Back to Search Start Over

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

Authors :
Laura Broeker
Joseph G. Johnson
Rita F. de Oliveira
Harald E. Ewolds
Stefan Künzell
Markus Raab
Source :
Acta Psychologica, Vol 224, Iss , Pp 103521- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

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.

Subjects

Subjects :
Psychology
BF1-990

Details

Language :
English
ISSN :
00016918
Volume :
224
Issue :
103521-
Database :
Directory of Open Access Journals
Journal :
Acta Psychologica
Publication Type :
Academic Journal
Accession number :
edsdoj.3a3b7d0536dd414b9557d8dc1fb11a02
Document Type :
article
Full Text :
https://doi.org/10.1016/j.actpsy.2022.103521