Computers in Human Behavior Reports (Jan 2021)
New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)
Abstract
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.