How important are age and motivation to change in rehabilitation programs?

How important are age and motivation to change in rehabilitation programs?

When attempting to change criminal behavior through rehabilitation, clinicians should pay attention to clients’ age and level of motivation because greater maturity and motivation are strengths related to program effectiveness for those individuals. This is the bottom line of a recently published article in Law and Human Behavior. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | Law and Human Behavior | 2019, Vol. 43, No. 6, 558-567

Age and Motivation Can Be Specific Responsivity Features That Moderate the Relationship Between Risk and Rehabilitation Outcome

Authors

Cole A. Higley, University of Texas at El Paso
Caleb D. Lloyd, Centre for Forensic Behavioural Science, Swinburne University of Technology
Ralph C. Serin, Carleton University

Abstract

Objective: Specific responsivity features are not directly targeted in offender rehabilitation programs but may impact a client’s receptivity. We investigated if two features may explain why high-quality correctional programs do not uniformly impact all high-risk, high-needs clients. Hypotheses: The current study was exploratory. We hypothesized a relationship between higher static risk and poorer program outcomes and then explored if this relationship was attenuated by age and motivation. Method: Program providers rated the performance of incarcerated males (n = 2,417, Mean age = 33.6, SD = 9.9, Range = 18 – 81) who attended one of six types of programs during incarceration (for general, violent, and sexual offenders). Using risk scores calculated at prison entry, we predicted performance and official record recidivism. Preprogram motivation and age were moderators. Results: Five of 24 exploratory multilevel models revealed an attenuated relationship between risk and program outcome among older offenders (percent variance explained = 17.9% within violence groups; 11.5% within living skills groups; and a 9% difference in predicted recidivism rates among high-risk attendees of family violence groups) and offenders with higher preprogram motivation (percent variance explained = 43.6% within violence groups, and a 7% difference in predicted recidivism rates among high risk attendees in living skills groups). Conclusions: Age and motivation can be specific responsivity features that may deserve attention in rehabilitation practice. However, observed effects may have been weakened by underdeveloped, single-indicator measurement strategies.

Keywords

specific responsivity, age, motivation, rehabilitation, risk

Summary of the Research

“Key elements that underlie effective correctional programs are well known, but high-quality correctional programs do not have uniform impact on all participants. The Risk-Need-Responsivity (RNR) model of criminal rehabilitation inherently posits differential program impact, such that stronger effects should occur among participants of higher static risk (the risk principle) and higher criminogenic needs, if those individualized needs are effectively targeted in assigned programs. However, program success still varies among high-risk, high-need participants” (p. 558-559).

“The remaining features assumed to be relevant to this variation are often situated within the responsivity principle. The principle of general responsivity states that programs should use strategies empirically related to behavior change, specifically cognitive–behavioral and social learning techniques. By contrast, the principle of specific responsivity states that correctional programs should be designed and adapted to maximize participants’ receptivity and engagement, either by taking advantage of existing prosocial traits or effectively counteracting any traits that will hinder participation. Polaschek (2012) critiqued the current state of knowledge about the principle of specific responsivity for representing an unfocused “kitchen sink” approach whereby any potentially relevant clinical features among program clients are subsumed into a broad, ill-defined category that is characterized by relatively weak empirical evidence. Overall, there is surprisingly little evidence from applied correctional rehabilitation research among adult clients regarding which clinically relevant traits (a) moderate successful program completion, (b) deserve consideration as established features of specific responsivity, and thus (c) may require strategic attention from clinicians and program facilitators to increase the effectiveness of interventions” (p. 559).

“The purpose of the current study was to examine the relationship between criminal history risk and rehabilitation program outcomes in the context of age and motivation to change. Although the current study is exploratory, we initially expected an association between higher static risk and poorer program performance, and then expected to observe an attenuation of this association in the presence of older age and higher motivation for change. The present large sample of adult males who participated in correctional programs while incarcerated is relatively unique, given much prior work on specific responsivity features has focused upon juvenile program attendees” (p. 560).

“Given we examined six separate samples (drawn from different types of correctional program) in our exploratory models, statistically significant results were inconsistently found. We are unsure whether the pattern of results signifies a meaningful pattern, and our primary conclusion is that further efforts to replicate the present findings is warranted, preferably using more comprehensive and prospective measurement of motivation and psychosocial maturity. However, we also hypothesize that the attenuating effects of motivation and older age may be stronger among individuals with more complex criminal histories and levels of need (i.e., in the violence, family violence, and living skills domains), since we observed moderating effects only in these groups (using the best measures available in the routinely collected dataset, but that had clear conceptual shortcomings)” (p. 565).

“We also speculate that there may be more consistent and informative results if future researchers pay greater attention to conceptualizing and measuring the psychological underpinnings of these two moderating variables. Specifically, we suggest that it is worth considering what components are relevant within the ill- defined concept of age-related maturity and various ways to measure these components among participants of rehabilitation pro- grams. Similarly, although more conceptual and empirical work has examined motivation within rehabilitation programs, this multifaceted concept deserves greater exploration and definition (including examining its component parts of cognitive, emotional, and behavioral indicators). Overall, the results support that non-criminogenic specific responsivity factors are important considerations when attempting to enhance prosocial behavioral change, and rehabilitation processes should be considered as occurring within an intrapersonal, interpersonal, and environmental context” (p. 566).

Translating Research into Practice

“Analyses suggest that age and motivation to change may not be universal specific responsivity factors among all offender groups in all programs, but among some of our samples, older age and higher preprogram motivation were associated with improved outcomes to a higher degree than expected, given simultaneous levels of risk. Specifically, in five of the 24 models we explored, the results suggested that noncriminogenic responsivity factors can moderate the relationship between risk and outcome (program performance and future recidivism). Thus, these noncriminogenic responsivity factors were not direct risk factors but nonetheless appeared to attenuate the effect of risk on outcome. Thus, results suggest practitioners may have opportunities to capitalize on the waning influence of risk among older clients (as defined in this study, starting at mid-to-late 30s) and those that present as more motivated to change. In addition, because motivation, unlike age, is malleable, the results support the use of preprogram primers to engage clients to increase motivation to change prior to the start of a correctional program, more comprehensive assessments of motivation, and motivational engagement techniques within programs. Specifically, our results suggest that utilizing motivational interviewing techniques would be a meaningful investment toward increasing post-program success among participants in violence reduction and living skills programs, if those techniques can successfully engage participants to move beyond merely contemplating change toward preparing for and engaging in action toward change. Drawing from MORM’s [Multifactor Offender Readiness Model] conceptualization of the fit between individual and program goals, we suspect it would be a good investment for facilitators to spend time early in a program helping participants consider how the program’s learning goals may benefit their personal goals” (p. 565).

Other Interesting Tidbits for Researchers and Clinicians

“Nevertheless, the current study provides justification for rehabilitation researchers to pursue further development of theory and measurement surrounding age-related maturity and motivation to change. Both variables show strong promise for being established as clear features of specific responsivity that require greater re- search and clinical attention. If correctional agencies are able to make empirically informed decisions about placing clients in correctional programs that both target criminogenic risk and successfully address noncriminogenic barriers and strengths, those agencies will be in a unique position to more strongly influence positive behavioral change. Future research would benefit from exploring specific process variables (more specific features of specific correctional groups) that may enhance responsivity, increase effort toward changing criminogenic needs, and lead to rehabilitation success” (p. 566).

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Authored by Amanda Beltrani

Amanda Beltrani is a doctoral student at Fairleigh Dickinson University. Her professional interests include forensic assessments, professional decision making, and cognitive biases.

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