In academic research it is often required to conduct research studies. Interestingly, each study requires a unique approach that is customized to fit the situation, requirements, and desired outcomes for the given study. In order to fully understand the process of determining the appropriate study type for individual studies, an example case will be detailed in the following paragraphs. Specifically, the analysis that follows will determine the type of study, the strengths and weaknesses of this type of study, and the potential biases and effects on findings of the type of study as it relates to research to determine whether or not smoking is a risk factor for pancreatic cancer. The data collection method that has been identified for this study is the use of two study groups of 100 patients, one group with pancreatic cancer and one group without pancreatic cancer, and their individual electronic medical records will be analyzed to determine past smoking history.

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Type of Proposed Study
The type of study that is being utilized by the example research study is that of an epidemiological quantitative correlative study. The epidemiological study attempts to determine what factors are associated with diseases (risk factors), and what factors may protect people or animals against disease (protective factors) (Cornell University, 2011). The quantitative correlative study refers to the activity to determine whether or not there is a correlative relationship between two variables, if so, whether or not that correlative relationship is positive or negative (Creswell, 2003). To determine this, numerical data is gathered and subjected to statistical analysis such as Pearson’s correlation. A positive correlation is expressed by statistical analysis results of +1, no correlative relationship exists at 0, and a negative correlative relationship exists at -1. In this case, the variables would include patients with pancreatic cancer and patients who have a history of smoking. The use of medical record data would represent the instrument by which numerical data would be gathered in order to conduct statistical analysis.

Strengths of Study
The use of an epidemiological quantitative correlative research study has two primary strengths. First, it will enable the researcher to determine the main factors that are associated with a particular disease, in this case, weather smoking is associated with pancreatic cancer. Further, epidemiological studies are able to help researchers to determine what types of measures can help to prevent against a particular disease, such as avoiding smoking to prevent pancreatic cancer. The second strength of this study type is that it allows for a very analytical reflection of the data that can provide researchers with a realistic picture of whether or not there is a correlative relationship, either positive or negative, between smoking and pancreatic cancer. Subjecting medical record data to statistical analysis will be able to tell researchers how many pancreatic cancer patients smoked and how many without pancreatic cancer smoked. This will help researchers to see if patients with pancreatic cancer had more histories of smoking than those without, or if smoking was more equally distributed between the two groups.

Weaknesses of Study
One potential weakness of this study type is that although the epidemiological approach allows for the identification of what factors may be associated with a particular disease, this approach cannot actually prove that causality exists. Specifically, epidemiological evidence can only show that this risk factor is correlated with a higher incidence of the identified study group exposed to that risk factor, as the higher the correlation the more certain the association, but it cannot prove the causation (Cornell University, 2011). This problem appears to translate over to the quantitative correlative study approach. Available information on the subject indicates that while correlational studies can suggest that there is a relationship between two variables, they cannot prove that one variable causes a change in another variable, and as such correlation does not equal causation (Cherry, 2013)

Potential Bias and Effect on Findings
One of the most prevalent biases that could exist within this study involves the fact that smoking can cause, and has been proven to cause, a number of other health issues, including heart disease, as well as lung, mouth, and throat cancer. Further, a number of other risk factors have already been found to precipitate pancreatic cancer, such as genetics, diabetes, obesity, and poor diet (Mayo Clinic, 2012). As such, it may be difficult to determine which risk factor led to the case of pancreatic cancer when the other identified risk factors are not considered in the analysis as some patients may have two or more of these risk factors. Ignoring the other possible risk factors could significantly limit the accuracy of the research and negatively affect the resulting findings by making them appear stronger than they really are.

  • Cherry, K. (2013, February 19). Correlational Studies. Retrieved from Web site:
  • Cornell University. (2011). Epidemiology. Retrieved from Cornell University Web site:
  • Creswell, J. W. (2003). Research design: Qualitative, quantitative, and mixed method approaches (2nd ed). Thousand Oaks, CA: Sage Publications.
  • Mayo Clinic. (2012, April 10). Pancreatic cancer: Causes. Retrieved from The Mayo Clinic Web site: