title: Development of an automatic response mode to improve the clinical utility of sequential risk-taking tasks.
abstract: Sequential risk-taking tasks, especially the Balloon Analogue Risk Task (BART), have proven powerful and useful methods in studying and identifying real-world risk takers. A natural index in these tasks is the average number of risks the participant takes in a trial (e.g., pumps on the balloons), but this is difficult to estimate because some trials terminate early because of the consequences of those risks (e.g., when the desired number of balloon pumps exceeds the explosion point). The standard corrective strategy is to use an adjusted score that ignores such event-terminated trials. Although previous data supports the utility of this adjusted score, the authors show formally that it is biased. Therefore, the authors developed an automatic response procedure, in which respondents state at the beginning of each trial how many risks they wish to take and then observe the sequence of events unfold. A study comparing this new automatic and the original manual BART shows that the automatic procedure yields unbiased statistics whereas maintaining the BART's predictive validity of substance use. The authors also found that providing respondents with the expected-value-maximizing strategy and complete trial-by-trial feedback increased the number of risks they were willing to take during the BART. The authors interpret these results in terms of the potential utility of the automatic version including shorter administration time, unbiased behavioral measures, and minimizing motor involvement, which is important in neuroscientific investigations or with clinical populations with motor limitations.
authors.affiliation: Department of Psychology, Michigan State University, East Lansing, MI 48824, USA. tim.pleskac@gmail.com
authors.forename: Timothy J
authors.initials: TJ
authors.lastname: Pleskac
authors.forename: Thomas S
authors.initials: TS
authors.lastname: Wallsten
authors.forename: Paula
authors.initials: P
authors.lastname: Wang
authors.forename: C W
authors.initials: CW
authors.lastname: Lejuez
mesh_terms: D001331:Automation / Q000379:methods; D015982:Bias; D005260:Female; D006801:Humans; D008297:Male; D011581:Psychological Tests / Q000592:standards*; D012309:Risk-Taking; D019966:Substance-Related Disorders / Q000453:epidemiology*; D011795:Surveys and Questionnaires; D013997:Time Factors; D055815:Young Adult