developing an understanding for some different qualitative methods
This week we focused on developing an understanding for some different qualitative methods. What are two or three assumptions that are made specific to qualitative research? Be specific in your description of each one.
Please answer one of the two prompts noted below. Your posts this week should demonstrate critical reflection upon the assigned readings.
1. This week we focused on developing an understanding for some different qualitative methods. What are two or three assumptions that are made specific to qualitative research? Be specific in your description of each one. When considering some of the various qualitative methods that are out there, what challenges might they pose to a study’s validity, reliability, and generalizability?
2. A tremendous amount of research is conducted each year through secondary analysis. What is secondary analysis and what are the advantages and disadvantages of using secondary data? Give an example of a study that was done using secondary data analysis and summarize the findings briefly. Be sure the study is peer-reviewed.
Finally, what are some additional questions that you have about the different qualitative methods that are out there? Use this as an opportunity to gain some clarity on the research methods discussed this week.
Good evening Dr. Wohlers and class,
I have selected to answer the second question regarding secondary analysis and its advantages and disadvantages. I will also include an example of a study and its findings.
Secondary analysis according to Heaton (2008) “involves the re-use of pre-existing qualitative data derived from previous research studies” (p. 34). Over the last thirty years this method of qualitative data analysis has been garnered much attention in the social sciences. Heaton (2008) also classifies secondary analysis into three modes: formal data sharing (information placed into public or private databases), informal data sharing (physically passing off data to another or pooling of data amongst individuals), and self-collected data (an individual using data they personally collected in another study). A recurring theme in the purpose of secondary analysis is its use to examine existing data to solve a different question than it was originally intended for, (Glaser, 1963, as cited in Smith, 2008).
Smith (2008) posits that secondary analysis enables researchers to view vast amounts of information that one could not replicate on their own, and also allows others to view questions that the original researchers had not considered.
Much information (especially concerning government-amassed data) is considered to be potentially full of error by means of bias and poor quality (Smith, 2008). It will be important for the researcher to consider bias. It is always vital to ensure you are using valid information, as the body of literature grows one would think that more faulty information would inevitably be present.
An example study described by Smith (2008) took place in South Wales in 2004. Researchers took existing data from the National Assembly Government for Wales’ in effort to explain inequality and “patterns of social, economic, and educational disadvantage” (p. 111) in South Wales. By utilizing this already existing information, they were able to determine the most and least deprived areas. This kind of study could be used anywhere to make policy recommendations without using a substantial amount of time and resources for new studies.
A question I have following this week’s lessons and reading is the difference between content analysis and secondary analysis. They seem very similar to me. Thank you,
Heaton, J. (2008). Secondary analysis of qualitative data: an overview. Historical Social Research, 33(3), 33-45. https://doi.org/10.12759/hsr.33.2008.3.33-45
Smith, E. (2008). Using Secondary Data in Educational and Social Research. Open University Press. https://web-s-ebscohost-com.ezproxy2.apus.edu/ehost/ebookviewer/ebook/bmxlYmtfXzI2NTg2NF9fQU41?sid=e16398a9-b988-4436-8c77-72e2eab4c3a0@redis&vid=3&format=EB&rid=1
In the following discussion post, I will answer the second question. I look forward to your comments, questions and feedback!
In short, secondary analysis “involves the utilisation of existing data, collected for the purposes of a prior study, in order to pursue a research interest which is distinct from that of the original work” (Heaton 1998). In other words, information collected by researchers in one or more earlier studies is reused, but this time to answer another research question. This research question could be completely novel, but it could also be similar to the original research question, but from a new perspective (Hinds, Vogel and Clarke-Steffen 1997). Even though “secondary analysis is often undervalued or perceived to be the preserve of only those interested in the re-use of large-scale survey data,” it is also applicable to smaller-scale qualitative research (Hinds, Vogel and Clarke-Steffen 1997). Note that it is different from archival research, since “archival research involves investigators carrying out primaryresearch that is unobtrusive in nature” (AMU, 2022).
There are a number of advantages to secondary analysis. First of all, “the collection of primary data can be an expensive, time-consuming, and even wasteful approach to social enquiry” (Hinds, Vogel and Clarke-Steffen 1997). When looking at the methods for primary qualitative research presented in the coursework, both interviewing and focus groups can indeed require a lot of time and/or money. Recruiting candidates, explaining the study and the consent procedure to them, and then treating the actual topic while also providing the facilities for the process to take place can quickly become time-intensive. Therefore, not making use of already existing data that can answer your research question and instead going through this process again is a waste of effort. In addition, secondary allows researchers to combine the data gathered by different studies. Since the secondary study could entail a topic completely unrelated to the initial studies’ topics, this allows for the combination of data from virtually any field of study, which can positively affect the distribution of the sample under study and therefore the generalizability of the study. An example of this could be a study in which interview results are analyzed to find a relationship between age and average sentence length. In selecting data, the researcher could then make sure to rule out any other possible factors that might affect sentence length, to isolate the factor of age.
However, secondary research also comes with some drawbacks. Qualitative data is always collected within a specific context, set by the environment, the topic and the researcher. When revisiting data and especially when using it to answer a question that it was not originally collected for, researchers “risk being ‘naively realist’ if they treat data as foundational, neutral and ‘cleansed’ of [context]” (Tarrant 2017, 602). Ethics and availability can also cause problems (Heaton 1998). Is the secondary researcher the one who also conducted the initial research? If so, were participants aware of the possibility that their data would be reused for other purposes, and if so, did they consent to this? If another researcher conducted the initial research, how can the collected data safely be transferred? How can sensitive data be treated without infringing on the participants’ privacy? These are all important questions that will have to be answered before engaging in secondary research.
In summary, secondary research is very promising as it can lead to new insights based on data that is already collected, leading to a highly efficient form of research. There are some obstacles and drawbacks that secondary researchers have to take into account, but these should not prevent secondary research from being conducted altogether.
An example of a study that was conducted through secondary research is Digital Leadership in the Economies of the G20 Countries: A Secondary Research (Cahyadi and Magda 2021). The study used data previously collected by Cisco, Cornell University and the World Economic Forum to “investigate the digital leadership capabilities of the G20 countries in terms of digital readiness, innovation, and competitiveness 4.0 and to determine the relationship between these variables” (Cahyadi and Magda 2021, 1). In short, the study found that G20 countries were leaders in global digitalization, albeit because of different components of digital leadership.
Thank you for reading!
AMU. 2022. “Types of Research: Archival.” Accessed May 30, 2022. https://myclassroom.apus.edu/d2l/le/enhancedSequenceViewer/58433?url=https%3A%2F%2Ff54cbe36-23a9-4505-85fe-e251f80ec34d.sequences.api.brightspace.com%2F58433%2Factivity%2F6901422%3FfilterOnDatesAndDepth%3D1
Cahyadi, Afriyadi, and Róbert Magda. 2021. “Digital Leadership in the Economies of the G20 Countries: A Secondary Research.” Economies9, no. 1: 32.
Heaton, Janet. 1998. “Secondary analysis of qualitative data.” Social Research Update 22.
Hinds, Pamela S., Ralph J. Vogel, and Laura Clarke-Steffen. 1997. “The Possibilities and Pitfalls of Doing a Secondary Analysis of a Qualitative Data Set.” Qualitative Health Research 7, no. 3: 408-424.
Tarrant, Anna. 2017. “Getting out of the swamp? Methodological reflections on using qualitative secondary analysis to develop research design.” International Journal of Social Research Methodology 20, no. 6: 599-611.
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