Procedures Used to Identify Reoffending Risk - Literature review Example

Recidivism Student’s Name: Institution: Recidivism Introduction Recidivism is marked by return to crime. The term is derived from the Latin word recidere whose meaning is falling back. Therefore, recidivism is used often interchangeably with other words such as reoffending or repeat offending. In a criminal justice context, it can be described as the reversion of a person to criminal behavior after they have been convicted of an offense before, sentenced and corrected. Recidivism occurs when any one of the following kinds of events take place during the initial two years of the offender being in the community; a reconviction for a fresh offense, a re-arrest with no conviction disposition information available of the post-release criminal history record or a revocation of supervision which maybe either post prison supervision or probation. For every crime that is committed, there are 3 fundamental elements. These include a suitable target, a motivated offender and the absence of capable guardians (Graycar & Grabosky, 2002). However, repeat offenders present a striking dimension to this crime model. With repeat offenders, it means that they are motivated to commit more crime. These offenders are usually more often resistant to regulatory responses that have been put in place with the aim of preventing their criminality. In many cases, these offenders are responsible for a significant number of crimes that are reported and those that go unreported. Therefore, initiatives that aim to reduce the offending of these repeat offenders have the potential of delivering sustainable fall in crime rates. As such, research in repeat offending offers a methodology of comprehending crime and criminal activity within the context of fluctuating crime rates, increasing concern for public safety and the growing accountability in the public sector. Such a research has the prospect of identifying the size and traits of the recidivist population, enhance comprehension of the factors that are correlated with the high rates of offending and help in evaluating the effectiveness of programs that are designed to reduce offending. People usually come into contact with the criminal justice system. When this happens, they pass through numerous processing stages. At every stage, a person’s risk of repeating the offense is usually assessed by the justice system. Risk assessments are conducted by professionals in the justice department on a daily basis. Assessments may be conducted at the pre-trial stage, prior to sentencing, when evaluating security level in custody, before release and after breaches or critical incidents happen (Hart, 1995). Risk assessments can be informal or formal in nature. Whatever the case, these assessments are significant of the process of criminal justice since it is a way of differentiating between those offenders who have a potential of repeating an offense and those who have a lower risk of recidivism. However, controversy has dogged the accuracy of these assessments. These assessments are aimed at predicting future behavior and can sometimes be subject to error. The outcome of an assessment carries with it immense implications for both the society and the assessed person. For the offender, the assessment decides their freedom while for the society; it determines whether a likely dangerous individual has been released back into the community. This paper, therefore, seeks to conduct a critical analysis of the procedures that are used to identify reoffending risk. The paper will pay attentions to ways in which recidivism risk is assessed and the ways in which it is measured. Methods of Assessing Risk There are various methods used in assessing the risk of reoffending. However, these methods fall under two broad categories namely actuarial and clinical. Actuarial prediction utilizes risk factor tools and statistical models. It is a form of statistical production which predicts the behavior of an individual based on how other individuals have acted when in similar situations (Walters, 2006). Clinical prediction involves the observation of an offender by a psychologist or psychiatrist. In this case, clinicians usually assess risk based on their theoretical knowledge, professional training and experience with offenders. Clinical Risk Assessment A typical clinical assessment involves a judgment by a mental health professional concerning the risk a particular person poses. The clinician is either a forensic psychiatrist or psychologist. The clinician usually interviews and /or observes the person. He or she might utilize checklists or rating schemes that are developed by other professionals. All the available information that concerns the offender’s behavior and personality as well as the details of the crime itself is put into consideration. In a clinical assessment, the risk factors that are used are usually differ with the individual being assessment and can change over time. According to Mann (1995), they include mental disabilities, personal history, social skills, behavior and attitudes. When these individual characteristics are considered as a whole, they provide the clinician with a picture of the individual in question. Therefore, a decision about the likely harm the individual may pose is then made. According to Gordon and Jones (1986), the Supreme Courts in Canada and the United States have recognized the clinical assessment method as a constitutionally valid measure for assessing risk. However, despite this method attaining legal recognition, its ability to accurately differentiate offenders who will repeat an offense from those will not is questionable. When performing an assessment on an individual, clinicians usually fail to take into consideration risk factors such as criminal history, age and gender. Belfrage (1998) carried out a study of forensic psychiatrists with the aim of determining the extent to which certain factors influenced institutionalized offenders’ risk assessments. These factors included age, the crime committed, prior offenses and psychiatric diagnosis. The results revealed that only the type of crime committed distinguished offenders who were classified as high-risk from those classified as low-risk. Other studies have indicated that when provided with sufficient information, laypersons can make clinical predictions that are as accurate as those of the clinicians. In some instances, they can make better predictions. Menzies et al (1994) examined the accuracy of laypersons and clinician predictions of dangerousness among Metropolitan Toronto Forensic Service patients by using the Dangerous Behavior Rating Scale (DBRS). The 3 outcome measures that were used include criminal behavior, violent behavior and general incidents. The study indicated that clinicians were no better than laypersons in the assessment of risk. In fact, the study found that laypersons were better at using the DBRS than clinicians. In addition, studies show that clinicians usually come to various conclusions after assessing the same person. Webster et al (1985) cite a study on clinician agreement, which showed that clinicians did make differing predictions even after discussing cases with each other. This difference in clinical opinion could be as a result of the lack of precision in clinical training. It is such findings that put into question the aspect of clinical expertise in predicting dangerousness. This is because this assessment method comes out as arbitrary since the fate of the offender depends on the clinician who conducts the risk assessment. This method of assessment can be marred by prejudice or misinterpretation leading to wrong predictions. This could result in low-risk offenders being remanded while high-risk offenders are released into the community. Therefore, clinical assessment method has some loopholes and shortcomings when using as a way of assessing the risk of recidivism. Actuarial Risk Management When an offender gets assessed using an actuarial tool, their specific characteristics are inventoried, and his risk is determined by the level to which he possesses various risk factors that are associated with recidivism. The information that is put under consideration in the assessment process is usually drawn from an institutional intake report and case files. These include the offender’s employment status, education level, suspected or known mental disabilities and the criminal history of the criminal. This information is useful later in assessing the risk that might be posed by offenders who are under consideration for release. For instance, if a particular trait that is common to those offenders who recidivate is found in a potential parolee, that individual’s risk is judged greater than one to those who do not display the characteristics. In the same way, persons who display traits common to non-recidivists are considered low-risk. Actuarial assessments have the benefit of providing offenders with more substantial information on their status and making the system appear less arbitrary (Serin, 1993). Actuarial risk assessment lays its primary focus on unchangeable or static factors that influence recidivism. Various studies have shown that the static risk factor with the biggest influence on general recidivism is prior contact with the mental health or criminal justice systems (Gottfredson, 1994). General recidivism refers to all types of criminal offences. Violent offence recidivism is predicted best by prior mental illness, violent offences and a history of substance abuse (Sheridan & Limandri, 1995). Sexual offence recidivism is particularly more common among offenders with prior sexual offences, one or more boy victims, victims who are not family members and those who have shown a sexual preference for children (Hanson, 1997). Those sex offenders who repeat offences that are violent and non-sexual are individuals who are typically young, unmarried or of a minority race. Static or unchangeable factors are easy to code since no rater judgment is necessary. Therefore, they are used widely in actuarial risk assessment tools. However, an inventory of static variables only cannot give a clear picture of risk since these factors will never be altered though the likelihood of an offender recidivating can change. Offenders receive treatment in correctional facilities with the aim of reducing the probability of future offending. If a particular offender’s risk of repeating an offence is lessened by way of treatment, then static factor inventory cannot measure the change in this risk. Dynamic factors have also been realized to predict recidivism. In some cases, they are better than static factors. The knowledge of dynamic factors is necessary in assessing the changes that occur in an offender’s risk level. By way of participation in rehabilitative programming, an offender might become less likely to repeat an offence. However, parole and corrections officials cannot be able to measure this change unless they assess the offender on the basis of factors that are changeable. Dynamic factors that are connected to general recidivism include social achievement, substance abuse, antisocial personality and interpersonal conflict (Hanson & Harris, 1998). Factors associated with sex offenders include antisocial lifestyle, poor social support and a tolerable attitude towards sexual assault. Antisocial history and treatment behavior are also significant variables in the failure of conditional release. Various actuarial scales are used in assessing the risk of reoffending. Some notable examples of these scales include (SIR) Statistical Information on Recidivism, Sex Offender Need Assessment Rating (SONAR) and (VRAG) Violence Risk Appraisal Guide. According to Webster (1994), the VRAG was developed to initially assess recidivism among offenders who are mentally disturbed. This scale considers several aspects including age, schizophrenia, personality disorder, criminal record and marital status. The SIR scale uses static factors such as marital status, age and other factors that are linked to the criminal history of the offender. Scores on this scale indicate whether an offender is low or high risk for recidivism. According to Hanson and Harris (2000) SONAR can be used in conjunction with other actuarial tools in risk assessment. The scale measures the change in risk levels throughout the course of an offender’s sentence by laying focus on dynamic factors that are linked to recidivism. These factors include intimacy deficits, tolerance towards sexual offending, social influences, general and sexual self-regulation. It also measures four acute factors which include anger, substance abuse, negative mood and victim access (Hanson & Harris, 2000). However, neither the clinical or actuarial method of risk assessment and prediction has proven particularly accurate. Each method has its proponents who argue that one is superior then the other. According to Grubin (1999), several studies indicate that actuarial judgments are better than clinical judgments. However, the indicators, which lay the basis for actuarial assessments, have not been sufficiently standardized. Gottfredson (1994) finds actuarial assessments more effective than clinical assessments and regards the accuracy of actuarial methods as being modest. Offender Characteristics used in Measuring Recidivism The variation in recidivism rates are based on certain offender characteristics. The first characteristic is gender. Generally, women will recidivate at a lower rate than men. This is because women tend to change after the correctional process. Women will have a low risk of reoffending once they have been released. Age is also a trait. Recidivism rates tend to reduce relatively constantly as age increases (Dawes et al, 1989). A younger offender has a higher probability of repeating an offence. As the person ages, they begin to get a sense of purpose of life. Individuals realize that they should make something positive out of their lives. As such, such people have an extremely low risk of repeating these offences. Recidivism rates can also be associated with race and ethnicity. According to a study by Elbogen (2002), black offenders are more likely to repeat an offence (32.8 percent) than are the Hispanic offenders (24.3 percent). White offenders are least likely to repeat an offence at 16 percent. Another characteristic is the employment status. Individuals with a stable employment in the year before their instant offense are less likely to recidivate than those who do not have employment. This is because these people probably get caught up in the middle of things without their intention. Therefore, once they are freed, they are less likely to repeat the offense again. The education attainment is also a factor. Offenders who have less than a high school education will have a higher likelihood of recidivating. According to Hollin and Palmer (2006), offenders who have a higher educational level will be less likely to repeat an offense. According to marital status, offenders who have not been in a marriage are most likely to recidivate. They are followed by those who are divorced with the married being the least likely. Another offender characteristic is illicit drug use. Offenders who use illicit drugs within one year prior to their instant offense have a higher rate of recidivism than those people who do not use illicit drugs. These are some of the characteristics that are used by assessment tools in predicting the risk of reoffending. The three basic measures that are used in the measurement of reoffending or recidivism are re-arrest, reconviction and recommitment to prison for a fresh offence (Gendreau & Goggin, 1996). Each of these measures has their strengths and weaknesses. Re-arrest is not mainly used since an arrest does not indicate that a new offense has actually happened. Convictions are an indication that a new offense occurred. On the other hand, commitments to prison are an indication that a relatively serious new offense did occur. Reoffense is measured as the date of the first felony offense after release from prison. It is referred to as a reoffense since it used the new offense date instead of the date of conviction or of readmission to the department (McGrath, 2001). This technique of measuring recidivism indicates how soon after release the offender commits a new crime. Commitment to prison or reimprisonment is measured as the date of return to prison after reoffense, the first offense after release from prison (Sutton, 1994). Rates that are reported on reimprisonment are lower than those of reoffense for the same period of follow-up. Not all offenders who are reconvicted are sentenced to prison. This technique of measuring recidivism indicates how soon after release the offender will return to prison for a new crime. Recidivism cannot be accurately measured by just using arrest data since not every crime is discovered. It can be measured by using different ways such as interviewing offenders with the aim of determining whether they have committed crimes since exiting or entering a program. It can also be done by analyzing criminal justice events that are officially recorded including arrests, convictions, violation of supervision and commitments to prison (Mann, 1995). Another way is to chart a new offence over an elapsed time frame such as substance abuse. However, the most sensitive measure is to measure the time that has elapsed until the next crime. Conclusion Although risk assessments may provide statistically significant success rates, they cannot yield accurate predictions in a substantial number of cases. The predictive accuracy of professional risk assessments is only slightly better than chance (Hanson & Thornton, 1999). False negatives and false positives are usually a concern in any risk assessment. False positives are persons who are judged as high-risk but do not recidivate upon their release. On the other hand, false negatives are those persons who are judged to be low-risk yet they re-offend. While people are skeptical about the predictions of future events, the fear and uncertainty that usually accompanies the release of potentially dangerous individuals into the community leads to dependence on risk assessments to assist in easing public concerns. What assessments offer is a likelihood or probability of recidivism for each offender. The responsibility of determining this is designated to parole officials, corrections workers and judges. They determine whether a person’s freedom should be revoked on the basis of the risk of recidivism. Adding to these problems that are linked with risk assessment is a room for biases. Biases can infringe into the assessment process. Even though corrections workers and clinicians might strive to be objective, it is common knowledge that any kind of task taken by a human being is likely to be influenced by his or her opinion or perspective. Despite these problems, risk assessments can be enhanced or improved. According to Milner and Campbell (1995), actuarial prediction is generally viewed as the more accurate way of risk assessment. On their own, actuarial and clinical models are both mediocre in their ability to predict. A suitable recommendation would be the use of a combinational of both clinical and statistical models. According to Litwack (1993), clinical expertise coupled with some form of statistical prediction allows the greatest accuracy of prediction at the present time. Another suggestion that has been put forward is the use of both static and dynamic factors when predicting risk. The bottom line is that, risk assessment is and will always be a fallible process. 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