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June 1, 2026International Journal of Offender Therapy and Comparative Criminology0 citations

How to Combine the Static-99R With the SAPROF-SO

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DTDavid ThorntonMOMark E. OlverNGNorma E. Garza

Key Points

  • This research aims to explore how protective factors in the SAPROF-SO influence the recidivism risk inferred from Static-99R scores.
  • Data collected from 467 men with sexual offending history in Canada and New Zealand
  • Used logistic regression to analyze the predictive power of Static-99R and SAPROF-SO
  • Developed an Excel-based calculator for clinical application of findings
  • Both Static-99R and SAPROF-SO scores predicted 5-year sexual recidivism
  • The presence of protective factors significantly moderated the risk implied by Static-99R scores
  • Clinical assessment can benefit from integrating both tools to better gauge recidivism risk.

Abstract

The SAPROF-SO was developed as a measure of protective factors relevant to sexual recidivism to support a balanced, holistic assessment of recidivism risk. Traditionally, sexual recidivism risk has been largely understood in terms of the density of risk factors presented by the individual, as measured by instruments like the Static-99R. This paper investigated how far the recidivism risk implied by a Static-99R score would be moderated by the presence of protective factors as measured by the SAPROF-SO Version 1. Data representing 5-year sexual recidivism, along with scores on Static-99R and the SAPROF-SO Version 1, were collated from previously collected samples of men with a history of sexual offending who had been selected for prison treatment programs designed to reduce sexual recidivism risk in Canada and New Zealand, giving a combined sample of N = 467. Fitting a logistic regression equation to predict 5-year sexual recidivism indicated that both instruments were predictive, with the SAPROF-SO powerfully moderating the level of risk implied by Static-99R scores. Implications for clinical assessment are discussed and an Excel-based calculator implementing the logistic regression equation was developed for clinical use.

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Cite This Study

Thornton et al. (2026) studied this question.

synapsesocial.com/papers/6a1d236002fbce9130638ff4https://doi.org/10.1177/0306624x261456066
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