Violence Risk - Assessment and Management E-Book

Christopher D. Webster

• Herausgeber: John Wiley & Sons
• Kategorie: Geisteswissenschaft
• Sprache: Englisch

Seitenzahl: 519

Veröffentlichungsjahr: 2013

Beschreibung

This expanded and updated new edition reflects the growing importance of the structured professional judgement approach to violence risk assessment and management. It offers comprehensive guidance on decision-making in cases where future violence is a potential issue.

• Includes discussion of interventions based on newly developed instruments
• Covers policy standards developed since the publication of the first edition
• Interdisciplinary perspective facilitates collaboration between professionals
• Includes contributions from P.Randolf Kropp, R. Karl Hanson, Mary-Lou Martin, Alec Buchanan and John Monahan

Leseprobe

Contents

Tribute

List of Figures

List of Tables

List of Boxes

About the Authors

Other Books by the Authors

Foreword

Which Elements of Structure Help?

Which Approaches Are Strongest in Which Populations?

“Broken Legs” and “Overrides”

Which Factors Should Clinicians Address in Treatment?

Conclusion

Preface to the Second Edition

Acknowledgments

1 Decision Points

Laws

Interfaces

Professional Ethics and Standards

Notes

2 Points of View

Psychoanalysis

Phenomenology

Conventional Behaviorism

Radical Behaviorism

Brain–Behavior Relationships

The Relevance of Theory to Assessing and Managing Risks

Scientific Methods

Recent Theoretical Innovations

Notes

3 Predictions and Errors

Predictions Under Duress

Actuarial Predictions

Predictions in the Individual Case

Prediction Errors

The Actuarial vs. Clinical Debate

Checklists

Notes

4 Developmental Trajectories

Severe Developmental Problems

Intellectual Deficit Problems

Conduct and Personality Problems

SNAP: Working Backwards from a Treatment Program to the Creation of Risk Assessment Devices

Development of the EARL-20B and the EARL-21G

Testing the EARLs

Development of the SAVRY

Development of the START:AV

Concluding Remark

Notes

5 Symptomologies

Introduction

Symptoms and Causal Mechanisms

Functional Psychoses

Threat/Control Override (TCO)

Moods

Anxiety Disorders

Impulse Control Disorders

Paraphilias

Learning Disability and Neurodevelopmental Disorders

Acquired Brain Injury (ABI)

Dissociative and Conversion Disorders

Malingering and Factitious Disorders

Concluding Remarks

Notes

6 Personality Disorders

Definitions and Classifications

Epidemiology and Natural History

Personality Disorders and Violence

Psychopathy

Notes

7 Substance Abuse

Definitions and Classifications

Substance Abuse and Violence

Note

8 Factors

The Search for Risk Factors at the Metropolitan Toronto Forensic Service (METFORS)

The Search for Risk Factors in the MacArthur Study

Complexities

Gathering Facts for Factors

Notes

9 SPJ Guides

Tube Map

Scientific Verification of SPJ Schemes

Constructing SPJ Schemes

Development of the HCR-20

Testing the HCR-20: Versions 1 and 2

Development of the START

Testing the START

Established SPJ Schemes Covered in Other Chapters

Other SPJ Risk Assessment Devices

SPJ Schemes Which Could Be Developed

Notes

10 Competitions

Notes

11 Planning

Introductory Considerations

Formulations

SPJ and Planning

Notes

12 Transitions

Measuring the Effects of Transitions

Achieving Successful Transitions

Preparing Clients for Transitions

Notes

13 Sequential Redirections

Contemporary Influences

Structured Professional Judgment and Intervention Planning

Pedals (Footholds): History and Therapeutic Alliance

History

Therapeutic Alliance

Link 1: Awareness

Link 2: Identity

Link 3: Idiosyncrasies

Link 4: Predictability

Link 5: Engagement

Link 6: Plans

Link 7: Situational Complexities

Link 8: Support and Coordination of Services

Link 9: Monitoring

Link 10: Resilience

Gearing

The Chain in Action

Notes

14 Implementations

Maximizing the Chances for Successful Implementation

Minimizing the Chances for Successful Implementations

Conclusions

Notes

15 Teaching and Researching SPJ Guides

Developing Expertise

Gaining Mastery

Confirming Fidelity

Notes

16 Spousal Assaulters

Principles of Spousal Assault Risk Assessment

Spousal Assault Risk Assessment Guide

Danger Assessment (DA)

Domestic Violence Screening Inventory (DVSI)

Ontario Domestic Assault Risk Assessment (ODARA)

Notes

17 Sex Offenders

Recidivism Base Rates

Female Sexual Offenders

Online Sexual Offenders

Recidivism Risk Factors

Overall Evaluations of Risk

The Effectiveness of Treatment

Summary and Conclusions

18 Teams

Notes

19 Communications

Notes

20 Getting It Wrong, Getting It Right (Mostly)

Getting It Wrong

Getting It Right

Notes

Questions

Afterword

Show Me the Money: Risk Assessment as Cost Containment

Show Me the Money: Risk Management as Chimera

To Manage Violence Risk, Rely on “Dynamic” Risk Factors?

Risk and Uncertainty: “The Unknowable Contingencies of Life”

Note

References

References

Index

This edition first published 2014© 2014 John Wiley & Sons, Ltd

Edition history: John Wiley & Sons, Ltd. (1e, 2007)

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Library of Congress Cataloging-in-Publication Data

Webster, Christopher D., 1936–Violence risk-assessment and management : advances through structured professional judgement and sequential redirections / Christopher D. Webster, Quazi Haque, Stephen J. Hucker ; with contributions by P. Randolf Kropp, R. Karl Hanson, Mary-Lou Martin. – 2e.        pages cm    Includes bibliographical references and index.

    ISBN 978-1-119-96114-7 (cloth) – ISBN 978-1-119-96113-0 (pbk.) 1. Dangerously mentally ill. 2. Violence. 3. Risk assessment. I. Title.    RC569.5.V55W43 2013    616.85′82–dc23

2013021886

A catalogue record for this book is available from the British Library.

Cover design by Design Deluxe

Tribute

Light on his feetA man of the theatreEducated and dramaticCultivated and debonairRather aristocraticIronic and mischievousCommanding presence

A presence he usesIn the team he leadsKindly and thoughtfullyAnd with restrained compassionWhen talking to benighted peopleEntangled with the unfeeling criminal lawFerreting out what actually happenedPerhaps in some desperate alleyCrowded in by a gang

It will call for a diagnosisThat’s what judges wantIn deciding what to doBut could the Bard help?Marlowe or Dostoyevsky?Sometimes it takes moreThan a scanty police reportTo get to the real nub of it.

Dr. F.A.S. Jenson (1924–1994)Sometime Clinical Director, Metropolitan TorontoForensic Services (METFORS),Clarke Institute of Psychiatry

List of Figures

List of Tables

9.1

Item descriptors in the HCR-20, VI (1995) and V2 (1997)

9.2

Item descriptors in the HCR-20, V3 (2012)

9.3

Item descriptors in V1.1 of the START (2009)

17.1

Sexual recidivism rates (%)

17.2

Established risk factors for sexual recidivism

17.3

Characteristics with little or no relationship with sexual recidivism

List of Boxes

1.1

Best practices in managing risks (themes loosely adapted from guidelines proposed by the DoH (2007), RCP (2008), and RMA (2005))

19.1

The Emeritus Professor of International Law and the Police Court Brief

19.2

Professor Emeritus (after O., Further Forensic Fables, Butterworth, 1928, summarized by C.D.W.)

20.1

Adverse setting circumstances

20.2

Positive setting circumstances

About the Authors

Chris D. Webster has collaborated with many colleagues over the past 20 years in the development and testing of several SPJ schemes (HCR-20, SARA, SVR-20, EARL-20B, EARL-21G, WRA-20, ERA-20, START, and START:AV). He writes on the subject of risk assessment and management and at scientific and professional meetings speaks on the topic whether invited to do so or not. For most of his career, he was Professor of Psychiatry, Psychology, and Criminology at the University of Toronto. Presently he is Professor Emeritus of Psychiatry at the University of Toronto and Professor Emeritus of Psychology at Simon Fraser University.

Quazi Haque is a forensic psychiatrist and honorary lecturer based at the Institute of Psychiatry, King’s College London. He completed his LLM at Northumbria University. At King’s College, London, he helped to develop a national clinical risk management training program and research network with the invaluable assistance of the first author and local colleagues. Over his career, he has researched and taught widely on the topic of risk assessment and management. He sits on several national committees that influence the development and implementation of policies and practices in the field of mental health. Presently, he is Executive Medical Director at Partnerships in Care, a national independent provider of forensic and civil mental health services in the United Kingdom.

Steve J. Hucker, a forensic psychiatrist, has specialized over many years in the study of sex offending. In addition, he offers opinions more broadly on behalf of a wide range of persons within the spheres of corrections and law and mental health. Over the course of his career, he has been responsible for the operation of major clinical assessment and treatment programs. As well as evaluating risks in the individual case, he is also called upon to give opinion about organizations charged with treatment and security responsibilities. He is Professor of Psychiatry at the University of Toronto.

Other Books by the Authors

Autism: New Directions in Research and EducationClinical Assessment and ManagementMental Disorder and Criminal ResponsibilityConstructing DangerousnessDangerousnessClinical CriminologyThe Violence Prediction SchemeImpulsivityClinical Assessment and ManagementRelease Decision MakingRisk Assessment and Management of Violence by the Mentally DisorderedGirlhood AggressionEssential Writings in Violence Risk Assessment and Management

Foreword

The past 20 years have seen a range of attempts to improve the ability of mental health professionals to assess and manage the risk of their patients harming others. One of the most productive has been the development and testing of so-called “structured” approaches. The clinician using a structured approach rates an individual on a range of items known to correlate with violence risk and uses those ratings to allocate the individual to an overall score (where an actuarial method is used) or category (for structured professional judgment (SPJ) methods). Structured approaches help ensure that important pieces of information are not missed and, because the items and the score allotted to them are available for examination, they are more transparent. Research suggests also that their long-term predictive accuracy is greater than that of traditional, unstructured, approaches. The task that remains is to establish to what degree structured approaches are clinically useful.

This is less obvious than it at first seems. Clinicians operating without a structured instrument, after all, have certain advantages. First, their interactions with their patients put them in a position to do more than combine risk factors. People sometimes act for reasons and clinicians who talk to their patients can use those reasons, and someone’s immediate circumstances, in their assessment (Buchanan, 1999). Even if this doesn’t help much over months or years – people’s reasoning and circumstances change – it may help over shorter periods. Second, researchers seek to limit the amount of missing data in follow-up studies. Missing data are a fact of clinical life, yet clinicians still seem to make reasonably accurate predictions (AUC 0.66; see Lidz, Mulvey, & Gardner, 1993; Mossman, 1994). The accuracy of structured approaches may be less when applied in clinical, not research, settings (de Vogel and de Ruiter, 2004).

These and other concerns mean that any contest between the usefulness of structured and unstructured approaches is unlikely to have a “winner.” Instead, we should be considering what forms of integration, beyond using structured approaches to provide clinicians with an aide memoire, make the most sense. But there are some preliminary issues for research to address first.

Which Elements of Structure Help?

If structured approaches are more accurate than unstructured ones over the longer term, where does their additional accuracy come from? A structured assessment has several elements. Providing a list of items for the assessor to address is one (Monahan, 2008). But it also allows the assessor to rate those items in reliable ways, ensuring that others can understand the findings and offering the opportunity to monitor change over time. Third, a structured approach can score the responses on each item. Fourth, it can combine these item scores to generate an overall score. Finally, it can provide thresholds to be applied to the overall score or, conceivably, to responses on each item, with the object of guiding clinical decision-making.

Several of these elements of structure have been shown to be useful elsewhere in medicine. Checklists reduce anesthetic (Charlton, 1990) and surgical (Haynes et al., 2009) complication rates. Integrating information from mammograms using an algorithm predicts malignancy more accurately than do clinicians working without structure from the same X-rays (Getty et al., 1988). We don’t yet know which elements of structure benefit violence risk assessment. They may not be the same as for the rest of medicine. Anesthetic and surgical checklists are intended to prevent mistakes, not to predict and prevent purposeful acts.

Both SPJ and actuarial approaches employ the first, second, and third stages of structure listed here, but the two methods differ with respect to the fourth and fifth. The VRAG, an actuarial method, weights and combines item responses (Harris, Rice, & Quinsey, 1993) while the HCR-20, an SPJ one, encourages clinicians to use those responses in reaching an “overall judgment” (Webster et al., 1997). In addition to establishing which aspects of structure are most valuable, future empirical research may indicate whether the answers are the same for actuarial and SPJ approaches. The answers affect resources. Rating items reliably can be time consuming and requires training and supervision. Even a checklist can come with substantial costs, not all of which derive from the need for staff training and client interviews. Risks, once identified, become potential sources of liability unless they are addressed.

Which Approaches Are Strongest in Which Populations?

The tendency for the predictive validity of structured instruments to “shrink” when they are used on samples different from those on which they were developed probably derives, in part, from the heterogeneity of patient violence and its correlates. Different variables predict violent behavior in different settings (McDermott et al., 2008, McNeil et al., 2003; Thomson et al., 2008) and different variables predict different types of violent behavior (Sjöstedt and Grann, 2002). Risk assessment instruments maximize their accuracy by utilizing the correlates of violence that exist in the settings in which they are tested. By the same token, they lose some of that accuracy when those correlates change.

Thus the HCR-20 includes mental illness as a risk factor. The VRAG algorithm, however, treats schizophrenia as protective (Harris, Rice, & Quinsey, 1993). This difference is usually explained in terms of the samples used in the development of the instruments: schizophrenia is protective when compared with personality disorder and the VRAG samples contained large numbers of personality disordered people in addition to the mentally ill. The availability of this type of information is important, because mental health services seeking to introduce a structured approach can look at the samples in which each instrument has been shown to be valid and choose their instrument accordingly.

But other forms of heterogeneity are more complex, making it difficult to know when a scale has been appropriately tested. Symptoms of mental illness have consistently been shown to predict in-patient violence (McNeil et al., 2003; McNeil and Binder, 1994) yet “active symptoms of major mental illness” as defined by the HCR-20 failed to predict violence in an international study of 240 men with schizophrenic disorders discharged from general and forensic psychiatry units and followed up in the community (Michel et al., 2013). The patient groups are presumably similar in many ways, but the risk factors for violence seem to be different.

No two clinical settings are identical and even in the same setting, patient groups change over time. This means that the ideal state of affairs from the point of view of reliability and validity, when an instrument is tested afresh in each new setting, can only be approached, not realized. One long-term solution may be to integrate validity testing into the procedures under which an instrument is used. The problem is most likely not limited to structured instruments: one would expect clinicians working without the aid of a structured format to do worse in unfamiliar surroundings. It seems important to know how the predictive accuracy of both clinical and structured approaches changes with the circumstances in which those approaches are applied.

“Broken Legs” and “Overrides”

A long-standing question for actuarial approaches has been whether and when a score can be “over-ridden” (see Harris and Rice, 1997). Elsewhere in medicine, permitting exceptions to actuarially derived algorithms sometimes seems to help. Although Getty et al.’s mammogram algorithm, described earlier, did better than unstructured clinicians, the best results were achieved by clinicians who had available the result of the algorithm but who could then decide whether or not to make an exception (unstructured clinical judgment AUC 0.83; algorithm 0.86; combined 0.88). The same may be true for risk assessment. Clinicians’ final judgments, using the HCR-20 but not governed by an algorithmic combination of the item scores, outperform an actuarial use of the same instrument in females (de Vogel and de Ruiter, 2005), criminal offenders (Douglas, Yeomans, & Boer, 2005), and forensic psychiatric patients (Douglas, Ogloff, & Hart, 2003).

While discretion of this type is central to SPJ, actuarial scales have varied in their attitude to “overrides” (see Quinsey et al., 2006). One way forward would be to define the circumstances in which overrides will apply and study whether or not using them makes predictions more accurate. In this way, actuarial approaches will maintain their transparency. While the experience of radiology suggests that any consequent improvement in predictive accuracy may be slight, defined exceptions to actuarial algorithms could have other advantages too.

Clinicians need to be able to respond appropriately in unusual circumstances (direct threats with a weapon in hand, for instance) and are more likely to adopt structured approaches that allow them to do so. Empirical research may also tell us why permitting overrides seems to help, sometimes. Clinicians who outperform the “HCR-20 used actuarially” may either be making use of extra information or combining the information collected by the instrument more effectively. Getty et al. were unsure which was helping their radiologists, but suspected that it was their ability to use information not captured by the algorithm (Getty et al., 1988).

Which Factors Should Clinicians Address in Treatment?

Where actuarial approaches recommend treatment interventions, those interventions usually combine psychiatric treatment with therapy aimed at “criminogenic needs” (Quinsey et al., 2006, p. 249). Individual items are not identified as means of monitoring risk. Instead, the actuarial approach is used to allocate a client to the most appropriate setting where treatment can take place. SPJ, on the other hand, identifies areas of clinical concern where treatment can be targeted. Some reviews go further, suggesting that changes in “clinical” and “risk” variables, such as insight and psychotic symptomatology, can then be used to monitor progress (Maden, 2007; Webster and Hucker, 2007). If this works, it seems a good reason for clinicians to adopt an SPJ approach.

Whether it does, in fact, work requires empirical exploration. One question is, do scores on “clinical” and “risk” variables change as the level of risk changes? Detailed observation may show that some variables that are rated by structured instruments can be used to monitor risk while others cannot. A second question is, can this change be brought about by treatment? The mere existence of a change that mirrors violence risk, while potentially a valuable tool in risk management, does not prove the case one way or the other. Perhaps we will simply be able to recognize a risk without being able to do anything about it. An intervention study, however, might show that treatment addressing “clinical” or “risk” variables reduced aggression.

Even then, distinguishing the effect of “SPJ-oriented” interventions, perhaps psychological treatment to improve insight (Kemp et al., 1996), or pharmacological interventions aimed at impulsivity, will be difficult. The generic treatments recommended by actuarial approaches, including medication management and attending to social stressors, do many of the same things. The justification for trying to distinguish the cause of any change must be that managing risk means more than just assessing it. An approach that integrates assessment and management will be more useful to clinicians than one that does not.

Conclusion

Most of the important decisions regarding a patient’s care are reached for several reasons, not just one. The decision as to whether to offer to admit a patient, for instance, depends partly on the risk that the patient presents to himself and other people but also on such factors as the likely benefits of admission and the consequences if the patient remains in the community. If the patient who has been assessed as presenting a risk declines the offer of admission, the decision required becomes still more complicated.

The relationships between these considerations are not simple, and a full description of the role of violence risk assessment in clinical practice requires an understanding of the complex and dynamic array of factors that affect clinical decision-making. It is this type of understanding that will tell us, for instance, whether we should be concerned that clinical placement seems not always to follow VRAG score, even in Ontario (Quinsey et al., 2006), or that tribunal decisions to extend detention seem to be similarly unrelated to how patients score on structured instruments (McKee, Harris, & Rice, 2007).

These and other questions were addressed in the first edition of this book with a level of sophistication often lacking in reviews of empirical research. In this second edition, the authors have succeeded also, as they did in the first, in presenting demanding concepts and sometimes complicated data in a style that is a pleasure to read. Assessing clinical risk requires knowledge of the relevant literature but also an awareness of the importance of the individual and his interaction with the environment. Both of these are dealt with authoritatively here. Mental health professionals interested in improving the clinical assessment and management of violence risk will not be disappointed.

Alec Buchanan

References

Buchanan, A. (1999) Risk and dangerousness. Psychological Medicine, 29, 465–473.

Charlton, J. (1990) Checklists and patient safety. Anaesthesia, 45, 425–426.

de Vogel, V. and de Ruiter, C. (2004) Differences between clinicians and researchers in assessing risk of violence in forensic psychiatric patients. Journal of Forensic Psychiatry and Psychology, 15, 145–164.

de Vogel, V. and de Ruiter, C. (2005) The HCR-20 in personality disordered female offenders: A comparison with a matched sample of males. Clinical Psychology and Psychotherapy, 12, 226–240.

Douglas, K., Ogloff, J. and Hart, S. (2003) Evaluation of a model of violence risk assessment among forensic psychiatric patients. Psychiatric Services, 54, 1372–1379.

Douglas, K., Yeomans, M. and Boer, D. (2005) Comparative validity analysis of multiple measures of violence risk in a sample of criminal offenders. Criminal Justice and Behavior, 32, 479–510.

Getty, D., Pickett, R., D’Orsi, C. and Swets, J. (1988) Enhanced interpretation of diagnostic images. Investigative Radiology, 23, 240–252.

Harris, G. and Rice, M. (1997) Risk appraisal and management of violent behavior. Psychiatric Services 48, 1168–1176.

Harris, G., Rice, M. and Quinsey, V. (1993) Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Criminal Justice and Behavior, 20, 315–335.

Haynes, A., Weiser, T., Berry, W. et al. (2009) A surgical safety checklist to reduce morbidity and mortality in a global population. New England Journal of Medicine, 360, 491–499.

Kemp, R., Hayward, P., Applewhaite, G. et al. (1996) Compliance therapy in psychotic patients: Randomised controlled trial. British Medical Journal, 312, 345–349.

Lidz, C., Mulvey, E. and Gardner, W. (1993) The accuracy of predictions of violence to others. Journal of the American Medical Association 269, 1007–1011.

Maden, A. (2007) Treating Violence: A Guide to Risk Management in Mental Health, Oxford University Press, Oxford.

McDermott, B., Quanbeck, C., Busse, D. et al. (2008) The accuracy of risk assessment instruments in the prediction of impulsive versus predatory aggression. Behavioral Sciences and the Law, 26, 759–777.

McKee, S., Harris, T. and Rice, M. (2007) Improving forensic tribunal decisions: The role of the clinician. Behavioral Sciences and the Law, 25, 485–506.

McNeil, D. and Binder, R. (1994) Screening for risk of inpatient violence. Validation of an actuarial tool. Law and Human Behavior, 18, 579–586.

McNeil, D., Gregory, A., Lam, J. et al. (2003) Utility of decision support tools for assessing acute risk of violence. Journal of Consulting and Clinical Psychology, 71, 945–953.

Michel, S., Riaz, M., Webster, C. et al. (2013) Using the HCR-20 to predict aggressive behavior among men with schizophrenia living in the community: Accuracy of prediction, general and forensic settings, and dynamic risk factors. International Journal of Forensic Mental Health, 12, 1–13.

Monahan, J. (2008) Structured risk assessment of violence, in Textbook of Violence Assessment and Management (eds R. Simon and K. Tardiff), American Psychiatric Publishing, Arlington, VA, pp. 17–33.

Mossman, D. (1994) Assessing predictions of violence: Being accurate about accuracy. Journal of Consulting and Clinical Psychology, 62, 783–792.

Quinsey, V., Harris, G., Rice, M. and Cormier, C. (2006) Violent Offenders. Appraising and Managing Risk, 2nd edn, American Psychological Association, Washington, DC.

Sjöstedt, G. and Grann, M. (2002) Risk assessment: What is being predicted by actuarial prediction instruments? International Journal of Forensic Mental Health, 1, 179–183.

Thomson, L., Davidson, M., Brett, C. et al. (2008) Risk assessment in forensic patients with schizophrenia: The predictive validity of actuarial scales and symptom severity for offending and violence over 8–10 years. International Journal of Forensic Mental Health, 7, 173–189.

Webster, C. and Hucker, S. (2007) Violence Risk: Assessment and Management, John Wiley & Sons, Chichester.

Webster, C., Douglas, K., Eaves, D. and Hart, S. (1997) HCR-20: Assessing risk for violence (Version 2). Mental Health, Law, and Policy Institute, Simon Fraser University, Vancouver, BC.

Preface to the Second Edition

Every book needs a hook, though it did not need the specific stimulus of the tragedy at Sandy Hook – the December 2012 school shooting in Newtown, Connecticut, which resulted in the loss of 26 lives. This and other such sensationally violent crimes seem always to raise questions about a possible connection with mental illness. People are surprised that experts, like our contributors, cannot immediately and confidently answer such very reasonable and obvious questions as “How did it happen, why did it happen? How can similar circumstances be prevented?” All we know is that there can never been a simple answer to the Sandy Hook and similar regularly occurring and widely proclaimed tragedies.