What Is Qualitative Data?
A well-researched article can generate a powerful impact when numbers represent an important fact. For instance, you would feel shocked to find out exactly how much more likely you are to develop mental health issues if you scroll on your phone for more than 3 hours a day. The numbers don’t lie, right?
However, it can be hard to contextualize quantitative facts. That’s where qualitative data can come in, to provide a more human context to help readers make sense of those digits. In psychology studies, qualitative data is used to understand the experiences, perceptions, thoughts, and feelings of study participants. It aims to understand and explain the why and how of a research question, as opposed to the how much or how many.1
Real-Life Examples of Qualitative Data
Collecting qualitative data can involve a psychology researcher interviewing subjects with a mental health diagnosis to understand the subjective experience of their symptoms.2
Having a focus group discussion with consumers for market research is another example of how qualitative data is used. A facilitator would ask a focus group open-ended questions about their attitudes, perceptions, and opinions about a company’s product or service.
A human resources department conducting personal interviews with employees to understand job satisfaction and workplace culture is also an example of qualitative data.
The 3 Types of Qualitative Data
There are 3 types of qualitative data:3
- Binary: Binary data is what computers use to read. Information is coded as ones and zeros. Qualitative data examples include evaluating a statement as ‘true or false’ or responding to a question that only has a ‘yes or no’ answer.
- Ordinal: Ordinal data is information that is categorized based on a range or order. For instance, a question that asks you to rank how much you agree with a statement from ‘strongly agree’, ‘agree’, ‘disagree’ to ‘strongly disagree’.
- Nominal: Nominal data is when information is named or labeled under two or more categories. The categories do not have an order to them. For instance, gender, marital status and ethnicity are considered nominal data.
Methods of Collecting Qualitative Data
There are several important steps to consider before collecting qualitative data. Dr. Stephanie J. Wong, Ph.D., a Licensed Clinical Psychologist and author of Cancel the Filter: Realities of a Psychologist, Podcaster, and Working Mother of Color shared that research proposals need to be submitted to an Institutional Review Board (IRB).
An external organization must evaluate the proposal for potential risks and benefits to participants, and ways you will collect, protect, analyze, and share the data. This applies to both quantitative and qualitative studies. Once your study is approved, there are several ways qualitative data can be collected.1
- Interviews: Interviews are one of the most common ways to collect qualitative data. Personal interviews use a one-on-one approach between an interviewer and a subject to gather how they think and feel about a topic or concept. This can be structured where the interviewer asks predetermined questions. Interviews can also be unstructured and conversational where the interviewer uses open-ended questions but adapts depending on the subject’s responses. The interviews can be recorded and transcribed for qualitative analysis.
- Observations: This qualitative data collection method involves observing participants and gathering information about their behaviors, actions and reactions. Observational data could also be captured via photos, video and audio recordings.
- Document Analysis: Qualitative data can also be collected from old records. Sources can be formal like medical files, financial statements, or incident reports. However, less formal sources that can be analyzed include emails, journal entries, social media posts or comments, and content in online forums.
Analysis Techniques for Qualitative Data
Dr. Wong explained that qualitative data can be analyzed in various ways, including identifying trends, creating categories of themes, and informing quantitative analysis or studies. Here are some analysis techniques for qualitative data:4
- Coding: Coding qualitative data involves categorizing and labeling pieces of information. A system is used to organize the information so that themes, patterns, or concepts can be identified.
- Thematic Analysis: When the data is coded, they are grouped under overarching themes. A theme is a pattern that is seen in the qualitative data. Thematic analysis helps to reveal the research participant’s insights and experiences.
- Content Analysis: Content analysis is used when there is a large dataset that includes text, visual, and/or audio information. It uses a systematic approach to categorize the characteristics of the content. It then measures the frequency of these categories to identify themes and trends.
Qualitative vs. Quantitative Data
It’s easy to remember the difference between qualitative and quantitative data. Qualitative data qualifies and quantitative data quantifies what is being investigated.5
Qualitative data is descriptive and does not use numbers. Quantitative data is measurable and uses numbers.
Qualitative data is used to understand subjective experiences and perceptions by identifying themes and patterns. Quantitative data is used to determine significant associations based on statistical analysis. Both types of data can be valuable in answering research questions.
“There may be a perception that quantitative research is more scientifically accurate than qualitative research, although both provide value,” explains Dr. Wong.
The Advantages and Potential Drawbacks of Qualitative Data
There are advantages and disadvantages to using qualitative data for your study. Dr. Wong shares that qualitative research is particularly helpful in exploring a topic with a limited amount of research, such as outcomes among specific populations.
“[Qualitative data] can provide rich data that may not be captured by quantitative research and can inform future quantitative studies,” adds Dr. Wong.
However, a drawback is that qualitative research is typically conducted with small sample sizes, which limits the ability to generalize the data to larger groups of people.
Additionally, there is potential for bias since the analysis can be influenced by the researcher’s subjective interpretation.
Lastly, collecting qualitative data typically requires in-depth interviews which can be time-consuming.
Quantitative research is more efficient as it can typically accommodate larger sample sizes and software can be utilized to track and analyze the data.
Therefore, qualitative data is used to understand the nuances of a situation and explore the meaning behind experiences and findings. When deciding on a method of data collection for your study, it’s important to choose one that aligns with your research question and to take into consideration your time, budget, expertise, and available resources. If possible, using both qualitative and quantitative methods can give you a more comprehensive understanding of what you’re researching.