Qualitative and quantitative researches have benefits and disadvantages, can be suitable only for certain types of studies, and require a different range of sampling. Technological development and demand for new knowledge made scientists try mixing the methods to receive more precise results (Ostlund et al., 2011). Indeed, the mixed-method approach is frequently used for studies with extensive sampling where experience-based information is combined with the numeral one (Ostlund et al., 2011).
For instance, the recent COVID-19 outbreak-related studies require statistical data about the cases, duration of treatment, or demographical details, while the personal experiences with symptoms are also considerable. This paper aims to discuss a hypothetical pandemic-based situation where utilizing a mixed-methods approach would be beneficial, assess the cooperation of quantitative and qualitative data, and discuss the potential challenges.
COVID-19 pandemic forced healthcare systems worldwide to adjust most practices to address the disease conditions in various cases. For example, vaccination for pregnant women requires research because multiple factors, personal and external, influence the decisions and recommendations. In a study exploring the need to receive the COVID-19 vaccine for a particular group, qualitative data would provide records categorized as personal experience of having the infection, pregnancy description, and other necessary themes.
The quantitative data to retrieve can contain the general information about vaccinations nationwide, the outbreak’s size, and risk rates for cases’ quantity increase. In research where statistics and experiences are equally important, generalization methods can be exercised to explore populations and transferability (Polit & Tatano-Beck, 2010). Consequently, the mixed-methods approach would benefit such a study because the broader scope of evidence would be collected, making the results more rigorous and reliable.
Qualitative data is commonly gathered through interviewing and retrieving large scopes of descriptive records about participants’ experiences. Conversations-based can complement the quantitative part of the study as the responses contain the numerical information, or the quantity of positive and negative answers can be further recalculated to the evidence-based rating (Guetterman et al., 2019).
Statistical data about the numbers of COVID-19 cases at specific locations can influence the interviews’ structure for participants and explore their experiences more deeply. For instance, the knowledge that a pregnant woman is from a state with a significant number of infected can be asked about her fears or thoughts that influence the decision to vaccinate. Quantitative data complements the qualitative by providing a foundation for selecting a direction of research and helping scientists categorize and code the responses (Guetterman et al., 2019). The mixed-methods approach is necessary for exploring various cases where pregnant women need COVID-19 vaccination and considering the statistics to predict the decision’s outcomes.
Exploring the need for pregnant women to receive the COVID-19 vaccine with the mixed-methods approach can be complicated due to two significant challenges. Indeed, the statistics based on the interviews must be validated, and issues like private data disclosure might occur during the process (LoGiudice & Bartos, 2021). Informed contests and methodology discussions are necessary to be performed with participants to address that challenge. Furthermore, the quantitative part of a study might not correlate with the qualitative, and to solve that problem, a null hypothesis or grounded theory must be developed (LoGiudice & Bartos, 2021). The conditions of pregnant women might need to be detailed to provide more information for successfully using the mixed-methods approach.
Qualitative and quantitative research methods are used as a combination in modern studies because they provide more evidence-based conclusions, making the results reliable and credible. Exploring if pregnant women should be vaccinated from COVID-19 requires both statistical and experience-based information to be analyzed and assessed according to the outcomes of a pandemic. The mixed-methods approach allows numeric and descriptive data to complement each other by expanding the field of research, yet ethical and information incorrectness challenges might occur.
References
Guetterman, T. C., Babchuk, W. A., Howell Smith, M. C., & Stevens, J. (2019). Contemporary approaches to mixed methods–grounded theory research: A field-based analysis. Journal of Mixed Methods Research, 13(2), 179-195. Web.
LoGiudice, J. A., & Bartos, S. (2021). Experiences of nurses during the COVID-19 pandemic: A mixed-methods study. AACN Advanced Critical Care, 32(1), 14-26. Web.
Ostlund, U., Kidd, L., Wengstrom, Y., & Neneh, R. (2011). Combining qualitative and quantitative research within mixed method research designs: A methodological review. International Journal of Nursing Studies, 48(3), 369-383. Web.
Polit, D. F., & Tatano-Beck, C. (2010). Generalization in quantitative and qualitative research: Myths and strategies. International Journal of Nursing Studies, 47(11), 1451-1458. Web.