Submit 2-3 pages describing the Methods/Design and Statistical Analysis that you will use in your project. Use the evidence from the peer reviewed articles that you have critically appraised and synthesized. Follow APA format and cite references. Include the following:
Describe the evaluative criteria (indicators or variables) to be addressed in answering each evaluation question.
Describe the research approaches to be used to answer each question and why they are appropriate to the evaluation questions posed.
Describe in specific detail how data will be collected related to each of your evaluative criteria/indicators. Discuss exactly how the data be collected, when, and by whom. Describe any data collection tools in terms of their development and appropriateness in answering the evaluation questions. Provide information on validity and reliability of tools, if available. Explain why the data collection methods are appropriate to the research approach, type of data, and purpose of the evaluation.
Describe how you will analyze the data, including specific statistical tests to be used. Include dummy data tables if applicable to show how you will display your findings.
Expectations
Length: 2-3 pages
Format: APA 7th ed.
Research: At least one peer reviewed reference within the last 5 years
Methods/Design and Statistical Analysis
Student name
Institution
Course name
Instructor’s name
Date
PICOT Question:
In opioid-addicted adults(P), how do short-term residential drug treatment programs (ten to twelve weeks)(I) compare with long-term residential drug treatment programs (greater than twelve weeks)(C) affect sobriety rates (O) twelve months after being discharged(T) from a treatment facility?
Evaluation Questions:
- Are there any significant differences in relapse rates for patients who received short-term residential drug treatment and patients who received long-term residential drug treatment 12 months after discharge?
- Are there any significant differences in the quality of life between patients who received short-term residential drug treatment and those who received long-term residential drug treatment 12 months after discharge?
Evaluative Criteria
All the evaluation questions focus on determining if there are significant differences in specific variables between patients who received long-term and those who received short-term treatment. The first question examines relapse rates as the main variable to be measured against time spent in drug treatment programs. The second question examines the quality of life as the main variable. As per Manning et al. (2019) patients with addiction issues experience a significant reduction in their quality of life including their mental health, physical health, and social life. Apart from reducing the risk of relapse, effective substance abuse treatment should improve the quality of life of patients. Therefore, it is important to determine if short-term and long-term treatment impact their quality of life differently.
Research Approaches
All the evaluation questions will be measured using quantitative methods. According to McGowan et al. (2015), quantitative methodologies can be effective in evaluation research since they facilitate collection of numerical data that provides insight on the scope of the issue under research. These methodologies can also help establish if there is a causal influence of a specific program on the recipients and even compare groups involved in research. For the current study, quantitative methodologies can help determine if there is a causal influence of long-term and short-term drug treatment on relapse rates and quality of life. The research also involves two groups of patients: those who received long-term treatment and those who received short-term treatment. Quantitative methods will enable the comparison of outcomes for each group and provide an evidence-based answer to the research question.
Data Collection
The data will be collected using questionnaires administered by the researchers to the participants at least 12 months after they are discharged from long-term and short-term treatment facilities. The participants will be required to provide demographic information such as age, gender, and employment status. To measure relapse rates, participants will be required to answer a yes/no question on whether they relapsed. Relapse cases will be then confirmed using medical tests such as blood tests and urine toxicology to improve the accuracy of the findings.
For the quality of life, the data will be collected using the World Health Organization Quality of Life Assessment (WHOQOL) tool. According to Caballero et al. (2013), the instrument is a valid and reliable measure of the quality of life and can be used among people from diverse cultures. The tool demonstrates sufficient test-retest reliability, good internal consistency, and good test-retest reliability. The tool measures four domains: psychological, physical, environment, and social domains. For the current study, the participants will be required to complete the WHOQOL tool. All participants will be assessed to determine if they have sufficient ability to complete the questions on their own. If they do not demonstrate sufficient ability, interviewer-assisted forms will be used.
Appropriateness of Data Collection Methods
The data collection methods are quantitative hence they are appropriate for the evaluation. The methods will facilitate the collection of data on relapse rates and the quality of life of the patients. Questionnaires are also less costly and can be easily administered to a high number of participants. Since the research will involve members of a rural community in Ohio, the sample size will likely be relatively small hence it would be easy to administer the questionnaires. However, the main limitation of using a small sample size is that the findings will not be generalizable to all patients with opioid addiction in the country.
Data Analysis
The data analysis process will focus on comparing relapse rates and quality of life between patients who received long-term drug abuse treatment and those who received short-term treatment. Therefore, the main data analysis method will be the independent T-test which according to Kim (2015), measures whether two groups have a statistically significant difference. The test provides information such as mean difference, t-value, and p-value. A p-value that is less than 0.05 is regarded as statistically significant and would demonstrate that the two groups under study have significant differences.
Other data analysis methods such as descriptive statistics will also be used to provide a summary of the patients’ demographic characteristics. The data analysis process will be conducted using SPSS as the main statistical tool. The data will mainly be presented using tables and graphs. Dummy data tables that will be used to display the findings are included below:
Summary Statistics
| Variable | Group | N | Mean | Standard deviation | Standard error |
| Relapse rate | Short-term addiction treatment group | ||||
| Long-term addiction treatment group | |||||
| Quality of Life Results | Short-term addiction treatment group | ||||
| Long-term addiction treatment group |
Independent t-test results
| t-value | Significance Value | Mean Difference | |
| Relapse rates |
| t-value | Significance Value | Mean Difference | |
| Quality of Life |
References
Caballero, F., Miret, M., Power, M., Chatterji, S., Tobiasz-Adamczyk, B., & Koskinen, S. et al. (2013). Validation of an instrument to evaluate quality of life in the aging population: WHOQOL-AGE. Health and Quality of Life Outcomes, 11(1). https://doi.org/10.1186/1477-7525-11-177
Kim, T. (2015). T test as a parametric statistic. Korean Journal of Anesthesiology, 68(6), 540. https://doi.org/10.4097/kjae.2015.68.6.540
Manning, V., Garfield, J., Lam, T., Allsop, S., Berends, L., & Best, D. et al. (2019). Improved Quality of Life Following Addiction Treatment Is Associated with Reductions in Substance Use. Journal of Clinical Medicine, 8(9), 1407. https://doi.org/10.3390/jcm8091407
McGowan, L., Stafford, J., Thompson, V., Johnson-Javois, B., & Goodman, M. (2015). Quantitative Evaluation of the Community Research Fellows Training Program. Frontiers in Public Health, 3. https://doi.org/10.3389/fpubh.2015.00179