Feel it and deal with it: mental health practitioners' experiences of exposure to the trauma of survivor clients

Empathic engagement by the trauma therapist with another person's traumatic experiences is believed to create risks for the helping professional. Much attention has been focused upon the mental health professional experiencing symptoms of distress as a result of their exposure to the material of clients who survive traumatic incidents. This thesis contains the findings of a qualitative study that centres on a group of male mental health professionals and their experiences of exposure to the trauma material of survivor clients. The participants of the study practise within an internal Employee Assistance Program that provides, among other duties, a 24 hour, 7 day response to critical incidents to a heavy transport industry. Using semi-structured, in-depth interviews, the effects on the trauma therapists are explored by analysing their reactions to their survivor clients' accounts, the impact of these experiences upon their psychological schema, the organisational culture in which they practise and its influence upon their experiences and the methods participants use to cope with the psychological effects of exposure to trauma material. Participants' experiences are closely examined for critical comparisons with vicarious traumatization. Therapists' responses reveal their continued ability and motivation to empathically engage with the trauma material of survivor clients despite the potential risks.

A study of outcomes measures in forensic mental health

Outcomes measures, which is the measurement of effectiveness of interventions and services has been propelled onto the health service agenda since the introduction of the internal market in the 1990s. It arose as a result of the escalating cost of inpatient care, the need to identify what interventions work and in what situations, and the desire for effective information by service users enabled by the consumerist agenda introduced by Working for Patients white paper. The research reported in this thesis is an assessment of the readiness of the forensic mental health service to measure outcomes of interventions. The research examines the type, prevalence and scope of use of outcomes measures, and further seeks a consensus of views of key stakeholders on the priority areas for future development. It discusses the theoretical basis for defining health and advocates the argument that the present focus on measuring effectiveness of care is misdirected without the input of users, particularly patients in their care, drawing together the views of the many stakeholders who have an interest in the provision of care in the service. The research further draws on the theory of structuration to demonstrate the degree to which a duality of action, which is necessary for the development, and use of outcomes measures is in place within the service. Consequently, it highlights some of the hurdles that need to be surmounted before effective measurement of health gain can be developed in the field of study. It concludes by advancing the view that outcomes research can enable practitioners to better understand the relationship between the illness of the patient and the efficacy of treatment. This understanding it is argued would contribute to improving dialogue between the health care practitioner and the patient, and further providing the information necessary for moving away from untested assumptions, which are numerous in the field about the superiority of one treatment approach over another.

Knowledge engineering for mental-health risk assessment and decision support

Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Belief nets for mental health

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Discovering knowledge structures in mind maps of mental health risks

This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

Dr. June Christmas, Commissioner of mental health, at City Hall for Intro 2

General note: Title and date provided by Bettye Lane.