The Structure of Deception: Validation of the Lying Profile Questionnaire

Abstract

While deception is considered as a common phenomenon with important implications, its conceptualization and study as a dispositional trait is under-represented in the literature. Critically, and despite scientific evidence supporting the existence of individual differences in lying, a validated measure of dispositional deception is still lacking. This study aims to explore the structure of dispositional deception by developing and validating a short and reliable 16-item questionnaire to characterize the lying pattern of individuals. Our findings suggest the existence of four distinct latent dimensions to lying, namely frequency, ability, negativity, and contextuality. We establish the convergent validity of our measure of lying by showing significant relationships with social desirability, malevolent traits, cognitive control deficits, normal and pathological personality traits, as well as demographic variables such as sex, age, and religiosity. Overall, the present study introduces a general framework to understanding deception as a dispositional trait which future deception studies can build on, accounting for the inter-individual variability in lying.

Long-Short Ensemble Network for Bipolar Manic-Euthymic State Recognition Based on Wrist-worn Sensors

“…During processing, a low-pass butterworth filter of order 4 at 1.5Hz is applied to better capture both the tonic and phasic component of the signal [12]. From the cleaned signal, a high-pass butterworth filter of order 2 at 0.05Hz is applied to extract the phasic component of the signal [11], [12]. Skin Conductance Response (SCR) peaks are then identified by extracting the local maxima of the filtered signal, rejecting peaks with an amplitude below 10% of the standard deviation from the mean of the amplitude as implemented in [11].…”

“…Within this work, a band-pass butterworth filter of order 3 was applied between 0.5 and 8Hz to the signal. The systolic peaks were then extracted from the filtered signal based on the method described in [13] and implemented in [11]. The distances between these peaks are referred to as NN to emphasize the fact that abnormal beats have been removed [7].…”