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Related Experiment Videos

Effects of outside issues on the comparison question test.

Charles R Honts1, Susan Amato, Anne Gordon

  • 1Department of Psychology, Boise State University, Idaho 83725-1715, USA. chonts@boisestate.edu

The Journal of General Psychology
|February 24, 2004
PubMed
Summary

Outside issues significantly impact the validity of the Comparison Question Test (CQT), falsely labeling innocent individuals as deceptive. This finding is crucial for understanding false positive rates in CQT applications.

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Area of Science:

  • Psychology
  • Forensic Science
  • Criminology

Background:

  • The Comparison Question Test (CQT) is a widely used polygraph technique for deception detection.
  • Concerns exist regarding the CQT's validity, particularly in real-world scenarios where extraneous factors may influence results.

Purpose of the Study:

  • To investigate the impact of an "outside issue" on the accuracy of the CQT.
  • To determine if the CQT can reliably differentiate between guilty and innocent individuals when extraneous issues are present.

Main Methods:

  • A laboratory mock-crime study was conducted with 192 participants.
  • A 2x2x2 factorial design examined mock theft (tested issue) and an "outside issue" (e.g., a separate theft).
  • Participants were tested using the CQT, with some also asked questions about the outside issue.

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Main Results:

  • The presence of an outside issue significantly increased false positive outcomes, moving scores of innocent participants towards deception.
  • The impact of the outside issue on guilty participants was minimal.
  • Questions about outside issues did not effectively detect the outside issue but served as comparison questions.

Conclusions:

  • Extraneous "outside issues" can compromise the validity of the CQT, leading to inaccurate deception assessments.
  • The findings highlight a critical limitation of the CQT, potentially explaining high false positive rates in certain applications.
  • Further research is needed to refine polygraph techniques to mitigate the influence of confounding variables.