976;Newell, Weston, Tunney, & Shanks, 2009;Rolison, Evans, Dennis, & Walsh, 2012).…”

Section: Estimation Tasks and Mpclmentioning

confidence: 99%

“…The fine-grained pseudo-continuous cue dimensions also allow the detection of cue directions: i.e. whether cues are positively or negatively related to the criterion (Bröder et al, 2010;Newell et al, 2009;Rolison et al, 2012;von Helversen et al, 2013). Most importantly, across trials, the fine-grained pseudo-continuous cue dimensions can facilitate the abstraction of cue weights from observations of how much change on each cue dimension generates changes on the criterion dimension.…”

Section: Predictionsmentioning

confidence: 99%

See 1 more Smart Citation

Cue abstraction and ideal prototype abstraction in estimation tasks

Henriksson

2019

Journal of Cognitive Psychology

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This study investigates abstracted processes and introduces a new prototype abstraction model adapted to estimation tasks. This prototype abstraction model assumes that the processing of whole exemplar patterns supports the detection of the underlying statistics necessary for the abstraction of two extreme prototypes on the continuous criterion dimension of the task. The prototypes are stored in memory as valid reference points for future similarity-based judgments. This prototype model was compared with the cue abstraction model, which assumes that people abstract cue weights in learning and add the cue information from exemplars to infer their criterion values varying on the continuous dimension. This study hypothesises that the training mode and the number of exemplars in training interact and affect subsequent model performance at test. The results from an experiment confirmed this hypothesis and showed that observational training supports an efficient prototype abstraction and feedback training supports an efficient cue abstraction.

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Dual-processes in learning and judgment: Evidence from the multiple cue probability learning paradigm

Cited by 15 publications

References 35 publications

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

Information Use Differences in Hot and Cold Risk Processing: When Does Information About Probability Count in the Columbia Card Task?

How Do Psychiatrists Apply the Minimum Clinically Important Difference to Assess Patient Responses to Treatment?

Cue abstraction and ideal prototype abstraction in estimation tasks

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