The other factors that might be expected to be predictive of the likelihood to recidivate (age, gender, race/ethnicity, and number of prior DWI offenses and other prior criminal offenses) were also examined, as available. This ensured that any ISP group effects found in each State were not an artifact of some other factor on which the groups might have been different, although the two comparison groups had been composed via stratified random sampling to match the intervention group on these factors. (Differences among counties in Oregon were also examined.)
Age
After adjusting for the impacts on recidivism due to the other factors mentioned, a similar general pattern for age was found among all three States: Younger offenders were more likely to recidivate, with the risk dropping monotonically as age cohorts progress to the oldest offenders, who were least likely to recidivate. These age effects were significant to p<.001 in all three States, as noted in the previous tables for those States’ analyses. Using the age cohort of 30 to 39 as the baseline, the following relative likelihood factors for broader groupings of the age cohorts were obtained, as shown in Table 7.
Table 7. Relative Likelihood of Recidivism Age Minnesota Oregon New York
<30 +30.4% +8.2% +36.3% 30-39 (reference level) 40-49 -14.4% -9.5% -22.5% 50-59 -14.4% -12.5% -41.3% 60+ -13.1% -37.0% -55.2% Sex
After adjusting for the impacts on recidivism due to the other factors mentioned, females were less likely to recidivate than males. The magnitude of this effect was quite similar in all States: 10.7% less likely in New York (p<.001), 14.3% less likely in Oregon (p=.002), and 15.2% less likely in Minnesota (p=.003).
Race/Ethnicity
This factor was only available for the New York data. After adjusting for the impacts on
recidivism due to the other factors mentioned and contrasting all minority groups with the White category due to its predominant size of offender numbers, African Americans were found to be 14.3% more likely to recidivate (p<.001), and Hispanics were found to be 9.2% less likely to recidivate (p<.001).
Prior DWIs
A measure for this variable could not be reliably estimated in the Minnesota data (at least not in the full “real” range that would have been recorded) due to the unusually short pre-index offense period. For the other two States, prior DWI offenses was a potent predictor of future recidivism. (All relative likelihoods here were significant well beyond p<.001.) Relative to those with just a single prior, those with two priors were 27.1% (New York) and 34.2% (Oregon) more likely to recidivate. For those with three priors, the increased risk was 43.5% (New York) and 69.6% (Oregon) more likely than first offenders; and for those with four or more priors, the increased risk was 73.0% (New York) and 105.8% (Oregon) more likely.
Other Prior Offenses
In New York, we had available a detailed database of other criminal convictions, which included far more than just traffic offenses. Having more prior criminal convictions was also highly predictive of future recidivism although the amount per each additional prior is not a constant value or increment, as the relationship was curvilinear (i.e., additional risk, in absolute terms, diminishing as priors accumulated). For example, a person with just one prior felony was 14.7% more likely to recidivate then someone with none. A person with two prior felonies was 24.2% more likely to recidivate; a person with three prior felonies was 31.5% more likely to recidivate. To provide a higher reference point on this logarithmic shaped function of diminishing marginal risk, a person with eight prior felonies was 50% more likely to recidivate then someone with zero. The same relationship of increased risk per prior convictions was also found for
misdemeanors but of a slightly smaller magnitude (about 2% less). Both of these were significant well beyond p<.001.
ISP Costs
All of these programs charge offenders to participate. Table 8 lists a brief summary of costs to the offender, operational costs of the programs, and reported cost savings by the programs to the public where the information was provided. Detailed explanations follow the table.
Table 8. ISP Program Costs and Savings
Program Cost to Offenders Costs of Programs Savings Provided by Programs Nebraska Standardized
Model for Delivery of Substance Abuse Services
Nebraska offers a combination of
sliding scale, and flat fee for alcohol and other drug assessment and
treatment services
set fees for assessment
fee-for-service voucher system
State paid to develop the system and a standardized assessment tool
Wisconsin Pretrial Intoxicated Driver Intervention Program
(Varies by county) A combination of county, State and Federal funds pay for these county programs
Staggered Sentencing for Multiple DWI Convicted Offenders 10th District Court, Cambridge, MN
Fines Treatment
Electronic monitoring costs $8-14/day
Up to $765,000 annually in grants
Reduction of jail time and related costs—$3K per offender ($60/day) Serious Offender Program
Clark County, NV Fines Treatment Electronic monitoring Interlock VIPs
Estimated annual savings of $500,000 in costs of jailing offenders
DWI Enforcement Program Westchester County, NY
Fines
Admin fee $30/mo Treatment
Interlock ($90/mo approx.)
Westchester County funds the probation department; NY State provides some funding
DWII Intensive Supervision Probation Program Multnomah County, OR
Repeat missed fines $5K; Felony Fine max $100K; Treatment $25-40 per week electronic-monitoring costs paid to vendor 24/7 Sobriety Project
South Dakota
Offenders pay for twice daily testing ($1 for each test)
Saved $70 per day for 320,000 days in jail DWI Supervised Probation
Program
Fremont County, WY
Supervision fee $25/mo Program is funded by a State grant