Dyer, Wendy A. (2001) The identification of the careers of mentally disordered offenders using cluster analysis in a complex realist framework. Doctoral thesis, Durham University.
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Abstract
Custody diversion teams were introduced in order to divert mentally disordered offenders away from the criminal justice system and custody because of concerns about the growing prevalence of psychiatric disorder in prison populations. This research explores the impact of one such team on the psychiatric and criminal careers of people referred to it. The framework provided by a complex realist approach, along with the technique cluster analysis, were used to identify and map the different institutional careers experienced by people referred to the Cleveland Diversion Team and the different paths their careers took as a consequence of the team's actions. Five different types of career were identified. Careers One and Two describe experiences of criminalisation - violent offenders with no psychiatric history who were referred, assessed and diagnosed but had no health or social care needs identified and were not referred again. Careers Three and Four describe experiences of criminalisation - violent offenders with a psychiatric history half of whom (Career Three) were referred, assessed and diagnosed, had health or social care needs identified and were not referred again; the remainder (Career Four) were not assessed or diagnosed, nor did they have needs identified and consequently all were re-referred repeatedly. Career Five represents neither medicalisation or criminalisation - individuals referred for information and for whom little else is known. The implications of these findings include re-focusing the diversion service on Careers Three and Four. This would avoid stigmatising Careers One and Two and achieve positive outcomes by assessing and meeting the needs of all those in Careers Three and Four. In addition there is the promising application of this methodology elsewhere in other research which involves the analysis of large and complex datasets describing social processes.
Item Type: | Thesis (Doctoral) |
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Award: | Doctor of Philosophy |
Thesis Date: | 2001 |
Copyright: | Copyright of this thesis is held by the author |
Deposited On: | 01 Aug 2012 11:44 |