How a Mixed Methods Research Design Can Add Meaning to Our Findings in STEM
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The purpose of conducting research is to convey knowledge that is both accurate and applicable outside of a lab setting. Yet, as researchers we often limit ourselves between opting for one of two divided categories: quantitative or qualitative methods. Within hard science, we are most commonly using quantitative-based research designs as this method provides data in a numeric form. From these numbers, we are able to complete various statistical tests that include descriptive statistics (mean, median, and standard deviation), as well as inferential statistics such as t-tests, ANOVAs, or multiple regression correlations (MRC). Conducting research that involves these various forms of analysis, allows researchers to derive important facts from the data, including preference trends, differences between groups, and demographics (Madrigal, D., & McClain, B., 2012). For example, anthropometry is the science of obtaining systematic measurements of the physical properties of the human body, primarily dimensional descriptors of body size and shape. For ergonomic product design with consideration for better safety, comfort and health, anthropometry is helpful in gathering rich information about a specific population of workers (Islam, A., et al., 2013). To illustrate, a research study examining 5,434 Indian male agricultural workers used anthropometric values to help design effective tractor-seat dimensions that promote operator comfort, thereby improving work performance and reducing risk of accidents. (Metha, C. R., et al., 2008). While quantitative data has strength in numbers, it can be difficult to accurately interpret and fails to offer insights into the meaning of their values.
On the other hand, qualitative research strives to gather experiential information to offer a deep understanding of social phenomena.More specifically, many of those phenomena included quantifying details about human behavior, emotion, personality characteristics, and other information that is lost and disregarded with quantitative research. Methods of obtaining such data can include interviews, focus group discussions, and/or participant observations. Although qualitative findings cannot be easily reduced to numbers, interpretive information can be achieved through various coding processes to discover themes and consistent descriptions of core-meaning. Furthermore, while qualitative data may seem more reserved among soft sciences, these methods have been increasingly accepted by the health research community over the past two decades, with a rise in publication of qualitative studies (Harding G, Gantley M.,1998).
As the value of using qualitative methods has grown, there has been an increasingly high interest to combine it with quantitative-based methods, creating the term “mixed-methods" (Wisdom, J., & Creswell J, W., 2013). Mixed-methods research provides a more complete and synergistic utilization of data that achieves deeper insights and confidence into a researcher's findings. A recent review of health services research in England has shown an increase in the proportion of studies classified as mixed methods, from 17% in the mid-1990s to 30% in the early 2000s (O’Cathain, A, Murphy, E, Nicholl, J., 2007). While it can be challenging to conceptualize the use of mixed methods research design in the healthcare system, areas involved in STEM have benefitted from this sort of understanding.
For instance, an effective mixed-methods study considered the increasing number of African HIV-infected women in the UK that are becoming pregnant, which then supported the understanding of the various outcomes and experiences of pregnancy in migrant African women living with HIV in the UK (Tariq, S, et al.., 2012). This complex study encompassing both medical and sociocultural factors including the use of quantitative data from the Health Improvement Network (THIN) UK primary care database and conducted qualitative interviews with doctors, health visitors, and nurses to record observations in a healthcare setting. Insights from this study included differences between the type of maltreatment concerns recorded by doctors in the quantitative data-set and the qualitative research showcased concerns that came through the interviews with doctors from the primary care team.
Another successful mixed-method study focused on the barriers to accessing Tuberculosis (TB) diagnosis for rural-to-urban migrants with chronic cough in Chongqing, China (Long, et al., 2008). This study started with a prospective cohort of adult TB suspect migrants and permanent residents. Information on healthcare-seeking experiences were collected using a questionnaire and further analyzed to identify TB cases. Furthermore, focus group discussions and interviews were held to obtain a more in-depth insight on the issue. Due to this study's approach, researchers were able to capture an all-encompassing understanding of factors affecting delay in TB diagnosis, which would not have been possible with the questionnaire data alone.
Considering that New Brunswick has the highest concentration of residents over the age of 65 in Canada, the Frailty and Aging Research Engagement (FARE) initiative along with the Department of Social Development have joined forces to promote multifaceted mixed-methods research. For example, some of the New Brunswick selected researchers, Dr. Keith Brunt and Dr. Jean-Francois Legare, will supervise a team for their project, “Benefits of a Telehealth home-monitoring program for patients living with frailty undergoing heart surgery”. Researchers will test Telehealth home-monitoring and observe how this emerging technology will allow patients to return home and remain in contact with their health-care team for the first 30 days following surgery. This research is an ongoing collaboration between UNB and Horizon Health Network that is attempting to consider the benefits of understanding their patients by using a mixed-methods based research design. Likewise, the Horizon Health Network's Office of Research Services offers a lunch and learn series called “Explore!”. In April 2020, they will be hosting a session titled “How can I start doing qualitative / mixed methods research? It's not just content analysis!”. This session will help educate researchers on how to develop study protocol, with quantitative, qualitative or mixed methodology, create a data analysis plan, and much more. For more information click here.
Regardless of the strengths attributed to using a mixed-method research design, many researchers argue that it is neither possible nor desirable to combine quantitative and qualitative methods in a study as they represent conflicting ways of viewing the world and how we collect information about it (Murphy, E., et al., 1998). While many researchers may disagree with this statement, there are some downsides to the use of mixed methods that must be considered. Firstly, combining two vastly different methodologies in one study can be time-consuming and may require skills in both quantitative and qualitative methods. Thus, the use of mixed methods may alter the timeline of the study and the results may not be able to be properly interpreted if the researchers have limited experience with both types of data. Secondly, achieving true integration of quantitative and qualitative data can be difficult. It is often suggested that research use various analytic strategies, but this can be hard to achieve as it requires innovative thinking to make meaningful links between them. Finally, many researchers cite challenges presenting the results of mixed methods research as a barrier to conducting this type of research (Bryman A., 2007).
Though mixing research methods may pose challenges, this form of research provides a holistic approach that offers depth, detail, and the data to back it up. For those interested in conducting mixed-methods research, an effective starting place is with the guidelines found in “Designing and conducting mixed methods research” by Creswell, J, W., & Plano Clark, V, L. (2011). This book targets individuals across the social and human science fields learning about mixed methods research for the first time. With a reader-friendly approach, the authors go step-by-step through the process of conducting a study, from deciding whether or not to use mixed-methods, understanding its historic and philosophical underpinnings, and outlines the process of collecting, analyzing and interpreting data in mixed methods research. Whether you are a seasoned researcher or new to this field of discovery, it is important to consider all variations of your research question design in case you want to “mix it up.”
References
Creswell, J, W., & Plano Clark, V, L. (2011). Designing and Conducting Mixed Methods Research, 2nd edn.Thousand Oaks Sage Publications.
Bryman A.(2007). Barriers to integrating quantitative and qualitative research. Journal of Mix Methods Research;1:8–22.
Harding, G., &, Gantley, M. (1998) Qualitative methods: beyond the cookbook. Family Practice Journal. 15(1), 76–90.
Islam, A., Asadujjaman, Nuruzzaman, & Hossain. (2013). Ergonomics Consideration for Hospital Bed Design: A Case Study in Bangladesh. Journal of Modern Science and Technology, 1(1), 30–44.
Long, Q., Li, Y., Wang, Y., Yue, Y., Tang, C., Tang, S., Squire, S,B., & Tolhurst, R. (2008). Barriers to accessing TB diagnosis for rural-to-urban migrants with chronic cough in Chongqing, China: a mixed methods study, BMC Health Services Research , 8, 202.
Madrigal, D., & McClain, B. (2012, September 3). Strengths and Weaknesses of Quantitative and Qualitative Research. Retrieved from https://www.uxmatters.com/mt/archives/2012/09/strengths-and-weaknesses-of-quantitative-and-qualitative-research.php.
Metha, C. R., Gite, L. P., Pharade, S. C., Majumder, J., & Pandey, M. M. (2008).Review of anthropometric considerations for tractor seat design‟, International Journal of Industrial Ergonomics, 38 (5-6), 546-554.
Murphy E, Dingwall, R, Greatbatch, D, Parker S, & Watson P. (1998) Qualitative research methods in health technology assessment: a review of the literature. Health Technol Assess, 2, 1–274.
O’Cathain, A, Murphy, E, & Nicholl, J.(2001) Why, and how, mixed methods research is undertaken in health services research in England: a mixed methods study. BMC Health Serv Res, 7, 85.
Tariq, S., Pillen, A., Tookey, P, A., Brown, A, E., & Elford, J. (2012). The impact of African ethnicity and migration on pregnancy in women living with HIV in the UK: design and methods. BMC Public Health, 12, 596.
Wisdom, J., & Creswell J, W. (2013). Mixed Methods: Integrating Quantitative and Qualitative Data Collection and Analysis While Studying Patient-Centered Medical Home Models. Rockville, MD: Agency for Healthcare Research and Quality. AHRQ Publication No. 13-0028-EF