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Schizophrenia Readmissions Reduction: Data Analysis Essay

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Description of Sample

The research study aims to discover the effectiveness of peer-led self-management programs in reducing readmissions among adults with schizophrenia. In this case, the target population is adults with schizophrenia who tend to attend one of the medical centers that take part in this study. A simple random sampling technique will be used to select participants, and it implies that each respondent will be randomly chosen to take part in the study to avoid bias and ensure the validity of information (Johnson & Christensen, 2013). It is estimated to have 250 participants due to a potential 30-40% dropout rate.

The participants have to be within the 21-65-years-old age range, and both males (70%) and females (30%) will take part in this study. These numbers are estimated and may change after the randomization of participants is accomplished.

To determine the effectiveness of the chosen intervention, the total number of participants (250) will be split into control (125) and experimental (125) groups. The participants will be randomly divided while relying on the concepts of randomization (Balakrishnan, 2014). In this instance, both groups will receive professional medical treatment, but the experimental group will also participate in peer-led self-management programs. The educational sessions will be organized by well-trained adults (5) with schizophrenia, who successfully manage their condition in their lives and are recommended by the medical centers (Chan et al., 2013).

The data will be collected using questionnaires. To analyze the demographic data, descriptive statistics will be used. In the first place, the whole data set will be split into categories, including gender (male or female) and age (21-30; 31-40; 40-65; 65+). Using this method is crucial since it enhances data screening procedures and helps understand a relationship between the variables (Sreejesh, Mohapatra, & Anusree, 2014). For example, it will help us understand whether there is a correlation between gender, age, and proposed intervention. At the same time, mean, median, and mode values will be calculated, as they assist in understanding general tendencies by determining the average, middle, and the most frequent values (Sreejesh et al., 2014).

Data Analysis

It is apparent that in the first place, the information will be collected by using a mixed approach that implies relying on both qualitative and quantitative methods. To find proof of the hypothesis, the data will be collected with the help of surveys (subjective data) and interviews (qualitative data). Thus, to analyze the acquired information, apart from randomization, different statistical tests have to be used. One of them is regression analysis. It could be said that it is one of the most appropriate methods in the context of the selected topic, as it aims to find a relationship between variables while determining the reasons for these outcomes (Uyanik & Guler, 2013).

In this case, it will help portray graphically a relationship between peer-led self-management programs and conditions of the patients that will be evaluated by the medical indicators and interviews with them. Thus, descriptive statistics such as mode, median, and mean will be calculated to determine general tendencies. Interviews will assist in unveiling additional insights concerning the topic while the information will be split into categories to ensure that it supports data in surveys (Alshenqeeti, 2014).

In turn, it will be reasonable to use related statistical software to randomize participants, split data into categories, and conduct regression analysis. In this instance, relying on SPSS can help calculate both descriptive (mean, mode, and mean) and inferential statistics, as it is one of the most actively used programs in different fields of research (Johnson & Christensen, 2013). Utilizing it will speed the overall evaluation process, as different formulas can be used to input data effectively and perform the required calculations (Johnson & Christensen, 2013).

References

Alshenqeeti, H. (2014). Interviewing as a data collection method: A critical review. English Linguistics Research, 3(1), 39-45.

Balakrishnan, N. (2014). Methods and applications of statistics in clinical trials: Concepts, principles, trials, and designs. Hoboken, NJ: John Wiley & Sons.

Chan, S., Li, Z., Klainin-Yobas, P., Ting, S., Chan, M., & Eu, P. (2013). Effectiveness of peer-led self-management program for people with schizophrenia: A protocol for a randomized control trial. Journal of Advanced Nursing, 70(6), 1425-1435.

Johnson, B., & Christensen, L. (2013). Educational research, qualitative, quantitative, and mixed approaches. Thousand Oaks, CA: SAGE Publications, Inc.

Sreejesh, S., Mohapatra, S., & Anusree, M. (2014). Business research methods: An applied orientation. New York, NY: Springer Science+Business Media.

Uyanik, G., & Guler, N. (2013). A study of multiple linear regression analysis. Procedia – Social and Behavioral Sciences, 106(1), 234-240.

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IvyPanda. (2020, July 30). Schizophrenia Readmissions Reduction: Data Analysis. Retrieved from https://ivypanda.com/essays/schizophrenia-readmissions-reduction-data-analysis/

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1. IvyPanda. "Schizophrenia Readmissions Reduction: Data Analysis." July 30, 2020. https://ivypanda.com/essays/schizophrenia-readmissions-reduction-data-analysis/.


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IvyPanda. "Schizophrenia Readmissions Reduction: Data Analysis." July 30, 2020. https://ivypanda.com/essays/schizophrenia-readmissions-reduction-data-analysis/.

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IvyPanda. 2020. "Schizophrenia Readmissions Reduction: Data Analysis." July 30, 2020. https://ivypanda.com/essays/schizophrenia-readmissions-reduction-data-analysis/.

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IvyPanda. (2020) 'Schizophrenia Readmissions Reduction: Data Analysis'. 30 July.

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