Qualitative research (QlR) and quantitative research (QnR) each have their own strengths and weaknesses. When it comes to the rubber meeting the road, both types of research are immensely important. Some researchers have argued that neither is genuinely independent of each other while others go as far as proclaiming, “There is no such thing as qualitative data” (Writing@CSU, 2012). I personally believe that both are so intricately linked, one without the other is generally inadequate for effective evidenced-based treatment outcomes. Both types should be considered in order to address behavior and clinical issues. Now on to my brief and limited perspective about some of the shortcomings . . .
If you are a strict researcher interested in facts substantiated by definitive measurements, then qualitative research is not your thing. Qualitative research focuses on holistic processes through a narrative and subjective analysis (Polit & Beck, 2012). Since people’s perspectives are the receptacle of inquiry, numerical data, questionnaires, and other inventories are generally unnecessary. The researcher often works with the subjects in the field to learn about the interested phenomena. The results can often reflect the researchers’ original bias or the subjects’ worldview. It may be difficult to determine exact mechanisms of underlying principles since the researcher is striving to find out the how or why phenomena occur in the absence of scientific experimentation (Polit & Beck, 2012). It is generally observational in nature and as a result is challenged when determining causal factors.
Quantitative research seeks to understand variables and causal pathways with quantifiable data and controls (Answers Research, 2011). What QnR often fails to do is see the 30,000-foot picture since it is focusing on specific variables. Since the bigger picture is usually missed, additional or alternative causal factorsn, and confounding variables are overlooked. Even though this type of inquiry's lens is limited, some of the things touted as strengths are statistical power and large amounts of data. This can be expensive and complicated. As a result, financial interests can creep into bias, reported, data, and outcomes (Freedman, 2011). QnR also tends to be shorter in duration not allowing for deeper, long-term statistical intervention analysis. In addition, misuse of data, simple errors, and research bias can reduce the validity and accuracy of the underlying hypothesis (Freedman, 2011).
References
Answers Research, (2011). Articles: Quantitative vs. qualitative. Retrieved February 6, 2012 from www.answersresearch.com/article9.php
Freedman, D. (2011). Lies, Lies, Damned Lies, and Medical Science. The Atlantic Monthly. Retrieved February 6, 2012 from www.theatlantic.com/magazine/ archive/2010/11/lies-damned-lies-and-medical-science/8269
Polit, D. and Beck, C. (2012). Nursing research: Generating and assessing evidence for nursing practice [9th ed.]. Philadelphia, PA: Lippincott Williams & Wilkins.
Writing@CSU, (2012). The qualitative vs. quantitative research debate. Colorado State University. Retrieved February 6, 2012 from http//:writing.colostate.edu/guides/research/ gentrans/pop2f.cfm
The first step towards conducting qualitative analysis of your data is to gather all of the comments and feedback you want to analyse.
ReplyDeleteQualitative Analysis