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Serial Sexual Assaults: A Longitudinal Examination of Offending Patterns Using DNA Evidence

NCJ Number
252707
Date Published
Author(s)
Rebecca Campbell, Steven J. Pierce, Dhruv Sharma, Hannah Feeney, Rachael Goodman-Williams, Wenjuan Ma
Annotation
In order to estimate the frequency of serial sexual assaults, this study used the DNA testing of sexual assault kit (SAK) biological evidence, followed by submission of the DNA to CODIS, so as to determine whether the DNA of the SAK offender matched the DNA of unknown offenders from other sexual assault investigations.
Abstract
The study’s starting query involved a sample of about 7,000 previously untested SAKs from Detroit, Michigan. The study examined how many sex offenders with DNA left at a crime scene committed more than one sexual assault, based on DNA matches in CODIS from other sexual assaults identified through a criminal history records check. For the offenders who were suspected of committing multiple sexual assaults (based on CODIS and criminal history record data), researchers used growth mixture models to identify their patterns of serial sexual offending over time. The rates of repeat sexual offending documented in this study (39.7 percent of unique and identifiable perpetrators) are higher than recidivism studies (typically 10-15 percent); however, the current study’s data sources may also underestimate actual offending, because many sexual assault victims do not have a SAK collected and/or report their assault to the criminal justice system. Even with these caveats, however, the researchers argue that using CODIS data and criminal history records are still a useful and credible data source for studying patterns of sexual assault offending. The sizeable number of serial sex offenders identified in this study should encourage law enforcement investigators to view investigations as likely serial, rather than first-time offenses. They should also view the testing of SAKs as a high priority for this reason. 3 tables, 2 figures, 27 references, and appended supplementary data
Date Created: March 24, 2019