Implementing a mixed method approach introduces two or more evaluation methods, using quantitative and qualitative data. In addition, they incorporate multiple designs and data collection techniques that encompasses various techniques to evaluate and describe a study (USAID, 2013). The mixed-method design uses three rationale cases to help strengthen an evaluation: First, different evaluation questions require different methods, or a single evaluation question requires more than one method to answer all components (USAID, 2013).
Second, when different methods are used to answer the same elements of a single question, which increases the confidence of validity and reliability of the evaluation results (USAID, 2013). This method is also referred to as triangulation. Third, the result of a previous evaluation method influences future mixed-method designs (USAID, 2013). Meanwhile, mixed-method design reveals unanticipated results; provide a deeper understanding of why or why not change is occurring; capture a wider range of perspectives (USAID, 2013).
The importance of collecting data through Likert-scale survey will provide narrative date and numerical data. These two types of data sources will lead to the Conversion Analyses Technique. The Conversion Analysis Technique looks at two types of data from one data source, which would be the Likert-scale and with the results you can look at the statistical analysis of inmate’s behavior from the cognitive behavioral treatment (USAID, 2013). The analytical output for the conversion analysis technique will take the quantitative results data set and compare them with the results from the qualitative data (USAID, 2013).
The qualitative method that would be used for cognitive behavioral therapy analysis with inmates, would implement random selection of medium risk inmates, who are serving a 2 to 5-year prison sentence. It would be classified as a field experiment, because the inmates would be evaluated in their environment. By random selection there will be 250 inmates selected for the study. Each inmate will participate in a 25 question Likert-scale survey. At the end of the inmate’s prison term they will take the survey again, which the results will be compared with the previous results. The Likert-scale assumes that the strength/intensity of an attitude is linear and can be measured (McLeod, 2019).
In many studies the participants know that they are being studied, but in the cognitive behavioral therapy the participants do not know that they are being studied. So, that would be the difference in that aspect of the collecting data. If the participants are unaware that they are being studied the validity and reliability of the study will be strong. I would measure the frequency using the Likert-scale: Always, often, sometimes, rarely, and never. The dilemma of the Likert-scale is that the participants may try to portray themselves in a positive light, instead of being honest (McLeod, 2019). Triangulation would not be used in this study, because keeping the study simple and not trying to incorporate different methods and evaluation would take away from the purpose and understanding why cognitive behavioral therapy is imperative in the prison system.
SPSS would be the best option to enter the collected data. The respondents and questions would be given a variable name, the summary of statistics can compare means with a t-test and one-way ANOVA. Using SPSS there can be a calculation of the frequency distribution and the results can be generated on a chart or bar graph. In addition, it will help distinguish data from the beginning of the study versus the data collected at the end of the inmate’s prison term (SPSS, 2009).
