Risk Assessment For General Assault And Partner Abusers 2004-04

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Acknowledgements

A special thanks to Bill Sedo and Ron Coles, both of who played an integral part in providing risk assessment information on the probationers. In addition, we wish to acknowledge the work of our research assistants, Tiffany Davis, Erik Gaudreault, and Kim Smallshaw for their coding of the recidivism data and Karl Hanson and Annie Yessine for their helpful comments on an earlier version of this report.

The views expressed are those of the authors and do not necessarily reflect those of Public Safety and Emergency Preparedness Canada or Manitoba Department of Justice (Corrections).

Executive Summary

Assessment of risk and needs is central to offender classification and case management as it assists in assigning levels of supervision and directing services. Although there are validated risk/need instruments that are predictive of general criminal re-offending, it is often believed that these particular tools are inadequate for predicting violent re-offending. Consequently, specialized risk/need assessments are often administered to violent offenders with the belief that these instruments enhance the prediction of specific violent offences such as sexual assault, domestic violence, or general assault.

The present report describes two studies that evaluated two specialized assessment tools: the Secondary Risk Assessment for General Assault (SRA-GA) and the Secondary Risk Assessment for Partner Abusers (SRA-PA). The SRA-GA was designed to assess offenders who are generally assaultive (excluding sexual and domestic assaults). The SRA-PA was designed to assess offenders who are violent in their intimate relationships. Neither of these two specialized risk/need instruments has been validated by previous research.

Study 1 examined the predictive accuracy of the SRA-GA and compared it to a general risk/need assessment tool called the Primary Risk Assessment (PRA). The sample consisted of 444 violent probationers from Manitoba who were followed-up for two years. The results indicated that the SRA‑GA (r = .30, p < .01) and the PRA (r = .30, p < .01) were equally predictive of violent recidivism. Examination of the individual items of the SRA-GA suggested some minor revisions to the instrument; however, these revisions had little impact on the instrument's overall predictive accuracy with violent re-offending (r = .34, p < .01). Additional analyses identified three items that could be added to the PRA to enhance this general instrument for the prediction of violence. However, this too resulted in only minor improvements to its predictive accuracy.

Study 2 examined the accuracy of the SRA-PA and the PRA to predict domestic violence. The sample consisted of 613 probationers with a history or concerns regarding intimate partner violence. The results of the two-year follow-up indicated that the total scores on the SRA-PA (r = .13, p < .01) and the PRA (r = .12, p < .01) were statistically significant but weak predictors of domestic violence recidivism. Analysis of the SRA-PA items found that only one of the 12 items was predictive of domestic violence recidivism. These results suggest that continued use of the SRA-PA is questionable.

Together, the studies suggest that the two specialized risk/need scales in this report did not meaningfully add to predictive accuracy above and beyond general risk/need instruments. Furthermore, the SRA-PA was a particularly poor predictor of domestic violence recidivism. These results highlight the importance of continued evaluative efforts to ensure that whatever assessment tools are being used are empirically supported.

Risk Assessment for General Assault and Partner Abusers

The classification of offenders is critical to the delivery of effective correctional services. Good classification systems determine appropriate levels of supervision and the type and intensity of correctional programs necessary to reduce re-offending. Research has shown that offenders vary in their risk for re-offending and that this risk can be reliably and accurately assessed. The assessment of risk can consist of both static (e.g., age, prior convictions) and dynamic (e.g., employment, substance abuse) risk factors. Dynamic risk factors are commonly referred to as criminogenic needs. Studies suggest that when correctional programs target criminogenic needs at a level of intensity that matches the offender's level of risk, significant reductions in re-offending can occur (see Andrews & Bonta, 2003 for an extensive review).

Assessing risk is an important component of offender classification (other components include, for example, the assessment of needs and resource availability). When it comes to the assessment of offender risk, actuarial based assessment is superior to unstructured clinical judgement (Grove, Zald, Lebow, Snitz & Nelson, 2000). Actuarial methods use explicit criteria for the assessment of risk that are validated by research. Although there are numerous actuarial instruments available to assess risk, the most promising of these are the ones that systematically and objectively measure both static and dynamic factors (Gendreau, Little & Goggin, 1996). These "risk/need" instruments provide information both on the risk to re-offend as well as the offender's needs. With this information, classification decisions regarding supervision and treatment can be made that are empirically related to reductions in re-offending.

Offender Classification in Manitoba Community Corrections

The probation service in the province of Manitoba has a long history of employing actuarial risk assessment. In 1982, the Community and Youth Corrections Division of the Manitoba Department of Justice adopted the Wisconsin risk/need classification system. The Wisconsin classification system consists of two forms: an 11-item risk scale and a 12-item need scale (Baird, Heinz & Bemus, 1979). After validation of the risk scale on over 4,000 probation and parole clients from the state of Wisconsin, the Wisconsin classification system was quickly adopted by a number of jurisdictions in North America.

Over the years, there were three validation studies of the Wisconsin classification scales as it was used in Manitoba (Barkwell, 1991; Bonta, Parkinson, Pang, Barkwell & Wallace-Capretta, 1994; Sabourin, 1986). The most recent evaluation (Bonta et al., 1994) led to major modifications to the risk and need scales. Items were dropped, scoring was simplified and, most importantly, the risk and needs forms were combined into one scale. The result was the Primary Risk Assessment (PRA) instrument. The PRA became the standard offender assessment tool for adults in Manitoba Community Corrections.

Some offenders are thought to require special attention when it comes to offender classification. One example is the violent offender. Violent crimes (general assaults, sexual offences and domestic violence) and the offenders who commit such crimes often receive close scrutiny by the criminal justice system and they are seen as different from other offenders. When faced with the violent offender, correctional staff often questions the validity of applying a general offender classification instrument. Specifically, their concern is that the general instrument, having been developed to predict any recidivism, may not be up to the task of predicting violent re-offending.

The concern over the usefulness of general offender risk scales with violent offenders has led to the development of specialized instruments designed to measure the risk for violent offending. For example, the Static-99 (Hanson & Thornton, 2000) assesses risk for sexual recidivism; the Violence Risk Appraisal Guide (VRAG: Harris, Rice, & Quinsey, 1993) assesses risk for violent recidivism; and the Spousal Abuse Risk Assessment (SARA; Kropp, Hart, Webster, & Eaves, 1999) assesses risk for domestic violence recidivism. Each of these instruments attempts to assist criminal justice professionals to make "better" classification decisions by providing an evaluation on risk for specific types of re-offending.

The empirical support for these specialized risk instruments vary. The predictive validity of the Static‑99 has been replicated in numerous studies and with very large samples (Hanson, Morton, & Harris, 2003). The VRAG has shown to be predictive of violent re-offending (Glover, Nicholson, Hemmati, Bernfeld, & Quinsey, 2002; Kroner & Loza, 2001; Loza & Loza-Fanous, 2001), however, the administration of the instrument requires an assessment of psychopathy with the Psychopathy Checklist- Revised (PCL-R) (Hare, 1990). The PCL-R is a restricted test with administration limited to those persons who have been trained and certified in its use. Finally, the easy to administer SARA has, at this point in time, few empirical investigations regarding its predictive validity (Grann & Wedin, 2002; Kropp & Hart, 2000).

The evolution of Manitoba's classification system reflected the need for and development of specialized risk assessment for classification purposes. Prior to introducing specialized risk assessment instruments, policy directed that all sexual offenders, partner abusers and assaultive offenders were to be considered high-risk, regardless of their PRA ratings. As 50% to 60% of Manitoba's probation population consists of assaultive offenders, probation officers were overwhelmed with the number of offenders designated as high-risk. Furthermore, staff expressed little confidence in the PRA to evaluate the risk for violent offending. As a result, there was a need for specialized assessment tools to differentiate among violent offenders and to assist in program delivery.

The Secondary Risk Assessment Scales

Following a review of the risk assessment literature and consultations with risk assessment experts and program specialists in Manitoba Corrections, three separate Secondary Risk Assessment (SRA) instruments were developed to assess risk for specific types of violent offending. There was a scale for sexual offenders (SRA-SO), for partner abusers (SRA-PA), and for general assaulters (i.e., not domestic and not sexual; SRA-GA).

For each of the SRA scales, the items are divided into two sections. The first section, labelled Historical Risk Factors, consists of items that fit the nature of the offence. For example, the SRA-PA has items assessing past history of domestic assault convictions and violations of "Non-Contact" orders whereas the SRA-SO includes items assessing prior sexual assault convictions and deviant sexual preferences. The second section is labelled Risk Factors That Change and contains a number of dynamic items. For example, the SRA-GA has items assessing acceptance of responsibility for assault and attitudes towards violence. Items in the SRA-PA assess responsibility for the domestic assault and attitudes towards violence in relationships and the SRA-SO items assess attitudes towards sexual offending and empathy for sexual assault victims.

Once developed, these SRAs were introduced into the offender classification system in 1997. Policy directed that all sexual offenders were to be assessed with the SRA-SO, all partner abusers were to be assessed with the SRA-PA, and all assaultive offenders, whose crimes were neither sexual nor domestic, were to be assessed with the SRA-GA. At least one of the following three criteria were required to determine if an offender was assessed with a SRA: 1) the presence of a violent index offence, 2) the presence of a violent conviction in the past five years, and 3) an override factor where there was a concern regarding violent offending. Staff was expected to administer the appropriate SRA and use this information in the classification decisions. During training sessions, staff was also advised that the SRAs were not validated and caution should be exercised when using them. Research would eventually evaluate the SRA's predictive validity.

In 2002, Karl Hanson evaluated the predictive validity of the SRA-SO with 204 adult male offenders from Manitoba. He found that the SRA-SO was not significantly related to sexual, violent or general recidivism and only weakly associated with any recidivism, which included technical violations. Only one of the 12 items, early onset of sexual offending, was significantly correlated to sexual recidivism. This evaluation led to a change in policy regarding specialized assessment for sexual offenders; assessment with the SRA-SO is now used only for clinical planning purposes.

The Present Study

The SRA-GA and SRA-PA remained unvalidated. The present report describes two studies that evaluated the predictive validity of the SRA-GA and the SRA-PA. Each study had two general goals. The first goal was to evaluate the ability of the SRA scales to predict the specific type of violent re-offending it was designed to predict and to suggest potential improvements. The second goal was to examine the benefits, if any, of using specialized risk assessments with violent offenders beyond simply administering the PRA.

Manitoba Justice (Corrections) provided PRA and SRA data on two separate samples of adult offenders: one sample of generally assaultive probationers and a separate sample of partner abusers. Canadian Police Information Centre (CPIC) records from the Royal Canadian Mounted Police (RCMP) provided recidivism information. In addition, for the partner abuse sample, detailed domestic violence recidivism information was gathered through Manitoba's Computerized Offender Management System (COMS).

Study 1: Evaluation of the SRA-GA

Method

Participants

Study 1 consisted of 444 probationers (246 males and 198 females) for whom we had RCMP criminal history records. The offenders were assessed between May 1996 and October 2000 thereby ensuring a minimum two years of follow-up. The large proportion of female offenders was likely due to our sampling of probationers. A sample of incarcerated offenders who had the SRA-GA completed showed a much higher proportion of males (183 males versus 36 females).

Offenders were assessed with the PRA and the SRA-GA (as per policy guidelines) because they had either: (a) a current violent (excludes partner assault and sexual offences) conviction (n = 383: 86%), (b) a prior assault conviction within 5 years of a current non-violent conviction (n = 32: 7%), or (c) they did not meet either of these criteria but staff had concerns about his/her propensity to violence (n = 29: 7%). The average age at assessment was 29.6 years (SD = 9.1). There were no statistically significant differences in age between the men (M = 29.8; SD = 9.9) and the women (M = 29.4; SD = 8.0).

Risk Assessment Instruments

Primary Risk Assessment (PRA). The PRA consists of the following 15 items: Address Changes, Time Employed, Drug or Alcohol Use, Attitude, Age, Sex, Number of Prior Convictions, Type of Prior Convictions, Family/Marital Relationships, Financial Situation, Emotional Stability, Mental Ability, Peers/Companions, Employment, and Academic/Vocational Skills. Most items are scored either as 0 or 1, or 0, 1, or 2. One item (Type of Prior Convictions) is scored from 0 to 3. The total score is the sum of all the items and scores can range from 0 to 22. Scores 5 or lower are considered Low Risk for re-offending, scores 6 to 11 are considered Medium Risk, and scores 12 or higher are considered High Risk.

In the present sample, the mean PRA score was 9.6 (SD = 3.8). The mean PRA score for males (n = 246) was 10.9 (SD = 3.7) and the mean score for females (n = 198) was 7.9 (SD = 3.3), significantly lower (t = 8.6, p < .01) than for males.

SRA-GA. The SRA-GA contains 11 items. The first five items make up the Historic Risk Factors section: Current Convictions, Prior Assault Convictions, History of Aggressive Behaviour, Use of Weapons, and 'No Contact' Condition Violations. All of these items are scored as 0, 2 or 4 except Use of Weapons, which is scored as 0, 1, or 2. The remaining 6 items make up the Risk Factors That Change section: Acceptance of Responsibility, Victim Empathy, Attitudes Towards Violence, Awareness of Warning Signs, Relapse Prevention Skills, and Motivation for Treatment. These items are scored as 0, 1, or 2. The total SRA-GA score is the sum of all the items and scores can range from 0 to 30. Scores 9 or lower are considered Low Risk for violent re-offending, scores 10 to 19 are considered Medium Risk, and scores 20 or higher are considered High Risk.

In the present sample, the mean SRA-GA score was 13.9 (SD = 5.7). Males (n = 246) scored significantly higher than females (n = 198) on the SRA-GA
(15.3 (SD = 5.8) vs. 12.1 (SD = 5.1), t = 6.1, p < .01). The correlation between the PRA and the SRA-GA was .57, p < .01.

Measurement of Recidivism

For each offender, recidivism information was coded from CPIC records. General recidivism was defined as any new conviction (including technical violations) within two years of assessment date. The overall general recidivism rate was 44.6% with males having a significantly higher recidivism rate than females (55.3% vs. 31.3%; χ2 (1, N = 444) = 25.5, p < .01).

Violent recidivism was defined as any violent conviction (e.g., assaults, robbery, sexual offences, weapon offences, and threats) within two years of the assessment date. The overall violent recidivism rate was 24.3%. Male probationers recidivated at a higher rate than female probationers (32.9% vs. 13.6%; χ2 (1, N = 444) = 22.1, p < .01). Offenders with a violent index offence (n = 383) had a violent recidivism rate of 24.0% whereas offenders with a non-violent index offence (n = 61) but with a violent history or a concern to staff had a recidivism rate of 26.2%.

Assessing Predictive Validity

Total scores on both the PRA and SRA-GA were significantly related to both general and violent recidivism (see Table 1). In addition, the measures performed equally well for male and female offenders when Pearson correlational analyses were conducted. However, when the data was analyzed according to risk level groupings, the results were not as consistent. The violent recidivism rates for the three risk levels of the SRA-GA were significantly different from each other but not for the PRA. When the violent recidivism rates for males were examined, it was the PRA that showed a statistically significant increase in violent recidivism across risk levels not the SRA-GA. For female offenders, the violent recidivism rates for the PRA and the SRA-GA Risk levels increased but not in a statistically significant step-wise fashion. For example, on the SRA-GA, the violent recidivism rate for High Risk female offenders (28.6%) was significantly higher than for Low Risk (10.3%) but not significantly different from the Medium Risk female offenders (12.8%). Thus, the present cut-off scores for the PRA and SRA-GA are not very helpful for offender classification purposes.

Table 1. Pearson correlations of the PRA and SRA-GA with General and Violent Recidivism and Violent Recidivism Rates by Risk Level
Sample Any Recidivism
r (CI)
Violent
Recidivism
r (CI)
Violent Recidivism by Risk Level % (n)
a. Low b. Medium c. High Group differences
Full (N= 444)PRA
PRA .43**
(.35 - .50)
.30**
(.21 - .38)
9.3
(75)
18.6
(220)
 40.3
(149)
c > (b = a)
 SRA-GA .38**
(.29 - .45)
.30**
(.21 - .38)
9.7
(113)
25.7
(245)
39.5
(86)
c > b > a
Males (N = 246)
PRA .40**
(.29 - .50)
.26**
(.14 - .37)
4.3
(23)
27.4
(106)
43.6
(117)
c > b > a
SRA-GA .33**
(.22 - .44)
.28**
(.16 - .39)
8.9
(45)
36.0
(136)
43.1
(65)
(c = b) > a
Females (N = 198)
PRA .33**
(.20 - .45)
.18*  
(.04 - .31)
11.5
(52)
10.5
(114)
28.1
(32)
c > (a = b)
SRA-GA .33**
(.20 - .45)
.21**
(.07 - .34)
10.3
(68)
12.8
(109)
28.6
(21)
c > (a = b)

Notes: * p < .05; **p < .01; CI = 95% Confidence Interval.

As the PRA and the SRA-GA were significantly correlated (r = .57, p < .01), we examined the relative predictive utility of combining the two instruments through multiple regression analysis. Multiple regression analysis allows one to evaluate the power of combining multiple measures (in our case, the PRA and SRA-GA) to predict outcome (i.e., violent recidivism). The results of the multiple regression analyses indicated that although the SRA-GA added to the prediction of violent recidivism (R2change = .03; p < .01), the increase in predictive power of combining the two instruments was quite small (RPRA & SRA-GA = .34, p < .01) in comparison to the predictive power of each instrument alone (rPRA = .30, p < .01 and rSRA-GA =.30, p < .01).

Can We Improve Upon the Risk Assessment for Violent Offenders?

As noted earlier, the notion of a specialized assessment for specific sub-groups of offenders gave rise to a number of risk/need instruments tailored to predict specific types of criminal activity. The SRA‑GA is one such specialized instrument designed to predict violent recidivism. There is a debate in the literature, particularly in regards to predicting violence, whether or not specialized violence risk/need instruments predict better than general risk/need instruments (Gendreau, Goggin, & Smith, 2002). The present results, which demonstrated that the PRA, a general risk/need instrument, performed just as well as the specialized SRA-GA instrument suggests that a specialized instrument in this case added little to the prediction of violent re-offending.

Nonetheless, it may be possible to improve assessments of violent recidivism in one of two ways. First, we can try to improve upon the SRA-GA by modifying the items that comprise the scale. The second approach is to integrate the best items from of the SRA-GA into the PRA. We describe these two approaches next.

Improving the SRA-GA through item modification. We undertook an analysis to explore the relationship between the individual items of the SRA-GA and violent recidivism. The goal with this item analysis was to evaluate each item's contribution to the prediction of violent recidivism. Given that the patterns of correlations for males and females were almost identical, the subsequent analyses combined all offenders.

For each of the 11 items of the SRA-GA, the correlations with violent recidivism were calculated. In addition, we examined the recidivism rates associated with each possible score that an item received. Each item was evaluated based on: a) the magnitude of its relationship to violent recidivism, and b) the observed violent recidivism rates for each possible score it could receive. An item was deemed adequate when it showed a positive correlation to violent recidivism of .10 or higher and demonstrated an increase in violent recidivism across the item's ratings with a difference of 10% or more between the highest and lowest item score.

The left side of Table 2 presents the correlations of the historical items with violent recidivism and also the recidivism rates for each score on the item. The correlations for the dynamic items with violent recidivism and their associated recidivism rates are presented in the right side of Table 2.

Only three items of the SRA-GA were not significantly associated with violent recidivism, specifically, Current Conviction, 'No Contact' Condition Violations and Awareness of Warning Signs. The remaining items were significantly related (p < .05 or p < .01) to violent recidivism with correlations ranging from r = .10 to r = .25. In addition, the items Current Conviction and 'No Contact' Condition Violations did not demonstrate a step-wise increase in violent recidivism rates across the three scores.

Although probationers scoring 0 on the item 'No Contact' Condition Violations demonstrated a lower violent recidivism rate (22.8%) than those scoring 4 (31.1%), the probationers scoring 2 actually showed the highest violent recidivism rate (32.3%). Conceptually, this item attempts to assess a willingness to violate non-association orders, a factor found in previous research to be predictive of violent recidivism (Harris, Rice, & Quinsey, 1993). These results suggest that this item could be revised to simply assess the presence or absence of any known violation of a 'No Contact' order, regardless whether the individual is arrested. However, when we dichotomized the scoring of this item, the correlation with violent recidivism increased only slightly (r = .08, ns).

Table 2. Pearson Correlations and Violent Recidivism Rates for the SRA-GA Items (N = 444)
Historical Risk Factors
Item

Score

n

Violent Recidivism

Risk Factors That ChangeItem

Score

n

Violent Recidivism

Current Conviction


 

r = .01

Accepting Responsibility

 

 

r = .14**

Not assaultive 0 61 26.2% Accept full/partial responsibility 0

123

17.9%
Threats/assaults no harm 2 169 21.9% Accepts partial responsibility 1 218 22.9%
Credible threats/harm 4

55

25.7% Refuses to accept responsibility 2 103 35.0%
Prior Assault Convictions

 

 

r = .25*

Victim Empathy

 

 

r = .11*

None/current only 0 202 15.3% Adequate empathy 0 77 15.6%
One prior 2 92 17.4% Partial empathy 1 185 23.8%
Two or more priors 4 150 40.7% Superficial/no empathy 2 182 28.6%
History of Aggressive Behaviour

 

 

r = .24**

Attitudes Towards Violence

 

 

r = 18**

No evidence 0 164 13.4% None supportive of violence 0 132 12.9%
Attempts/threats 2 71 15.5% Minimal/not strongly held 1 219 27.4%
Previous assaults 4 209 35.9% Strongly held attitudes 2 93 33.3%
Use of Weapon

 

 

r = .10*

Awareness of Warning Signs

 

 

r=.08

No weapons used

0

279

20.4%

None supportive of violence

0

66

18.2%

Threats to use weapons 1 56 33.9% Minimal/not strongly held 1 213 23.5%
Used weapon to harm 2 109 29.4% Strongly held attitudes 2 165 27.9%

'No Contact' Condition Violations

 

r = .07 Relapse Prevention Skills

 

 

r=.18**

No violations/orders 0 368 22.8% Carefully avoids situations 0 99 16.2%
Violated but not arrested 2 31 32.3% Limited contact with situations 1 189 19.6%
Violated and arrested 4 45 31.1% Frequent contact with situations 2 156 35.3%

 

 

 

 

Motivation for Treatment

 

 

r = .22**

Motivated and cooperative 0 208 15.9%
Low motivation but cooperative 1 195 28.2%
Unwilling, refuses, dropped out 2 41 48.8%

Notes: * p < .05; ** p < .01.

Finally, although Use of Weapon demonstrated a significant correlation with future violent offending, the discrimination in rates for the different scores was poor (e.g., probationers scoring 1 had a rate of 33.9% while those with the higher score of 2 had a lower violent recidivism rate of 29.4%).  Once again, simplifying the scoring for this item by collapsing the categories of the threat of use with the actual use of a weapon into one category, thus giving a 0-1 scoring scheme, yielded only a small improvement in predictive accuracy (r = .12, p < .05).

In summary, the item analysis suggested the following revisions to the SRA-GA. First, eliminate the item Current Conviction from the instrument as this item demonstrated little predictive or discriminative validity. Second, revise the scoring of two items. For the item Use of Weapon, previous scores of 1 and 2 (indicating a use of a weapon for threatening or to harm) could be collapsed into one score of 2. A score of 0 would remain unchanged (i.e., no weapons was used for threats or for harm). For the item 'No Contact' Condition Violations, scores of 2 and 4 (indicating the individual violated a 'No Contact' order with or without an arrest) could be collapsed into a single score of 2.

In order to evaluate the predictive and discriminative accuracy of these revisions to the SRA-GA, a new score (Revised SRA-GA) was calculated. This Revised SRA-GA was still significantly related to the PRA (r = .59, p < .01). Its predictive accuracy with respect to any recidivism (r = .38, p < .01) and violent recidivism (r = .31, p < .01) however showed almost no improvement compared to the original SRA-GA (r's of .38 and .30 respectively, p < .01). Finally, a multiple regression analysis was conducted using the PRA and the Revised SRA-GA to predict violent recidivism. The results indicated that the Revised SRA-GA significantly added to the prediction of violent recidivism (R2change = .03; p < .01). However, there was no improvement in overall predictive accuracy for the revised (RPRA & Revised SRA-GA  = .34, p < .01) compared to the original (RPRA & SRA-GA  = .34, p < .01) SRA-GA in conjunction with the PRA.

Enhancing the PRA. In this investigation, the PRA predicted violent recidivism as well as the SRA‑GA despite the fact that the PRA does not contain any items that specifically refers to violent behaviour. Therefore, one potential way of improving the PRA is to add a few items that assess violence. Consequently, we conducted an analysis of the SRA-GA that was intended to identify items predicting violence that could be appended to the PRA.

First, a multiple regression analysis examined all the items of the SRA-GA and selected the best predictors. A step-wise method was used to ensure that any collinearity would be accounted for amongst the items. This analysis identified two significant predictors: Prior Assault Convictions (b = .231; t = 5.08; p < .01) and Motivation for Treatment (b = .197; t = 4.34; p < .01). A third item, History of Aggressive Behaviour, approached significance (b = .113; t = 1.92; p = .056). Taken together, these three items were significantly related to violent recidivism (R = .33, p < .01). The item Prior Assault Convictions evaluates prior assaults that resulted in official convictions whereas the item History of Aggressive Behaviour evaluates prior assaults (or threats) that did not result in formal convictions.

Next, the sum of these three items was added to the total PRA score and the predictive accuracy of this Enhanced PRA (original PRA plus the three items) was evaluated. Table 3 shows both the Pearson correlations and the areas under Receiver Operating Characteristic curve (AUC). A Receiver Operating Characteristic analysis is unaffected by base rates and selection ratios. An AUC of 1.0 represents perfect prediction whereas an AUC of .50 represents chance. Both types of statistical analyses showed the Enhanced PRA related to violent recidivism as well as any recidivism. However, as the overlapping confidence intervals indicate, the Enhanced PRA did not perform better then the original PRA or the SRA-GA.

Table 3. Predictive Validity Estimates of the PRA, SRA-GA and the Enhanced PRA
  Any Recidivism Violent Recidivism Any Recidivism Violent Recidivism
  r (CI) r (CI) AUC (CI) AUC (CI)
PRA .43 (.35-.50) .30 (.21-.38) .74 (.70-.79) .69 (.64-.75)
SRA-GA .30 (.21-.38) .30 (.21-.38) .72 (.67-.76) .70 (.64-.75)
Enhanced PRA .46 (.40-.52) .34 (.26-.42) .77 (.72-.81) .73 (.67-.78)

Notes: All predictive validity estimates significant (p < .01); CI = 95% Confidence Interval.

Discussion

There are two main purposes for conducting a specialized risk/need assessment. One, the specialized risk/need assessment will improve prediction of a specific type of re-offending above and beyond a general re-offending risk/need instrument. Two, the specialized risk/need assessment will enhance case management decisions by identifying appropriate treatment needs/targets and assigning appropriate levels of supervision and treatment. In the case of the SRA-GA, the focus is on generally assaultive offenders and violent re-offending.

Contrary to the belief that general risk/need assessment instruments are not well suited to the prediction of violence, the results from the first study indicated that the PRA does in fact predict violent re-offending just as well as the SRA-GA, a specialized tool for violence. A detailed analysis of the SRA-GA found that one item could be deleted because it showed no association with violent recidivism and that the scoring for two other items could be simplified without diminishing the predictive validity of the instrument. However, there was no appreciable improvement to the Revised SRA-GA's predictive accuracy.

Although scores on the PRA and SRA-GA were equally predictive of violent recidivism, a question was asked whether combining the two instruments would enhance the prediction of violent recidivism. Multiple regression analyses showed that when the results from the PRA and SRA-GA (or its Revised version) were combined, there was a significant, but relatively minor, improvement in the prediction of violent recidivism.

Finally, one of the weaknesses of the PRA (i.e., no items directly related to violence) was addressed by identifying three items from the SRA-GA that could be added to the PRA. However, total scores on the Enhanced PRA predicted no better the original PRA.

Study 2: Evaluation of the SRA-PA

Method

Participants

A total of 613 probationers (502 males and 111 females) served as the basis for analysis. The probationers were assessed prior to 2000 (October 1996 to December 1999) to ensure a minimum two years of follow-up.

Offenders were assessed with the PRA and the SRA-PA (as per policy guidelines) because they had: (a) a current partner assault conviction (n = 542: 88%), (b) a prior partner assault conviction within 5 years of a current conviction for a non-partner abuse related offence (n = 38: 6%), or (c) they did not meet either of these criteria but staff had concerns about the propensity for partner abuse (n = 33: 5%). The average age at assessment was 32.7 years (SD = 9.0). The average age for men was 32.8 years (SD = 9.1) and 32.2 years (SD = 8.4) for women (t = 0.66; ns). 

Risk Assessment Instruments

Primary Risk Assessment (PRA). The mean PRA score was 9.6 (SD = 3.6) with 13.2% (n = 81) in the Low Risk range, 58.6% (n = 359) in the Medium Risk range, and 28.2% (n = 173) in the High Risk range. Males (M = 9.7; SD = 3.6) scored significantly higher on the PRA (t = 2.23, p < .05) than females (M = 8.9; SD = 3.4).

SRA-PA. The SRA-PA contains 12 items. The first six items make up the Historic Risk Factors section: Current Convictions, Prior Partner Abuse Convictions, History of Aggressive Behaviour, Use of Weapons, 'No Contact' Condition Violations, and Suicide Thoughts/Attempts. All of these items are scored as 0, 2 or 4 except Use of Weapons, which is scored 0, 1, or 2. The remaining 6 items make up the Risk Factors That Change section: Acceptance of Responsibility, Victim Empathy, Attitudes Towards Violence, Awareness of Warning Signs, Relapse Prevention Skills, and Motivation for Treatment. These items are scored as 0, 1, or 2. The total SRA-PA score is the sum of all the items and scores can range from 0 to 34. Scores 10 or lower are considered Low Risk for re-offending with a violent domestic offence, scores 11 to 20 are considered Medium Risk, and scores 21 or greater are considered High Risk.

The mean SRA-PA score was 14.9 (SD = 5.5) with 21% (n = 129) of the offenders classified Low Risk, 61% (n = 376) Medium Risk, and 18% (n = 108) High Risk. There was no significant difference on SRA-PA scores (t = 1.74, ns) between males (M = 15.1; SD = 5.6) and females (M = 14.1; SD = 4.8). The PRA and SRA-PA were significantly correlated (r = .60, p < .01).

Measurement of Recidivism

Recidivism information was coded from CPIC Records and detailed domestic violence recidivism information was gathered through Manitoba's Computerized Offender Management System (COMS). CPIC records were received on October 30, 2002 from the RCMP. COMS was accessed in the summer of 2003 and information dated on or before October 30, 2002 was recorded. All offenders had a minimum follow-up period of 2 years from the date of assessment.

General recidivism was defined as any new conviction (including technical violations) within two years of assessment date. The overall general recidivism rate was 36.1% with no significant difference between males (37.5%) and females (29.7%).

Violent recidivism was defined as any violent conviction (e.g., assault, threats, robbery, sexual assault, and weapon offences) within two years of the assessment date regardless whether it was domestically related or not. The overall violent recidivism rate was 15.0%, with males having a significantly higher rate (16.9%) than females (6.3%). No significant differences in violent recidivism rates were found between offenders with a partner abuse index offence (n = 542; violent recidivism = 15.5%) and offenders with a non-partner abuse index offence but with a domestic violence history or a concern to staff (n = 71; violent recidivism = 11.3%).

Domestic violence recidivism was defined as any domestic violence related arrest (e.g., assault, threatening, criminal harassment, breach of non-contact/non-association) within two years of the assessment date. Arrest was chosen rather than conviction to increase the base rate. However, even with arrest as our outcome criterion, the base rates of domestic violence remained relatively low. The overall domestic violence recidivism rate was 11.4%, with males having a significantly higher rate (13.1%) than females (3.6%). No significant differences in domestic violence recidivism rates were found between offenders with a partner abuse index offence (n = 542; domestic violence recidivism = 12.0%) and offenders with a non-partner abuse index offence but with a domestic violence history or a concern to staff (n = 71; domestic violence recidivism = 7.0%).

Assessing Predictive Validity

To evaluate the predictive accuracy of the PRA and the SRA-PA, Pearson correlations between the total scores for the two instruments and general, violent and domestic violence recidivism were calculated. The results are presented in Table 4. In addition, with respect to the prediction of domestic violence recidivism the AUC for the PRA was .62 (CI = .55 - .68) and .61 for the SRA-PA (CI = .54 - .68). The PRA and SRA-PA were significantly related to all outcome measures. This pattern was also observed with male offenders but not with female offenders, likely due to the small female offender sample size and very low base rates of recidivism (there were only seven violent female recidivists and only four domestic violent recidivists). As a result of so few female domestic violence recidivists, the remainder of the results are based upon the male offenders only.

The three risk levels for each instrument failed to show an orderly, step-wise progression in domestic violence recidivism rates that was statistically significant. Statistical significance in domestic violence rates was only observed at the extreme risk levels. Offenders assessed as High Risk on the PRA had a significantly higher domestic violence recidivism rate (17.6%) than male offenders assessed as Low Risk (6.3%) and offenders assessed as High Risk on the SRA-PA had a higher domestic violence recidivism rate (20.8%) than those assessed as Low or Medium Risk (9.3% and 12.1%).

We further examined the relative predictive utility of combining the two instruments through multiple regression analysis (male offenders only). In this analysis, we evaluated the power of combining the PRA and the SRA-PA to predict domestic violence recidivism. The results of the multiple regression analyses indicated that the SRA-PA did not significantly add to the PRA in the prediction of domestic violence recidivism (R2change = .01; p > .05).

Item Analysis of the SRA-PA

Although the total score on the SRA-PA was significantly related to domestic violence recidivism, the predictive validity estimates were weak and not significantly greater than those achieved by the PRA alone. An item analysis was conducted using the same methodology as in Study 1 but with domestic violence recidivism as the criterion. The analysis revealed that only one item, 'No Contact' Condition Violations, showed a statistically significant association (r = .16; p < .01) to domestic violence recidivism. The correlations with domestic violence recidivism with the remaining 11 items ranged from r = –.01 to r = .06 (all not statistically significant).

Table 4. Pearson Correlations of the PRA and SRA-PA with General, Violent And Domestic Violent Recidivism and Domestic Violent Recidivism Rates by Risk Level
  Any Recidivism
r (CI)
Violent
Recidivism
r (CI)
DV
Recidivism
r (CI)
DV Recidivism by Risk Level % (n)
a. Low b. Medium c. High Group differences
Sample (N= 613)
PRA .25**
(.17 - .32)
.15**
(.07 - .22)
.12**
(.04 - .20)
4.9
(81)
10.6
(359)
16.2
(173)
(c = b) > a
SRA-PA .17**
(.09 - .25)
.15**
(.07 - .22)
.13**
(.05 - .20)
 8.5
(129)
10.4
(376)
 18.5
(108)
c > (b = a)
Males (N = 502)
PRA .27**
(.18 - .35)
.16**
(.07 - .24)
.12**
(.03 - .20)
6.3
(63)
12.4
(291)
 17.6
(148)
(c = b) > a
SRA-PA .17**
(.08 - .25)
.17**
(.08 - .25)
.13**
(.04 - .21)
9.3
(108)
12.1
(298)
20.8
(96)
c > (b = a)
Females (N = 111)
PRA .14 
(–.05 - .32)
.02 
(–.17 - .20)
 .09 
(–.10 - .27)
0
(18)
2.9
(68)
 8.0
(25)
N/A
SRA-PA .15 
(–.03 - .33)
–.05 
(–.24 - .14)
.06 
(–.13 - .24)
4.8
(21)
3.8
(78)
0
(12)
N/A

Notes: * p < .05; ** p < .01; CI = 95% Confidence Interval; N/A = non-applicable due to small cell size.

Discussion

The results from Study 2 provide weak empirical support for the use of the SRA-PA to identify partner-abusing offenders of varying risk levels. Although the SRA-PA was significantly related to domestic violence recidivism, the relationship was small, and no different than that of the PRA. Additionally, the SRA-PA failed to show an orderly, statistically significant step-wise increase in domestic recidivism across risk levels. Only offenders in the High Risk range of the SRA-PA demonstrated higher domestic violence recidivism than offenders scoring in the Low and Medium Risk ranges. Furthermore, the item analysis found that only one of the 12 items of the SRA-PA was predictive of domestic violence recidivism.

Overall, these results suggest that future efforts be directed towards alternative measures to assess domestic violence risk in partner abusing offenders. There are some possible measures such as the SARA (Kropp, Hart, Webster, & Eaves, 1999) and the Ontario Domestic Assault Risk Assessment (ODARA; Hilton, Harris, Rice, Lang, & Cormier, in press). However, these instruments are relatively new and also require further validation. Another option may be to develop a new risk/need assessment instrument for domestic violence cases that would incorporate the present findings and new research that was unavailable when the original SRA-PA was developed. Regardless of the option, to implement a valid and useful risk/need assessment tool for partner violence will require time and resources.

General Conclusions

Effective case management protects society by providing services to offenders that reduce the probabilities of recidivism. For each offender, decisions must be made in regards to the appropriate level of supervision and rehabilitative programs. Accurate and valid assessments of offenders' risk to re-offend and criminogenic needs provide crucial information for these decisions. Although there are validated risk-need instruments that assess general offending, specialized risk/need tools are often used with violent offenders because it is believed that these specialized measures provide information that more accurately predict violent re-offending.

The present investigation examined the predictive validity and utility of two specialized risk/need instruments: the SRA-GA designed to be used with generally assaultive offenders and the SRA-PA for partner-abusers. In the first study, we found that both the general PRA and the specialized SRA-GA were moderate predictors of violent re-offending. However, neither measure was superior to the other. Even combining the two measures did not significantly improve the prediction of violent re-offending. Item analyses of the SRA-GA suggested eliminating one item and simplifying the scoring on two other items, but these revisions resulted in no significant increase in the instrument's predictive validity. Finally, we considered integrating three items from the SRA-GA with the PRA. Once again, we did not find higher predictive accuracy for the Enhanced PRA over the original PRA.

The second study examined the PRA and the SRA-PA with partner-abusing probationers. As with the first study, both measures were equally predictive of domestic violent re-offending. However, scores on both instruments were weak predictors. Only one of the 12 items of the SRA-PA predicted domestic violence recidivism. Overall, the results indicated that the SRA-PA added little, with or without the PRA, to discriminate groups of offenders with varying rates of domestic violence re-offending. Thus, we concluded that an alternative instrument is needed to more accurately determine the risk and needs of partner-abusing offenders.

In conclusion, the general risk-need instrument performed as well as two specialized measures of violent and domestic violence re-offending. The results from the two studies, however, do not necessarily mean that the development of specialized offender risk scales is unlikely to improve upon more generalized assessment instruments. What may be important is the type of behaviour that is being predicted. The determinants of general violent and assaultive behaviour may be no different than the predictors of non-violent law violations. There is some evidence that the individual predictors of general recidivism are the same as those of violent recidivism (e.g., Bonta, Law & Hanson, 1998). When these individual items are brought together to form generalized risk scales, they predict both general and violent recidivism (e.g., Gendreau, Goggin & Smith, 2002). In this study, the original PRA (AUC = .69, CI = .64 - .75) performed as well as the VRAG, a widely used scale specifically designed to predict violence (AUC = .72; http://www.mhcp-research.com/ragpage.htm).

The question arises whether more specific types of violent offending require more specialized tools. An obvious example is sexual re-offending. However, even here there is the suggestion that such specialized assessments may add little in terms of prediction (Hanson & Morton-Bourgon, 2004). In study 2, the SRA-PA was a very modest predictor of domestic violence. But, the PRA also did not perform particularly well. However, another study using a general offender risk-need scale was found to predict domestic violence (Hanson & Wallace-Capretta, 2000). In the area of risk prediction for partner assault, there is astonishingly little in scale development (Dutton & Kropp, 2000). There are a few predictive validity studies of the SARA but they have been plagued by small sample sizes (Grann & Wedin, 2002). A recent study of the ODARA appears particularly promising. Hilton and her colleagues (in press) reported for the ODARA an AUC of .72 on their cross-validation sample. In general, validating partner assault scales are particularly difficult because police do not usually note on official criminal records whether the violent offence was domestic-related or not. Thus, considerable effort is required to gather the information from other sources.

Finally, one of the lessons learned from the research described in this report is that we cannot take for granted a new risk instrument that was developed with the best intentions and the best expert advice available at the time. As we found in these two studies, the need for empirical evaluation cannot be underestimated. For any organization, development and on-going evaluation are prerequisites to best practices.

References

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