Perceived Prejudice among African Americans in Healthcare

Data Collection Procedures 

Observation 

The research on perceived prejudice and discrimination among African Americans in Healthcare requires efficient data collection methods. One of the methods applicable would be observation. This method requires the researcher to collect data without seeking the subject of the study (Ainsworth, 2020) . They would need to strategize themselves in a health institution and observe the activities going on, singling out the relevant information and making judgments according to their perspective. For instance, one would count how many African American patients were given standard treatment and how many received mediocre services. The researcher will also observe and make conclusions on how Caucasian and Asian patients are being treated. 

Interviews 

Interviews are also necessary data collection methods to derive data from the participants. The researcher needs to formulate a list of questions that they could verbally discuss with the participants. This could be done face to face or through a video/voice call. Interviews need to be conducted on African American participants to obtain their views on healthcare discrimination. The researcher should also interview participants from other races to identify their perspectives on racial health discrimination. Interviews have been proven to be more interactive and genuine, thus enabling the provision of accurate data. 

Questionnaires 

This data collection method requires the development and compilation of open-ended or close-ended questions for the participants to answer (Ainsworth, 2020) . These questions are mostly printed in forms and handed to the participants. Soft copies are also acceptable. The most effective questions for this research are close-ended questions for easier data analysis. The questionnaire should include questions such as; Do you receive preferential treatment while receiving services from healthcare facilities? There should be yes/no checkboxes beside every question in a close-ended questionnaire. 

Data analysis 

Inferential statistics 

Regression analysis is the most appropriate for inferential analysis in this study. Regression analysis is a method of data analysis that aims to find a relationship between the dependent and independent variables in a study (Bhatia, 2018) . In this study, the researcher tries to find a relationship between an individual's race and the quality of health care services accorded to them from the data collected. This method consists of plotting a graph of dependent variables against independent variables using the data and statistics collected. Using this illustration, a regression line is drawn in the middle of the data points. This enables the researcher to answer with certainty the hypotheses questions. For instance, from the data collected and plotted in the graph, one is able to determine the percentage of individuals denied health care services because of their African American race and the percentage of individuals who have not experienced healthcare discrimination based on their race or ethnicity. This method is useful in making future predictions and forecasts in the healthcare industry. 

Descriptive statistics 

The most appropriate data analysis strategy for descriptive statistics in this study is calculating the mean from the data collected. This is otherwise known as finding the average, and it is relatively easy to obtain, considering that the questionnaires provided had close ended questions, which are easier to sort and analyze (Dillard, 2018) . This method is appropriate for this study as it enables the researcher to determine the percentage of individuals who have experienced prejudice and discrimination based on their race in the healthcare system. The mean can be derived by dividing the number of samples that responded yes to racial discrimination by the total participants. If there is a need for obtaining a percentage, the mean is multiplied by a hundred. This method is efficient for summarizing individual variables and identifying patterns in the healthcare industry (Bhatia, 2018) . 

Contribution to the Field 

Many benefits could be derived from the results of this research. If the results favor the hypothesis that African American patients get insufficient care due to prejudice and discriminatory empathy from healthcare providers, the system will be able to identify this as an issue in the medical field. It will enable the necessary personnel to recognize this as an issue and implement strategies to curb racism in the healthcare system. 

These results will also create awareness for individuals about racial discrimination in healthcare centers. This will enable citizens to be vigilant and look out for such cases. If a vigilant individual notices such an incident, they are able to reprimand and warn the offender, and if the case is serious, they would be able to report to the authorities. The results will also enable individuals from the African American community to understand their rights and recognize when they are being treated unfairly. 

The results will also point out the problems and niches in healthcare facilities that require improvement. Healthcare providers will also acquire knowledge of cases that would be considered as incidents of discrimination. The results will also enable the authorities to develop laws and legislations concerning racial discrimination in the healthcare system. 

If the results favor the second hypothesis stating that African American patients get adequate care and there is no prejudicial and discriminatory empathy from healthcare providers, the healthcare industry personnel will be able to implement strategies that maintain and improve these standards. The government would be able to reward the healthcare providers for their exemplary work and fair treatment. Individuals from all races would recognize and appreciate the efforts of the healthcare system. 

Research limitations 

This study might prove to be costly, especially during the data collection stages. Data collection methods such as questionnaires will require a researcher to spend a lot, especially on printing. Other expenses may include participants' transportation to the interview center, or storage fee for the hard copy data, awaiting analysis. 

Another limitation is that the study is time-consuming, and the researcher might need to set aside a considerable amount of time for this experiment. This is mandatory for quality results. Data collection needs to be done effectively as well as data analysis, and none of these steps should be rushed. 

The results of this study may also be subjected to bias. This may be as a result of dishonest participants and those who alter their experiences. Another limitation is that the researcher might encounter uncooperative or hostile participants who might not be willing to participate in the study. Some government laws and regulations might disadvantage the researcher during the study. 

Discussion and reflection 

I believe this study is necessary to prove either if the hypothesis stated in part one. It is important to investigate whether the inefficient treatment of African American individuals in healthcare facilities is viable. I believe that this study's results will act as a reflection of racial discrimination in the United States, which will enable the nation to improve on fairness. I also believe that the layout of this proposal is a perfect guideline for conducting an effective study. The methods of data collection and data analysis provided are bound to produce correct results if followed to latter. This proposal could also help the researcher source funding to conduct the study, as it is precise and well detailed. Despite the limitations stated, this research is achievable. 

References 

Ainsworth, Q. (2020).  Data Collection Methods . JotForm. Retrieved 11 January 2021, from https://www.jotform.com/data-collection-methods/. 

Bhatia, M. (2018).  Your Guide to Qualitative and Quantitative Data Analysis Methods - Atlan | Humans of Data . Atlan | Humans of Data. Retrieved from https://humansofdata.atlan.com/2018/09/qualitative-quantitative-data-analysis-methods/. 

Dillard, J. (2018).  5 Most Important Methods For Statistical Data Analysis . Bigskyassociates.com. Retrieved 11 January 2021, from https://www.bigskyassociates.com/blog/bid/356764/5-Most-Important-Methods-For-Statistical-Data-Analysis.