The prevalence effect in fingerprint identification: Match and non‐match base‐rates impact misses and false alarms
Abstract
The prevalence effect is a phenomenon whereby target prevalence impacts performance in visual search (e.g., baggage screening) and visual comparison (e.g., face‐matching) tasks – people more often 'miss' infrequent target stimuli. The current study investigated prevalence effects in fingerprint identification – an important visual comparison task used in criminal investigations. Participants (N = 287) judged 100 fingerprint pairs where the prevalence of match trials was either 10% (low), 50% (equal), or 90% (high), and half received trial‐level feedback on their performance. As predicted, low match prevalence increased errors on match trials (i.e., misses), whereas high match prevalence errors on non‐match trials (i.e., false alarms) – but only when participants received feedback. These effects were largely driven by changes in bias (C), rather than sensitivity (d’). These results suggest that the combination of feedback and match prevalence can impact the types of errors that fingerprint examiners may make in practice.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
People who work in the justice and legal systems have past experiences that may cause bias due to the prevalence effect.
“People who work in the justice and legal systems have past experiences. These may cause a bias due to the prevalence effect”
From Biased and biasing: the hidden bias cascade and bias snowball effects (2025) · cites this paper as Growns and Kukucka, 2021
Cites
Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015) · Journal of Statistical Software · doi:10.18637/jss.v067.i01 · Cited by 86,835 · see citing works
<b>lmerTest</b> Package: Tests in Linear Mixed Effects Models
Kuznetsova, A., Brockhoff, P. B., & Christensen, R. H. B. (2017) · Journal of Statistical Software · doi:10.18637/jss.v082.i13 · Cited by 24,346 · see citing works
Calculation of signal detection theory measures
Harold Stanislaw, A., & Todorov, N. (1999) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03207704 · Cited by 3,087 · see citing works
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 · see citing works
Judd, C. M., Westfall, J., & Kenny, D. A. (2012) · Journal of Personality and Social Psychology · doi:10.1037/a0028347 · Cited by 1,236 · see citing works
Strengthening forensic science in the United States : a path forward
Policy, L. (2009) · National Academies Press eBooks · Cited by 961 · see citing works
The forensic confirmation bias: Problems, perspectives, and proposed solutions.
Kassin, S. M., Dror, I. E., & Kukucka, J. (2013) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2013.01.001 · Cited by 634 · see citing works
Self-citationRare items often missed in visual searches
Wolfe, J. M., Horowitz, T. S., & Kenner, N. M. (2005) · Nature · doi:10.1038/435439a · Cited by 524 · see citing works
Low target prevalence is a stubborn source of errors in visual search tasks.
Wolfe, J. M., Horowitz, T. S., Wert, M. J. V., Kenner, N. M., Place, S. S., & Kibbi, N. (2007) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.136.4.623 · Cited by 419 · see citing works
Accuracy and reliability of forensic latent fingerprint decisions
Ulery, B. T., Hicklin, R. A., Buscaglia, J., & Roberts, M. A. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1018707108 · Cited by 350 · see citing works
Cognitive and human factors in expert decision making: Six fallacies and the eight sources of bias
Dror, I. E. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c00704 · Cited by 333 · see citing works
Varying Target Prevalence Reveals Two Dissociable Decision Criteria in Visual Search
Wolfe, J. M., & Wert, M. J. V. (2010) · Current Biology · doi:10.1016/j.cub.2009.11.066 · Cited by 292 · see citing works
Krishan, K., Kanchan, T., & Bumbrah, G. S. (2012) · Journal of Forensic and Legal Medicine · doi:10.1016/j.jflm.2011.12.018 · Cited by 289 · see citing works
Young, A. W., & Burton, A. M. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.11.007 · Cited by 235 · see citing works
Behavioral and electrophysiological evidence for configural processing in fingerprint experts
Busey, T. A., & Vanderkolk, J. R. (2004) · Vision Research · doi:10.1016/j.visres.2004.08.021 · Cited by 232 · see citing works
Perceptual expertise in forensic facial image comparison
White, D., Phillips, P. J., Hahn, C. A., Hill, M. Q., & O’Toole, A. J. (2015) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2015.1292 · Cited by 191 · see citing works
Repeatability and Reproducibility of Decisions by Latent Fingerprint Examiners
Ulery, B. T., Hicklin, R. A., Buscaglia, J., & Roberts, M. A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032800 · Cited by 183 · see citing works
Wolfe, J. M., Brunelli, D. N., Rubinstein, J., & Horowitz, T. S. (2013) · Journal of Vision · doi:10.1167/13.3.33 · Cited by 162 · see citing works
Rare Targets Are Rarely Missed in Correctable Search
Fleck, M. S., & Mitroff, S. R. (2007) · Psychological Science · doi:10.1111/j.1467-9280.2007.02006.x · Cited by 158 · see citing works
Mollon, J. D., Bosten, J. M., Peterzell, D. H., & Webster, M. A. (2017) · Vision Research · doi:10.1016/j.visres.2017.11.001 · Cited by 146 · see citing works
Lieberman, J. D., Carrell, C. A., Miethe, T. D., & Krauss, D. A. (2008) · Psychology Public Policy and Law · doi:10.1037/1076-8971.14.1.27 · Cited by 123 · see citing works
The paradox of human expertise: why experts get it wrong
Dror, I. E. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9780511978098.011 · Cited by 117 · see citing works
Langenburg, G., Champod, C., & Wertheim, P. A. (2009) · Journal of Forensic Sciences · doi:10.1111/j.1556-4029.2009.01025.x · Cited by 116 · see citing works
Why do we miss rare targets? Exploring the boundaries of the low prevalence effect
Rich, A. N., Kunar, M. A., Wert, M. J. V., Hidalgo-Sotelo, B., Horowitz, T. S., & Wolfe, J. M. (2008) · Journal of Vision · doi:10.1167/8.15.15 · Cited by 115 · see citing works
Dror, I. E., & Mnookin, J. L. (2010) · Law Probability and Risk · doi:10.1093/lpr/mgp031 · Cited by 111 · see citing works
Evaluating the feature comparison strategy for forensic face identification.
Towler, A., White, D., & Kemp, R. I. (2017) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000108 · Cited by 108 · see citing works
Even in correctable search, some types of rare targets are frequently missed
Wert, M. J. V., Horowitz, T. S., & Wolfe, J. M. (2009) · Attention Perception & Psychophysics · doi:10.3758/app.71.3.541 · Cited by 95 · see citing works
Thinking forensics: Cognitive science for forensic practitioners
Edmond, G., Towler, A., Growns, B., Ribeiro, G., Found, B., White, D., Ballantyne, K., Searston, R. A., Thompson, M. B., Tangen, J. M., et al. (2017) · Science & Justice · doi:10.1016/j.scijus.2016.11.005 · Cited by 95 · see citing works
Self-citationFeedback training for facial image comparison
White, D., Kemp, R. I., Jenkins, R., & Burton, A. M. (2013) · Psychonomic Bulletin & Review · doi:10.3758/s13423-013-0475-3 · Cited by 90 · see citing works
The Effect of Abnormality-Prevalence Expectation on Expert Observer Performance and Visual Search
Reed, W. M., Ryan, J. T., McEntee, M. F., Evanoff, M. G., & Brennan, P. (2011) · Radiology · doi:10.1148/radiol.10101090 · Cited by 86 · see citing works
The Nature of Expertise in Fingerprint Matching: Experts Can Do a Lot with a Little
Thompson, M. B., & Tangen, J. M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0114759 · Cited by 74 · see citing works
Expertise in Fingerprint Identification
Thompson, M. B., Tangen, J. M., & McCarthy, D. J. (2013) · Journal of Forensic Sciences · doi:10.1111/1556-4029.12203 · Cited by 71 · see citing works
Face processing: Systems, Disorders and Cultural Differences
Bindemann, M. (2017) · Kent Academic Repository (University of Kent) · Cited by 71 · see citing works
Scientific validation of fingerprint evidence under Daubert
Haber, L. R., & Haber, R. N. (2007) · Law Probability and Risk · doi:10.1093/lpr/mgm020 · Cited by 70 · see citing works
The Effect of Feedback on Face‐Matching Accuracy
Alenezi, H. M., & Bindemann, M. (2013) · Applied Cognitive Psychology · doi:10.1002/acp.2968 · Cited by 68 · see citing works
More than Zero: Accounting for Error in Latent Fingerprint Identification
Cole, S. A. (2005) · bepress Legal Repository · Cited by 58 · see citing works
Finding needles in haystacks: Identity mismatch frequency and facial identity verification.
Bindemann, M., Avetisyan, M., & Blackwell, K.-A. (2010) · Journal of Experimental Psychology Applied · doi:10.1037/a0021893 · Cited by 56 · see citing works
Infrequent identity mismatches are frequently undetected
Papesh, M. H., & Goldinger, S. D. (2014) · Attention Perception & Psychophysics · doi:10.3758/s13414-014-0630-6 · Cited by 54 · see citing works
Using cognitive psychology research to inform professional visual search operations
Biggs, A. T., Kramer, M. R., & Mitroff, S. R. (2018) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2018.04.001 · Cited by 53 · see citing works
The Application of Signal Detection Theory to Decision-Making in Forensic Science
Phillips, V., Saks, M. J., & Peterson, J. (2001) · Journal of Forensic Sciences · doi:10.1520/jfs14962j · Cited by 51 · see citing works
Decision processes in visual search as a function of target prevalence.
Peltier, C., & Becker, M. W. (2016) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/xhp0000248 · Cited by 49 · see citing works
The effects of increasing target prevalence on information processing during visual search
Godwin, H. J., Menneer, T., Cave, K. R., Thaibsyah, M., & Donnelly, N. (2015) · Psychonomic Bulletin & Review · doi:10.3758/s13423-014-0686-2 · Cited by 44 · see citing works
The prevalence effect is determined by past experience, not future prospects
Lau, J. S.-H., & Huang, L. (2010) · Vision Research · doi:10.1016/j.visres.2010.04.020 · Cited by 44 · see citing works
The Error in ‘Error Rate’: Why Error Rates Are So Needed, Yet So Elusive
Dror, I. E. (2020) · Journal of Forensic Sciences · doi:10.1111/1556-4029.14435 · Cited by 43 · see citing works
Nakashima, R., Kobayashi, K., Maeda, E., Yoshikawa, T., & Yokosawa, K. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00166 · Cited by 41 · see citing works
Spatial and temporal separation fails to counteract the effects of low prevalence in visual search
Kunar, M. A., Rich, A. N., & Wolfe, J. M. (2010) · Visual Cognition · doi:10.1080/13506280903361988 · Cited by 37 · see citing works
The Emergence of Perceptual Expertise with Fingerprints Over Time
Searston, R. A., & Tangen, J. M. (2017) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2017.08.006 · Cited by 35 · see citing works
Are forensic scientists experts?
Towler, A., White, D., Ballantyne, K. N., Searston, R. A., Martire, K. A., & Kemp, R. I. (2018) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2018.03.010 · Cited by 35 · see citing works
Growns, B., & Martire, K. A. (2020) · Forensic Science International Synergy · doi:10.1016/j.fsisyn.2020.05.001 · Cited by 34 · see citing works
Self-citationPrevalence-based decisions undermine visual search
Schwark, J., MacDonald, J. A., Sandry, J. D., & Dolgov, I. (2013) · Visual Cognition · doi:10.1080/13506285.2013.811135 · Cited by 33 · see citing works
Papesh, M. H., Heisick, L. L., & Warner, K. A. (2018) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000156 · Cited by 30 · see citing works
Kunar, M., Watson, D., Taylor-Phillips, S., & Wolska, J. (2017) · Journal of experimental psychology. Applied · doi:10.1037/xap0000132 · Cited by 27 · see citing works
Wrongful convictions and the Blackstone ratio: An empirical analysis of public attitudes
Keijser, J. W. D., de Lange, E., & van Wilsem, J. (2014) · Punishment & Society · doi:10.1177/1462474513504800 · Cited by 26 · see citing works
Nakashima, R., Watanabe, C., Maeda, E., Yoshikawa, T., Matsuda, I., Miki, S., & Yokosawa, K. (2014) · Psychological Research · doi:10.1007/s00426-014-0616-y · Cited by 20 · see citing works
Juror appraisals of forensic evidence: Effects of blind proficiency and cross-examination
Crozier, W. E., Kukucka, J., & Garrett, B. L. (2020) · Forensic Science International · doi:10.1016/j.forsciint.2020.110433 · Cited by 16 · see citing works
Self-citationGrowns, B., & Martire, K. A. (2020) · Journal of Experimental Psychology Applied · doi:10.1037/xap0000266 · Cited by 16 · see citing works
Self-citationWeatherford, D. R., Erickson, W. B., Thomas, J., Walker, M. E., & Schein, B. (2020) · Cognitive Research Principles and Implications · doi:10.1186/s41235-019-0204-1 · Cited by 16 · see citing works
Xiong, M., Greenleaf, R. G., & Goldschmidt, J. (2016) · International journal of law, crime and justice · doi:10.1016/j.ijlcj.2016.10.001 · Cited by 15 · see citing works
Influence of being videotaped on the prevalence effect during visual search
Miyazaki, Y. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00583 · Cited by 11 · see citing works
Flagged first, then by citations
1 of the 60 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Quigley‐McBride, A., Dror, I. E., Roy, T., Garrett, B. L., & Kukucka, J. (2022) · Forensic Science International Synergy · doi:10.1016/j.fsisyn.2022.100216 · Cited by 45 · see citing works
Self-citationInconclusives and error rates in forensic science: a signal detection theory approach
Arkes, H. R., & Koehler, J. J. (2021) · Law Probability and Risk · doi:10.1093/lpr/mgac005 · Cited by 36 · see citing works
Kunkler, K. S., & Roy, T. (2023) · Forensic Science International Synergy · doi:10.1016/j.fsisyn.2023.100341 · Cited by 31 · see citing works
Biased and biasing: the hidden bias cascade and bias snowball effects
Dror, I. E. (2025) · Behavioral Sciences · doi:10.3390/bs15040490 · Cited by 29 · see citing works
Match me if you can: Evidence for a domain-general visual comparison ability
Growns, B., Dunn, J. D., Mattijssen, E. J. A. T., Quigley‐McBride, A., & Towler, A. (2022) · Psychonomic Bulletin & Review · doi:10.3758/s13423-021-02044-2 · Cited by 28 · see citing works
Self-citationFeedback moderates the effect of prevalence on perceptual decisions
Lyu, W., Levari, D. E., Nartker, M. S., Little, D. S., & Wolfe, J. M. (2021) · Psychonomic Bulletin & Review · doi:10.3758/s13423-021-01956-3 · Cited by 18 · see citing works
Wolfe, J. M. (2022) · Cognitive Research Principles and Implications · doi:10.1186/s41235-022-00362-0 · Cited by 11 · see citing works
Growns, B., Towler, A., Dunn, J. D., Salerno, J. M., Schweitzer, N. J., & Dror, I. E. (2022) · Cognitive Research Principles and Implications · doi:10.1186/s41235-022-00413-6 · Cited by 11 · see citing works
Self-citationThe low prevalence effect in fingerprint comparison amongst forensic science trainees and novices
Growns, B., Dunn, J. D., Helm, R. K., Towler, A., & Kukucka, J. (2022) · PLoS ONE · doi:10.1371/journal.pone.0272338 · Cited by 9 · see citing works
Self-citationRath, H. J., Rocha, B., Smith, A. M., & Smalarz, L. (2025) · Behavioral Sciences · doi:10.3390/bs15091191 · Cited by 3 · see citing works
Forensic Science Decision-Making
Growns, B., & Neal, T. M. S. (2024) · Cambridge University Press eBooks · doi:10.1017/9781009119375.013 · Cited by 5 · see citing works
Self-citationA guide to measuring expert performance in forensic pattern matching
Robson, S. G., Searston, R. A., Thompson, M. B., & Tangen, J. M. (2024) · Behavior Research Methods · doi:10.3758/s13428-024-02354-y · Cited by 3 · see citing works
Examiner consistency in perceptions of fingerprint minutia rarity
Quigley‐McBride, A., Eldridge, H., & Gardner, B. O. (2024) · Forensic Science International · doi:10.1016/j.forsciint.2024.112244 · Cited by 2 · see citing works
Lyu, W., Trueblood, J. S., & Wolfe, J. M. (2025) · Cognitive Research · doi:10.1186/s41235-025-00632-7 · Cited by 2 · see citing works
Amaral, M. E. A., & Bruni, A. T. (2023) · Revista Brasileira de Direito Processual Penal · doi:10.22197/rbdpp.v9i2.819 · Cited by 2 · see citing works
Quigley‐McBride, A., & Blackall, T. L. (2025) · Behavioral Sciences · doi:10.3390/bs15091145 · Cited by 1 · see citing works
On the Importance of Recognition and Mitigation of Bias in Forensic Science
Davis, D., Miller, G. A., Hart, D. J., & Hogan, A. A. (2024) · Springer eBooks · doi:10.1007/978-3-031-56556-4_5 · Cited by 1 · see citing works
Biedermann, A., & Champod, C. (2024) · The International Journal of Evidence & Proof · doi:10.1177/13657127241278069 · Cited by 1 · see citing works
Face processing in photographic identity documents
Feng, X. (2021) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)
An Efficient Fingerprint Extraction and Matching Algorithm for Imaging Device
Geng, Y., Li, Y., Zhang, X., & Jin, A. (2025) · International Conference on Vision, Image and Signal Processing (ICVISP) · doi:10.1109/icvisp68610.2025.11451681
- Authors
- Growns, B., & Kukucka, J.
- Affiliations
- Arizona State University (US)
- Towson University (US)
- Corresponding author
- Growns, Bethany
- Venue
- Applied Cognitive Psychology
- Publisher
- Wiley
- Published
- 2021-02-12
- Volume
- 35
- Issue
- 3
- Pages
- 751-760
- ISSN
- 0888-4080 (ISSN-L)
- 1099-0720
- OpenAlex
- W3126621167
- Cited by
- 20
- References
- 60
- Citations by year
- 2025: 5 · 2024: 5 · 2023: 2 · 2022: 5 · 2021: 3
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Applied Cognitive Psychology (publishedVersion)
- UC Research Repository (University of Canterbury) (submittedVersion)
- Funders
- National Science Foundation (1823741)
- Towson University
- Topics
- Social Sciences › Psychology › Social Psychology › Deception detection and forensic psychology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- fingerprint recognition, target prevalence, base rates, false alarms, Miss, feedback, bias, sensitivity, forensic identification, visual comparison
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
