New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)

The pandemic caused by COVID-19 led to the distribution of excessive pseudoscientific information and fake news that has confused the general population. In the field of forensic psychiatry, lie detection is essential to determine if the witness is telling the truth with the purpose of making fair a...

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Autor principal:	Álex Escolà-Gascón
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Lie-detection techniques CBCA Forensic psychiatry Witness credibility Fake news Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
Acceso en línea:	https://doaj.org/article/a1c96d2b8409422ab764ba5ae4e537bf
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spelling	oai:doaj.org-article:a1c96d2b8409422ab764ba5ae4e537bf2021-12-01T05:03:38ZNew techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)2451-958810.1016/j.chbr.2020.100049https://doaj.org/article/a1c96d2b8409422ab764ba5ae4e537bf2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S245195882030049Xhttps://doaj.org/toc/2451-9588The pandemic caused by COVID-19 led to the distribution of excessive pseudoscientific information and fake news that has confused the general population. In the field of forensic psychiatry, lie detection is essential to determine if the witness is telling the truth with the purpose of making fair and effective decisions. In this research, we present a new approach that uses the pseudoscientific beliefs related to COVID-19 and 4 psychometric scales of the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2) to detect and predict lies. A total of 268 participants were classified into two groups: the control group (n = 132) and the quasi-experimental group (n = 136). The quasi-experimental group participants received instructions to lie as they wished in response to a number of questions on a content exam (called exam 1) based on a short children’s film. The participants had to indicate which and how many questions they had lied on. The quasi-experimental group was only required to lie in exam 1. A second exam (called exam 2) was also administered to assess whether the participants could recognize which news items about COVID-19 were false or true. The control group was not required to lie on any exam. Several multiple regression models were applied. The 4 scales of the MMSI-2 predicted 71.2% of the lies for exam 1 and 41.5% of the lies for exam 2. The control group participants obtained lower average scores on exam 1 than the quasi-experimental group in the “F” and “Si” scales. The theory of signal detection is proposed as a possible explanation of the effectiveness of the MMSI-2 scales in lie detection.Álex Escolà-GascónElsevierarticleLie-detection techniquesCBCAForensic psychiatryWitness credibilityFake newsElectronic computers. Computer scienceQA75.5-76.95PsychologyBF1-990ENComputers in Human Behavior Reports, Vol 3, Iss , Pp 100049- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Lie-detection techniques CBCA Forensic psychiatry Witness credibility Fake news Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990
spellingShingle	Lie-detection techniques CBCA Forensic psychiatry Witness credibility Fake news Electronic computers. Computer science QA75.5-76.95 Psychology BF1-990 Álex Escolà-Gascón New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
description	The pandemic caused by COVID-19 led to the distribution of excessive pseudoscientific information and fake news that has confused the general population. In the field of forensic psychiatry, lie detection is essential to determine if the witness is telling the truth with the purpose of making fair and effective decisions. In this research, we present a new approach that uses the pseudoscientific beliefs related to COVID-19 and 4 psychometric scales of the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2) to detect and predict lies. A total of 268 participants were classified into two groups: the control group (n = 132) and the quasi-experimental group (n = 136). The quasi-experimental group participants received instructions to lie as they wished in response to a number of questions on a content exam (called exam 1) based on a short children’s film. The participants had to indicate which and how many questions they had lied on. The quasi-experimental group was only required to lie in exam 1. A second exam (called exam 2) was also administered to assess whether the participants could recognize which news items about COVID-19 were false or true. The control group was not required to lie on any exam. Several multiple regression models were applied. The 4 scales of the MMSI-2 predicted 71.2% of the lies for exam 1 and 41.5% of the lies for exam 2. The control group participants obtained lower average scores on exam 1 than the quasi-experimental group in the “F” and “Si” scales. The theory of signal detection is proposed as a possible explanation of the effectiveness of the MMSI-2 scales in lie detection.
format	article
author	Álex Escolà-Gascón
author_facet	Álex Escolà-Gascón
author_sort	Álex Escolà-Gascón
title	New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
title_short	New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
title_full	New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
title_fullStr	New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
title_full_unstemmed	New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
title_sort	new techniques to measure lie detection using covid-19 fake news and the multivariable multiaxial suggestibility inventory-2 (mmsi-2)
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/a1c96d2b8409422ab764ba5ae4e537bf
work_keys_str_mv	AT alexescolagascon newtechniquestomeasureliedetectionusingcovid19fakenewsandthemultivariablemultiaxialsuggestibilityinventory2mmsi2
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New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)

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