Handbook of Recidivism Risk / Needs Assessment Tools
Description
Correctional and healthcare professionals around the world utilize structured instruments referred to as risk/needs assessment tools to predict the likelihood that an offender will recidivate. Such tools have been found to provide accurate and reliable evaluations and are widely used to assess, manage, and monitor offenders both institutionally as well as in the community. By identifying offenders in need of different levels of intervention, examining causal risk factors, and individualizing case management plans, risk/needs assessment tools have proven invaluable in addressing the public health issue of recidivism. Recidivism Risk/Needs Assessment Tools brings together the developers of the most commonly-used risk/needs assessment tools to provide a comprehensive overview of their development, peer-reviewed research literature, and practical application.
Written by the leading professionals in the field of risk/needs assessment, the book provides chapters on: Recidivism Risk Assessment in the 21st Century; Performance of Recidivism Risk Assessment Instruments in Correctional Settings; Correctional Offender Management Profiles for Alternative Sanctions (COMPAS); the Federal Post-Conviction Risk Assessment Instrument; the Inventory of Offender Risks, Needs, and Strengths (IORNS); the Level of Service (LS) Instruments; the Ohio Risk Assessment System (ORAS); the Self-Appraisal Questionnaire (SAQ); the Service Planning Instrument (SPIn); the Static Risk Offender Needs Guide-Revised (STRONG-R); the Offender Group Reconviction Scale (OGRS); the Forensic Operationalized Therapy/Risk Evaluation System (FOTRES); the RisCanvi; and more.
* Systematically identifies currently-validated recidivism risk/needs assessment tools
* Reviews research on recidivism risk/needs assessment tools used internationally
* Each chapter presents sufficient detail to decide whether a given recidivism risk/needs assessment tool is right for your practice
Recidivism Risk/Needs Assessment Tools is ideal for correctional, probation and parole, and behavioral health professionals.
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Persons
JAY P. SINGH, PhD, PhD, is the Founder of the Global Institute of Forensic Research and is affiliated with the Department of Psychiatry and the Wharton School of Business at the University of Pennsylvania.
DARYL G. KRONER, PhD, is a Professor at Southern Illinois University and reviewed the effectiveness of offender programs at the Illinois Department of Corrections.
J. STEPHEN WORMITH, PhD, is a Professor of Psychology at the University of Saskatchewan, and Director of the Centre for Forensic Behavioural Science and Justice Studies.
SARAH L. DESMARAIS, PhD, is an Associate Professor and Coordinator of the Applied Social and Community Psychology Program at North Carolina State University.
ZACHARY HAMILTON, PhD, is an Associate Professor of Criminal Justice and Criminology and the Director of the Washington State Institute for Criminal Justice at Washington State University.
Content
Notes on Contributors xv
Preface: Recidivism Risk Assessment in the 21st Century xxiii
John Monahan
Part I Introduction 1
1 Performance of Recidivism Risk Assessment Instruments in U.S. Correctional Settings 3
Sarah L. Desmarais, Kiersten L. Johnson, and Jay P. Singh
Characteristics of Risk Assessment Instruments 4
Characteristics of Samples and Studies 5
The Current Review 5
Method 6
Review Protocol 6
Search Strategy 6
Results 10
Characteristics and Content of Instruments 10
Sample and Study Characteristics 12
Performance of Recidivism Risk Assessment Instruments 14
Discussion 19
Limitations 21
Conclusions 21
Author Note 22
References 22
Supplemental Table 29
Part II Risk/Needs Assessment in North America 31
2 The CAIS/JAIS Approach to Assessment 33
Christopher Baird
Introduction 33
History of Development 33
Development and Validation of Risk Assessment 35
Development of CAIS/JAIS Needs Assessment Instruments 38
Development, Synopsis, and Evaluation of CMC/SJS 39
Synopsis of CMC Supervision Strategies 41
CMC Evaluation Results 44
Current Issues and Future Directions 45
References 46
3 Correctional Offender Management Profiles for Alternative Sanctions (COMPAS) 49
Tim Brennan and William Dieterich
Introduction 49
Purposes of COMPAS 49
Predictive Risk Assessment 49
Explanatory and Needs Assessment 50
Avoiding the Various Disconnects between Assessment, Treatment, and Outcomes 50
Different versions for Different Organizational Purposes and Target Populations 50
Methodological Goals 50
Background and History of Development 50
Incorporate Theoretical Guidance in Selecting Relevant Scales to Achieve a Comprehensive Coverage of Explanatory Factors 50
Incorporate Empirical Guidance from Meta-analytic Research on Predictive Factors 51
Incorporate the Strength/Resiliency Perspective 51
Incorporate Gender-Responsive Risk and Need Factors 51
Dynamic vs. Static Items in COMPAS Risk Assessments 51
Built-In Data Validity Tests and Error-Checking 51
Flexible Access to External "In-Depth" Diagnostic Assessments 51
Advanced Analytical Methods for Risk Prediction 52
Multiple Dependent Criterion Variables 52
Systematic Re-validation and Calibration to Accommodate Offender Population Changes 52
Ease of Use and Efficiency 52
Scalability-Agency Control Over Data Needs and Staff Workloads for Specific Processing Decisions 53
Integrated Database and Seamless Links from Risk/Needs Assessment to Case Management, Treatment Goals, Treatments Provided, and Outcomes 53
Generalizability of Predictive Accuracy Across Regions, Agencies, and Racial/Gender Categories 53
Versions of COMPAS 53
Youth COMPAS 53
Reentry COMPAS 54
Women's COMPAS 54
Norming or Standardization Samples 54
Settings for COMPAS Assessments (Pretrial, Community Corrections, Prison/Jail) 55
Web-based Implementation of Assessments and Subsequent Treatment and Outcome Data 55
Predictive and Needs/Explanatory Scales 55
Additional Risk Models for Other Criminal Justice Criterion Outcomes 56
Measures of Predictive Accuracy 56
Independent Validation Studies by External Researchers, from Diverse Geographical Areas 56
Follow-up Data and Time Frames 56
Internal Classification for Jails/Prisons for Offender Management and Responsivity 56
Theoretical Foundations of COMPAS 57
Social Learning Theory 57
The General Theory of Crime 57
Strain Theory/Social Marginalization 57
Routine Activities Theory 57
Social Disorganization/Sub-cultural Theories 58
Control/Restraint Theories 58
Data Collection and Interviewing 58
Official Records/File Review 58
Interview Section 58
Self-Report Paper and Pencil Section 59
Scoring Guidelines 59
Administrator Qualifications and Training Modules 59
Basic 2-day Training 59
Software Training 59
Train-the-Trainer Workshops 60
Anomaly or Error Detection 60
Coding Integrity Checks 60
Reliability Research 60
Internal Consistency Reliability 60
Test-Retest Reliability 61
Inter-rater Reliability 61
On-Screen Hyperlinks to Give Staff Immediate Access to Question Definitions 62
Systematic Identification, Removal, or Revision of Problematic Questions 62
Using Machine Learning (ML) Classifiers to Achieve High Reliability of Prison Classification Assignments 62
Latent Factor Structure of the Overall COMPAS Assessment Domain 62
1. Early Starter, High Violence Risks with Very Low Social Capital 63
2. Extent of Criminal Involvement 63
3. Social Marginalization 63
4. Violence 63
5. Antisocial Personality and Attitudes 63
6. Socialization and Social Learning in Antisocial Environments 63
7. Transience, Unstable Residence, Drugs, and Poor Social Adjustment 63
8. Antisocial High-Risk Lifestyle 63
Criterion Validity: Predictive and Concurrent Validity 64
Predictive Validity of COMPAS Has Been Replicated in Multiple Jurisdictions, Multiple Agencies, and by Different Research Teams 64
Predictive Validity Across Gender and Racial Groups (Criterion Related Validity) 64
Content Validity-Coverage of Relevant Factors 66
Meta-analytic Selection 67
Theory-based Selection 67
Predictive Validity of Specific COMPAS Subscales 67
Calibration 68
Discrimination and Dispersion 68
Construct Validity-Factorial, Concurrent, and Criterion Validity 69
Factorial Validity of COMPAS Subscales 69
Construct and Convergent Validity 69
Substance Abuse 70
COMPAS Subscale Correlates with Official Criminal Behaviors and Age of Onset 70
Criminal Attitudes and Criminal Personality Scales 70
Implementation Research 70
User Satisfaction 70
Impact Evaluation and Cost/Benefit Analyses of COMPAS 71
Current Issues and Future Directions 71
1. Data Analytic Advances 71
2. Advances in Automated Data Collection Procedures 72
3. Diverse Pathways to Crime and New Internal Classifications for Prisons 72
4. Advances in Decision Analytic Methods for Setting Cut Points in Risk Assessment Scales 72
References 72
4 The Federal Post-Conviction Risk Assessment Instrument: A Tool for Predicting Recidivism for Offenders on Federal Supervision 77
Thomas H. Cohen, Christopher T. Lowenkamp, and Charles Robinson
Introduction 77
Overview of Risk Assessment Tools 79
History of Actuarial Instruments in the Federal Probation System 79
Development and Implementation of the Federal Post Conviction Risk Assessment Instrument 81
Administration and Scoring of the PCRA 82
Officer Section of the PCRA 82
Handling Scoring Omissions and Missing Data 83
Offender Section of the PCRA 84
Highlighting Addressable Criminogenic Needs 84
The Role of Supervision Overrides in the PCRA's Risk Assessment Mechanism 85
The PCRA Assessment and Reassessment Policy 85
Overview of Research Using the PCRA 86
Revalidation of the PCRA's Predictive Validity 86
Investigating the PCRA's Dynamic Characteristics 88
Studies Investigating the PCRA for Race/Gender Bias 92
Evaluating the Predictive Value of the PICTS Criminal Thinking Styles 92
The PCRA and Special Offender Populations 93
Studies Using the PCRA to Investigate Supervision Overrides, Implementation of the Low-Risk Policy, the Presence of Responsivity Issues, and Convergence of Long-Term Recidivism Rates Across Risk Levels 94
PCRA 2.0 and the Future of the PCRA 96
Conclusion 97
References 97
5 The Inventory of Offender Risk, Needs, and Strengths (IORNS) 101
Holly A. Miller
Rationale and Development of the IORNS 102
Standardization 106
Reliability 106
Validity 107
Construct Validity 107
Internal Structure 109
Predictive Validity 109
Tracking Change through Treatment 110
Case Illustration 111
Utility and Future Directions of the IORNS 114
References 114
6 The Level of Service (LS) Instruments 117
J. Stephen Wormith and James Bonta
The Origins and Evolution of the Level of Service (LS) Instruments 118
The Theoretical Underpinnings of the LS 119
Administration 121
Reliability 124
Validity 126
Current Issues, Concerns, and Future Directions 132
Summary and Conclusions 135
References 139
7 The Ohio Risk Assessment System 147
Edward J. Latessa, Brian Lovins, and Jennifer Lux
Overview 147
Theoretical Framework 150
The Creation and Validation of the ORAS 150
Administering the ORAS 151
Training Requirements and Qualifications 152
The Validity of the Ohio Risk Assessment System 153
Ohio Validation 153
ORAS Pretrial Assessment Tool 153
ORAS Community Supervision Tool 153
Indiana Validation 154
Texas Validation 155
ORAS Prison Intake Tool 156
Ohio Risk Assessment System-Reentry and Supplemental Reentry Tools 157
The Reliability of the Ohio Risk Assessment System 158
Implementation Research 159
Use of the ORAS 160
Benefits of ORAS 160
Current Issues and Future Directions 161
References 162
8 Self-Appraisal Questionnaire (SAQ): A Tool for Assessing Violent and Non-Violent Recidivism 165
Wagdy Loza
Development of the SAQ 165
Description of the SAQ Scales 166
Uses of the SAQ 166
Who Can Administer the SAQ? 166
Administering the SAQ 167
Scoring the SAQ 167
Interpreting the Score of the SAQ 168
Example of Reporting the Results of the SAQ 168
Training 168
Limitations of the SAQ 168
Studies Demonstrating the Psychometric Properties of the SAQ 169
Reliability of the SAQ 169
Subscale/Total Correlations 169
Construct Validity 170
Concurrent Validity 170
Predictive Validity 171
The Validity of the SAQ for Use with Female Offenders 173
SAQ as a Classification Measure 173
Comparison Studies with Other Instruments 173
The SAQ and Deception 173
Cultural Diversity Comparisons 174
Predictive Validity of the SAQ for Use with Mentally Ill Offenders 175
The Validity of the SAQ for Use with Young Offenders 175
Postgraduate Research Projects 175
Research Agenda 175
Conclusion 175
Case Study: High Risk 176
Reason for Referral: Intake Assessment 176
References 177
9 Service Planning Instrument (SPIn) 181
Natalie J. Jones and David Robinson
Overview 181
History and Development 182
Theoretical Foundations 184
Content and Measurement 185
Measurement of Strengths 186
Administration and Training 187
Psychometric Properties 187
Research Samples 187
Reliability Research 188
Predictive Validity Research 189
Discussion 194
References 196
10 The Static Risk Offender Needs Guide - Revised (STRONG-R) 199
Zachary Hamilton, Xiaohan Mei, and Douglas Routh
Overview 199
Recidivism Prediction Spotlight 200
Item Types 202
Instrument Purpose(s) 203
Target Population and Setting 204
Time Frame of Prediction 204
Theoretical Framework 204
History of Development 205
The Static Risk Assessment 205
The Offender Needs Assessment 206
The STRONG-R 206
Subscale Construction 206
Methodological Advances 207
Customization and the STRONG-R 207
Criminogenic Need Domains 208
Administration and Training 209
Training at Implementation 209
Ongoing Training for Quality Assurance 211
Reliability and Validity Research 212
Latent Structure 212
Content Validity 214
Internal Consistency 215
Inter-rater Reliability 215
Convergent/Divergent Validity 218
Concurrent Validity 219
Predictive Validity 220
Implementation of the STRONG-R 221
Current Issues and Future Directions 222
Software Applications 222
Responsivity, Case Planning, and Management 223
Methods of Customization 224
References 225
Part III Risk/Needs Assessment Abroad 229
11 Offender Group Reconviction Scale 231
Philip Howard
Overview 231
History of Development, and Key Differences between the Versions 231
The Copas Rate, and Unusual Changes in OGRS Score 232
The Introduction of Offence-free Time and Violence Prediction in OGRS4 233
Summary of Risk Factors Scored in Each Version 234
Operationalizing Recidivism and the Follow-up Period 234
Theoretical Framework 236
Administration 236
Reliability and Validity Research 237
Implementation in Correctional Practice 238
Current Issues and Future Directions 239
References 240
12 Forensic Operationalized Therapy/Risk Evaluation System (FOTRES) 243
Leonel C. Gonçalves, Astrid Rossegger, and Jérôme Endrass
Overview 243
History of Development 243
Description of FOTRES and its Subscales 243
Review of FOTRES Versions 246
Theoretical Framework 247
Scope of Application 247
Risk Characteristics 247
Target Offense 247
Offense Mechanism Hypothesis 247
Administration 248
Validity and Reliability Research 249
Implementation Research 250
Case Studies 251
Current Issues and Future Directions 251
References 252
13 The RisCanvi: A New Tool for Assessing Risk for Violence in Prison and Recidivism 255
Antonio Andrés-Pueyo, Karin Arbach-Lucioni, and Santiago Redondo
Introduction 255
A Brief Overview of the Catalan Correctional System 255
The RisCanvi: A New Tool for Risk Assessment of Prison Recidivism 256
The RisCanvi: Structure and Some Psychometric Properties 258
Using the RisCanvi in Practice 264
Conclusions 266
Acknowledgments 267
References 267
Part IV Conclusion 269
14 Risk Assessment: Where Do We Go From Here? 271
Faye S. Taxman
What Are Major Issues Affecting the Development and Evaluation of Risk Assessment Tools? 272
Do Risk Assessment Tools Accurately Identify the Probability of Recidivism (Predictive Validity)? 273
Do the Risk Assessment Instruments Differentiate Between Those in the Justice System and Those That Are not in the Justice System? 275
Are the Methods to Score Items and Categorize Risk Appropriate? 275
Are Instruments Neutral on Race, Gender, and Other Key Demographic Issues? 277
Do the Domains on the Risk Assessment Instruments Have Construct and Content Validity? 278
How to Implement Risk Assessment Instruments so They Are Useful in Practice Including Case Planning, Resource Allocation, Treatment Referral or Placement, and Clinical Progress? 280
Conclusion 281
References 282
Appendix 285
Index 305
