Evaluating cognitive sequential risk-taking models: Manipulations of the stochastic process

dc.contributor.advisorWallsten, Thomas Sen_US
dc.contributor.authorPleskac, Timothy Josephen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.description.abstractThis dissertation evaluates, refines, and extends to a new paradigm, a set of stochastic models that describe the cognitive processes of individuals while they complete multiple trials of the Balloon Analogue Risk Task (BART; Lejuez et al., 2002). Wallsten, Pleskac, and Lejuez (2004) designed the models using prospect theory and a Bayesian learning process to better understand why the BART correlates so well with self-reported risky behaviors. The models differed in terms of the individuals' beliefs of the task's probabilistic structure and when option evaluations occur. The models revealed that although respondents use a Bayesian learning process to understand the task, they misunderstand the BART's stochastic process as stationary. Results also indicated that individuals' attitudes toward outcomes are, in part, a source of the BART's success. From these conclusions a new task was developed that allows manipulations of both the actual stochastic structure and the individuals' level of knowledge regarding the structure. Participants (N = 71) completed four different conditions of the task. Fitting the various cognitive models to each individual's data revealed that only a subset of the models correctly distinguished between the stochastic processes underlying the different conditions. Incorporating prospect theory's weighting function and a trial-dependent bias component into the models accounted for performance differences between conditions. Of the assorted model parameters, only prospect theory's value function correlated with external self-reported risky drug use. The results also showed that the learning component of the original BART may cloud its association to risky behaviors. Implications in terms of gambling tasks and the cognitive models will be discussed.en_US
dc.format.extent507128 bytes
dc.subject.pqcontrolledPsychology, Cognitiveen_US
dc.subject.pqcontrolledPsychology, Experimentalen_US
dc.subject.pqcontrolledPsychology, Generalen_US
dc.subject.pquncontrolledjudgment and decision makingen_US
dc.subject.pquncontrolledstochastic modelsen_US
dc.subject.pquncontrolledrisk takingen_US
dc.subject.pquncontrolledmathematical psychologyen_US
dc.titleEvaluating cognitive sequential risk-taking models: Manipulations of the stochastic processen_US


Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
495.24 KB
Adobe Portable Document Format