Switch rates vary due to expected payoff but not due to individual risk tendency

Laura Bröker, Joseph G Johnson, Rita Ferraz de Oliveira, Harald Ewolds, Stefan Künzell, Markus Raab

Publikation: Beitrag in FachzeitschriftZeitschriftenaufsätzeForschungBegutachtung

Abstract

When switching between different tasks, the initiation of task switches may depend on task characteristics (difficulty, salient cues, etc.) or reasons within the person
performing the task (decisions, behavioral variability, etc.). The reasons for variance in switching strategies, especially in paradigms where participants are free to
choose the order of tasks and the amount of switching between tasks, are not well researched. In this study, we follow up the recent discussion that variance in
switching strategies might be partly explained by the characteristics of the person fulfilling the task. We examined whether risk tendency and impulsiveness
differentiate individuals in their response (i.e., switch rates and time spent on tasks) to different task characteristics on a tracking-while-typing paradigm. In detail,
we manipulated two aspects of loss prospect (i.e., “payoff” as the amount of points that could be lost when tracking was unattended for too long, and “cursor speed”
determining the likelihood of such a loss occurring). To account for between-subject variance and within-subject variability in the data, we employed linear mixed
effect analyses following the model selection procedure (Bates, Kliegl, et al., 2015). Besides, we tested whether risk tendency can be transformed into a decision
parameter which could predict switching strategies when being computationally modelled. We transferred decision parameters from the Decision Field Theory to
model “switching thresholds” for each individual. Results show that neither risk tendency nor impulsiveness explain between-subject variance in the paradigm,
nonetheless linear mixed-effects models confirmed that within-subject variability plays a significant role for interpreting dual-task data. Our computational model
yielded a good model fit, suggesting that the use of a decision threshold parameter for switching may serve as an alternative means to classify different strategies in
task switching.
OriginalspracheEnglisch
Aufsatznummer103521
ZeitschriftActa Psychologica
Jahrgang224
Seitenumfang13
ISSN0001-6918
DOIs
PublikationsstatusVeröffentlicht - 01.04.2022

Zitation