Qualitative Data

Qualitative data refers to any non-numeric forms of data that are typically textual, audio, images, or video recordings, which can be transcribed or described. This data type includes field notes, interviews, social media content (e.g., posts, comments), archival documents, and more.

Qualitative data delves into the “why” and “how” of research questions, aiming to understand underlying motivations, behaviors, and experiences. It can complement quantitative data in mixed methods studies by providing deeper insights, context, and understanding of complex research phenomena.

Despite of its advantages, handling and analyzing qualitative data requires specialized skills, tools, and techniques to overcome the following challenges:

Volume and lack of structure: qualitative data is often unstructured, voluminous, and more time-consuming to organize and analyze.
Subjectivity: researchers may have different perspectives on the meaning and significance of qualitative data, leading to potential biases, and reliability and validity issues.
Labor-intensive and sensitivity: collecting, transcribing and analyzing large volumes of qualitative data can be time-consuming. Also, qualitative data processing and analysis typically requires multiple iterations and refinements and extra effort, including the removal of sensitive information, when applicable.

Qualitative researchers should be aware of the above limitations and plan accordingly in order to identify ways to improve the transparency and reusability of their work.

Scientific Rigor in Qualitative Research

Scientific rigor manifests differently in qualitative research. Unlike quantitative research, which produces numerical results, qualitative research yields findings. These findings consist of insights, themes, and patterns that emerge from analyzing non-numerical data. They offer a descriptive and interpretive understanding of the studied phenomenon and play a crucial role in theory-building and contextual understanding, laying the groundwork for exploring phenomena in depth and inform practical applications.

A key challenge in qualitative research is establishing the credibility of these findings, as they lack the objective metrics used in quantitative research, such as validity and reliability checks. Also, instead of aiming for generalizability to a broader population, qualitative research provides in-depth insights into specific contexts or groups, enhancing our understanding of the subject matter within those contexts.

Qualitative researchers use the concept of “trustworthiness” as a foundational scientific rigor principle, which is built on four key pillars:

Credibility: the confidence in the truthfulness of the findings.
Transferability: the extent to which the findings are applicable to other contexts.
Dependability: the consistency of the findings and their potential for replication.
Confirmability: the degree to which the findings are shaped by the respondents rather than influenced by researcher bias or personal interests.

Later in this course, we’ll cover some practical recommendations to increase the trustworthiness of your qualitative research findings.

Data Types in Qualitative Research

Qualitative data encompasses a variety of types, including written text, recordings, imagery, and cultural artifacts. Written text can be found in diaries, personal notes, letters, emails, news articles, official documents, policies, medical records, meeting minutes, and other organizational documents. Recordings consist of audio and video materials, along with their transcriptions. Imagery includes photographs and artwork, while cultural artifacts cover literature, film, music, and products or prototypes that reflect the experiences of research participants and their communities.

The sources of qualitative data can be broadly categorized into two groups: direct interaction with human participants and existing materials generated independently of a research protocol. Direct interaction may involve interviews or focus groups, while existing materials can include social media posts, community-produced content, and various organizational records. These diverse sources allow researchers to explore and analyze a wide range of topics.

Methods of collecting qualitative data involve several approaches. Direct interaction methods, such as interviews and discussions, provide firsthand insights. Content analysis of existing materials—like social media, literature, and news articles—allows researchers to examine public discourse and cultural narratives. Additionally, observing artifacts in context, such as in museums or cultural events, can reveal deeper meanings. Reviewing secondary sources, including official reports and news articles, further enriches the understanding of the phenomenon under study. Together, these methods and sources yield valuable insights into attitudes, behaviors, and cultural norms.

💭 Discussion: Can you think of any examples where an everyday artifact can be used in research to provide valuable insights about a specific group?

A collection of protest signs from a social movement could be one. These signs might initially appear to be simple expressions of demands or slogans. However, analyzing the language, imagery, and symbolism used can uncover underlying values, emotions, and the collective identity of the movement. For instance, the choice of words, the use of humor or anger, and the symbols depicted can reveal insights into the group’s attitudes towards authority, their sense of justice, and the cultural or references that have historically resonate with them. This deeper analysis helps us understand the broader social and political context of the movement.

Qualitative data can be collected through various research methods. Defining the best approach to obtain qualitative data depends on several factors, including the research question(s), the dispersion of research subjects, the nature of the data needed, and the study context. Below, are the most common methods:

Document analyses: Examination of written or recorded materials to gain insights into past events, attitudes, and experiences.
Open-ended digital surveys: Online questionnaires with open-ended questions to collect qualitative data at scale to capture participants’ opinions, experiences, and suggestions.
Focus Groups: Moderated discussions among a small group of participants representing the targeted population or the community of interest, allowing researchers to observe interactions and gather collective insights on a specific topic.
Observations: Close monitoring and recording of behaviors, interactions, and phenomena in natural physical or online settings and the context in which those are generated. Observations might be naturalistic - when researchers observe people in their natural setting without interference - or participatory - when the investigator becomes an active member of the group being observed.
Field Work: Researchers produce annotations based on their observations, reflections, and impressions during fieldwork, capturing nuances and contextual details that other methods may not capture.
Case Studies: In-depth examination of a single individual, group, or organization, using multiple data sources to explore complex phenomena within real-life contexts.
Ethnography: Immersive, long-term engagement with a particular community or culture, aiming to understand its social dynamics, rituals, and practices through participant observation and interaction. It may also be conducted online to explore communities and cultures formed and active through computer-mediated social interaction.
One-to-one Interviews: Direct conversations between the researcher and participants, allowing in-depth exploration of thoughts, experiences, and perspectives. Interviews can be structured, semi-structured, or unstructured and be conducted utilizing various means (phone, online, in-person).

This course will use qualitative research data from direct interactions between researchers and human participants through interviews. Before we delve into the specifics, it’s crucial to recognize the significance of a data management plan in guiding your research process effectively.

Recommended/Cited Sources:

Creswell, J. W., & Creswell, J. W. (2007). Qualitative inquiry & research design: choosing among five approaches (Second edition.). Sage Publications. (UCSB Library Catalog)