SUO Research Proposal Template Chapters 4-5 BUS 8115 and BUS 8120

Chapter 3 contains a descriptive discussion of the conduct of this study and how

it informed the problem. The detailed explanation supports future design replication, data collection, and analysis. The description of the population and sample ensured that the reader could understand the research subjects. The MHLS data collection tool allowed valid and reliable data collection. As described, data analysis procedures followed ethical practices. This chapter's discussion on limitations and delimitations expands the discussion in Chapter 1.

The purpose of this quantitative causal-comparative study was to examine the MHL levels of African American clergy in Arizona and to see if and to what extent a difference exists in A) knowledge of professional help available, B) knowledge of risk factors and causes, C) knowledge of self-treatment, based upon the MHLS Questionnaire (O’Connor & Casey, 2015) between African American clergy who have at least a four-year bachelor’s degree or higher and those who do not have at least a four-year bachelor’s degree. The specific independent variable is (a) level of education (those who did and did not receive a four-year bachelor’s degree). Given the high number of African American individuals who turn to African American clergy for general assistance with their mental health issues and the lack of available research about the MHL of African American clergy, this study is particularly timely. This study added to the current literature by investigating the MHL of African American clergy. As more information and research are made available to the churches and mental health professionals regarding the MHL of African American clergy, it allows them to become better equipped to offer services to individuals in churches dealing with mental health illnesses (Gorczynski et al., 2017).

This study explored the levels of (MHL) between African American clergy with at least a four-year bachelor’s degree and those without a four-year bachelor’s degree. The participants of the study are Black clergy, predominantly African American churches. This group comprises African American or Black clergy, including ministers, elders, and pastors, both male and female, in Arizona. The sample size for this study was calculated through G*Power analysis, then increased by 15 % to account for possible attrition, and an additional 15% for the possible nonparametric test is 36 clergy (see Appendix E). Using sufficient statistical power, the sample size allowed the researcher to determine the differences between groups. Participants completed a 35-question scale-based measure that measured MHL (O’Connor & Casey, 2015). This study used the online platform SurveyMonkey to administer the survey. The specific steps which were taken to address the research questions are described in this chapter. This chapter is written to provide a logical flow from the problem statement and its background to the data analysis. Included in the chapter is a review of the purpose of the study, the identified problem, and how the quantitative method addressed the research questions.

In the African American community, religion and spirituality serve as a resource for coping with mental health challenges and protective factors against various mental health challenges (White, 2017). For this study, several variables were considered independent and dependent variables. The education of African American clergy was the independent variable. This researcher believed that the key issue that identified the differences between the African American clergy is the level of education. Three dependent variables were considered for this study: the knowledge of professional help available, knowledge of risk factors and causes, and knowledge of self-treatment as seen in below in Table 2. Several issues influence clergy mental health literacy. The purpose of this quantitative causal-comparative study is to determine the mental health literacy of African American clergy. This study dove into the MHL of African American clergy and the level of education made on the MHL. This sample size consisted of 36 African American clergy in Arizona who are pastors of predominantly African American churches. The following research questions guide this quantitative study:

RQ1: If and to what extent does a difference exist in the knowledge of professional help available between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree?

H1o: A statistically significant difference does not exist in the knowledge of professional help available between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree?

H1a: A statistically significant difference does exist in the knowledge of professional help available between AA clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree?

RQ2: If and to what extent does a difference exist in knowledge of risk factors and causes between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree?

H1o: A statistically significant difference does not exist in knowledge of risk factors and causes between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree.

H1a: A statistically significant difference does exist in knowledge of risk factors and causes between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree.

RQ3: If and to what extent does a difference exist in knowledge of self-treatment between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree?

H1o: A statistically significant difference does not exist in knowledge of self-treatment between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree.

H1a: A statistically significant difference does exist in knowledge of self-treatment between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree.

This study used a quantitative methodology. The quantitative approach was chosen based on the gap in the literature and the need to help determine the mental health literacy of African American clergy. The quantitative methodology and the research questions best answered the problem statement presented. The rationale for selecting a quantitative methodology was that this approach allowed the researcher to analyze data statistically to understand a relationship or differences between four variables. The four variables in question were the dependent variables of the following abilities knowledge of self-treatment, knowledge of risk factors and causes, knowledge of professional help available, and the independent variable of education level. The causal-comparative design determines whether individuals in one group differ from individuals in another group based on one or more variables (Umstead & Mayton, 2018). The causal-comparative design seeks to find any present relationships between independent and dependent variables only after the event has already happened (Fraenkel & Wallen, 2009).

The identified gap in the literature calls for an assessment to see if a difference exists between clergy who have completed at least a four-year bachelor's degree and those who have not completed a least a four-year bachelor's degree. Statistical differences that are measured and analyzed are the foundation that quantitative methodologies are built (Apuke, 2017). Determining these clergy's mental health literacy helped address the lack of mental health care support received from African American clergy. Quantitative data would work best for this research because the outcomes from this research are easily measured and seen by objectifying the data. Quantitative methodology is appropriate when the researcher’s collect variables and inferences from particular samples of quantifiable populations (Queiros et al., 2018). The results from a quantitative method are more objective than those from a qualitative method, which makes the quantitative method best suited for foundational research (Doucette, 2017).

Quantitative research allows the researcher to use structured procedures and formal instruments to collect data (Queiros et al., 2018). All quantitative analysis requires instruments to measure how and to what extent variables change when affected by another variable (Howell, 2010; Martin & Bridgmon, 2012). Validated tools address the research questions and hypotheses when conducting quantitative research. Myers and Powers (2017) share that the biases common to qualitative observational research decrease when using validated instruments. Quantitative methods provide for analyzing data gathered through polls, questionnaires, and surveys (Mellinger & Hanson, 2020). Quantitative methods also focus on using data that the researcher can generalize across several groups (Roni et al., 2020). Quantitative data are interpreted by conducting statistical analysis. Statistics are based on mathematic principles and are considered scientifically objective (Ong & Puteh, 2017).

A research design provides the logic or plan for conducting research (Baran, 2020). Four designs are associated with the quantitative methodology: causal-comparative, correlational, experimental, and quasi-experimental. The causal-comparative design was the best approach to answer the research questions, determine statistically significant differences in the collected survey data, and analyze the data set. A causal-comparative design was chosen for this study, which investigates the effects of an independent variable on a dependent variable by comparing two or more groups (Brewer & Kibn, 2010). Correlative design is another closely related research design option for this study. The difference we find between causal-comparative and correlational designs is that when choosing the causal-comparative, the groups have been formed (Fraenkel & Wallen, 2009). The correlational design for research does not look for differences between various groups but seeks to find relationships within a single group (Fraenkel & Wallen, 2009). According to researchers, true experimental designs are the highest level of research and allow the researcher to establish cause and effect by manipulating the independent variables (Slack & Draugalis, 2001). There are similarities between these design options, which include the inability to manipulate the independent variable and the lack of control groups, limiting the generalizability of the results (Brewer & Kibn, 2010).

The descriptive design was considered for this study. Descriptive studies measure specific population characteristics and determine if there is any association (Kelley et al., 2003). While it was necessary to gather data from the sample, and descriptive statistics were performed, this level of analysis could not answer the research questions. The following section discussed the population and sample section for this study.

The causal-comparative design method was appropriate in this study because it is used to identify cause-effect relationships that may be present. A causal-comparative design is a research methodology; compared to the other designs, the quantitative causal-comparative method explores the relationship between two or more groups and one independent variable. A causal-comparative survey design allows comparing two subjects to assess differences (Nardi, 2018). The causal-comparative design looks retrospectively at whether an event caused something to occur, allowing subjects to be grouped immediately (Brewer & Kibn, 2010). The causal-comparative design also seeks to find a relationship between variables after specific actions or events have occurred. According to Lodico et al. (2010), a causal-comparative design effectively evaluates the relationship or consequences of existing differences between two groups. This design would be best because it allows the researcher to choose participants who already belong to a particular group that the researcher is interested in further studying (Blackstone, 2018).

Causal-comparative designs are best used when the researcher seeks to establish an association between two or more variables (Nardi, 2018) as seen in Table 3. To justify the use of causal-comparative methods, the problem statement and the research questions were considered by the researcher. To address the research questions in this study, the researcher conducted closed-end surveys that examined the MHL of African American clergy. There are a few challenges that are present when the researcher uses the causal-comparative design. When considering the causal-comparative design, issues such as lack of randomization, inability to manipulate independent variables, and focus on standardized performance (such as tests) must be addressed. The possibility is that the groups being studied may differ on some other significant variables besides the target variable of interest. This other variable may be why there is an observed difference between the groups.

One single dependent variable was identified for this study: the education of African American clergy. There were three independent variables for this study; If and to what extent does a difference exist in the knowledge of professional help available between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree? If and to what extent does a difference exist in knowledge of risk factors and causes between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree? If and to what extent does a difference exist in knowledge of professional help available between African American clergy who completed at least a four-year bachelor’s degree and those who have not completed a least a four-year bachelor’s degree? Qualitative data analysis is the interpretation of data retrieved from other documentation received from validated instruments. This researcher also considered different research designs for this study: descriptive design, experimental design, and correlational design. The descriptive designs are not used to test hypotheses about a phenomenon; however, this design is used to gather information about your target population (Bloomfield & Fisher, 2019).

The target population of this study consisted of African American clergy located in Arizona who are members of the African American Christian Clergy Coalition. Convenience sampling was used to find participants for this study. As Etikan et al. (2016) noted, convenience sampling is a type of nonprobability or nonrandom sampling where members of the target population meet specific criteria, such as being easily accessible to the researcher or willing to participate in a research study. Convenience sampling is often used in quantitative research studies. However, convenience sampling can sometimes result in lower response rates.

To obtain site authorization (see Appendix B), an authorization request letter was sent to the AACCC director of operations. The authorization request included a brief description of the study, goals for the study, and sources of data to be collected. A timeline for the study was provided along with this researcher's commitment to providing aggregate data from the study after completion.

Due to the size of the target population, a smaller sample size was used. The researcher used a convenience sample for this study. Convenience sampling is nonprobability sampling, where members of the target population meet specific practical criteria such as easy accessibility or willingness to participate in a study (Etikan