What is qualitative research?

Qualitative research, commonly called “interpretive research”, is a method that relies heavily on “thick” verbal descriptions of a particular social context being studied. Qualitative research is an inquiry approach in which the inquirer explores a central phenomenon (one key concept), asks participants broad, general questions, collects detailed views of participants in the form of words or images, analyzes and codes the data for description and themes, interprets the meaning of the information drawing on personal reflections and past research, and writes the final report that includes personal biases and a flexible structure.

The General Characteristics of Qualitative Research

Qualitative research has several defining characteristics:

• Real-world data sources: Qualitative researchers gather data from real-world settings, situations, and people. This could involve observations, interviews, documents, etc. directly from the source, not through surveys or remote methods.
• Descriptive data: The data collected is descriptive and comprehensive, usually in the form of words, images, audio/video, and other non-numerical formats. This allows for in-depth, nuanced insights.
• Holistic approach: Qualitative research emphasizes understanding the whole picture, including processes, relationships, and implications. The focus is not just outputs and outcomes.
• Inductive analysis: Qualitative data analysis uses an inductive approach to identify themes, patterns, and concepts that emerge from the data. Researchers do not start with hypotheses to test.
• Describes participant meanings: A key goal of qualitative research is to describe the meanings, perceptions, and perspectives of research participants. Findings are reported from their point of view.

Writing Good Qualitative Research Questions

Questions narrow the purpose of qualitative research. There are two main types of qualitative research questions:

• Central question: The central question is the most general question you could ask about the topic. It establishes the purpose and focus for the entire study. The central question needs to be open-ended, broadly focused, and highlight the central phenomenon being explored.
• Sub-questions: Sub-questions divide the central question into more specific topic areas to investigate. Limit sub-questions to a reasonable number that adequately address the central phenomenon without becoming too narrow or specific.

When writing qualitative research questions, avoid “quantitative terms” such as:

• Comparisons
• Relating variables
• Proving hypotheses
• Measuring variables
• “Relate”
• “Influence”
• “Impact”
• “Effect”
• “Cause”

The goal is to use open-ended questions focused on gathering descriptive data on the central phenomenon from the perspective of research participants.

Methods of Qualitative Research Design

Qualitative Study Design

Data Collection

Data collection involves gathering information to address the research questions. Common qualitative data collection methods include interviews, focus groups, observations, and analysis of documents or artifacts. The researcher may collect data themselves through fieldwork, or utilize existing documents and records relevant to the research topic.

Data Analysis

Qualitative data analysis involves reviewing the textual data to identify themes, patterns, concepts, insights, and understandings. Common qualitative analysis techniques include coding, categorizing, interpreting, comparing/contrasting, and drawing conclusions. Analysis is inductive and iterative, not following a fixed sequence but rather a back-and-forth process.

Data Representation

Data representation refers to how the researcher presents the data and communicates the findings. In qualitative research this often takes the form of quotes, excerpts, narratives, and descriptions that convey key themes and meanings. Visuals like matrices and models may also represent relationships between concepts.

Data Interpretation

Data interpretation involves making sense of the findings and drawing conclusions. The researcher interprets by reflecting on the analyzed data in relation to the research questions, situated within the context of existing theories and literature on the topic.

Data Validation

Validation in qualitative research establishes the accuracy and credibility of the findings. Strategies may involve member checking, triangulation, providing rich descriptions, clarifying researcher bias, and discrepant evidence analysis.

Qualitative Tradition

The researcher chooses an approach such as phenomenology, grounded theory, ethnography, narrative inquiry, or case study based on the goals and focus of the study. The tradition shapes the methods used in data collection, analysis, and interpretation.

Example of Qualitative Research Methods

• Narrative research

Narrative research focuses on studying an individual’s life story and experiences. The researcher collects data through many forms, like interviews, documents, pictures, etc. This method aims to provide insight into how people make sense of their lives and their perceived reality.

• Phenomenology

Phenomenological research aims to understand and describe the “essence” of a phenomenon from the perspective of those who have experienced it first-hand. Data is collected through in-depth interviews with participants about their lived experiences. The goal is to identify shared meanings and the core of the phenomenon.

• Ethnography

Ethnography involves studying the shared patterns of behaviors, beliefs, and language within a culture-sharing group. Data collection methods include participant observation, interviews, and artifact analysis. The researcher is immersed in the culture over an extended period.

• Grounded Theory

Grounded theory utilizes data to generate or discover a theory. The researcher analyzes data through coding, memo-writing, and diagramming. Data collection and analysis occur simultaneously, allowing theories to emerge from the data rather than preceding it.

• Case Study

Case studies investigate a contemporary phenomenon in depth and in its real-world context. Data collection involves multiple sources like interviews, documents, observation, etc. The goal is an in-depth understanding of a case or bounded system from various perspectives.

Considerations for Selecting People/Sites to Study:

There are four key considerations when selecting participants and sites to study in qualitative research:

• Relevance to the research question - The people and sites selected should directly relate to the central phenomenon being studied and help the researcher learn more about it. The sample should be purposefully selected.
• Small sample size - Qualitative studies typically rely on small sample sizes, unlike quantitative studies. The goal is an in-depth understanding, not statistical power from large samples. Sample sizes are kept small, often under 50 participants.
• Researcher access - The researcher needs to be able to gain access to the participants and sites in order to collect data. If certain populations or locations are not accessible, they may need to be excluded from the potential sample.
• Permissions obtained - Before collecting any data, the researcher must obtain the necessary permissions from the institutional review board, organizations, and individuals involved. Informed consent is essential in qualitative research.

Types of information Collected in Qualitative Research

Observations

• Recording what the researcher sees, hears, and experiences in the research setting.
• May be overt (participants know they are being observed) or covert (without the participants’ knowledge).
• Allows researchers to view participants in their natural environment.

Interviews

• In-depth conversations with research participants.
• May be structured (pre-determined questions), semi-structured (mix of set questions and open discussion), or unstructured (open-ended questions).
• Allows participants to describe detailed personal perspectives.

Documents

• Materials and records related to the topic, such as policies, minutes, correspondence, journals, media.
• Provide background context and verify findings.

Audio-Visual Materials

• Photos, videos, or audio recordings documenting the research site and participants.
• Capture detailed, nuanced data that may be missed in observations.

The Threats to Validity in Qualitative Studies

Qualitative research faces certain validity threats that the researcher must be aware of and mitigate through careful research design and data analysis. The two main threats are observer bias and observer effects.

Observer bias refers to invalid information resulting from the perspective or biases the researcher brings to the study and imposes upon it. For example, if a researcher has preconceived assumptions or expectations about the outcomes of the study, they may inadvertently guide participant responses or interpret findings to confirm their assumptions. The researcher must identify their own biases and remain open to unexpected results.

Observer effects refer to the impact of the observer’s participation on the setting or participants being studied. For instance, participants may feel inclined to give socially desirable responses or censor sharing sensitive information if they perceive the researcher’s presence as intrusive. The observer’s participation in activities can also alter the natural dynamics of the setting. Strategies like building trust with participants, blending into the research setting, and collecting data over an extended period can help reduce observer effects.

Strategies to Enhance Validity and to Reduce Bias

To enhance validity and reduce bias in qualitative research, researchers can utilize several strategies:

• Extend the time spent observing the setting to gather more in-depth data over a longer period. The longer period allows the researcher to notice inconsistencies, outliers, and evolving trends.
• Include more participants in the study to make the results more representative of the population. With a larger sample size, outliers and anomalies can be more easily identified.
• Focus on building trust with participants to access more detailed and honest data. Developing rapport helps participants feel comfortable sharing sensitive information.
• Identify personal biases, perspectives, and preferences by reflecting internally and asking for external feedback from others. Seeking out biases allows the researcher to consciously minimize their influence.
• Work with another researcher and compare independent observations and impressions. Having multiple perspectives highlights blindspots and reveals areas of potential bias.
• Offer participants a chance to review verbatims for accuracy after data collection ends. Participant validation helps ensure the data reflects their views and intended meanings.
• Journal reflections, uncertainties, and concerns during the study to examine when analyzing data. Referring to this record helps identify areas where bias could have influenced interpretations.
• Carefully examine unusual results or contradictions for potential explanations. Thoroughly analyzing outliers may reveal meaningful insights rather than mere anomalies.
• Use a variety of data sources to corroborate and confirm findings through triangulation. Comparing data from multiple collection methods highlights inconsistencies and minimizes the impact of biases.