Need for Cognition is associated with a preference for higher task load in effort discounting [Previously: "When easy is not preferred: A discounting paradigm to assess load-independent task preference"]

Abstract

When individuals set goals, they consider the subjective value (SV) of the anticipated reward and the required effort, a trade-off that is of great interest to psychological research. One approach to quantify the SVs of levels of a cognitive task is the Cognitive Effort Discounting Paradigm by Westbrook and colleagues (2013). However, it fails to acknowledge the highly subjective nature of effort, as it assumes a unidirectional, inverse relationship between task load and SVs. Therefore, it cannot map differences in effort perception that arise from traits like Need for Cognition, since individuals who enjoy effortful cognitive activities likely do not prefer the easiest level. We aim to replicate the analysis of Westbrook and colleagues with our adaptation, the Cognitive and Emotion Regulation Effort Discounting paradigm, which quantifies SVs without assuming that the easiest level is preferred, thereby enabling the quantification of SVs for tasks without objective order of task load.

Can we measure effort in cognitive tasks? Examining the application of Additive Conjoint Measurement and the Rasch model

“…I was able to locate several studies that had employed N-back tasks and either had openly available data or the authors were able to share their data (Beh et al, 2021;Blacker & Curby, 2013;Tiberghien et al, 2017;Westbrook et al, 2020;Westbrook et al, 2013;Zerna et al, 2022). These studies had used a variety of N-back task items; for example, some used only one task (i.e., 3-back; Blacker & Curby (2013); Tiberghien et al (2017)) whereas others used a range of items (i.e., 0-,2-, and 3-back; Beh et al (2021); 1-to 4-back; Westbrook et al (2020); Zerna et al (2022); or 1-to 6-back; Westbrook et al (2013)). Thus, some people in the combined dataset had missing data for certain N-back items.…”

“…were produced to provide sufficient matrix sizes for checks 20 , I limited checks for cancellation to the largest dataset I could create from these studies. This meant that checks were conducted in the 1-to 4-back items of Westbrook et al (2020;and Zerna et al (2022) combined data. This resulted in a dataset of 149 participants.…”

Estimating individual subjective values of emotion regulation strategies

“…Then no SV will be 1, but still, the SVs of all strategies can be interpreted as absolute values and in relation to the other strategy's SVs (see Figure 1). In a separate study, we will test our adapted paradigm together with a n-back task and explore whether this paradigm can describe individuals that do not prefer the easiest n-back option (see Zerna, Scheffel et al 34 ).…”

“…In the first session participants filled out a demographic questionnaire and completed an n-back task with the levels one to four. Then, they completed an effort discounting (ED) procedure regarding the n-back levels on screen, followed by a random repetition of one n-back level 34 . The second session took place exactly one week after session one.…”

“…Intraclass correlation coefficient (ICC), ρ, was reported for each model (null model, as well as full model). The presented MLM followed the conceptualization of Zerna, Scheffel, et al 34 To investigate whether individual SVs predict ER choice (H7a), a χ2 test with predicted choice (highest SV of each participant) and actual choice was computed.…”