Karissa’s post
Observational Studies: Advantages and Disadvantages
All study designs have their advantages and disadvantages. Some positive factors of observational studies are that they give critical, descriptive information and data on effectiveness and safety over a long period of time (Gilmartin-Thomas et al., 2018). Clinical trials often can not provide long-term data, making observational studies beneficial and more cost-effective (Gilmartin-Thomas et al., 2018). Observational studies also do not create any changes within their participants’ circumstances or implement any interventions. On the downside, implementation and modifications are essential factors in research to improve outcomes or decipher the effectiveness of the intervention, which is not included in an observational study(Gilmartin-Thomas et al., 2018). Some examples of descriptive observational studies are case reports and case series, ecological studies, and cross-sectional studies, which are reletively easy to execute; however, in some research areas, cohort studies are used, which can be more challenging to perform and expensive, which is a drawback (Gilmartin-Thomas et al., 2018).
Experimental Studies: Advantages and Disadvantages
Randomized clinical trials (RCT) are experimental studies. This type of study is regarded as the gold standard of study design (Munnangi & Boktor, 2023). An advantage of experimental studies is that they avoid complications and reduce selection bias due to the randomization of subjects by separating them into a control group and an experimental group (Munnangi & Boktor, 2023). Doing this assists the researcher in isolating the effect of the intervention by comparing the outcomes of the groups (Munnangi & Boktor, 2023). Unfortunately, RCTs have a downside: they can be very costly and time-consuming. Participants can refuse, withdraw, crossover, and can be non-compliant, which can impact the integrity of randomization of the data obtained during the process (Munnangi & Boktor, 2023).
Epidemiological Study Biases
Most studies will have biases, and epidemiologic studies are no different. An epidemiological study focuses on assessing a determinant’s impact on an outcome in clinical and medical domains. If measurement errors occur systematically, it increases the risk of biases, resulting in invalid findings; however, incidental measurement errors can lead to inaccurate reporting of results as well (Chew, 2019). Increasing the sample size can reduce biases and increase precision; however, avoiding or trivializing the biases will exacerbate them (Chew, 2019). Some facets of a research study that can impact the findings and process are as follows: “paucity of similar studies, poor study design and implementation, low test agent efficacy, no predetermined statistical analysis, insufficient reporting, bias, and conflicts of interest” (Chew, 2019, para 2). Moreover, measurement errors will be found throughout the research process, which is standard; therefore, appropriate writing and reporting skills are essential to creating accurate studies.
References
Chew, B.H. (2019). Planning and conducting clinical research: The whole process. Cureus. 2019 Feb 20;11(2):e4112. doi: 10.7759/cureus.4112. PMID: 31058006; PMCID: PMC6476607.
Gilmartin-Thomas, J.F., Liew, D., & Hopper, I. (2018). Observational studies and their utility for practice. Aust Prescr. 2018 Jun;41(3):82-85. doi: 10.18773/austprescr.2018.017. Epub 2018 Jun 1. PMID: 29922003; PMCID: PMC6003013.
Munnangi, S. & Boktor, S.W. (2023). Epidemiology of study design. . In: StatPearls . Treasure Island (FL): StatPearls Publishing; 2023 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK470342/
Kyla Baucom’s post
Kyla Baucom
3:17pmJun 12 at 3:17pm
Research designs vary across studies and are accompanied by intrinsic risks versus benefits for each type. The two primary study designs discussed are experimental study designs and observational study designs. Experimental studies examine causal relationships between one or more independent or dependent variables (Pinquart, 2022). Experimental studies often include an intervention on some or all members of a specific group (Ranganathan & Aggarwal, 2018). These studies are valuable at directly identifying the effect of an intervention by identifying one variable’s impact on another (Pinquart, 2022). However, these studies must utilize randomization and control or eliminate third variables to truly determine causation. Contrarily, an observational study examines a naturally occurring variation between an exposure and an outcome (Ranganathan & Aggarwal, 2018). Observational studies involve researchers investigating individuals without manipulating variables or implementing interventions (Pinquart, 2022). Observational studies are easier to conduct since an intervention is not performed. Moreover, they are often cheaper since the cost of an intervention does not need to be considered. However, controlling for variables with this study design can be difficult.
Various degrees of bias frequently exist across the continuum of research studies and study designs. Bias occurs when there is a flaw during the research process, such as in the design, data collection, statistical methods, or interpretation of data (Popovic & Huecker, 2022). Bias can occur during the research planning stage if participants are selected non-randomly, termed sampling bias. Moreover, selection bias occurs if the selected population does not closely mimic the target population. Bias can also occur during data collection if values vary due to personal interpretation by a researcher, also termed observer bias. This is especially apparent in studies with any degree of subjectivity to data collection. Observer bias closely ties into confirmation bias, which occurs when a researcher seeks information that validates a preexisting belief. Finally, publication bias occurs post-interpretation when statistically significant results are published while excluding additional findings (Popovic & Huecker, 2022). Understanding bias is critical to increasing external validity and the general applicability of study results. By remaining aware of different forms of bias, researchers can reduce its impact and produce quality results for evidence-based medicine practices.
References:
Pinquart, M. (2022). Experimental studies and observational studies. In Encyclopedia of Gerontology and Population Aging (pp. 1748-1756). Cham: Springer International Publishing.
Popovic, A., & Huecker, M. R. (2022). Study bias. In StatPearls . StatPearls Publishing. Retrieved June 12th, 2022, from https://www.ncbi.nlm.nih.gov/books/NBK574513/
Ranganathan, P., & Aggarwal, R. (2018). Study designs: Part 1 – An overview and classification. Perspectives in Clinical Research, 9(4), 184–186. https://doi.org/10.4103/picr.PICR_124_18Links to an external site.
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