Observational Studies

Careful design and analysis of observational studies is essential because they are not structured to control for these external factors, thus they are especially prone to bias and confounding (Dreyer et al., 2010; Hemkens et al., 2018; Song & Chung, 2010). In an ideal world, people would be able to use randomized control trials more often, however, sometimes it is simply unethical or impractical to conduct an RCT (Scales et al., 2005; Song & Chung, 2010). For example, when investigating socioeconomic impacts on health or surgical procedures.

Due to the complex design and conduct of observational studies, they have been deemed to be “the most necessary and difficult” studies to conduct (Harper, 2019). Observational studies are conducted in real-world settings and can investigate the impact of health policies on populations and explore the distribution of health outcomes across groups (Dreyer et al., 2010). RCTs simply cannot achieve these same results. Observational research also allows participants to be followed for longer periods of time meaning that one can evaluate changes in health outcomes throughout the lifespan. Furthermore, observational studies affordably provide a larger number of participants in comparison to RCTs (Dreyer et al., 2010). This allows investigations into differences between subgroups in the population (e.g., different age groups, disease subtypes) (Ligthelm et al., 2007). Given the breadth of topics that observational studies can cover, it is no surprise that it is the most common study design used in biomedical research (Funai et al., 2001).

Why STROBE?

Due to a high prevalence of observational studies in biomedical research, widespread poor reporting means that an enormous amount of the medical literature has issues. Research has shown that items concerning the methodology and results of observational studies are particularly poorly reported reported (Irani et al., 2018; Jeelani et al., 2014; Kim et al., 2012; Langan et al., 2010; Papathanasiou & Zintzaras, 2010; Poorolajal J et al., 2011). Details about participants, data collection methods, and analyses are common problems. Missing details on how many people were eligible to participate, consented, and lost to follow-up questions the generalizability of results. Whereas, missing data, the reliability of the data collection instruments used, how the data was analyzed, and missing disclosures of funding sources can be worrying as motives for certain narratives or results may be hidden. Therefore, a reporting guideline for observational research is critically needed to reinforce replicability and reproducibility and instill greater confidence in the trustworthiness of results.

What is STROBE?

The STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) Statement is a 22-item checklist that details the key information needed when reporting the results of an observational study (Elm et al., 2007) (Figure 1). It is also accompanied by an Explanation and Elaboration (E&E) document that provides further details for each checklist item and gives examples of good reporting (Vandenbroucke et al., 2007).

STROBE comes as a downloadable checklist. You can download a fillable Word checklist (or static pdf) on the STROBE website. There is also a Writing Aid Tool for Microsoft that you can download and install which includes the STROBE checklist within the software.

For detailed background and guidance on STROBE you can read the Explanation and Elaboration (Vandenbroucke et al., 2007) article. Briefly put, STROBE does not dictate how to conduct research nor the specific order that items should be written in (only that they should be under the relevant IMRaD heading). Some items may not be applicable to your study, just state so and explain why. STROBE is not meant to be a “procedural straightjacket”, rather, think of it as a life jacket. Its structure may be helpful for study planing or peer review but it is not designed for that purpose.

References

Dreyer, N. A., Tunis, S. R., Berger, M., Ollendorf, D., Mattox, P., & Gliklich, R. (2010). Why Observational Studies Should Be Among The Tools Used In Comparative Effectiveness Research. Health Affairs, 29(10), 1818–1825. https://doi.org/10.1377/hlthaff.2010.0666

Elm, E. von, Altman, D. G., Egger, M., Pocock, S. J., Gotzsche, P. C., Vandenbroucke, J. P., & for the STROBE Initiative. (2007). The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Annals of Internal Medicine, 147(8), 573. https://doi.org/10.7326/0003-4819-147-8-200710160-00010

Funai, E. F., Rosenbush, E. J., Lee, M. J., & Del Priore G, null. (2001). Distribution of study designs in four major US journals of obstetrics and gynecology. Gynecologic and Obstetric Investigation, 51(1), 8–11. https://doi.org/52882

Harper, S. (2019). A Future for Observational Epidemiology: Clarity, Credibility, Transparency. American Journal of Epidemiology, 188(5), 840–845. https://doi.org/10.1093/aje/kwy280

Hemkens, L. G., Ewald, H., Naudet, F., Ladanie, A., Shaw, J. G., Sajeev, G., & Ioannidis, J. P. A. (2018). Interpretation of epidemiologic studies very often lacked adequate consideration of confounding. Journal of Clinical Epidemiology, 93, 94–102. https://doi.org/10.1016/j.jclinepi.2017.09.013

Irani, M., Hassanzadeh Bashtian, M., Khadivzadeh, T., Ebrahimipour, H., & Asghari Nekah, S. M. (2018). Weaknesses in the Reporting of Cross-sectional Studies in Accordance with the STROBE Report (The Case of Congenital Anomaly among Infants in Iran): A Review Article. Iranian Journal of Public Health, 47(12), 1796–1804. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6379628/

Jeelani, A., Malik, W., Haq, I., Aleem, S., Mujtaba, M., & Syed, N. (2014). Cross-Sectional Studies Published in Indian Journal of Community Medicine: Evaluation of Adherence to Strengthening the Reporting of Observational Studies in Epidemiology Statement. Annals of Medical and Health Sciences Research, 4(6), 875–878. https://doi.org/10.4103/2141-9248.144889

Kim, M. R., Kim, M. Y., Kim, S. Y., Hwang, I. H., & Yoon, Y. J. (2012). The Quality of Reporting of Cohort, Case-Control Studies in the Korean Journal of Family Medicine. Korean Journal of Family Medicine, 33(2), 79–88. https://doi.org/10.4082/kjfm.2012.33.2.79

Langan, S., Schmitt, J., Coenraads, P.-J., Svensson, A., Elm, E. von, & Williams, H. (2010). The Reporting of Observational Research Studies in Dermatology Journals: A Literature-Based Study. Archives of Dermatology, 146(5), 534–541. https://doi.org/10.1001/archdermatol.2010.87

Ligthelm, R. J., Borza, V., Gumprecht, J., Kawamori, R., Wenying, Y., & Valensi, P. (2007). Importance of observational studies in clinical practice. Clinical Therapeutics, 29 Spec No, 1284–1292.

Papathanasiou, A. A., & Zintzaras, E. (2010). Assessing the Quality of Reporting of Observational Studies in Cancer. Annals of Epidemiology, 20(1), 67–73. https://doi.org/10.1016/j.annepidem.2009.09.007

Poorolajal J, Cheraghi Z, Irani Ad, & Rezaeian S. (2011). Quality of Cohort Studies Reporting Post the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement. Epidemiology and Health, Epidemiology and Health, 33, 33, e2011005–e2011005. https://doi.org/10.4178/epih/e2011005, 10.4178/epih/e2011005

Scales, C. D., Norris, R. D., Peterson, B. L., Preminger, G. M., & Dahm, P. (2005). Clinical research and statistical methods in the urology literature. The Journal of Urology, 174(4 Pt 1), 1374–1379.

Song, J. W., & Chung, K. C. (2010). Observational Studies: Cohort and Case-Control Studies. Plastic and Reconstructive Surgery, 126(6), 2234–2242. https://doi.org/10.1097/PRS.0b013e3181f44abc

Vandenbroucke, J. P., Elm, E. von, Altman, D. G., Gotzsche, P. C., Mulrow, C. D., Pocock, S. J., Poole, C., Schlesselman, J. J., & Egger, M. (2007). Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Epidemiology, 18(6), 805–835. https://doi.org/10.1097/EDE.0b013e3181577511