Abstract

Previous research on statement analysis has mainly concerned accounts by witnesses and plaintiffs. In our studies we examined true and false statements as told by offenders. It was hypothesized that SVA and MASAM techniques would enhance the ability to discriminate between true and false offenders' statements. Truthful and deceptive statements (confessions and denials) were collected from Swedish and Polish criminal case files. In Experiment 1, Swedish law students (N = 39) were asked to assess the veracity of statements either after training in and usage of MASAM or without any training and using their own judgements. In Experiment 2, Polish psychology students (N = 34) assessed veracity after training in and usage of either MASAM or SVA or without prior training using their own judgements. The veracity assessments of participants who used MASAM and SVA were significantly more correct than the assessments of participants that used their own judgements. Results show, that trained coders are much better at distinguishing between truths and lies than lay evaluators. There were significant difference between total scores of truthful and false statements for both total SVA and MASAM and it can be concluded that both veracity assessment techniques are useful in assessing veracity. It was also found, that the content criteria most strongly associated with correct assessments were: logical structure, contextual embedding, self—depreciation, volume of statement, contextual setting and descriptions of relations. The results are discussed in relation to statement analysis of offenders' accounts.

Highlights

  • Enhancing legal actors ability to make correct suspects’ statements veracity judgments is of pivotal importance both during criminal investigations and court proceedings

  • Coders from the Uppsala University using Multivariable Adults’ Statements Assessment Model (MASAM) reached a total accuracy rate of 70.03% (250 out of 357), truthful accounts were correctly classified in 77.53% of the cases (144 among 183) and false statements were correctly classified in 61.22% of the cases (106 among 174)

  • The overall accuracy of MASAM veracity assessment was significantly higher than both: rating with the use of Statement Validity Assessment (SVA) (χ2 = 8.28, p < .005) and judgment without training (χ2 = 106.12, p < .001); SVA ratings were significantly more accurate than ratings without the use of content analysis method (χ2 = 60.31, p < .001)

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Summary

Introduction

Enhancing legal actors ability to make correct suspects’ statements veracity judgments is of pivotal importance both during criminal investigations and court proceedings. The underlying assumptions in verbal lie detection are that truth tellers exhibit coherence between statement and belief, whereas liars experience a discrepancy between the two[5], that liars have to think harder and that they try more than truth-tellers to make a convincing impression[4], and that people talk in different ways about events which are based upon their experience in comparison to what they only have imagined and fabricated [3,4,5].As a result of previous research there are several known speech content criteria—based techniques available today. Results of previous studies suggest, that MASAM is a useful tool discerning between memories of self-experienced real—life events and fabricated or fictitious accounts [10]

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