Predictive Power of Dynamic (vs. Static) Risk Factors in the Finnish Risk and Needs Assessment Form

A1 Originalartikel i en vetenskaplig tidskrift (referentgranskad)

Interna författare/redaktörer

Publikationens författare: Salo B, Laaksonen T, Santtila P
Publiceringsår: 2019
Tidskrift: Criminal Justice and Behavior
Tidskriftsakronym: CRIM JUSTICE BEHAV
Volym: 46
Nummer: 7
Artikelns första sida, sidnummer: 939
Artikelns sista sida, sidnummer: 960
Antal sidor: 22
ISSN: 0093-8548


We estimated the predictive power of the dynamic items in the Finnish Risk and Needs Assessment Form (Riski- ja tarvearvio [RITA]), assessed by caseworkers, for predicting recidivism. These 52 items were compared to static predictors including crime(s) committed, prison history, and age. We used two machine learning methods (elastic net and random forest) for this purpose and compared them with logistic regression. Participants were 746 men who had and 746 who had not reoffended during matched follow-up periods from 0.5 to 5.8 years. Both RITA items and static predictors predicted general and violent recidivism well (area under the curve [AUC] = .74-.78), but to combine them increased discrimination only slightly over static predictors alone (Delta AUC = .01-.03). Calibration was good for all models. We argue that the results show strong potential for the RITA items, but that development is best focused on improving usability for identifying treatment targets and for updating risk assessments.


dynamic risk factors, recidivism, risk and needs assessment, RITA

Senast uppdaterad 2020-29-03 vid 04:52