Advances toward validating examiner writership opinion based on handwriting kinematics

• NCJ Number: 304266
• Journal: Forensic Science International Genetics Volume: 318 Dated: January 2021
• Author(s): Danica M. Ommen; Cami Fuglsby; Michael P. Caligiuri
• Date Published: January 2021
• Grant Number(s): 2017-DN-BX-0148
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)
• Award: Kinematic Validation of FDE Determinations about Writership in Questioned Handprinting and Handwriting

Annotation

This study sought to establish the scientific validity of expert writership opinions and the two-stage approach to evidence interpretation using measures derived from research on handwriting motor control.

Abstract

A National Research Council report on strengthening forensic science raised concern over the lack of scientific studies that support the validity of examining and interpreting forensic evidence; however, establishing the foundational validity of subjective methods can be challenging. Regression-based procedures were used to address two experimental issues: 1)  the relative contributions of kinematic and pressure features in predicting examiner support for alternate writership propositions when examining pairs of questioned handwriting samples; and 2) the extent to which information about the rarity of the kinematic feature dissimilarity scores improves the accuracy of a predictive model based on dissimilarity alone. Regarding the first question, the study identified a multifactor model consisting of feature dissimilarity scores and their population distributions having correlation coefficients (R2) of 0.84 and 0.88 for the same-writer and different-writers propositions, respectively. Temporal features contributed up to 21 percent to the predictive value of the model, whereas spatial features contributed only 9 percent and pen pressure contributed up to 17 percent. When models were compared reflecting a single-stage process (based on feature dissimilarities) of forming opinions with models reflecting a two-stage process (based on feature dissimilarities and rarity) the study found that the two-stage models had an average of 15.25 percent greater predictive value than single-stage models. These findings support the scientific validity of FDE writership determinations and underscore the importance of the two-stage approach for evidence interpretation. (publisher abstract modified)