Qualitative research offers unique insights into complex phenomena that quantitative methods often miss. Krithika Sundaram in this blog discusses the importance of qualitative research and how it could be organised better.
CONTEXT
As I embarked on the journey of qualitative research to measure the complex phenomenon of food security at the household level during the COVID period, I initially anticipated a domain primarily defined by narratives gathered through focus group discussions and in-depth interviews. But as I delved into the nuances of using the tool, I discovered that the world of qualitative research encompasses far more depth and complexity.
Recently, there has been a growing demand for using qualitative analysis in research, driven either by the “necessity” for using it or by the desire to undertake “unconventional” research to publish in high-impact journals. Researchers often fixate on the procedural steps but sadly overlook their true purpose in conducting meaningful research.
Instead of focusing on defining qualitative research, the blog will use narratives to help readers understand what qualitative research is and examine what makes a good qualitative researcher, common mistakes to avoid, and the value of qualitative analysis for gaining insight into various concepts. The aim is to elucidate why and how you should use qualitative research. To make the blog concise, I have restricted it to qualitative methods such as focus groups and in-depth interviews to elaborate on the significance of the research.
THE ESSENCE OF QUALITATIVE RESEARCH
Why is qualitative research important? Because using a qualitative tool helps you understand the story or real issues behind a phenomenon. A story that otherwise would have gone unnoticed or misreported using quantitative analysis, which quantifies the phenomenon, unlike qualitative research, which explores the phenomenon. Researchers use qualitative research to understand the views of the respondents from their point of view, rather than using standardized questions or questionnaires that actually fail to understand the real hidden story of the issue.
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Issues that are actually complex or sensitive to understand often defy measurement through quantitative means and demand deeper understanding and different methods of measurement. Let us take the case of farmer suicides. When we speak about farmer suicides, quantitative research may rather list out factors such as high input costs, a lack of credit system, and middlemen as reasons, but it may fail to capture the risk and the lives of farmers that lead to the unfortunate situation. The factors (answering the question “what”) that led to the event can be measured using quantitative research, but to measure “why” and “how” that event occurred, qualitative research is indispensable. Probing the why and how of the actual causal process that led to a particular situation will make the data more insightful. So instead of focusing on the statistical correlation between the variables, the actual cause can be documented using qualitative techniques.
WHAT DOES IT TAKE TO BE A GOOD QUALITATIVE RESEARCHER?
If you ask what it takes to be a qualitative researcher, I would say that there are no hard and fast rules, but one criterion that would make a difference is being inquisitive. US-based sociologists Mario L. Small and Jessical M. Calarco, in their book “Qualitative Literacy: A Guide to Evaluating Ethnographic and Interview Research,” point out four criteria for a qualitative researcher: cognitive empathy, heterogeneity, palpability, and analytical capacity.
Cognitive empathy is the degree to which researchers understand those they interview. Being cognitively empathetic means understanding the beneficiary through their perceptions. Having a qualitative approach to understand why farmers are adopting and not adopting a particular innovation will help us understand the logic behind his decisions. However, the authors also point out that there is a line between empathy and sympathy. Sympathy more often leads to bias, but empathy helps to understand the views of others without being judgmental or politically correct. So, being empathetic while also being objective is important in qualitative research.
The second criterion, heterogeneity, depicts the degree of diversity in the group we have taken for study. This will help in understanding the experiences and motivations among individuals. For example, when you take up a study to understand the experiences of university students, getting insights from students from diverse backgrounds will give you different insights as each student will have unique experiences. Maintaining heterogeneity will help avoid out-group homogeneity bias.
The third criterion of palpability is the extent to which the reported findings are presented concretely rather than abstractly. Palpability ensures that the collected data is not generalized but has different layers to the story that are buried inside. For instance, when measuring household food security during COVID-19, I explained why farmers struggled to sell their products by detailing issues like transportation problems, trouble getting e-passes, and decreased consumer demand, instead of only stating that farmers had a tough time selling their products in the market. Such vivid accounts and illustrative transcripts will make the research more palpable and explain the emotional and physical stress the farmer had to undergo during the COVID period.
Analytical insight in qualitative research is another area that has to be given careful importance. Qualitative research is often said to have less rigor and validity, without any scientific objectivity. In qualitative research, researchers often get carried away with “too many” details. Identifying the underlying patterns and themes in the data is important to provide concrete evidence (inductive reasoning). The analysis of qualitative data does not follow a straight line of X as the cause of Y; rather, it is an interconnected and interwoven context that needs to be analysed until a verifiable interpretation is achieved. Qualitative studies of high quality justify the phenomenon through effective writing.
Building rapport
Building rapport with the respondents is a crucial step in extracting relevant data on a subject. Especially when revealing sensitive issues, the respondents should feel at home and be open about the topics to get accurate information. It is important to observe their surroundings and have an informal talk before pitching into the questions. As the researcher is an instrument, the participant-researcher relationship has a huge impact on the research outcomes.
Listen
There is a saying, “Listen to understand, not to say something back in return.” To have strong objectivity, it is important to understand the issues from the vantage point of farmers. Allowing them to talk and probe further when needed will help to get the actual insights and maximise objectivity. For instance, when you ask, “Why do you prefer natural farming to conventional farming techniques?” and then prompt the answer as “Because of high input costs?” This will only lead to bias. It is important to let the respondent talk to reveal the exact reality and maximise objectivity. Strong objectivity will help to see the story from different angles and with different perceptions.
What is objectivity in qualitative research?
Qualitative research is criticized for being less objective, as quantitative research has more standardized scales and testing procedures. The open-ended questionnaires and the analytical procedures used are said to be biased and unscientific because it is considered that they lack statistical validity and reliability, and the data is collected in alignment with the personal likes and dislikes of the researcher (Galdas P.2017). However, as more researchers are using qualitative research, the results have been yielding valuable knowledge as the data have only been co-produced with the respondents. (Zolvinski, Stephen, 2008.) One way to stay objective is through triangulation, i.e., cross-checking and comparing data from various sources such as peer debriefing, field notes, audio-visual materials, document analysis through policy briefs, official records, etc. For instance, having more than one focus group discussion instead of limiting it to one will decrease the chance of bias. You need to conduct FGDs until you reach a point of saturation, and you ought to not get any additional details.
COMMON MISTAKES TO AVOID IN QUALITATIVE RESEARCH
There might not be a hard and fast rule when it comes to using qualitative research, but using the right kind of approach would help in getting accurate results with objectivity.
Framing the questions and data collection
The common mistake qualitative researchers make is to frame generalized questions that differ from the research question. For instance, instead of framing the question as “Did you face food shortages during the COVID period?” put it as “Have you gone without food during the COVID period for any part of the day? And then probe further: “If so, what was the issue? Instead of asking how often you had food during the COVID period, ask them to narrate the events. This narrative will give clues and detailed insights about the issue.
Richard Kruger, in his book “Focus Group: A Practical Guide for Applied Research,” has explained the art of asking good questions using an interesting short story. A mother took her daughter to a psychologist to examine her before enrolling her in school. When the psychologist asked, “Are you a girl or boy?” The girl answered, “Boy.” Startled, he asked the second question: Do you want to be a girl or boy when you grow up? to which the girl replied, “Boy” again. When the mother asked the daughter the reasons for replying strangely, the daughter replied that when the questions were silly, she wanted to give silly answers. A good question should be conversational, avoiding jargon, easy and clear, and short and open-ended.
Analyzing the data using an iterative process/coding
Iterative means repeatedly revisiting the data. The whole process involves “moving back and forth between concrete data and abstract concepts, between inductive and deductive reasoning, and between description and interpretation” (Merriam, 2002).
While analysing the data and developing codes, the researchers mostly pick the exact “keywords” rather than extracting the real essence or meaning of the sentence. Another important pitfall is over coding, i.e., assigning too many, and under coding, i.e., assigning too few to a segment. Such coding issues will make it difficult to identify the main themes and patterns. It is important to have a consistent approach while coding to identify the theme or broader idea. Also, it is important not to let your bias influence coding. The data should speak for itself. Researchers unintentionally use codes that change the actual meaning of what the respondent has said. For example, if the farmer talks about the challenges of new technology, coding it as “resistance to change” is a stereotype bias. To avoid this, it is important to practice reflexivity. Reflexity includes self-awareness, role awareness (the researcher’s perceived expertise in a subject could influence coding), and transparent reporting.
Deciding on when to use focus group discussions or in-depth interviews
Focus group discussions do not always work in all situations, and qualitative researchers should know when and when not to use FGDs. A focus group works well if you need to understand the perspectives of different people. But if you want to cover sensitive topics or avoid conflicts over the topics, then in-depth interviews would work well. Either way, fixing your target audience is very important. You can go for a single-category design or a double-category design of FGD. Say, for example, that if you want to do a focus group discussion on the leadership style of panchayat sarpanch, then your FGDs should involve two or three groups of only panchayat leaders. If you want to do a contrast study with, say, farmers and extension experts, then go for a double-category design. If you want to conduct a study that involves multiple stakeholders, say in the case of a study on a pluralistic extension system where multi-stakeholders such as NGOs, public, private, and farmers will be involved, then go for a multi-category design where two FGDS in each category could be conducted. Also, ensure that the size of the focus group is small enough (a minimum of 5) so that everyone gets a chance to speak and large enough (up to 12) to provide different perspectives.
Translation and transcription issues
Transcription of the collected data is time-consuming, and the interviewer often has to make subjective decisions about what to include and what not. The focus should be on capturing the meaning rather than simply transferring what is said verbatim. For example, while transcriptioning the sentence “Um, the main issue um…during the COVID was um…job,” the intelligent verbatim could be “the main issue during the COVID was job loss.” But in certain instances, it is important to capture the details verbatim to retain the meaning of the content. Verbatim transcription is important when capturing sensitive topics, and it should be attributed in quotes so that it denotes that it is the respondent who has used the word and not the researcher. In cases where there is a need to capture specific nuances, emotions, and dialogues, verbatim transcription helps in the precise capture of data. So, careful considerations should be taken to provide accurate data. With issues related to translation, researchers can use back translation with the original to identify any discrepancies.
Ethical considerations
Qualitative researchers have the obligation to get the consent of the respondent and protect his personal information in cases of sensitive issues. It is essential to provide anonymity when needed and get proof of consent in written format for using the images or videos of the respondents. Especially in ethnography studies, we need to work with various cultural groups that are sensitive and require confidentiality to avoid external threats. Also, qualitative research requires prolonged interaction with the respondents, which involves upholding their integrity, respect, and justice. It is important to let the respondents know the nature of your study and how the results will be published and used.
THE DEBATE OVER QUALITATIVE VS. QUANTITATIVE
To precisely point this out, it is needless to debate whether qualitative or quantitative is best, as both methods can contribute considerable insights to research. Even quantitative research cannot give a valid result if the tools are not applied properly. To achieve objectivity, as mentioned earlier in the blog, it is important to have reflexivity, triangulation, and data saturation (data is collected until no new themes emerge) to improve the credibility of their work.
In a world of data and statistics, the subtle nuances of human emotions, experiences, and complexities are overshadowed. Qualitative research delves deep into the intricacies of human relationships to understand the “why” and the “how” behind what. It is about listening to the inner voices of the people and aiming to see the world through their eyes. By embracing such stories behind the numbers, qualitative research gives a whole new picture of the world around us.
References
Dr Krithika Sundaram is currently working as Manager, Social Science Research & Documentation, Shroffs Foundation Trust, Vadodara, Gujarat. She is an experienced senior-editor/reporter, with a degree in journalism and has worked in various national newspapers and magazines for more than seven years. She also holds a PhD in Extension Education from the Tamil Nadu Agricultural University. She can be reached at krithikasundaram.sft@gmail.com
The Blog very ably demystifies qualitative research between ‘Ifs” and “Buts” and not only enhances the growing importance of qualitative research but also how it could be organized better. Clear advantages/in-dispensability of qualitative research in providing unique insights (depth and complexity) on sensitive phenomena like food security situation during COVID, farmer suicides, etc. which get missed in quantitative analysis are well discussed. It is argued that factors (answering the question ‘what’) that led to the event can be measured using quantitative research, but to measure why and how that event occurred qualitative research is indispensable. It is important that she lists four criteria for a good qualitative researcher-cognitive empathy, heterogeneity, palpability, and analytical capacity besides having capability to build rapport with the respondents, listening to respondents, co-production of data with respondents, triangulation of data, etc. Also provides cautions about avoiding common mistakes to get accurate results with objectivity like framing the questions and data collection, analyzing the data using an iterative process/coding, deciding on when to use FGD or in-depth interviews, translation and transcription issues, ethical considerations etc. In other words qualitative research by embracing stories behind the numbers gives a whole new picture of the world around us. Provides very good references for further reading, understanding and use. Strong subject matter background, degree in journalism combined with long experience is an asset to explore such highly promising future lines of areas of contributions. Congratulations to Krithika and AESA for publishing the Blog.