difficulties with qualitative data analysis and interpretation

Respond to the discussion question below and provide responses to the two responses below:

Initial Question that requires a response:

• Discuss one or two difficult issues raised in the readings with regard to data analysis and interpretation in qualitative research, as it relates to the selected research question of the course project.
• Do any of those issues present difficulties severe enough to discourage the use of a qualitative approach as part of the study?
• Explain and defend your responses.

Response One:

Regardless of the circumstance, the problem of verifying some qualitative analyses is without trouble solved; in many cases, it is not. “Confirmation is probable to be impossible in the qualitative research,” but they also describe how an “audit trail” might be collected to capture the systematic steps in qualitative research. The problem here, in our view, is the merging of qualitative data and qualitative analysis into one phrase, “qualitative research steps (Wutich, & Bernard, 2016).” Utmost of the apprehensions that Tsai and equals raise involves the credentials of analyses comprise many inductive implications—inferences that can, indeed, be problematic to file. There are, nevertheless, numerous well-developed writings on detailing these inference steps (Wutich, & Bernard, 2016).

Other issues to consider in data analysis and qualitative research: the field of values and ethics. Concerning Data Analysis, it includes three aspects: a) the place and role of the researcher’s values in research; b) the role of research subjects; and c) the appropriate way(s) to use research products. These issues above need to be thought about, especially when dealing with a researched question within a project (Baptiste, 2001).

The different issues presented are not enough to discourage the use of qualitative approaches. It is conceivable to move nearer to an ordinary establishment of expectations for broadcasting qualitative analysis and, grounded on information, for replicating key thematic findings. When joined, information procedures ought to be clear about what types of reports the researcher’s trust can complete: authentication of a specific study or paths to minor studies(Wutich, & Bernard 2016). I have confidence in that for each analyst, values, beliefs, and interests are justly steady over time and space. They regulate what the particular analyst deliberates looked-for, and they form the outer confines of what the actual analyst ponders conceivable.

References

Baptiste, I. (2001). Qualitative data analysis (QDA): Common phases, strategic differences.* Forum: Qualitative Social Research, 2(3). Retrieved May 2012 from http://www.qualitative-research.net/index.php/fqs/article/view/917/2003

Wutich, A., & Bernard, H. R. (2016). Sharing qualitative data & analysis. With whom and how widely?: A response to ‘Promises and pitfalls of data sharing in qualitative research.’ Social Science & Medicine, 169, 199-200. DOI:10.1016/j.socscimed.2016.09.041

Response Two:

When conducted properly, a mixed methods research study can provide a rich explanation of the topic being studied. There are some challenges of which researchers should be aware when conducting qualitative research. These challenges include limited sample size, sampling bias, self-selection bias. Observation bias, the Hawthorne effect, observer-expectancy effect, and artificial scenario (Koks, 2015). Ranjbar, Khankeh, Khorasani-Zavareh, Zargham-Boroujeni, and Johansson (2015) state that two initial challenges a new researcher faces in qualitative research are research problem identification and research question formulation. Another challenge is choosing the correct methodology for the study (Ranjbar, Khankeh, Khorasani-Zavareh, Zargham-Boroujeni, & Johansson, 2015). If a research team is not organized and knowledgeable it can cause the study to be hindered in advancing understanding of the phenomenon being studied, resulting in poor interpretation and a lack of information to add to existing literature (Ranjbar, Khankeh, Khorasani-Zavareh, Zargham-Boroujeni, & Johansson, 2015).

There are common pitfalls to avoid in qualitative data analysis such as reducing data to numbers, generalizing, and not addressing limitations (Bhattacharjee, 2014). Reducing the qualitative data to numerical form defeats the ability to find out what information the data is presenting (Bhattacharjee, 2014). Generalizing the participants responses detracts from the meaning and uniqueness of the given answers (Bhattacharjee, 2014). It is important to present the limitations faced during data collection and analyzation to provide clarity of the inferences made (Bhattacharjee, 2014). Another common mistake is that new researchers often forget to look for confounding variables that may explain the results, which can create errors (Bhattacharjee, 2014).

These issues make looking at a qualitative research project seem daunting. Fortunately, if the researcher is patient and clearly defines what they are looking to study, the results can be extremely rewarding. The difficulties and issues that come up in qualitative research are not severe enough to discourage me from attempting a qualitative study. My rational is that careful planning and well-defined objectives should help to steer clear of the pitfalls. Also, facing challenges and adversity will help strengthen my abilities as a researcher.

References

Bhattacharjee, A. (2014, May 8). Qualitative Data Analysis – What is it About? Retrieved from https://blog.udemy.com/qualitative-data-analysis/

Koks, P. (2015, July 14). Six Challenges of Qualitative Data Analysis. Retrieved from https://online-metrics.com/qualitative-data/

Ranjbar, M., Khankeh, H., Khorasani-Zavareh, D., Zargham-Boroujeni, A., & Johansson, E. (2015). Challenges in conducting qualitative research in health: A conceptual paper. Iranian Journal of Nursing and Midwifery Research, 20(6), 635-641. doi:10.4103/1735-9066.170010

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