Influence of the Knowledge Produced by Forensic Criminology - Essay Example

Anticipate and evaluate the potential influence of the knowledge produced by forensic criminology on criminal justice policy and practice When you have identified your particular area of interest, (1)find a relevant piece of research that will help you to explain the issue and the effects this may have. You must be able to relate this piece of research to practice development within (2) one of the agencies within the criminal justice system or any partner-agency that might contribute to crime and disorder reduction. You then need to (3) discuss the research methodology, (4) what is the research about, (5) how was it done, (6) how does it add to your knowledge of the subject, (7) does it achieve the stated aims. (8) This can then be linked to the change in practice by the associated criminal justice agency. (9)How did this piece of forensic criminological research impact on service provision? Was it useful? (10) Did it lead to further evaluation and change in practice, or is the research currently informing practice. Research And Its Influence On Practice In The Criminal Justice System Sex offender management is one of the biggest concerns facing communities (Baratta et al., 2012). Because sex offenders are reintroduced into the community after completion of their sentences, the risk of recidivism cannot be ignored. To address this concern, various policies have been developed that include sex offender registries, long-term supervision protocols, treatment and supervision programs. What these initiatives assume is that the community supervision of sex offenders can cause a reduction in their risk of reoffending (Hanson et al., 2007). As seen in the case study of James and Craig, however, there does exist recidivism among sex offenders despite being on probation. Hanson et al. point out that risk of reoffending can be reduced through supervision only when the factors related to reoffending are monitored and addressed. The National Offender Management Service (NOMS) of UK is an agency under the Ministry of Justice and is responsible for supervising offenders both in the community and within custody (UK, NOMS, 2014). One of the approaches of this agency is the assessment and management of risk of sexual offenders who are released back into the community. Earlier, they used a static risk assessment tool called the Risk Matrix 2000 for assessing risks of sexual offenders reintroduced into the community (Nicholls and Webster, 2014). This tool was based on static risk prediction based on historical factors that are unchanging and that are statistically predictive of future acts of violent or sexual offending. However, research on risk prediction has now expanded and it is shown by researchers that risk needs to be predicted based on dynamic rather than static risk factors. Dynamic risk factors are changeable factors such as alcohol or drug consumption. One of the most eminent researches in this regard is that of Hanson et al. (2007) whose research influenced practice development within NOMS. In their research, Hanson, Harris, Scott and Helmus classified dynamic risk factors into Stable and Acute. The Stable factors include long term qualities personal skills, self management problems and learned behaviours while Acute factors last only momentarily. According to their research, Stable and Acute dynamic risk factors are predictors of imminent sexual offence. Based on these risk factors, various tools for risk assessment were developed and implemented under the National Probation Service. NOMS, in 2008, implemented a pilot of the Stable and Acute Dynamic Risk assessment tool based on the research by Hanson et al. (2007) (Nicholls and Webster, 2014). This tool was implemented across England and Wales in Police and Probation Services, and offered a structured method for the identification and measurement of dynamic risk factors through which sexual re-offending in convicts could be predicted (Nicholls and Webster, 2014). An evaluation of this tool was conducted in 2009 by McNaughton Nicholls et al. (2010). They found that the tool was of immense benefit for the management of risk of sexual reoffending the community. They described that the implementation of the tool helped increase awareness of critical risk factors, allowed a more targeted response to sexual offenders who posed a high risk, and also improved the management of sexual offenders by the agency through better partnership working because of shared information that resulted from assessment of the offenders on an individual basis. Subsequently, some drawbacks of the tool were identified such as the scope of administration of the tool varied widely among officers, its reliability was questioned, and some officers reported difficulty in interpreting some of the items in the assessment tool (McNaughton Nicholls et al., 2010). NOMS therefore developed its own tool called the Active Risk Management System (ARMS) dynamic risk assessment tool to overcome the previous drawbacks.  The use of the research by (1) Hanson et al. (2007) by (2) NOMS in developing a dynamic risk assessment tool for monitoring and managing risk of sexual reoffending in the community is a good example of how research leads to practice development within agencies in the criminal justice system. Description of Research The research by Hanson et al. (2007), ‘Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project’, discussed (4) here was aimed at advancing knowledge on risk factors for sexual reoffending so that better risk assessment could be made and risk of recidivism could be predicted. (3 and 5)The researchers identified dynamic risk factors for sexual offenders who were under community supervision. It presented a method using which stable, acute and static risk factors could be combined into one risk assessment. The risk factors selected for their study were based on earlier research and on empirically validated risk tools such as the Sex Offender Need Assessment Rating and Structured Risk Assessment. The main dynamic risk factors categories as stable include negative social influences, problems with sexual self-regulation, intimacy deficits, attitudes tolerant of sexual crimes, problems with general self-regulation, and lack of co-operation with supervision (Hanson et al., 2007). The acute factors that were identified were strongly related to sexual reoffending. These included collapse of social supports, emotional collapse, hostility, lack of cooperation with supervision, sexual preoccupations, substance abuse and victim access. In the case study, Harry Jones had most of these acute risk factors that include lack of cooperation with supervision, sexual preoccupations, substance abuse, and victim access. Hanson et al. based their research on adult sex offenders from 16 Canadian jurisdictions. They collected assessment information on 997 offenders from 156 officers (Hanson et al. 2007). To accumulate the sample size, they incorporated data collection into the routine supervision practice of the officers. This adds strength to the study and makes it a step ahead of other studies because by incorporating data collection as a routine part of the officers’ practice, they could identify its ease of implementation and predict how well it can be used in the future. The study is unique because it used a “truly prospective design” as the officers conducted the assessments during routine supervision (Hanson et al., 2007, p. 25). They organized the most promising acute, stable and static risk factors into a comprehensive assessment package that was further refined with the help of field testing with supervision officers. They then approached various jurisdictions that offered to train officers in implementing the assessment if they agreed to contributing data for three years (Hanson et al., 2007). Combined efforts of the community supervision officers and the Correctional Service of Canada facilitated data collection. The officers involved in the project collected information from sexual offenders based on “static risk factors upon intake”, “stable risk factors every six months”, and “acute risk factors at every offender contact”. They not only assessed the validity of individual risk factors but also that of the different methods of combining the risk factors into one assessment tool. They also investigated whether the supervision officers in the community could conduct valid and reliable assessments of personal and sensitive characteristics such as deviant sexual interests. (6) The study adds to existing knowledge by providing evidence that community supervision officers when trained, can score valid risk assessments of sex offenders. (7) The study successfully identified dynamic risk factors and classified them as stable and acute based on which a better risk prediction tool could be prepared. It successfully achieved the aims that it stated by demonstrating that supervision officers can successfully assess personal and social characteristics of sexual offenders that are related to violent, general or sexual recidivism. While previous research such as that by Hanson and Bussiere (1998) had shown that historical and static variables such as victim characteristics and offence history could be used to predict risk of recidivism, this study also showed that such static variables are moderately to largely associated with risk of recidivism. However, what the study adds is that the accuracy of such risk assessment can be improved to a great extent if a structured approach is used to combine acute, stable as well as static characteristics. The results of this study are consistent with that of earlier studies such as those by Beech et al. (2002) that showed that stable dynamic characteristics were of significant utility for recidivism prediction, even more than static actuarial measures. Hanson et al. state that their study is unique as it uses a “truly prospective design” wherein officers carried out the assessments as part of their routine practice of supervision. (8) This study is of significance because it resulted in a change in practice by the NOMS. This agency earlier used static risk assessment tools such as Risk Matrix 2000. However, because of the lack of reliability of such a tool for prediction of risk of recidivism among sexual offenders living in the community, they used the research by Hanson et al. to implement a Stable and Dynamic Risk assessment tool. They needed such a tool that could specifically be used for sexual offender management and that could be used with both the Police and the Probation. They thus started using this new tool which offered them a “structured method” for the identification and measurement of dynamic risk factors for prediction of sexual reoffending (Nicholls and Webster, 2014, p. 2). This research was useful for the risk assessment tool implement by NOMS because of the adoption of stable and acute classification of dynamic risk factors. One benefit of this was that it helped identify the targets (risk factors predicting recidivism) for intervention, which if altered, will reduce the likelihood of reoffending (Nicholls and Webster, 2014). Secondly, it also helped assess whether or not a sexual offender was making progress with regards to his/her treatment targets. Thirdly, it helped the supervising officers in monitoring the risk imposed by sex offenders reintroduced into the community. (9) The research is still informing current practice as the NOMS has devised its own risk assessment tool (Active Risk Management System - ARMS) that is based on the stable and acute dynamic risk factors identified by the research, which is in now being implemented on a pilot basis. One drawback of this study is that the risk factors listed by it could be influenced by treatment programs of sex offenders and this has not been accounted for by the study. References BARATTA, A., JAVELOT, H., MORALI, A., HALLEGUEN, O., and WEINER, L. (2012). The role of antidepressants in treating sex offenders. Sexologies, 21, 106-108. BARTON, Alana. (2004). Just Deserts Theory. Encyclopedia of Prisons & Correctional Facilities. Ed. 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