When it comes to health science research, there is no such thing as a one size fits all study design. Many study designs exist to accommodate clinical and population health research. Out of the many study designs, eight of them are common in health science research. Research projects may use components from a single design, while others may use elements from two designs. Using a variation of multiple designs helps with collecting and analyzing new data, analyzing existing data, and reviewing literature in health sciences (Jacobsen, 2016).
The design or designs selected must be appropriate for the goals of the study. Choosing the proper design is vital because each one is different and yields different results when applied to a data set. While it may be suitable to use one study approach on a research project, various methods can also be used together. Using different study approaches makes it easier to explore relationships between an exposure and a disease (Jacobsen, 2016). Other helpful factors to consider when selecting which method to use are the expected duration and cost of the study, the populations available for inclusion in the study, and the possible availability of data (Jacobsen, 2016). These factors are essential because they allow the researcher to see if the type of design or size of the population they want to sample is feasible.
Before a study design or designs are further developed, one must figure out which type of data they want to gather and how they are going to assemble it. One study approach is a primary analysis. A primary analysis allows you to collect new data from individuals. This type of analysis is time-consuming because you must collect new data from participants. However, the researcher has control over important details of the data selection process (Jacobsen, 2016). Another study approach is a secondary analysis, which uses existing data. The last study approach is a tertiary analysis which allows you to write a review article. Both of these study approaches are not as time-consuming as the primary analysis. Because the data is already present, it does not take long to progress from defining the study question to analyzing relevant data. However, both approaches are limited in how much data is available. Another drawback to these two analyses is that they may not include the exact variables or population the researcher is looking for (Jacobsen, 2016).
One type of study design is case series. A case series approach is used to describe a group of people who have the disease being studied. Another approach is a cross-sectional survey. This type of approach is used to describe the status of exposure or illness in a population. While the previous studies aim to describe diseases in populations, four other approaches aim to compare data. The first comparative approach, which examines exposure histories in people with a disease (cases) and people without disease (controls), is case control. This approach is used when a condition is relatively uncommon, but there are available cases to compare it to. The second approach is a cohort study. In this approach, rates of new diseases (incident) are compared in people with different exposure histories, or it follows a population forward in time to look for incident diseases. An experimental study compares outcomes in participants assigned to an intervention or control group.
The last comparative approach is a correlational study. This design compares the average levels of exposure and disease in several populations. It is mainly used to explore possible connections between an exposure and a disease using population-level data. Another approach that seeks to understand how individuals and communities perceive and make sense of the world and their experiences is qualitative design (Jacobsen, 2016). The last study approach is meta-analysis. This approach is used to synthesize existing knowledge (Jacobsen, 2016).
It is vital to adhere to all ethical standards when conducting research. One, following ethical standards protects participants by informing them of what the study is and how they play a role in it. Another reason why following ethical standards is essential is to provide accurate and honest answers to relevant issues in society. When following ethical guidelines, the researcher allows for reliable, unbiased, and fair results.
Over the years, ethical standards concerning human health research participants have been developed. With many human subjects, such measures are essential in protecting the health and dignity of these subjects. The Nuremberg Code was one of the first ethical standards set in place and mandated voluntary consent for experimental studies on humans (Jacobsen, 2016). This was a huge step in how humans were used and informed in the study they were participating. Another standard that further increased the ethics of education was the Declaration of Helsinki. This provided the guidelines for clinicians conducting clinical trials. This means that clinicians finally had to follow and adhere to specific rules when conducting experiments on human subjects. One study that explicitly protects human research participants is the Belmont Report. This report is the foundational document for the current U.S. federal policy for protecting human research participants (Pavao, 2020, Chapter 23: Designing the Study and Collecting Data).
About fifteen years before these standards were set in place, experimental studies were being conducted without much respect for human subjects. One study that highlights the importance of ethical standards is the Tuskegee Syphilis experiment. This study was conducted to analyze syphilis itself and to find treatment for blacks (“Tuskegee Study – Timeline – CDC – NCHHSTP,” n.d.). The study consisted of 600 black men, some who had syphilis, and some who did not. These participants were not informed of what the review was for, and most suffered because of it. This study continued for forty years, and in those forty years, the ethical standards were created and implemented. When analyzing this study and how the participants were selected, you can see how important it is to have consent systems in place. There were no formal consent process statements provided to the participants so that they would know what the study was and what it was for and whether or not they wanted to participate.
One study that followed the ethical standards was the Framingham Heart Study. This study was established in 1948. It was conducted to identify the common factors or characteristics that contribute to cardiovascular disease by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD suffered a heart attack or stroke (“Framingham Heart Study,” n.d.). Early on in the study, the first participants voluntarily agreed to be tested and monitored for the duration of the study. Later on, other participants were asked, by researchers, to participate. All subjects in this experiment were fully aware of the study being conducted which meant that the researchers were following all ethical guidelines.
Data management refers to the entire process of record-keeping (Pavao, 2020, Chapter 26: Analyzing Data). It is important because it is how you keep track of, clean, analyze, set it up to be analyzed, and to see patterns in your data. Before data is entered into a database, a codebook is created. A codebook “describes each variable and specifies how the collected information will be entered into a computer (Pavao, 2020, Chapter 26: Analyzing Data, Slide 4).” A codebook is similar to a blueprint for the data that needs to be entered into a database. It is also the place to describe how anticipated data problems will be handled (Jacobsen, 2016). It will also specify for each variable whether missing answers should be left blank in the database, indicated with a numeric code, or marked with the word “missing” (Jacobsen, 2016).
Following the creation of a codebook, is data entry. Data is entered into a database program that stores and organizes it (Jacobsen, 2016). One way to ensure that the information being entered is accurate, is through double entry. This entry method consists of the same data being entered by two individuals then being compared for accuracy (Jacobsen, 2016). After data has been entered, it is then cleaned.
Data cleaning “is the process of correcting any typographical or other errors in data files (Pavao, 2020, Module 2: Analyzing Data, Slide 4).” This step or process makes it easier to follow the initial data layout of the codebook by eliminating any errors such as typos. This step is also used to remove any questionable data. These types of responses may or may not coincide with the original entry, so it is best to check the original data. Data recoding consists of using existing variables in a database to create a new derived variable. This is done either through recoding based on categories or through calculating new values using mathematical operators. Because new values are being created, it is best to have several copies of the original file saved and never to replace any old data with new data. The last step in the data management process is data security. Data security “is the process of protecting computer files with passwords and other mechanisms for restricting unauthorized access and use (Pavao, 2020, Chapter 26: Analyzing Data, Slide 8).” This step is vital when sensitive information is being handled.
To conclude, from the different study designs and approaches to ethical and unethical research projects to data management, one must have more than a general understanding of these components to assign them to the appropriate study. If analyzed and observed correctly, researchers can recreate past studies to receive a modern-day approach and knowledge of what could have been done to prevent that significant event from happening. Moreover, if those who conduct health science research do not approach a study in such a manner, there will be a poor interpretation, if any, by future researchers, leading to the question of where they start on a given situation.
References
- Framingham Heart Study. (n.d.). Retrieved May 20, 2020, from https://framinghamheartstudy.org/fhs-about/history/epidemiological-background/
- Jacobsen, K. H. (2016). Introduction to Health Research Methods: A practical Guide. [Chegg]. Retrieved from https://ereader.chegg.com/#/books/978128412424
- Pavao, C.A.O. (2020). Chapter 23: Designing the Study and Collecting Data. Retrieved from https://gastate.view.usg.edu/d2l/le/content/2056813/viewContent/35387930/View
- Pavao, C.A.O. (2020). Chapter 24: Designing the Study and Collecting Data. Retrieved from https://gastate.view.usg.edu/d2l/le/content/2056813/viewContent/35387519/View
- Pavao, C.A.O. (2020). Chapter 26: Analyzing Data [PowerPoint Slide 4, 8]. Retrieved from https://gastate.view.usg.edu/d2l/le/content/2056813/viewContent/35387910/View
- Tuskegee Study – Timeline – CDC – NCHHSTP. (n.d.). Retrieved May 20, 2020, from https://www.cdc.gov/tuskegee/timeline.htm
