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Being accurate about accuracy in verbal deception detection

PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accura...

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Detalles Bibliográficos
Autores principales: Kleinberg, Bennett, Arntz, Arnoud, Verschuere, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687387/
https://www.ncbi.nlm.nih.gov/pubmed/31393894
http://dx.doi.org/10.1371/journal.pone.0220228
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author Kleinberg, Bennett
Arntz, Arnoud
Verschuere, Bruno
author_facet Kleinberg, Bennett
Arntz, Arnoud
Verschuere, Bruno
author_sort Kleinberg, Bennett
collection PubMed
description PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accuracy of a method is to find the optimal statistical separation between lies and truths in a single dataset. However, this method lacks safeguards against accuracy overestimation. METHOD & RESULTS: A simulation study and empirical data show that this procedure produces overoptimistic accuracy rates that, especially for small sample size studies typical of this field, yield misleading conclusions up to the point that a non-diagnostic tool can be shown to be a valid one. Cross-validation is an easy remedy to this problem. CONCLUSIONS: We caution psycholegal researchers to be more accurate about accuracy and propose guidelines for calculating and reporting accuracy rates.
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spelling pubmed-66873872019-08-15 Being accurate about accuracy in verbal deception detection Kleinberg, Bennett Arntz, Arnoud Verschuere, Bruno PLoS One Research Article PURPOSE: Verbal credibility assessments examine language differences to tell truthful from deceptive statements (e.g., of allegations of child sexual abuse). The dominant approach in psycholegal deception research to date (used in 81% of recent studies that report on accuracy) to estimate the accuracy of a method is to find the optimal statistical separation between lies and truths in a single dataset. However, this method lacks safeguards against accuracy overestimation. METHOD & RESULTS: A simulation study and empirical data show that this procedure produces overoptimistic accuracy rates that, especially for small sample size studies typical of this field, yield misleading conclusions up to the point that a non-diagnostic tool can be shown to be a valid one. Cross-validation is an easy remedy to this problem. CONCLUSIONS: We caution psycholegal researchers to be more accurate about accuracy and propose guidelines for calculating and reporting accuracy rates. Public Library of Science 2019-08-08 /pmc/articles/PMC6687387/ /pubmed/31393894 http://dx.doi.org/10.1371/journal.pone.0220228 Text en © 2019 Kleinberg et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kleinberg, Bennett
Arntz, Arnoud
Verschuere, Bruno
Being accurate about accuracy in verbal deception detection
title Being accurate about accuracy in verbal deception detection
title_full Being accurate about accuracy in verbal deception detection
title_fullStr Being accurate about accuracy in verbal deception detection
title_full_unstemmed Being accurate about accuracy in verbal deception detection
title_short Being accurate about accuracy in verbal deception detection
title_sort being accurate about accuracy in verbal deception detection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687387/
https://www.ncbi.nlm.nih.gov/pubmed/31393894
http://dx.doi.org/10.1371/journal.pone.0220228
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