2016), while other authors suggested that indirect behavioral measures could be accurate in detecting deception. However, these validity scales are often comprised of highly transparent items and are thus not always effective in detecting faking therefore, some authors developed different indices, based on the best combination of scales, that could differentiate between honest respondents and fakers (Bosco et al. Most tests include validity scales designed to detect response bias (Paulhus, 2002)-otherwise known as the systematic tendency to answer items of a self-report test in a way that interferes with accurate self-presentation. Indeed, up to 63% of applicants admit to faking on personality tests (Dwight & Donovan, 2003) 50% admit to exaggerating positive qualities, while 60% admit to de-emphasizing negative traits (Donovan, Dwight, & Hurtz, 2003). The general prevalence of faking-good is unknown however, Baer and Miller ( 2002) estimated its rate to be approximately 30% for job applicants. Faking-good, more specifically, is a behavior in which subjects present themselves in a favorable manner, endorsing desirable traits and rejecting undesirable ones. For this reason, test-takers may decide, depending on their motivation, to distort their responses to achieve personal goals such behavior is known as faking (Mazza, Orrù, et al., 2019 Sartori, Zangrossi, Orrù, & Monaro, 2017 Ziegler, MacCann, & Roberts, 2011). However, the most favorable responses to items on these tests are often easily determined. Personality questionnaires are the most popular tool used to measure personality for a variety of purposes, from pre-employment assessment to forensic evaluation (e.g., in the context of child custody hearings), (Burla et al., 2019 Mazza, Orrù, et al., 2019, Mazza, Monaro et al., 2019 Roma, Piccinni, & Ferracuti, 2016 Roma et al., 2013, 2014, 2019).
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Accordingly, the PIM scale was found to be more sensitive in distinguishing between honest and faking-good respondents, demonstrating high classification accuracy (80–83%). Relative to VR items, PIM items are shorter in length and feature no negations. The results showed that, on the PIM scale, faking-good participants were significantly slower in responding than honest respondents. A mixed design was implemented, and predictive models were calculated. A total of 120 volunteers were randomly assigned to one of four experimental groups and asked to respond to the Virtuous Responding (VR) validity scale of the PPI-R and the Positive Impression Management (PIM) validity scale of the PAI via a computer mouse. The main aim of the present study was to explore whether mouse tracking temporal indicators and machine learning models could improve the detection of subjects implementing a faking-good response style when answering personality inventories with four choice alternatives, with and without time pressure.
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Deliberate attempts to portray oneself in an unrealistic manner are commonly encountered in the administration of personality questionnaires.