When it is necessary to make data from research credible, healthcare managers and leaders can use numerous types of studies. They include case-control studies, cohort studies, and randomized clinical trials (RCTs), and each of them has specific peculiarities. Thus, the paper will offer examples of such studies and comment on what data can be collected with these tools, their bias, cost-effectiveness, and level of reliability.
Case-control studies are useful to assess the relationship between causes and effects. Munnangi and Boktor (2020) explain that this type focuses on a group with a condition and a group without it. Since the data are assessed retrospectively, a recall bias is present, while cost-effectiveness is considered a significant advantage (Munnangi & Boktor, 2020). The study by Nobel et al. (2020) is an example of a case-control study, while Johansen et al. (2017) admit that this design is lower than a cohort methodology in the hierarchy of studies. That is why it is also reasonable to comment on this type.
Cohort studies are helpful for determining the incidence of a condition by focusing on what exposures result in the given state of affairs. According to Munnangi and Bokter (2020), these studies can be retrospective when scientists analyze the collected data and prospective when researchers select a sample and watch whether they will experience a condition. Recall and selection biases affect this design, and the necessity to cover extended periods makes it expensive (Munnangi and Bokter, 2020). An article by Fuchs et al. (2018) is a cohort study example, and it offers reliable findings. It means that it is necessary to spend more time and resources to increase reliability.
Finally, RCTs are considered a highly efficient and useful study design. They randomly select the control and experimental groups to find an intervention effect (Munnagi & Bokter, 2020). A selection bias has some impact, but randomization is used to minimize it. This study type is expensive, while Verster et al. (2019) admit the reliability of its findings by stating that it is a standardized experimental intervention. Song and Baicker’s (2019) study is an RCT example in medical research. The information above demonstrates that all these types imply their own pros and cons, and the choice of a specific design should depend on the researchers’ aims.
References
Fuchs, F., Monet, B., Ducruet, T., Chaillet, N., & Audibert, F. (2018). Effect of maternal age on the risk of preterm birth: A large cohort study. PLos One, 13(1).
Johansen, C. Schüz, J., Andreasen, A.-M. S., & Dalton, S. O. (2017). Study designs may influence results: The problems with questionnaire-based case-control studies on the epidemiology of glioma. British Journal of Cancer, 116, 841-848.
Munnangi, S., & Boktor, S. W. (2020). Epidemiology of study design. In B. Abai et al. (Eds.), StatPearls [Internet]. StatPearls Publishing.
Nobel, Y. R., Phipps, M., Zucker, J., Lebwohl, B., Wang, T. C., Sobieszczyk, M. E., & Freedberg, D. E. (2020). Gastrointestinal symptoms and coronavirus disease 2019: A case-control study from the United States. Gastroenterology, 159(1), 373-375.
Song, Z., & Baicker, K. (2019). Effect of a workplace wellness program on employee health and economic outcomes: A randomized clinical trial. JAMA, 312(15), 1491-1501.
Verster, J. C., van de Loo, A. J. A. E., Adams, S., Stock, A.-K., Benson, S., Scholey, A., Alford, C., & Bruce, G. (2019). Advantages and limitations of naturalistic study designs and their implementation in alcohol hangover research. Journal of Clinical Medicine, 8(12).