Decision making and learning while taking sequential risks.
Abstract
A sequential risk-taking paradigm used to identify real-world risk takers invokes both learning and decision processes. This article expands the paradigm to a larger class of tasks with different stochastic environments and different learning requirements. Generalizing a Bayesian sequential risk-taking model to the larger set of tasks clarifies the roles of learning and decision making during sequential risky choice. Results show that respondents adapt their learning processes and associated mental representations of the task to the stochastic environment. Furthermore, their Bayesian learning processes are shown to interfere with the paradigm's identification of risky drug use, whereas the decision-making process facilitates its diagnosticity. Theoretical implications of the results in terms of both understanding risk-taking behavior and improving risk-taking assessment methods are discussed.
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The sequential nature of the BART implies a learning effect, which enables participants to determine the nonstationary probabilistic nature of the task.
“Pleskac (2008) observed that the sequential nature of the BART implies a learning effect, which enables participants to determine the nonstationary probablistic nature of the task.”
From Risk taking and sensitivity to punishment in children with ADHD, ODD, ADHD+ODD, and controls (2011) · cites this paper as Pleskac 2008
Alternative BART outcome measures have been used by other researchers.
“It should also be noted that alternative BART outcome measures have been used by other researchers (e.g., Lejuez et al. 2003; Pleskac 2008) and our sample size prevented examination of potential sex or racial-ethnic differences.”
From Risk taking and sensitivity to punishment in children with ADHD, ODD, ADHD+ODD, and controls (2011) · cites this paper as Pleskac 2008
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Self-citation
- Authors
- Pleskac, T. J.
- Affiliations
- Indiana University (US)
- Corresponding author
- Pleskac, Timothy J.
- ORCID
- Pleskac, Timothy J.
- Venue
- Journal of Experimental Psychology: Learning, Memory, and Cognition
- Published
- 2008
- Volume
- 34
- Issue
- 1
- Pages
- 167-185
- ISSN
- 0278-7393 (ISSN-L)
- 1939-1285
- OpenAlex
- W1980195663
- Cited by
- 121
- References
- 56
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 9 · 2022: 15 · 2021: 13 · 2020: 5 · 2019: 3 · 2018: 11 · 2017: 6 · 2016: 6 · 2015: 6 · 2014: 8 · 2013: 6 · 2012: 7
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Experimental Psychology Learning Memory and Cognition (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Drug Abuse (R21-DA14699)
- National Institute of Mental Health (MH019879)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Leadership, Behavior, and Decision-Making Studies
- Keywords
- decision making under risk, Bayesian learning, decision-making, mental representation, stochastic environments, risk-taking
- MeSH terms
- Adolescent, Adult, Association Learning, Bayes Theorem, Choice Behavior, Culture, Decision Making, Decision Theory, Female, Gambling, Humans, Individuality, Male, Pattern Recognition, Visual, Psychomotor Performance, Risk-Taking, Stochastic Processes, Health Behavior, Substance-Related Disorders
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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