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The use of qualitative over quantitative data research methods usually depends on the type and scope of the research project. There are also hybrid models that utilize both types of data. In this article, we’ll focus on when, why and how to use qualitative research methodology, and how to ensure that your qualitative research is, well…high quality.
Why Qualitative Research?
Quantitative research deals with numbers, graphs and charts. It’s most often used to test out or confirm hypotheses, assumptions and theories. At its core, this type of research is used to establish facts about a subject or topic. Facts that can be further proved or solidified with additional quantitative research, such as through experiments, close-ended survey questions, and observations that are countable or numbered.
Qualitative research, on the other hand, is expressed in words over numbers. We use qualitative research to understand experiences, thoughts, or concepts. With quality qualitative research, we can collect in-depth knowledge on topics and issues that are often not very well understood. These insights can be collected using instruments like open-ended survey questions, observations of behavior that are described with words over numbers, and reviews of literature that have explored similar theories and ideas.
Analyzing Qualitative Research
A quality research project is always dependent on quality analysis, be it a quantitative or qualitative study. There are several approaches to analyzing qualitative data, including discourse, thematic and textual analyses. Let’s take a brief look at each:
Discourse analysis:
This is a technique used to study spoken and/or written language, specifically in relation to social context. The goal is to understand how certain language use is utilized in real-world situations.
Thematic analysis:
This type of qualitative data analysis is when a set of text, like open-ended survey questions, or interview transcripts, are examined to determine common themes or overarching ideas and patterns.
Textual analysis:
This is a broader term for research methods that are used to describe and interpret, in order to understand, various texts. This can include literal, subtext, assumptions and symbolism, as well as values that the text is revealing to the researcher.
Methods to Enhance Data Quality in Qualitative Research
As in all forms of research, the quality of the research, including analysis of any data collected, is optimized when things are planned out before the research even begins. With a comprehensive research design and plan, the outcomes and quality of the research is all but guaranteed.
When planning your qualitative research study, keep in mind the following stages and steps:
First, ensure that any qualitative data collected is reliable and clearly organized. Once you’ve collected your data, prepare and organize it for analysis.
As you review and analyze your data, you’ll utilize the data coding tools that you develop during the research design phase. Of course, as you explore the data, you may need to revise or fine-tune data coding systems, but that’s to be expected.
As you explore the data, you’ll assign the different codes to what you find, whether you’re using discourse, thematic or textual analysis techniques. The data analysis codes will help you identify clear themes and patterns.
Data Quality Control in Qualitative Research
Quality control in all types of research, as we’ve mentioned, begins prior to the research even beginning, including the quality of the researcher and research team. For example, what are the credentials of the research team? Are there potential inherent biases based on the makeup of the research team and the research participants? If so, how is that being controlled for? What do participants know about the researcher, if anything? How are any assumptions, by either the researcher and his or her team, or the participants, being addressed?
When it comes to actual study design, is the best technique being utilized? How are participants selected for the study? Is it in a way that minimizes assumptions, biases, and other weak points that might be related to the research? For example, if participants were chosen out of convenience (weak), that can certainly affect the quality of the research. Additionally, choose carefully how any participants are included; different techniques garner different levels of quality of information. For instance, a face-to-face interview may feel intimidating to a participant, and they may not give as honest an answer as a telephone or email response.
The actual process of data analysis should include considerations on how, when and where data is collected and analyzed. For instance, were observation notes taken in front of participants? Were other people present in addition to researchers and participants? Is the research utilizing audio and/or visual recording to collect data? Were any follow-up interviews conducted, or did the data collection include follow-up questions? All of these aspects can improve or weaken the quality of the data and subsequent analysis, depending on how they are factored into the research conclusions.
For example, how many data coders are working with the data? What was their training, and have they been analyzed for consistency and reliability as a team? Did participants provide any feedback on the analysis of the data collected? When were themes and patterns identified? Before or after the data was collected and analyzed? When participants are quoted, is that identified within the data?
As you can see, the quality of your qualitative research can depend on, quite literally, hundreds of aspects and details. To design and undertake a high-quality qualitative research project, the study design itself should factor in as many quality markers as possible that reduce and/or eliminate points of weakness.
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