Unifying Evidence on Delay Discounting: Open Task, Analysis Tutorial, and Normative Data from an Italian Sample

Sara Garofalo, Luigi A. E. Degni, Manuela Sellitto, Davide Braghittoni, Francesca Starita, Sara Giovagnoli, Giuseppe di Pellegrino and Mariagrazia Benassi
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Sara Garofalo: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Luigi A. E. Degni: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Manuela Sellitto: Department of Comparative Psychology, Institute of Experimental Psychology, Heinrich-Heine University Düsseldorf, 40225 Düsseldorf, Germany
Davide Braghittoni: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Francesca Starita: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Sara Giovagnoli: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Giuseppe di Pellegrino: Department of Psychology, University of Bologna, 47521 Cesena, Italy
Mariagrazia Benassi: Department of Psychology, University of Bologna, 47521 Cesena, Italy

IJERPH, 2022, vol. 19, issue 4, 1-15

Abstract: Despite the widespread use of the delay discounting task in clinical and non-clinical contexts, several task versions are available in the literature, making it hard to compare results across studies. Moreover, normative data are not available to evaluate individual performances. The present study aims to propose a unified version of the delay discounting task based on monetary rewards and it provides normative values built on an Italian sample of 357 healthy participants. The most used parameters in the literature to assess the delay discount rate were compared to find the most valid index to discriminate between normative data and a clinical population who typically present impulsivity issues, i.e., patients with a lesion to the medial orbitofrontal cortex (mOFC). In line with our hypothesis, mOFC patients showed higher delay discounting scores than the normative sample and the normative group. Based on this evidence, we propose that the task and indexes here provided can be used to identify extremely high (above the 90th percentile for hyperbolic k or below the 10th percentile for AUC) or low (below the 10th percentile for hyperbolic k or above the 90th percentile for AUC) delay discounting performances. The complete dataset, the R code used to perform all analyses, a free and modifiable version of the delay discounting task, as well as the R code that can be used to extract all indexes from such tasks and compare subjective performances with the normative data here presented are available as online materials.

Keywords: delay discounting; normative data; ROC curves; criterion validity; medial orbitofrontal cortex; impulsivity (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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