Predicting Prison Misconducts

Paul Gendreau, Claire Goggin, Moira A. Law

Criminal Justice and Behavior · 1997 · 374 citations · 55 references

Concepts

TL;DR

A meta‑analysis of 39 studies (695 correlations) grouped predictors of prison misconduct into 16 domains, including personal characteristics, situational factors, and actuarial risk measures. The analysis found that personal and situational variables predict misconduct similarly, with antisocial attitudes, criminal history, and institutional factors being strongest, an interview‑based risk protocol yielding the highest actuarial correlations, and violent misconduct predictions showing larger effect sizes, leading to recommendations for assessment.

Abstract

A meta-analysis was conducted on 39 studies that generated 695 correlations with prison misconducts. Predictors of prison misconducts were grouped into 16 domains as follows: (a) personal characteristics ( n = 9), (b) situational factors ( n = 3), and (c) actuarial measures of antisocial personality and risk ( n = 4). Personal and situational variables were similar in their ability to predict prison misconduct. Within these two categories, antisocial attitudes and behavior (e.g., companions, prison adjustment), criminal history, and institutional factors were the strongest predictors. Among actuarial measures, an interview-based risk protocol produced the highest correlations with prison misconducts. The prediction of violent misconducts was associated with greater effect sizes than nonviolent misconducts. Despite the limitations of the database, several recommendations for assessing prison misconducts appear warranted.

References

55