QualGames: A Qualtrics implementation and a database of behavioral game theory tasks.

Authors

Shengchuang Feng, Nadhilla Melia, Akshay Abraham, Yuan Ni Chan, Li Ling Lee, Jia Ying Pei, Hui Shan Yap, David Hung, John Suckling, Chew Lee Teo, Trevor Robbins, Barbara Sahakian, Zoe Kourtzi, Victoria Leong, Annabel Chen, Henriette Hendriks, Georgios Christopoulos, and the CLIC Phase 1 Consortium

Published in

Behavior research methods. Volume 58. Issue 8. Jul 06, 2026. Epub Jul 06, 2026.

Abstract

Behavioral decision-making tasks are widely used to study individual and social preferences, including risk-taking, temporal discounting, and cooperation-related choices such as social value orientation, trust, and reciprocity, as well as more complex social behaviors examined through social dilemma and coordination games. These tasks are often administered along with typical survey questionnaires. However, scripting complexity limits their implementation on some popular online survey platforms (e.g., Qualtrics), which are commonly used to deploy studies across large populations. Here, we share a detailed experimental protocol and the corresponding source code, which enable the modular implementation of a decision-making battery in Qualtrics, including tasks such as the social value orientation, prisoner's dilemma, trust game, and baseline nonsocial risk preference tasks. Data from 392 participants in Singapore and 94 participants in the United States (US) were collected and analyzed to validate the task battery. Their responses exhibited good quality and high convergent and divergent validity across different tasks and aligned with basic predictions of behavioral decision theory (e.g., the reflection effect and loss aversion) and social decision-making theories (e.g., inequity aversion and betrayal aversion). Responses from 314 Singapore participants and 94 US participants are shared (with their consent). The source code for the task batteries could be used to expand the database and for hypothesis testing in decision-making research. The data could facilitate comparisons with other populations and the development of simulated agents to address logistical challenges in asynchronous experiments. Overall, we go beyond mere code and data sharing to foster large-scale behavioral game theory research.

PMID:
42410286
Bibliographic data and abstract were imported from PubMed on 07 Jul 2026.

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