Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Communications
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. nature communications
  3. articles
  4. article
Systematic review and meta-analysis of the evidence for an illusory truth effect and its determinants
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 27 February 2026

Systematic review and meta-analysis of the evidence for an illusory truth effect and its determinants

  • Steeven Ye1,2,
  • David Attali  ORCID: orcid.org/0000-0002-8295-38893,4,
  • Maria Ghazi  ORCID: orcid.org/0009-0001-6216-02671,5,
  • Arnaud Cachia1,6,
  • Mathieu Cassotti1,7 na1 na2 &
  • …
  • Grégoire Borst  ORCID: orcid.org/0000-0002-5815-34191,7,8 na1 na2 

Nature Communications , Article number:  (2026) Cite this article

  • 4620 Accesses

  • 15 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Decision making
  • Human behaviour

Abstract

Over the last four decades, studies provided evidence that individuals tend to rate statements as being more truthful when they are re-exposed to them, the so-called ‘illusory truth effect’. In light of a growing number of studies published since the previous meta-analysis in 2006 and concern of publishing biases, we conduct a meta-analysis on 182 studies and 366 effect sizes (N = 31,184 participants) published from 1977 to 2025. After correcting for small-study effects, we observe a small illusory truth effect (g = 0.37, 95% confidence interval [0.30, 0.44]), with a substantial within and between-study heterogeneity. Here, we show that multiple variables accounted for such heterogeneity, including the type of item, the instructions during the first exposure, the presence of veracity cues, and the duration of presentation on first exposure to the statement. We highlight the importance of the initial exposure and discuss practical implications regarding the current misinformation crisis.

Similar content being viewed by others

Inoculation and accuracy prompting increase accuracy discernment in combination but not alone

Article 04 November 2024

Misunderstanding the harms of online misinformation

Article 05 June 2024

The development of media truth discernment and fake news detection is related to the development of reasoning during adolescence

Article Open access 26 February 2025

Data availability

The data generated in this study is available in the Open Science Framework (OSF) repository under accession85 https://doi.org/10.17605/OSF.IO/2DB8S. No raw individual-level participant data were generated in this study. The processed data underlying all analyses, including extracted effect sizes, moderator coding, and imputed datasets, are available in the OSF repository. No data are subject to ethical, legal, or commercial restrictions.

Code availability

All analysis scripts used to perform the meta-analyses and generate the figures in this study are available in the OSF repository under accession https://doi.org/10.17605/OSF.IO/2DB8S.

References

  1. Hasher, L., Goldstein, D. & Toppino, T. Frequency and the conference of referential validity. J. Verbal Learn. Verbal Behav. 16, 107–112 (1977).

    Google Scholar 

  2. Dechêne, A., Stahl, C., Hansen, J. & Wänke, M. The Truth About the Truth: A Meta-Analytic Review of the Truth Effect. Personal. Soc. Psychol. Rev. 14, 238–257 (2010).

    Google Scholar 

  3. Henderson, E. L., Westwood, S. J. & Simons, D. J. A reproducible systematic map of research on the illusory truth effect. Psychon. Bull. Rev. 29, 1065–1088 (2022).

    Google Scholar 

  4. Ladowsky-Brooks, R. L. The truth effect in relation to neuropsychological functioning in traumatic brain injury. Brain Inj. 24, 1343–1349 (2010).

    Google Scholar 

  5. Moritz, S. et al. Repetition is good? An Internet trial on the illusory truth effect in schizophrenia and nonclinical participants. J. Behav. Ther. Exp. Psychiatry 43, 1058–1063 (2012).

    Google Scholar 

  6. Brashier, N. M., Umanath, S., Cabeza, R. & Marsh, E. J. Competing cues: Older adults rely on knowledge in the face of fluency. Psychol. Aging 32, 331–337 (2017).

    Google Scholar 

  7. Fazio, L. K. & Sherry, C. L. The Effect of Repetition on Truth Judgments Across Development. Psychol. Sci. 31, 11 (2020).

    Google Scholar 

  8. Henkel, L. A. & Mattson, M. E. Reading is believing: The truth effect and source credibility. Conscious. Cogn. 20, 1705–1721 (2011).

    Google Scholar 

  9. Corneille, O., Mierop, A. & Unkelbach, C. Repetition increases both the perceived truth and fakeness of information: An ecological account. Cognition 205, 104470 (2020).

    Google Scholar 

  10. De Keersmaecker, J. et al. Investigating the Robustness of the Illusory Truth Effect Across Individual Differences in Cognitive Ability, Need for Cognitive Closure, and Cognitive Style. Pers. Soc. Psychol. Bull. 46, 204–215 (2020).

    Google Scholar 

  11. Brashier, N. M., Eliseev, E. D. & Marsh, E. J. An initial accuracy focus prevents illusory truth. Cognition 194, 104054 (2020).

    Google Scholar 

  12. Pennycook, G., Cannon, T. D. & Rand, D. G. Prior exposure increases perceived accuracy of fake news. J. Exp. Psychol. Gen. 147, 1865–1880 (2018).

    Google Scholar 

  13. Smelter, T. J. & Calvillo, D. P. Pictures and repeated exposure increase perceived accuracy of news headlines. Appl. Cogn. Psychol. 34, 1061–1071 (2020).

    Google Scholar 

  14. DiFonzo, N., Beckstead, J. W., Stupak, N. & Walders, K. Validity judgments of rumors heard multiple times: the shape of the truth effect. Soc. Influ. 11, 22–39 (2016).

    Google Scholar 

  15. Moons, W. G., Mackie, D. M. & Garcia-Marques, T. The impact of repetition-induced familiarity on agreement with weak and strong arguments. J. Pers. Soc. Psychol. 96, 32–44 (2009).

    Google Scholar 

  16. Law, S., Hawkins, S. A. & Craik, F. I. M. Repetition-Induced Belief in the Elderly: Rehabilitating Age-Related Memory Deficits. J. Consum. Res. 25, 91–107 (1998).

    Google Scholar 

  17. Fazio, L. K., Rand, D. G. & Pennycook, G. Repetition increases perceived truth equally for plausible and implausible statements. Psychon. Bull. Rev. 26, 1705–1710 (2019).

    Google Scholar 

  18. Calvillo, D. P. & Harris, J. D. Exposure to headlines as questions reduces illusory truth for subsequent headlines. J. Appl. Res. Mem. Cogn. https://doi.org/10.1037/mac0000056 (2022).

  19. Udry, J. & Barber, S. J. The illusory truth effect: A review of how repetition increases belief in misinformation. Curr. Opin. Psychol. 56, 101736 (2024).

    Google Scholar 

  20. Vellani, V., Zheng, S., Ercelik, D. & Sharot, T. The illusory truth effect leads to the spread of misinformation. Cognition 236, 105421 (2023).

  21. Pennycook, G. & Rand, D. G. The Psychology of Fake News. Trends Cogn. Sci. 25, 388–402 (2021).

    Google Scholar 

  22. Edelson, S. M., Reyna, V. F., Singh, A. & Roue, J. E. The Psychology of Misinformation Across the Lifespan. Annu. Rev. Dev. Psychol. 6, 425–454 (2024).

    Google Scholar 

  23. Speckmann, F. & Unkelbach, C. Monetary incentives do not reduce the repetition-induced truth effect. Psychon. Bull. Rev. 29, 1045–1052 (2022).

    Google Scholar 

  24. Fazio, L. K., Brashier, N. M., Payne, B. K. & Marsh, E. J. Knowledge does not protect against illusory truth. J. Exp. Psychol. Gen. 144, 993–1002 (2015).

    Google Scholar 

  25. Calio, F., Nadarevic, L. & Musch, J. How explicit warnings reduce the truth effect: A multinomial modeling approach. Acta Psychol. (Amst.) 211, 103185 (2020).

    Google Scholar 

  26. Nadarevic, L. & Aßfalg, A. Unveiling the truth: warnings reduce the repetition-based truth effect. Psychol. Res. 81, 814–826 (2017).

    Google Scholar 

  27. Jalbert, M., Schwarz, N. & Newman, E. Only half of what i’ll tell you is true: Expecting to encounter falsehoods reduces illusory truth. J. Appl. Res. Mem. Cogn. 9, 602–613 (2020).

    Google Scholar 

  28. Lin, H. et al. Accuracy prompts protect professional content moderators from the illusory truth effect. PNAS Nexus 3, pgae481 (2024).

  29. Mitchell, J. P., Dodson, C. S. & Schacter, D. L. fMRI Evidence for the Role of Recollection in Suppressing Misattribution Errors: The Illusory Truth Effect. J. Cogn. Neurosci. 17, 800–810 (2005).

    Google Scholar 

  30. Begg, I. M., Anas, A. & Farinacci, S. Dissociation of processes in belief: Source recollection, statement familiarity, and the illusion of truth. J. Exp. Psychol. Gen. 121, 446–458 (1992).

    Google Scholar 

  31. Unkelbach, C. & Stahl, C. A multinomial modeling approach to dissociate different components of the truth effect. Conscious. Cogn. 18, 22–38 (2009).

    Google Scholar 

  32. Vosoughi, S., Roy, D. & Aral, S. The spread of true and false news online. Science 359, 1146–1151 (2018).

    Google Scholar 

  33. Unkelbach, C., Koch, A., Silva, R. R. & Garcia-Marques, T. Truth by Repetition: Explanations and Implications. Curr. Dir. Psychol. Sci. 28, 247–253 (2019).

    Google Scholar 

  34. Oppenheimer, D. M. The secret life of fluency. Trends Cogn. Sci. 12, 237–241 (2008).

    Google Scholar 

  35. Unkelbach, C. Reversing the truth effect: Learning the interpretation of processing fluency in judgments of truth. J. Exp. Psychol. Learn. Mem. Cogn. 33, 219–230 (2007).

    Google Scholar 

  36. Brashier, N. M. & Marsh, E. J. Judging Truth. Annu. Rev. Psychol. 71, 499–515 (2020).

    Google Scholar 

  37. Schwarz, N., Jalbert, M., Noah, T. & Zhang, L. Metacognitive experiences as information: Processing fluency in consumer judgment and decision making. Consum. Psychol. Rev. 4, 4–25 (2021).

    Google Scholar 

  38. Unkelbach, C. & Rom, S. C. A referential theory of the repetition-induced truth effect. Cognition 160, 110–126 (2017).

    Google Scholar 

  39. Udry, J. & Barber, S. J. The illusory truth effect requires semantic coherence across repetitions. Cognition 241, 105607 (2023).

    Google Scholar 

  40. Cheung, M. W.-L. Modeling dependent effect sizes with three-level meta-analyses: A structural equation modeling approach. Psychol. Methods 19, 211–229 (2014).

    Google Scholar 

  41. Van den Noortgate, W., López-López, J. A., Marín-Martínez, F. & Sánchez-Meca, J. Three-level meta-analysis of dependent effect sizes. Behav. Res. Methods 45, 576–594 (2013).

    Google Scholar 

  42. Peters, J. L., Sutton, A. J., Jones, D. R., Abrams, K. R. & Rushton, L. Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. J. Clin. Epidemiol. 61, 991–996 (2008).

    Google Scholar 

  43. Sterne, J. A. C. et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ l4898 https://doi.org/10.1136/bmj.l4898 (2019).

  44. Egger, M., Smith, G. D., Schneider, M. & Minder, C. Bias in meta-analysis detected by a simple, graphical test. BMJ 315, 629–634 (1997).

    Google Scholar 

  45. Rodgers, M. A. & Pustejovsky, J. E. Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes. Psychol. Methods 26, 141–160 (2021).

    Google Scholar 

  46. Sterne, J. A. C. et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ 343, d4002–d4002 (2011).

    Google Scholar 

  47. Buuren, S. V. & Groothuis-Oudshoorn, K. mice: Multivariate Imputation by Chained Equations in R. J. Stat. Softw. 45, 1–67 (2011).

  48. Van Buuren, S. Flexible Imputation of Missing Data, Second Edition. (Chapman and Hall/CRC, Second edition. | Boca Raton, Florida: CRC Press, [2019] |, 2018). https://doi.org/10.1201/9780429492259.

  49. Arkes, H. R., Hackett, C. & Boehm, L. The generality of the relation between familiarity and judged validity. J. Behav. Decis. Mak. 2, 81–94 (1989).

    Google Scholar 

  50. Bacon, F. T. Credibility of repeated statements: Memory for trivia. J. Exp. Psychol. [Hum. Learn. 5, 241–252 (1979).

    Google Scholar 

  51. Brown, A. S. & Nix, L. A. Turning lies into truths: Referential validation of falsehoods. J. Exp. Psychol. Learn. Mem. Cogn. 22, 1088–1100 (1996).

    Google Scholar 

  52. Silva, R. R., Garcia-Marques, T. & Reber, R. The informative value of type of repetition: Perceptual and conceptual fluency influences on judgments of truth. Conscious. Cogn. 51, 53–67 (2017).

    Google Scholar 

  53. Pfänder, J. & Altay, S. Spotting false news and doubting true news: a systematic review and meta-analysis of news judgements. Nat. Hum. Behav. 9, 688–699 (2025).

    Google Scholar 

  54. Nadarevic, L. & Erdfelder, E. On the relationship between recognition judgments and truth judgments: Memory states moderate the recognition-based truth effect. J. Exp. Psychol. Learn. Mem. Cogn. https://doi.org/10.1037/xlm0001460 (2025).

  55. Nadarevic, L., Schnuerch, M. & Stegemann, M. J. Judging fast and slow: The truth effect does not increase under time-pressure conditions. Judgm. Decis. Mak. 16, 1234–1266 (2021).

  56. Dechêne, A., Stahl, C., Hansen, J. & Wänke, M. Mix me a list: Context moderates the truth effect and the mere-exposure effect. J. Exp. Soc. Psychol. 45, 1117–1122 (2009).

    Google Scholar 

  57. Garcia-Marques, T., Silva, R. R. & Mello, J. Judging the Truth-Value of a Statement In and Out of a Deep Processing Context. Soc. Cogn. 34, 40–54 (2016).

    Google Scholar 

  58. Garcia-Marques, T., Silva, R. R., Mello, J. & Hansen, J. Relative to what? Dynamic updating of fluency standards and between-participants illusions of truth. Acta Psychol. (Amst.) 195, 71–79 (2019).

    Google Scholar 

  59. Nadarevic, L. & Erdfelder, E. Initial judgment task and delay of the final validity-rating task moderate the truth effect. Conscious. Cogn. 23, 74–84 (2014).

    Google Scholar 

  60. Garcia-Marques, T., Silva, R. R., Reber, R. & Unkelbach, C. Hearing a statement now and believing the opposite later. J. Exp. Soc. Psychol. 56, 126–129 (2015).

    Google Scholar 

  61. Ly, D. P., Bernstein, D. M. & Newman, E. J. An ongoing secondary task can reduce the illusory truth effect. Front. Psychol. 14, 1215432 (2024).

    Google Scholar 

  62. Chan, M. S., Jones, C. R., Hall Jamieson, K. & Albarracín, D. Debunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation. Psychol. Sci. 28, 1531–1546 (2017).

    Google Scholar 

  63. Ecker, U. K. H., Lewandowsky, S. & Chadwick, M. Can corrections spread misinformation to new audiences? Testing for the elusive familiarity backfire effect. Cogn. Res. Princ. Implic. 5, 41 (2020).

    Google Scholar 

  64. Swire-Thompson, B., Miklaucic, N., Wihbey, J. P., Lazer, D. & DeGutis, J. The backfire effect after correcting misinformation is strongly associated with reliability. J. Exp. Psychol. Gen. 151, 1655–1665 (2022).

    Google Scholar 

  65. Stanley, T. D. Limitations of PET-PEESE and Other Meta-Analysis Methods. Soc. Psychol. Personal. Sci. 8, 581–591 (2017).

    Google Scholar 

  66. Borenstein, M., Higgins, J. P. T., Hedges, L. V. & Rothstein, H. R. Basics of meta-analysis: I2 is not an absolute measure of heterogeneity. Res. Synth. Methods 8, 5–18 (2017).

    Google Scholar 

  67. Page, M. J. et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Int. J. Surg. 88, 105906 (2021).

    Google Scholar 

  68. R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, Austria, 2022).

  69. RStudio Team. RStudio: Integrated Development Environment for R. (RStudio, PBC., Boston, MA, 2020).

  70. Harrer, M., Cuijpers, P., Furakawa, T. A. & Ebert, D. D. Doing Meta-Analysis with R - A Hands-On Guide. (Chapman & Hall, 2022).

  71. Viechtbauer, W. Conducting Meta-Analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48 (2010).

  72. Wickham, H. et al. Welcome to the Tidyverse. J. Open Source Softw. 4, 1686 (2019).

    Google Scholar 

  73. Wilkinson, L. ggplot2: Elegant Graphics for Data Analysis by WICKHAM, H. Biometrics 67, 678–679 (2011).

    Google Scholar 

  74. Kowarik, A. & Templ, M. Imputation with the R Package VIM. J. Stat. Softw. 74, (2016).

  75. McGuinness, L. A. & Higgins, J. P. T. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res. Synth. Methods 12, 55–61 (2021).

    Google Scholar 

  76. Harzing, A. W. Publish or Perish. (2007).

  77. Ellington, E. H. et al. Using multiple imputation to estimate missing data in meta-regression. Methods Ecol. Evol. 6, 153–163 (2015).

    Google Scholar 

  78. Hedges, L. V. Distribution Theory for Glass’s Estimator of Effect size and Related Estimators. J. Educ. Stat. 6, 107–128 (1981).

    Google Scholar 

  79. Cohen, J. Statistical Power Analysis for the Behavioral Sciences. (Psychology Press, New York, NY, 2009).

  80. Borenstein, M., Hedges, L. V., Higgins, J. P. T. & Rothstein, H. R. Introduction to Meta-Analysis. (John Wiley & Sons, 2021).

  81. Cochrane Handbook for Systematic Reviews of Interventions. in Cochrane Handbook for Systematic Reviews of Interventions (eds Higgins, J. P. & Green, S.) i–xxi (John Wiley & Sons, Ltd, Chichester, UK, 2008). https://doi.org/10.1002/9780470712184.fmatter.

  82. Morris, S. B. & DeShon, R. P. Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychol. Methods 7, 105–125 (2002).

    Google Scholar 

  83. Van Aert, R. C. M. & Jackson, D. A new justification of the Hartung-Knapp method for random-effects meta-analysis based on weighted least squares regression. Res. Synth. Methods 10, 515–527 (2019).

    Google Scholar 

  84. Raudenbush, S. Analyzing effect sizes: Random-effects models. in The Handbook of Research Synthesis and Meta-Analysis (eds Hedges, L., Cooper, H. M. & Valentine, J. C.) 295–315 (Russell Sage Foundation, 2009).

  85. Ye, S. et al. Data and code for: Systematic review and meta-analysis of the evidence for an illusory truth effect and its determinants. Open Science Framework https://doi.org/10.17605/OSF.IO/2DB8S (2025).

Download references

Acknowledgements

We would like to thank Y. Al-Bandakji for her help in double-coding during data extraction, as well as A. De Carvalho for his valuable feedback on systematic review processes. We would also like to thank E.L. Henderson for sharing her materials. S.Y., M.G., M.C., and G.B. received funding from FakeAd ANR grant ANR−21-CE28-0025. S.Y. received fundings from a CIFRE grant 2022/1463 administered by the ANRT (Association Nationale de la Recherche et de la Technologie). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Author information

Author notes
  1. These authors contributed equally: Mathieu Cassotti, Grégoire Borst.

  2. These authors jointly supervised this work: Mathieu Cassotti, Grégoire Borst.

Authors and Affiliations

  1. Université Paris Cité, LaPsyDÉ, CNRS, Paris, France

    Steeven Ye, Maria Ghazi, Arnaud Cachia, Mathieu Cassotti & Grégoire Borst

  2. Global Science Organization, IPSOS, Paris, France

    Steeven Ye

  3. GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte-Anne, Unité de Neuropsychiatrie interventionnelle, Paris, France

    David Attali

  4. Institute Physics for Medicine Paris, Inserm U1273, CNRS UMR 8063, ESPCI Paris, PSL University, Paris, France

    David Attali

  5. Editions Nathan, Paris, France

    Maria Ghazi

  6. Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Imaging biomarkers for brain development and disorders, Université Paris Cité, Paris, France

    Arnaud Cachia

  7. Institut Universitaire de France, Paris, France

    Mathieu Cassotti & Grégoire Borst

  8. Laboratory for Interdisciplinary Evaluation of Public Policies (LIEPP), Sciences Po, Paris, France

    Grégoire Borst

Authors
  1. Steeven Ye
    View author publications

    Search author on:PubMed Google Scholar

  2. David Attali
    View author publications

    Search author on:PubMed Google Scholar

  3. Maria Ghazi
    View author publications

    Search author on:PubMed Google Scholar

  4. Arnaud Cachia
    View author publications

    Search author on:PubMed Google Scholar

  5. Mathieu Cassotti
    View author publications

    Search author on:PubMed Google Scholar

  6. Grégoire Borst
    View author publications

    Search author on:PubMed Google Scholar

Contributions

S.Y. contributed to conceptualization, methodology, formal analysis, investigation, data curation, visualization, writing—original draft preparation, and writing—review & editing. D.A. contributed to methodology, formal analysis, visualization, and writing—review & editing. M.G. contributed to methodology, investigation, and writing—review & editing. A.C. contributed to formal analysis, visualization, and writing—review & editing. M.C. and G.B. contributed to conceptualization, methodology, supervision, project administration, and writing—review & editing.

Corresponding author

Correspondence to Grégoire Borst.

Ethics declarations

Competing interests

S.Y., M.C., and G.B. were authors of one study included in this review. However, this study was evaluated using the same inclusion criteria and risk of bias assessment as all other studies. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Communications thanks Madeline Jalbert, Robert Miller and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information (download PDF )

Description of Additional Supplementary Files (download PDF )

Supplementary Data 1 (download XLSX )

Supplementary Data 2 (download XLSX )

Supplementary Data 3 (download XLSX )

Supplementary Data 4 (download XLSX )

Supplementary Data 5 (download XLSX )

Reporting Summary (download PDF )

Transparent Peer Review file (download PDF )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ye, S., Attali, D., Ghazi, M. et al. Systematic review and meta-analysis of the evidence for an illusory truth effect and its determinants. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70041-x

Download citation

  • Received: 27 October 2024

  • Accepted: 12 February 2026

  • Published: 27 February 2026

  • DOI: https://doi.org/10.1038/s41467-026-70041-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Videos
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Editors
  • Journal Information
  • Open Access Fees and Funding
  • Calls for Papers
  • Editorial Values Statement
  • Journal Metrics
  • Editors' Highlights
  • Contact
  • Editorial policies
  • Top Articles

Publish with us

  • For authors
  • For Reviewers
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Communications (Nat Commun)

ISSN 2041-1723 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing