Development and Validation of the Social Discounting Task: Short Form

Bibliographic Details
Title: Development and Validation of the Social Discounting Task: Short Form
Authors: Paige Amormino, August E. Graue, Abigail A. Marsh, Anne V. Wilson
Source: Social Psychological and Personality Science.
Publication Status: Preprint
Publisher Information: SAGE Publications, 2024.
Publication Year: 2024
Subject Terms: Prosocial Behavior, Psychometrics, Experimental Design and Sample Surveys, Social and Personality Psychology, Quantitative Methods, Social and Behavioral Sciences
Description: Social discounting—defined as hyperbolic reductions in generosity as social distance increases—is becoming more widely used in psychological research as an indicator of prosocial behavior and is most commonly measured by the Social Discounting Task (SDT). However, while robust, the SDT requires subjects to make 63 dichotomous decisions, which can be cumbersome and time-consuming. Thus, we created and validated a short-form version of the scale (SDT-SF) that reduces the inventory to 7 items. Across two pre-registered studies ( n = 993), we found that the SDT-SF responses were correlated with classic SDT responses ( r study1 = .67, p < .001; r study2 = .69, p < .001) and followed a similarly hyperbolic decay in generosity as social distance increased ( logk study1 = −3.70, p < .001; logk study2 = −3.42, p < .001). Replicating past work, both the classic SDT and the SDT-SF were correlated to similar degrees with Honesty-Humility ( r classic-SDT = .13, p < .05; r SDT-SF = .13, p < .05) and Identification with All of Humanity ( r classic-SDT = .17, p < .05; r SDT-SF = .17, p < .001). Our findings suggest the SDT-SF is a valid and reliable alternative measure to the SDT for investigating social discounting effects reliably and efficiently for researchers and participants.
Document Type: Article
Language: English
ISSN: 1948-5514
1948-5506
DOI: 10.1177/19485506251328706
DOI: 10.31234/osf.io/kvhzd
Rights: CC 0
URL: https://journals.sagepub.com/page/policies/text-and-data-mining-license
Accession Number: edsair.doi.dedup.....c022e86c87b7035390284797c83235da
Database: OpenAIRE
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