Does Truth Pay? Investigating the Effectiveness of the Bayesian Truth Serum with an Interim Payment: A Registered Report use asterix (*) to get italics

Claire M. Neville, Matt N. WilliamsPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

2024

<p>Self-report data is vital in psychological research, but biases like careless responding and socially desirable responding can compromise its validity. While various methods are employed to mitigate these biases, they have limitations. The Bayesian Truth Serum (BTS; Prelec, 2004) offers a novel survey scoring method to incentivise truthfulness by leveraging correlations between personal and collective opinions and rewarding ‘surprisingly common’ responses. However, the effectiveness of the BTS across disciplines remains inconclusive, with possible challenges including participant disbelief and uncertainty regarding incentives. Through a between-subject, experimental survey design, this study aims to assess the efficacy of the BTS, particularly in mitigating biases associated with sensitive questions, potentially inducing SDR. It will explore whether introducing an interim payment during the survey enhances BTS efficacy by demonstrating to participants that the researcher can and will reward honesty. Participants will be randomly assigned to three conditions: BTS alone, BTS with Interim Payment, and Regular Incentive. They will complete a questionnaire comprising ten sensitive questions, and analyses will compare mean scores between groups. The outcomes of this study will provide insights into the effectiveness of the BTS alone and with an interim payment in promoting honesty, with implications for survey design and data collection methods.</p> <p>&nbsp;</p>

Bayesian Truth Serum (BTS), Data integrity, Incentivising truthfulness, Response biases, Self-report data, Sensitive questions, Socially Desirable Responding (SDR), Survey methodology.  

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Social sciences

Martin Schnuerch suggested: Dr. Julia Meisters, julia.meisters@uni-duesseldorf.de , Martin Schnuerch suggested: Dr. Adrian Hoffmann, adrian.hoffmann@uni-duesseldorf.de

e.g. John Doe john@doe.com

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2024-05-02 06:40:18

Romain Espinosa

Philipp Schoenegger, Martin Schnuerch, Sarahanne Miranda Field