Verbal Lie Detection: Its Past, Present and Future.

Area of Science:

• Psychology
• Forensic Science
• Linguistics

Background:

• Verbal lie detection research originated in the 1970s, focusing on the link between deception and specific word usage.
• Key developments include Criteria-Based Content Analysis (CBCA), Reality Monitoring (RM), and Scientific Content Analysis (SCAN) as veracity assessment tools.
• The mid-2000s saw the rise of 'Interviewing to deception' with protocols designed to elicit verbal cues.

Purpose of the Study:

• To provide a comprehensive overview of the evolution of verbal lie detection research.
• To examine the methodologies, theoretical underpinnings, and effectiveness of various lie detection techniques.
• To explore the potential contributions of neuroscience to improving verbal lie detection.

Main Methods:

• Review of historical and contemporary research in verbal lie detection.
• Analysis of content analysis tools: Criteria-Based Content Analysis (CBCA), Reality Monitoring (RM), and Scientific Content Analysis (SCAN).
• Examination of interview protocols: Strategic Use of Evidence (SUE), Verifiability Approach (VA), Cognitive Credibility Assessment (CCA), and Reality Interviewing (RI).

Main Results:

• Established verbal criteria tools (CBCA, RM, SCAN) offer methods for veracity assessment.
• Interview protocols (SUE, VA, CCA, RI) aim to enhance the detection of deception through specific questioning strategies.
• Significant differences and similarities exist between these various content analysis and interview approaches.

Conclusions:

• Verbal lie detection has progressed from simple word analysis to sophisticated content analysis and interview techniques.
• Understanding the nuances of these methods is crucial for accurate veracity assessment.
• Neuroscience holds promise for advancing the field of verbal lie detection by providing new insights and improving existing methods.