Evidence map›Paper›PMID 41566107›Full record

ArticleBehavior research methods2026

Jokers in the deck: A new temperature setting for the Columbia Card Task.

Kevin Kapadia, Yunxiu Tang, Richard John

Abstract read
In one paragraph

Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kevin KapadiaUniversity of Southern California, Los Angeles, CA, USA. kevinkap@usc.edu.ORCID http://orcid.org/0000-0003-0935-7893
Yunxiu TangUniversity of Southern California, Los Angeles, CA, USA.
Richard JohnUniversity of Southern California, Los Angeles, CA, USA.

Funding

University of Southern California Doctoral Research Grant
6 · The paper itself

Abstract

The Columbia Card Task (CCT) is a behavioral measure of risk-taking (BMRT), which has been cited over 1,500 times (Google Scholar, 3/1/2024). The original game had two versions (Hot and Cold), measuring affective and deliberative decision-making, respectively. Each version included 54 scored rounds where the loss cards were placed at the end, and nine unscored rounds where the loss cards were placed systematically among the gain cards. Over time, the CCT has gone through many iterations on critical components, such as the number of rounds, the position of the loss cards, and the introduction of a new version (Warm). Despite this, there are several issues with the CCT, notably a need for convergent validity with other measures of risk-taking. This paper reviews different iterations of the CCT, introduces a new (Toasty) version of the CCT that is a hybrid of the hot and warm versions, explores the consequences of randomly placing the loss cards among the gain cards consistent with instructions provided to participants, and examines the impact of incentivizing participants based on their score. Results (N = 405) show that the Toasty version behaves similarly to the Warm but provides additional insights into risk-taking behavior. When loss cards are placed randomly, participants are still sensitive to the game's parameters (gain amount, loss amount, and number of loss cards) and reveal the loss cards roughly half the time. Incentivizing participants in our study had little impact on the number of cards revealed.

Indexed as

Decision MakingRisk-TakingGames, ExperimentalHumansAffective decision-makingBehavioral measure of risk-takingCCTDeceptionDeliberative decision-makingIncentivesSequential decision-making

Identifiers

PMID41566107
PMCPMC12823667

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.