Statistical Methods, Formal diversions
Statistical Methods
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Statistical Methods, Formal diversions
Formal diversions are increasingly used to dispose offenders with mental illness. The article “Is Diversion Swift?” by Allison, Siyu and Henry focuses on the duration between initial arrest and diversion. It assists in determining whether cases that require diversion are swift. In doing so it tends to compare the processes in Mental Health courts and Traditional Criminal Justice. The main areas of analysis of the two courts are the time taken to make an arrest, duration the suspect has to stay in custody and duration between court hearings and besides disposition outcomes. The authors further analyzed Mental Health cases on more specific areas like time taken to arrest a mental health offender, duration to refer to diversion program, duration for the diversion program to make a decision and finally duration for the offender to be enrolled into the program. After the detailed research, the authors were sure to determine how effective and just are the courts today in handling cases especially those that involve mental health patients and a their effects on traditional criminal justice.
Research methods used utilized both primary and secondary data. Secondary data was attained from several prior researches by scholars and institutions that are detailed in several scholarly journals and books. They heavily referred Morris and Steadman investigations of 2008 to determine the length of time taken to make an arrest in both non-MHC and MHC. They also referred to Steadman and colleagues study of Seven MHCs which paid attention to median duration between referral and acceptance decision. The researchers according to the article also relied on Essential elements of mental Health Court journal in understanding the 3 main stages of settling a court case in MHC; indentify, refer and acceptance. In addition to these secondary sources the research team future used primary sources to come up with well researched and objective results.
Primary data was attained from archival records that provided detailed data including demographic factors of participants from Medical Health Courts and also from country criminal justice. The data collected was from four main sites; San Francisco with 254 cases, Santa Clara 334, Hennepin country 248 and Marion country 211. The records provided detailed information on court charges, relevant dates and dispositions made on each case. The records also contained criminal history on courts, with close attention on their previous arrests and jail time for different crimes. This information was future compared to Federal Bureau of Assistance records which confirmed all the data required for the selected sample. Using the sample selected the researchers used the MacArthur study to determine the effectiveness of Mental Health courts in assisting treatment and engagement of mental health patients. Macarthur study required the sample to be categorized into two to enhance comparison; Mental Health court (MHC) and Treatment as Usual (TAU).
Measures of central tendency used are the mean and median to analyze the two groups of data MHC and TAU. Mean and median were attained form the 447 cases of MHC and compared to 600 TAU cases, the report attained a 6 months follow up to ensure consistently and accuracy. In addition, the sample data collected was information from four years 2005 to 2008 to provide primary variables that were necessary such as arrest dates, MHC enrollments date or TAU disposition date. From the demographics of the sample the researchers developed a bivariate correlation using the number of days of arrest to TAU outcomes. Mean and media lengths of time at which an arrest is made to the outcome are later attained and found that in both groups the length of time was 97 days for long cases and 60 days for short cases with the overall median of 16 days.
Using the median lengths the researchers attained different results from the representative sample. To begin with they established that mentally ill patients preferred Mental Health courts in three countries, they also found that it took 76 days to complete most defendant processes. However, the process was much slower for mentally ill offenders since it took 70 days while that of conventionally processed cases took 37 days. Therefore, the research showed no swift in diversion, indeed it proved that the process took twice as long in traditional process. From the secondary data, they concluded that before referral and disposition decisions are made 20 day period after arrest was necessary for most cases. They also found that disposition decisions were also affected by other factors rather than patient mental illness. The other common factor was whether the offender was detained in jail at the entire time or was free in the community.
The conclusions derived from the research using central tendency measures from the representative sample are quite accurate. This is because the sample was randomly selected from several credible sources. The researchers also took time to examine the sample and eliminate data that lacked necessary information. The central tendency measures used were mean and median which assisted in providing adequate comparison between the two groups of data; data from MHC and TAC. However, the data selected and central tendency measures used did not consider some important variable that may have affected the final result. The research method failed to consider criminal history factors and demographic factors of the time when the data was collected. Further, it failed to consider that personal characteristics of offenders may have influenced the main variable. Bottom line, the research was quite helpful in determining that mental illness affects the length of time between arrest and disposition but does not provide adequate answer has to whether diversion is swift.
Reference
Redlich, A. Siyu, L., Steadman, H. Callahan, L. Robbins, P. (2012) Is Diversion Swift?Comparing Mental Health Court and Traditional Criminal Justice Processing. CriminalJustice and Behavior. Sage
