The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The truth about lies: A meta-analysis on dishonest behavior.
Open accessAbstract
Over the past decade, a large and growing body of experimental research has analyzed dishonest behavior. Yet the findings as to when people engage in (dis)honest behavior are to some extent unclear and even contradictory. A systematic analysis of the factors associated with dishonest behavior thus seems desirable. This meta-analysis reviews four of the most widely used experimental paradigms: sender-receiver games, die-roll tasks, coin-flip tasks, and matrix tasks. We integrate data from 565 experiments (totaling N = 44,050 choices) to address many of the ongoing debates on who behaves dishonestly and under what circumstances. Our findings show that dishonest behavior depends on both situational factors, such as reward magnitude and externalities, and personal factors, such as the participant's gender and age. Further, laboratory studies are associated with more dishonesty than field studies, and the use of deception in experiments is associated with less dishonesty. To some extent, the different experimental paradigms come to different conclusions. For example, a comparable percentage of people lie in die-roll and matrix tasks, but in die-roll tasks liars lie to a considerably greater degree. We also find substantial evidence for publication bias in almost all measures of dishonest behavior. Future research on dishonesty would benefit from more representative participant pools and from clarifying why the different experimental paradigms yield different conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Conducting Meta-Analyses in R with the metafor Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464
Social Exchange Theory: An Interdisciplinary Review
Cropanzano, R., & Mitchell, M. S. (2005) · Journal of Management · doi:10.1177/0149206305279602 · Cited by 10,068
Beyond the Turk: Alternative platforms for crowdsourcing behavioral research
Peer, E., Brandimarte, L., Samat, S., & Acquisti, A. (2017) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2017.01.006 · Cited by 2,957
The Dishonesty of Honest People: A Theory of Self-Concept Maintenance
Mazar, N., Amir, O., & Ariely, D. (2008) · Journal of Marketing Research · doi:10.1509/jmkr.45.6.633 · Cited by 2,875
Higher social class predicts increased unethical behavior
Piff, P. K., Stancato, D. M., Côté, S., Mendoza-Denton, R., & Keltner, D. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1118373109 · Cited by 1,038
Intrinsic honesty and the prevalence of rule violations across societies
Gächter, S., & Schulz, J. F. (2016) · Nature · doi:10.1038/nature17160 · Cited by 551
Cited by
Data quality of platforms and panels for online behavioral research
Peer, E., Rothschild, D., Gordon, A., Evernden, Z., & Damer, E. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01694-3 · Cited by 1,718
Personality and prosocial behavior: A theoretical framework and meta-analysis.
Thielmann, I., Spadaro, G., & Balliet, D. (2020) · Psychological Bulletin · doi:10.1037/bul0000217 · Cited by 689
Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools
Kozyreva, A., Lewandowsky, S., & Hertwig, R. (2020) · Psychological Science in the Public Interest · doi:10.1177/1529100620946707 · Cited by 479
Self-citationNo evidence of moral licensing in a laboratory bribe-taking task
Bahník, Š., & Vranka, M. (2022) · Scientific Reports · doi:10.1038/s41598-022-16800-4 · Cited by 7
Metadata
- Authors
- Gerlach, P., Teodorescu, K., & Hertwig, R.
- Venue
- Psychological Bulletin
- Published
- 2019-01
- Volume
- 145
- Issue
- 1
- Pages
- 1-44
- ISSN
- 0033-2909 (ISSN-L)
- 1939-1455
- OpenAlex
- W2885014781
- Cited by
- 454
- References
- 6
- FWCI
- 41.25
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The truth about lies: A meta-analysis on dishonest behavior. https://app.cochat.ai/papers/10.1037/bul0000174
- The paper
- Gerlach, P., Teodorescu, K., & Hertwig, R. (2019). The truth about lies: A meta-analysis on dishonest behavior. Psychological Bulletin. https://doi.org/10.1037/bul0000174
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.