Using Data to Transform Community Correction Interventions Mike Randle Vice President of Summit County Programs Derek Ault Lead Research Specialist Oriana House, Inc.

Objectives Using state or other secondary data Recidivism and commitment data Using Assessment Data ORAS, CTS Collecting your own data Offender Input CQI and QA processes to improve fidelity EPICS, CPP, and ORAS Establishing research partnerships Focus group with offenders or staff

Using State or other secondary data Problem 1

Secondary Data Sources ODRC collects recidivism, commitment and release data for us Reports posted on website http://www.drc.ohio.gov/reports Can be used to identify trends and compare to state averages

County Recidivism Three year recidivism rates by county Recidivism defined as return to prison within timeframe Can breakdown rates to examine recidivism from technical violations and new crimes Additional state reports breaks down rates by follow-up period, sex, and release types

2011 DRC Exits – 3 Year Recidivism Rate Recidivism Reports – County* County of Commitment 2011 DRC Exits – 3 Year Recidivism Rate Total 2011 Total 2010 Total Percentage No Recidivism Technical Violation New Crime Recidivism Rate Points Change N % Summit 856 69.4 80 6.5 298 24.1 1234 30.6 29.8 0.8 State Total 16280 72.5 1205 5.4 4970 22.1 22455 27.5 27.1 0.4 *ODRC. (2015). County Three Year Recidivism Rates. http://www.drc.ohio.gov/LinkClick.aspx?fileticket=aaCnGtI83vQ%3d&portalid=0

CBCF, HH, ISP-407 Recidivism Includes all programs that receive funding from the ODRC CY 2010 Cohort (1, 2, and 3 year recidivism rates) CY 2011 Cohort (1 and 2 year recidivism rates) CY 2012 Cohort (1 year recidivism rate) Recidivism defined as, “failed supervision or community placement resulting in placement in Ohio’s prisons”

Recidivism Reports – CBCF, HH, ISP-407* Program Type 1st Year 2nd Year 3rd Year % Completing Program N CBCF Successful 15.3 26.6 29.9 4693 80.6 Unsuccessful 55.3 62.9 65.7 1127 19.4 Total 23.0 33.6 36.8 5820 100.0 HH 10.3 18.7 22.2 4223 67.9 45.8 52.9 1994 32.1 21.7 29.7 32.8 6217 ISP - 407 4.6 8.7 10.8 4678 54.4 46.9 53.0 54.6 3923 45.6 23.9 28.9 30.8 8601 . *ODRC. (2014). CBCF, Halfway House, and ISP-407 Recidivism Report http://www.drc.ohio.gov/web/Reports/Recidivism/Key%20Recidivism%20Information%20CY2010.pdf

County Level Commitments* FY and CY annual commitment reports County and offense level data Breakdown by sex Committing County 1st Deg 2nd Deg 3rd Deg 4th Deg 5th Deg Total N % Summit 95 8.7 195 17.9 384 35.2 194 17.8 222 20.4 1090 1790 9.0 3154 15.9 5794 29.2 4007 20.2 5078 25.6 19823 *ODRC. (2016). FY 2016 Commitment Report. http://www.drc.ohio.gov/LinkClick.aspx?fileticket=fxsbHO23kzY%3d&portalid=0

Application of Secondary Data

Using Client/Offender Assessment Data Problem 2

Assessment Data Routinely collected as part of offender intake or eligibility requirements Captures information on various offender characteristics While useful at the client/offender level, in the aggregate: Identify trends in client/offender population Ensure adherence to evidence base practices Measure change in client/offender behavior

ORAS Identifying client risk over years Trends looking at overall and domain scorea Intake Risk Level Q1 2016 Q1 2017 N % Low 37 17.8 16 10.9 Moderate 62 29.8 72 49.0 High 95 45.7 53 36.1 Very High 14 6.7 6 4.1 Total 208 100.0 147

Family and Social Support Neighborhood Problems ORAS CST Error Rates Q3-4 2016 CST Domains Criminal History Edu./ Emp./ Finances Family and Social Support Neighborhood Problems Substance Use Total # of errors 34 20 11 14 Average # of errors .23 .13 .07 .09 Error Rate(%) 3.80 2.24 1.48 4.70 4.56 N = 149 Assessments

TCU Criminal Thinking Scales Developed from the work of Glen Walters and the Bureau of Prisons in 1996  Psychological Inventory of Criminal Thinking Styles (PICTS) Provides an overall score and six subscale scores TCU CTS Scales Definition Personal Irresponsibility Blaming others/external factors for criminal behavior. Entitlement Feeling of privilege Power Orientation Need for power/ control over others Justification Minimalization of seriousness of antisocial acts Cold Heartedness Callousness Criminal Rationalization Negative attitude toward law and authority figures

TCU Criminal Thinking Scales 36 items rated on a 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = uncertain, 4 = agree, 5 = strongly agree) Scales contain an average of 6 items each Subscale scores are obtain by summing and dividing by the number of items included and multiplying by ten (10 – 50)

TCU Criminal Thinking Scales Knight, K., Garner, R. G., Simpson, D. D., Morey, J. T., & Flynn, P. M. (2006). An Assessment of Criminal Thinking. Crime Delinquency, 52(1). http://ibr.tcu.edu/forms/tcu-criminal-thinking-scales/

TCU Criminal Thinking Scales Specialized Cognitive Offender Programming and Education (SCOPE) – 2012

Application of Assessment Data

Collecting our own data Problem 3

Survey Data Easy method to collect client/offender satisfaction Identify population of focus Establishing timelines What to ask

Designing Surveys Residential Exit Evaluation Reports Demographics Intake Overall Programming Drug and Alcohol Treatment Cog Skills, Employment, and Education Programming My Caseworker Staff at the Post and on the Floor Post Release Facility Safety & Drug Use

Designing Surveys Be specific in your survey questions My Caseworker/PO… …helped me create realistic goals. …helped me identify triggers/targets. …helped create a plan to address triggers/targets. …acknowledged my concerns, opinions and feelings. …treated me respectfully. I liked my Caseworker/PO.

Designing Surveys Avoid double barreled or complex questions Role playing helped me practice what I learned in class. Role playing helped me practice what I learned in class and to identify my high risk thoughts/thinking errors. Role playing helped me identify my high risk thoughts/thinking errors.

Designing Surveys Keep language in mind (e.g. double negatives, jargon, complex sentences, bias, and reading level) The staff at the post and on the floor acknowledged my behavior and explained why it was positive or negative. The staff at the post and on the floor effectively used CCP skills.

Collecting Survey Data Data software – MS Excel, Access, SPSS, Remark Coding System 1 2 3 4 Strongly Disagree Disagree Agree Strongly Agree

Analysis Frequency – The number of how often a value occurs within a particular category. Often represented by ‘n’

Analysis Mean – (AKA Average) Sum of all responses divided by the total number of responses.

Analysis Percentage – An amount of something, often expressed as a number out of 100.

Survey Response Rates

Application of Satisfaction Data

QA / CQI processes to ensure fidelity Problem 4

Case Management Effective Practices in Correctional Settings II (EPICS-II) Audio tape submissions based on overall proficiency

Case Management

Case Management

Dual Coding

Additional QA and CQI Processes Core Correctional Practices (CCP) Frontline staff ORAS administration Caseworkers & Intake Specialists Group observation Cog Skill Specialists Education and Employment Specialists

Application of QA/CQI data

Establishing research partnerships Problem 5

Using Outside Researchers Some projects may need an outside evaluator/researcher to address: Limited resources Conflicts of interest Desire to maintaining anonymity or confidentiality Identifying research partnerships Local Universities State or county level organizations

Recent Research Collaborations PTSD and Trauma Interventions Ongoing training and evaluation Employee Focus Groups Maintain anonymity Client Utilization of Services Geospatial analysis and software

Steps to identifying local research partnerships Discussion Steps to identifying local research partnerships

Questions?