Professor Nick Alderman and Paul Mooney, of Elysium Neurological Services, discuss the subject of behavioural risk and how to support individuals and teams in assessing and managing that
For many years, clinicians in mainstream mental health and forensic services have made use of formal risk assessment tools that aid decisions regarding the treatment and management of people with challenging behaviour and /or offending histories. However, the applicability of such measures outside of the mainstream is questionable, and in in neurological or neurobehavioural services, there has been little formal research considering their validity and reliability, or indeed to question whether such tools would be helpful.
Risk assessment in this context has evolved over the past 50 years, after a seminal study by Ennis & Litwack (1974) who claimed that using clinical judgement alone to determine an individual’s risk was akin to ‘flipping coins in the courtroom’. As such, their view was that clinical judgement was no better than chance, nor was it particularly scientific. This was one of the studies that precipitated a large number of measures to be developed in the years that followed, referred to as ‘actuarial’ measures of risk.
Tools such as the Violence Risk Appraisal Guide (VRAG; Harris et al, 1993) and the Static-99 (Hanson, 1997) comprised static, and therefore unchangeable, factors that claimed to predict violent or sexual offending behaviours. However, over time, these fell out of favour as they (i) had variable reliability and validity for many populations, eg, Learning Disability (Lindsay et al, 2008), and (ii) they are based upon unchanging factors, and so do not account for behavioural change post-treatment.
In the mid-1990s, a new form of risk assessment was born: the Structured Professional Judgement (SPJ). SPJ tools, such as the HCR-20 Violence Risk Assessment (Webster et al, 1995; Douglas et al, 2013), Risk of Sexual Violence Protocol (RSVP; Hart et al, 2003) and Short-Term Assessment of Risk and Treatability (START; Nicholls et al, 2007) blended historical, current clinical and future focused variables, with the aim of understanding a person’s risk, as well as helping to generate management plans to mitigate it.
Such tools are now commonplace in clinical and forensic practice, yet their utility outside of mainstream prison and mental health populations remains questionable. For example, in a study considering risk assessment for people with Learning Disability and Autism across varying tiers of secure and community care (Lindsay et al, 2008), it was found that the HCR-20, arguably the most commonly used of the SPJ tools, was less predictive of risk behaviours than in the mental health population the tool was developed for. This unsurprising when considering some or the variables included in the schemes, such as relationship stability and employment history.
These factors are cited to represent a lifestyle predictive of violence in mainstream populations, but in Learning Disability, many people coming to the attention of services may have had similar problems as a result of cognitive deficit, communication difficulties or social disadvantage, rather than a chaotic and aggressive way of living.
Neurological populations
Neurological, and especially neurobehavioural, services can observe high levels of verbal and physical aggression from service users, as well as sexually disinhibited behaviours, property damage and self-harming. This is in addition to the risk of falls, fire and a general poor awareness of the environment as a consequence of cognitive impairment.
However, there are few studies that have sought to develop methodologies that help clinicians to quantify risk or to predict the likelihood of such behaviours before, during and after intervention. This is perhaps unsurprising given the heterogeneous nature of the population with which we work. In addition, research by Alderman et al (2018) found that the START, which has rapidly become a popular measure of risk in mental health populations, was unsuitable for neurobehavioural populations. The authors concluded that the tool did not efficiently predict challenging behaviours, but that the field would potentially benefit from measures designed with this population in mind.
Neurobehavioural (NbR) services often take the view that the best predictor of behaviour is past behaviour, which is a longstanding tenet of behaviourism. As such, NbR services often utilise tools such as the OAS-MNR (Alderman, Knight & Morgan, 1997) and SASBA (Alderman, Johnson, Green, Birkett-Swan & Yorston, 2008) as a means of collecting rich data that can inform functional analyses and intervention plans. Such tools are not referred to as ‘risk assessments’, but there is certainly an overlap in terms of how the data may be used.
A solution under our nose?
Clinical formulation has long been the bedrock of Applied Psychology, as a means of synthesising data from various sources into a coherent narrative and set of interconnected and testable hypotheses regarding a specific behaviour. As such, when conducted well, a clinical formulation should bypass the concerns raised by Ennis & Litwack and provide teams with a structured approach to aid our understanding of an individual and their behaviour, whether this be the result of ABI, progressive disorders or other underlying conditions. As such, rather than seeking to develop new tools, perhaps this may be our most reliable method of assessing risk.
Historically, formulation was seen as the domain of Applied Psychologists, as Applied Psychology training has a focus on the development of formulation skills. However, it is vital that such work is completed as a team, in order to ensure good validity and reliability of any decisions made – together we can see what individually we cannot.
There are numerous models that may be used to support teams to formulate the risks and needs of a given patient, all of which have pros and cons. However, all formulations require a consistent structure (a parity of approach tends to aid staff understanding) and a way of pulling together qualitative or quantitative data from a range of sources.
Arguably, this information should come from a range of reliable sources and at least incorporate a review of premorbid personality and behaviour; symptoms observed post-ABI, with consideration as to the specific areas of injury; and an analysis of the protective factors that aid the person’s resilience to cope with emotional and behavioural distress.
In addition, it makes sense to embed a data-led approach to help identify (i) the likely functions of the person’s behaviour, ie, to conduct a functional assessment using validated behavioural observation tools such as the OAS-MNR (Alderman et al, 1997), and (ii) reflect on potentially helpful measures that identify and/or quantify specific areas of functioning that would benefit from treatment, such as the SASNOS (Alderman, Wood & Williams, 2011).
While such a process moves away from a ‘checklist style approach’ used in mainstream services, and could be seen to be labour intensive, such an approach is arguably more robust, holistic and tailored for the individual, while still drawing upon tools already validated for this complex and heterogeneous population.
Paul Mooney BSc(Hons); MSc; CPsychol(Foren); AFBPsS; CSCi
- Clinical Director for Service Development & Improvement, Elysium Neurological Services
- Assistant Professor, School of Medicine, University of Nottingham
- Visiting Fellow, School of Psychology, University of Lincoln
Prof Nick Alderman BA (Hons), MAppSci, PhD, CPsychol, CSci, FBPsS
- Senior Clinical Director & Head of Psychology, Elysium Neurological Services
- Department of Psychology, Swansea University, Swansea, UK
References:
Alderman, N., Knight, C. & Morgan, C. (1997). Use of a modified Overt Aggression Scale in the measurement and assessment of aggressive behaviours following brain injury. Brain Injury, 11(7), 503-23.
Alderman, N., Major, G & Brooks, J (2018). What can structured professional judgement tools contribute to management of neurobehavioural disability? Predictive validity of the Short-Term Assessment of Risk and Treatability (START) in acquired brain injury. Neuropsychological Rehabilitation, Vol.28, No.3., pp448-465.
Alderman, N., Wood, R. L., & Williams, C. (2011). The development of the St Andrew’s-Swansea Neurobehavioural Outcome Scale: Validity and reliability of a new measure of neurobehavioural disability and social handicap. Brain injury, 25(1), 83-100. doi: 10.3109/02699052.2010.532849
Douglas, K. S., Hart, S. D., Webster, C. D., & Belfrage, H. (2013). HCR-20 (Version 3): Assessing risk of violence – User guide. Burnaby, Canada: Mental Health, Law, and Policy Institute, Simon Fraser University.
Ennis, B.J. & Litwack, T.R. (1974). Psychiatry and the Presumption of Expertise: Flipping Coins in the Courtroom. California Law Review, Vol.62, No.3, pp. 693-752.
Hanson, R. K. (1997). The development of a brief actuarial risk scale for sexual offense recidivism. (User Report 97-04). Ottawa: Department of the Solicitor General of Canada.
Harris, G. T., Rice, M. E. & Quinsey, V. L. (1993) Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Criminal Justice and Behaviour, 20, 315–335.CrossRefGoogle Scholar
Hart, S., Kropp, P.R., & Laws, D.R.; with Klaver, J., Logan, C, & Watt, K.A. (2003). The Risk for Sexual Violence Protocol (RSVP): Structured professional guidelines for assessing risk of sexual violence. Vancouver, BC: The Institute Against Family Violence.
Knight, C., Alderman, N, Johnson, C., Green, S., Birkett-Swan, L. & Yorstan, G (2008). The St Andrew’s Sexual Behaviour Assessment (SASBA): Development of a standardized recording instrument for the measurement and assessment of challenging sexual behaviour in people with progressive and acquired neurological impairment. Neuropsychological Rehabilitation, 18(2), 129-59.
Lindsay, W. R., Hogue, T. E., Taylor, J. L., Steptoe, L., Mooney, P., O’Brien, G., & Smith, A. H. W. (2008). Risk assessment in offenders with intellectual disability: A comparison across three levels of security. International Journal of Offender Therapy & Comparative Criminology, 52, 90-111.
Nicholls, T., Gagnon, N., Crocker, A., Brink, J., Desmarais, S., & Webster, C. (2007). START Outcomes Scale (SOS). Vancouver, Canada: BC Mental Health & Addiction Services.
Webster, C. D., Eaves, D., Douglas, K.S. & Wintrup, A. (1995). The HCR-20 Scheme: The assessment of dangerousness and risk, British Columbia: Simon Fraser University and British Columbia Forensic Services Commission.
