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A practical tool for information management in forensic decisions: Using Linear Sequential Unmasking-Expanded (LSU-E)

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Forensic analysts can reduce bias using procedural frameworks like Linear Sequential Unmasking-Expanded (LSU-E). This study presents a practical worksheet to help implement LSU-E in casework for improved decision quality.

Keywords:
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Area of Science:

  • Cognitive Psychology
  • Forensic Science
  • Decision Analysis

Background:

  • Biasing information can significantly impact forensic analysts' decisions.
  • The sequence of information delivery affects cognitive processing and decision-making in forensic analysis.
  • Existing frameworks like Linear Sequential Unmasking (LSU) and LSU-Expanded (LSU-E) offer research-based guidance for evaluating case information.

Purpose of the Study:

  • To introduce a practical tool for implementing the LSU-E framework in forensic casework.
  • To enhance the quality, repeatability, reproducibility, and transparency of forensic analysts' decisions.
  • To provide concrete guidance for bridging the gap between LSU-E research and practical application.

Main Methods:

  • Development of a practical worksheet based on the LSU-E framework.
  • Focus on parameters such as objectivity, relevance, and biasing power for information prioritization.
  • Guidance for optimal sequencing of information during forensic analysis.

Main Results:

  • The presented worksheet facilitates the practical implementation of LSU-E in forensic disciplines.
  • LSU-E implementation can improve decision quality by reducing cognitive bias.
  • The framework enhances the reliability and transparency of forensic analytical processes.

Conclusions:

  • The LSU-E framework, supported by the practical worksheet, offers a viable method to mitigate bias in forensic decision-making.
  • Implementing LSU-E can lead to more objective and consistent forensic analysis.
  • This approach supports the advancement of forensic science through evidence-based procedural improvements.