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January 3, 2020

"The Effectiveness of Prison Programming: A Review of the Research Literature Examining the Impact of Federal, State, and Local Inmate Programming on Post-Release Recidivism"

The title of this post is the title of this notable new research document authored by James Byrne on Behalf of the First Step Act Independent Review Committee. (Backgound on this important Committee can be found at this link.)  I do not believe that this Committee has yet produced much original substantive material, and I am not sure if this new 42-page research document (which is dated Dec. 2019) is a sign of more to come.  In any event, here is its introduction:

The First Step Act emphasizes the importance of BOP programming as a recidivism reduction strategy and includes sentence-reduction incentives for eligible inmates who participate in “evidence-based recidivism reduction programs.”  This memorandum reviews available research about the recidivism reduction effects of federal, state, and local prison programming in an attempt to determine to what extent such programming can fairly be described as evidence-based.  There are three distinct types of reviews that can be used to establish evidentiary criteria and determine “what works” in the area of prison programming (Byrne and Luigio, 2009).  The most rigorous such review would focus narrowly on the results of high quality, well-designed randomized control trials (RCTs) conducted during a specified period.  A minimum of two RCTs demonstrating effectiveness (and a preponderance of lower-level research studies producing similar results) would be necessary before a determination could be offered about whether a particular program or strategy “worked.”  This is the type of review strategy and scientific evidence relied on in the hard sciences.

A second review strategy allows identification of a program as evidence-based (or working) if there are at least two quasi-experimental studies with positive findings, and the majority of lower-quality studies point in the same direction.  This is the approach used in the reviews produced by the Campbell Collaborative.  A variation on this approach — representing a third type of evidence-based review — is found on the DOJ CrimeSolutions.gov website, where a program will be described as effective based on a rating of each applicable research study by two independent reviewers.

To be rated as effective, at least one high quality evaluation — RCT or well-designed quasi-experiment — needs to be identified.  This memorandum adopts the second standard described above to summarize the research under review (see Appendix B), but we have also examined all studies and reviews of prison programs identified by CrimeSolutions.gov.

Included in this review is a careful look at the available evaluation research on the BOP programming, focusing on the 18 “national model” prison programs identified by BOP.  Also included in this review is an examination of the much larger body of evaluation research conducted on the recidivism reduction effects of state and local prison programs.  This memorandum offers summary assessments of all relevant evaluation research and corresponding recommendations for DOJ and BOP to consider as they move to implement high quality, evidence-based programming in the federal prison system.

And here is a key paragraph labelled "Conclusion" after a detailed substantive discussion (with emphasis in original):

Completion of prison programming by federal prisoners does appear to provide an important signal that these individuals have begun to address — via BOP programming — problems that we know are linked to criminality: substance abuse, mental health deficits, and lack of education and/or employment skills.  However, a careful review of the evaluation research strongly suggests that the likely effects of participation in current prison programming on both treatment outcomes (i.e. improvement in identified need areas) and post release behavior are—statistically speaking—significant but marginal (i.e. about a .10 absolute difference between treatment and control groups is the likely result were these programs rigorously evaluated).  While prison programming is certainly one piece of the desistance puzzle, it appears that individuals will desist from crime upon release from prison based on a variety of individual and community level factors not directly related to the availability and/or quality of prison programming.  For this reason, accurate prison-based risk/need classification that links inmates at different risk/need levels to appropriate evidence-based prison programming should be followed by evidence-based reentry programming (Cullen, 2013).  While this report focuses on prison programming, we recognize the critical role of reentry programming and community context (e.g. structure, support, resources, location) in the desistance process.

January 3, 2020 at 03:10 PM | Permalink

Comments

Doug:

This is,by far, the most important issue with all the first step and second chance efforts.

For decades, we have know that recidivism rates have been extremely high and we only solve about 25% of crimes.

You, rightly, highlighted this:

"individuals will desist from crime upon release from prison based on a variety of individual and community level factors not directly related to the availability and/or quality of prison programming."

That has been my repeated concern within this blog.

Sociopath's won't change their ways, but some others will.

I have followed "Bridges to Life" for a very long time. They have an astoundingly low recidivism rate.

Posted by: Dudley Sharp | Jan 4, 2020 8:46:45 AM


http://www.aiobjectives.com/2019/12/03/world-of-post-humanism-and-artificial-intelligence/


Posthumanism is a philosophical perspective of how change is enacted in the world.
As a conceptualization and historicization of both agency and the “human,”
it is different from those conceived through humanism.
and what is the futuer of research in humanisim, and we explain different tools and
applications, and we are comparision of different appliocations,

Posted by: Aiobjectives | Jan 9, 2020 5:29:29 AM

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