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How Reflexivity in the Role of Researcher Affects the Research Process in Qualitative Research


As qualitative researchers, exploring one’s placement relative to an event and individual encounter is expected. By taking one’s identity, such as sexual orientation, religious affiliations, social stratifications, and culture, into consideration, it is easy to understand how these things influence the development of the research process and research outcome. This can be studied by reflexivity, as Ahern (1999) pointed out. Thus, reflexivity helps the researcher determine where they stand and how they create knowledge. Reflexivity differs from reflection in that it involves observation of human relationships with other people. In a qualitative research study, researchers are always in a place. This means that researchers explain in method sections, introductions, or other parts of a study their background (including work experience, cultural experience, and history), the way it relates to how they interpret research data, and the benefits they derive from it as opined by Cutcliffe (2003). Thus, the researcher’s reflexivity should be pursued early enough during the research process. By undertaking reflexivity across the research process, one can comprehend meaning within power structures and guarantee the trustworthiness of a study (Dingwall, 1997). The impetus of this research is to help understand how reflexivity in the mandate of the researcher implies the research process in qualitative research.

Looking for individuals’ meanings concerning their lives is a critical component of qualitative research, especially aspects such as phenomenology. How that meaning is understood depends on a researcher’s experiences, and to others, it matters. However, the globe is shaped by aspects such as sexual orientation, religious doctrines, and social stratification. One reason to become reflexive is to avoid reinforcing oppressive structures through the process of doing the research and the relationship with the sample pollution under study, as mentioned by Finlay (2002). Another reason to practice reflexivity is trustworthiness. The meaning of trustworthiness in qualitative research is how it relates to its intended aim. More importantly, this is the case for qualitative research because the person doing the study is a research instrument (Ahern, 1999). In addition, unlike most quantitative analyses, the results of qualitative research are not easily duplicated. As a result, the principles of credibility, transferability, and dependability are adopted to form the basis of trust in qualitative research. Credibility concerns how close the findings are to reality (Goldstein, 2017; Berger, 2015; Cutcliffe, 2003). Generalizability is about transferability, on the other hand.

Furthermore, reproducibility in qualitative research does not mean repeatability but consistency with participant data. Someone can attain these elements of trustworthiness in different ways. Taking a reflexive stance would increase the study’s credibility.

Qualitative researchers tend to make notes, often in the form of comments, on participants ‘comments during interviews and may summarize later in memos written immediately or soon after participating. Qualitative researchers also report on the subjective perspective of the researcher (Berger, 2015). The processes above are not extraneous to analyzing the data collected but are a natural extension. New people getting into research can begin to familiarize themselves with the process of reflexivity. For those new to qualitative research, some schools creatively conduct reflexivity. Art and creative methods can be employed to reflect upon oneself (Eriksen & Holtan, 2023).

Moreover, transcribing an interview gives one pause to consider (Lynch, 2000; Berger, 2015). Qualitative researchers possess other mechanisms for collecting data. However, how one does reflexivity will rely on the kinds of interrelatedness people are looking for, the nature of the research, and the scale of self-awareness of the researcher (Råheim et al., 2016; Berger, 2015). Finally, the fundamental issue is thus that as a researcher reflects on the data, interviews with participants, documents, and so on, which he or she admits to doing, few of us have time to pass the time of day without the purpose of doing so being transparent, so that he or she brings together the material together which was gathered in response to the research question.

Collection and Assessment of Qualitative Data

There is a value and a framework for ordering values that come with quantitative facts by definition. When we look up how many people live in New York and how many live in Tokyo, we probably picture the towns with their population counts in them. The elements in the periodic table are arranged by their atomic weight, and the “quality” of movies is shown by how well they do at the box office and how many reviews they get (Ahern, 1999; Berger, 2015; Cutcliffe, 2003). Additionally, quantitative data is more straightforward to gather and study because it uses numbers to tell us which towns are growing the fastest or whether one movie is “better” than another. Numbers are easy to understand. Even though quantitative methods are getting more complicated, the basic idea that numbers can give us a sense of measurement means that qualitative research can produce simple data access.

On the other hand, it can be harder to measure and manage qualitative statistics, as Braun and Clarke (2022) noted. Remember, movie reviews’ scores and movie theater income can give you a nanea of which movies people think are better or more popular than others. People who use this sense think bad movies get bad reviews and do not get enough people to go to the movies (Eriksen & Holtan, 2023). However, neither of these measures gets to the heart of what a truly great movie is, if that is even possible.

Managing qualitative data means putting all the data you gather in a qualitative study into the correct categories to be easily analyzed and put into order. Qualitative data management is to make valuable data parts for practical insights easy to understand and find so that you can analyze the data and show it to your research audience. The beginning of qualitative data handling could be better (Berger, 2015). You can put all of your study data into a single folder that stands for your project. For example, each interview record, field note set, and memo should have its file. It may seem obvious, but this part will give you some tips on handling qualitative data that will be very useful in the later stages of organizing your data before you analyze it. You can speed up finding themes and ideas that can help your research question by giving the data you collect from your study a solid framework.

Code System to Safe Guard Information

Making a system of “codes” or “labels” to give to parts of the data is an integral part of handling qualitative data. A theme, thought, idea, or phrase in the data can be used to make these codes. The marking method helps organize things more deeply so experts can put their data into groups and categories for a deeper look. Researchers have different ways to develop a coding system (Berger, 2015; Cutcliffe, 2003). For example, they can make a priori codes based on books or current ideas or in vivo codes that come straight from the data. Researchers can also use different coding methods, like open coding, theme coding, or discourse-based coding, based on their study question and method.

Data Management Plan

Researchers can get a lot out of making a detailed plan for handling their data files before they even start collecting data. For example, the plan should say how data will be gathered, how it will be kept private, how it will be organized during the research (for example, by how it was gathered or by type of data), how it will be stored and backed up to avoid loss, and how it will be thrown away if needed after the project is over (Eriksen & Holtan, 2023). This plan is like a road map for the research process. It helps researchers keep their data handling uniform and effective. If you want to understand why you need to handle qualitative data, you can think about the fact that the data you just collected is “raw data.” When you use qualitative methods, you usually end up with raw data that cannot be studied in a way that leads to solid study results (Cutcliffe, 2003). In the quest to make the text of an audio recording of a focus group easier to read and understand, the recording must first be turned into a copy.

Data reduction is crucial in qualitative research because it makes the raw qualitative data a more accessible and more focused form used. It is mostly about making vast amounts of data more accessible to understand without changing what the data is about. The process of reducing data starts as soon as it is collected. As the researcher digs deeper into the data, they find and highlight important information, pull out valuable parts, and eliminate data that might not help them reach their research goals. This process changes throughout the study project, from the beginning stages of collecting data to the end stages of analyzing that data. Some common ways to reduce the amount of data that needs to be stored are to paraphrase long stories, summarize long texts, or outline the main ideas (Walsh, 2003). As this process goes on, the data is also sorted and categorized into themes, topics, or trends that start to show up. It comes down to sorting and reducing the data into critical parts that show what the whole information is like, as Berger opines (2015). However, academics must be careful when reducing the data to ensure they do not oversimplify or distort it. Even though the information needs to be shrunk, it is necessary to keep the complexity and depth of the qualitative data. Because of this, researchers should go back to their original data often to ensure that the shortened data still has the same meaning and context as the original data. At the end of the data reduction process, there is a selected collection that is not only smaller but also organized in a way that makes it easier to do more research (Cutcliffe, 2003). After careful consideration, this information is used to draw valuable findings, insights, and suggestions from the qualitative research study.

Coding Qualitative data

Coding is one of the most critical steps in getting qualitative data ready for analysis. Coding is putting pieces of data into groups and giving them names that explain what they mean. Not only does this make the data more minor, but it also gives it meaning, turning raw data into units that can be analyzed. Even though there are different ways to code, open coding is often the first step for qualitative researchers. This is when the researcher goes through the data and gives codes based on what each section is about. These codes could be a word or a statement that says exactly what the piece of data is about (Mruck & Breuer, 2003; Pillow W, 2003; Råheim et al., 2016). At this point, the researcher generally lets the data decide the codes instead of forcing them to fit into pre-existing groups. In this way, the data’s validity and complexity are protected. As the coding goes on, similar numbers may be grouped into themes or groups. This helps to organize the data even more and makes it possible for connections to be made between different codes and themes. Researchers might find it helpful to make a codebook, which lists all the codes and what they mean while writing. This ensures that the writing is consistent, essential when more than one person is working on the study project. Remember that coding is a repetitive process, meaning you will probably need to go through the data and change the codes more than once (Berger, 2015; Cutcliffe, 2003; Walsh, 2003). As the researcher learns more about the data, they may understand it better, which could mean that the code system needs to be changed or improved. After writing, you might have a list of themes, groups, and subgroups that you can use to look further and figure out what they mean. Coding is the most crucial step between gathering data and analyzing it in a helpful way in qualitative research.

Advantages of Being Reflective

Reflectivity gives a person values, wealth, clarity, and personal development. These are good for fostering the integrity of the research process, the way the sample population under study is being treated, and the general wellness and development of the researcher. Researchers point out that reflexivity was necessary for clarity because it made positionality, emotion, and reaction more apparent (Tufford & Newman, 2012). These two things, being aware of your position about the research and having in mind the idea that there is no neutrality, although the majority of the individuals may assert that they can maintain neutrality in their research, kept people honest and stopped them from making false claims of being pure or objective. It helps researchers note what their voice is since, while it is crucial, they need to see beyond it (Cutcliffe, 2003; Finlay, 2002). Memos and records can help researchers remember what happened in the early stages of a project and keep them from forgetting or changing what happened (Walsh, 2003). They also helped them remember to keep an open mind.

For philosophical clarity, reflexivity was viewed as very significant. It was important for the researchers to understand why they ought to conceptualize and the kind of questions that they are required to ask during the interview process. It is attributed to the fact that the researcher is drawing a case from the version of knowledge of a person. Without cyclical self-inquiry, ideas disguised as professional knowledge could seep into one’s work, making it less accurate or valuable (Finlay, 2002; Goldstein, 2017). The advantages of reflexivity for ethics were closely linked. Ethics meant the investigator had to be honest about his or her goals, dreams, and possible personal gain. It also meant being open about the often-hidden power relationships between the investigator and the research being done. In this case, reflexivity is a way to build trust, fairness, honesty, and regard for the sample population (Cutcliffe, 2003). It was also seen as an approach to protect against dishonesty and unfairness when an imbalance occurs because power is not recognized. An individual cannot just judge other people’s lives without judging their own since reflexivity tests the relationship between knowledge and power.

Being conscious of oneself was also seen as helpful for the scholar. It gave a structure for thinking about, continuing, refreshing, and learning more about the study and an individual. As a way to handle the research experience, it could be used to deal with and get rid of challenging, surprising, or upsetting issues, keeping you from getting mentally worn out. Some people participating in the research thought that reflexivity could help normalize their feelings, contextualize them, and create the right amount of distance. Others thought it could also assist in shocking them and foster their efforts to move out of their comfort zone and see things from a different point of view (Lynch, 2000; Tufford & Newman, 2012; Walsh, 2003). People thought that focusing on the data and reacting to the content of the information was an excellent way to keep from getting too involved or too identified with it. Participants agreed that only a qualitative researcher who is not self-aware can be a good researcher.

Challenges to Reflexivity

Personal difficulty for the person doing the research is based on their psychological reaction to the sample population being researched. It is essential to mention that reflexivity can trigger many emotions and unpleasant feelings in people, which can easily negatively affect new researchers. Most researchers using reflexivity for the first time encounter many emotional challenges, and they may judge themselves. However, they must learn how to embrace such new feelings and mistakes that they make while doing the research. Finding the balance between being open and too busy might be problematic and challenging. “Asking others for feedback opens up more than I thought it would.” It can be excruciating to be open to comments you did not expect or are critical of (Cutcliffe, 2003; Ahern, 1999; Berger, 2015). Many people who answered said they used extra help, like mindfulness, meditation, therapy, creative writing, or “venting” with friends. However, they did not all agree on whether they thought reflexivity made the feeling of being swamped and filled worse or better. Some people thought this would happen anyway and that being self-aware helped them deal with their feelings, making them less painful (Mauther & Doucet, 2003; Walsh, 2003). Others thought concentrating on sensitive points of the researcher’s life made them more vulnerable and scared.

The most common problem with reflexivity when doing research is needing more time. Ostensibly, being reflective consumes much time and demands discipline, particularly after long hours and days of carrying out fieldwork. It is only sometimes possible due to the need to move quickly or take care of other obligations. A researcher has to deal with time first. The second issue for a researcher would be the need for more patience to let it happen (Cutcliffe, 2003). Being reactive and taking the time to execute it right can be a complex process. Reflexivity is self-indulgence in public reports but not when used in the study process, which might or might not end up in the written report. Again, researchers have different thoughts. Some believed that the more carefully someone practiced reflexivity, the less likely they would engage in incorrect “navel gazing” and egocentric distortion.


Reflection is a valuable skill for researchers because it helps them stay critically aware of themselves while doing their work. At the same time that it looks outward at what is happening, it also looks inward at the person who is looking. More than just a way to be honest or keep track of the research process, reflexivity is a way to use what you know about yourself to help and improve the study. Because of this, it can be used for a wide range of social work study methods. In other words, it works well for mixed-methods, qualitative, and quantitative tasks. However, judging how reflexive a study is still proving to be complicated. As was already said, just because an author’s reflexivity is not directly mentioned does not mean it was not there. So, what should I look for? Setting standards that can be used for many designs runs the risk of making something naturally unique into an object. However, writers and readers need rules to help them figure out if reflexivity is present.


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