The Guide to Thematic Analysis

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Want to know all about thematic analysis? Read this guide to get a foundational understanding of thematic analysis and its contribution to qualitative research.
Jörg Hecker
Neringa Kalpokas
Director, Training & Partnership Development
  1. What is Thematic Analysis?
  2. Advantages of Thematic Analysis
  3. Disadvantages of Thematic Analysis
  4. Thematic Analysis Examples
  5. How to Do Thematic Analysis
  6. Thematic Coding
  7. Collaborative Thematic Analysis
  8. Thematic Analysis Software
  9. Thematic Analysis in Mixed Methods Approach
  10. Abductive Thematic Analysis
  11. Deductive Thematic Analysis
  12. Inductive Thematic Analysis
  13. Reflexive Thematic Analysis
  14. Thematic Analysis in Observations
  15. Thematic Analysis in Surveys
  16. Thematic Analysis for Interviews
  17. Thematic Analysis for Focus Groups
  18. Thematic Analysis for Case Studies
  19. Thematic Analysis of Secondary Data
    1. Introduction
    2. What is secondary data in qualitative research?
    3. What are the advantages of thematic analysis of secondary data?
    4. Conducting thematic analysis on secondary qualitative data
  20. Thematic Analysis Literature Review
  21. Thematic Analysis vs. Phenomenology
  22. Thematic vs. Content Analysis
  23. Thematic Analysis vs. Grounded Theory
  24. Thematic Analysis vs. Narrative Analysis
  25. Thematic Analysis vs. Discourse Analysis
  26. Thematic Analysis vs. Framework Analysis
  27. Thematic Analysis in Social Work
  28. Thematic Analysis in Psychology
  29. Thematic Analysis in Educational Research
  30. Thematic Analysis in UX Research
  31. How to Present Thematic Analysis Results
  32. Increasing Rigor in Thematic Analysis
  33. Peer Review in Thematic Analysis

Thematic Analysis of Secondary Data

Thematic analysis is a flexible method used in qualitative research to identify, analyze, and report patterns (themes) within data. It provides a flexible and useful tool for expert and novice researchers to make sense of large datasets. This article focuses on the application of thematic analysis to secondary data. Secondary data refers to information that was collected by someone else for a different purpose but can be repurposed for a new research question. The process involves organizing and interpreting data to draw meaningful insights relevant to the research objectives. This discussion outlines what secondary data is, the benefits of applying thematic analysis to such data, and a guide to conducting the analysis effectively. It aims to offer a clear and concise overview for researchers considering this approach.

Qualitative data from secondary sources has unique advantages and disadvantages.

What is secondary data in qualitative research?

Secondary data consists of information that was originally collected for a purpose different from the current research question. Qualitative data of this type can come from a variety of sources, including academic studies, government reports, industry analyses, archives, and previously conducted surveys. It contrasts with primary data, which is data gathered directly from research participants firsthand by the researcher specifically for their research objectives.

Using a secondary data set can save researchers significant time and resources, as it leverages existing datasets, eliminating the need for data collection from scratch. However, it is crucial for researchers to assess the relevance, accuracy, and quality of secondary data to ensure it aligns with their research goals. Secondary data can serve various roles in research, such as providing background for a study, supporting or contradicting existing theories, or even as the main data source for analysis. Its versatility and accessibility make it a valuable resource in the research process, offering insights and information that might not be feasible to obtain otherwise.

What are the advantages of thematic analysis of secondary data?

Thematic analysis advantages when analyzing secondary data include a number of different considerations for qualitative researchers. First, it provides access to a vast amount of data without the need for time-consuming and often costly data collection processes. Researchers can analyze existing datasets to answer new research questions, making it a cost-effective approach. Additionally, secondary data often spans long time periods and diverse geographic locations, offering researchers the opportunity to conduct longitudinal studies and comparative analyses that might not be feasible with primary data collection.

Utilizing secondary data also allows researchers to cross-verify findings from primary data, enhancing the quality of their research. By analyzing data collected by others, researchers can identify patterns and themes that were not the focus of the original study, thus contributing new insights to the field. This re-analysis can uncover overlooked aspects of the data, providing a fresh perspective on the subject matter.

Moreover, thematic analysis of secondary data is particularly useful in sensitive research areas where primary data collection can be challenging due to ethical concerns. It offers a pathway to explore such topics without the need for direct interaction with participants, minimizing potential harm or distress.

Lastly, this approach supports the efficient use of existing resources, aligning with ethical research practices by avoiding unnecessary duplication of data collection efforts. It promotes a more sustainable approach to research by maximizing the utility of data that has already been gathered. Overall, the thematic analysis of secondary data is a practical, ethical, and insightful method that enhances the breadth and depth of qualitative research.

Conducting thematic analysis on secondary qualitative data

Conducting thematic analysis on secondary qualitative data involves several stages, from preparing the data for analysis to identifying themes and interpreting the findings. This process allows researchers to systematically work through a dataset, ensuring a comprehensive understanding of the data in relation to the research question. The following sections outline the key steps: preparing the data, identifying themes, and interpreting findings.

Preparing the data

The first step in conducting thematic analysis on secondary qualitative data is data preparation. This includes gathering all available data and familiarizing oneself with the content. Researchers must assess the data's relevance to their research question and consider any limitations or biases inherent in the data due to its original collection purpose. Data cleaning may also be necessary to remove irrelevant information and organize the data into a manageable format for analysis.

Identifying themes

Once the data is prepared, the next step is to begin the iterative process of coding the data and identifying potential themes. Coding involves labeling segments of the data with short phrases or keywords that summarize the content. This step requires researchers to read through the data multiple times, refining and grouping codes into potential themes as patterns begin to emerge. The aim is to reduce the data to a set of themes that capture the essence of the data in relation to the research objectives.

Interpreting findings

The final stage involves interpreting the identified themes and relating them back to the research question. This requires a detailed analysis of each theme, considering how they interact with each other and what they reveal about the data. Researchers should consider the implications of these themes for the existing literature and how they contribute to understanding the research topic. This stage is critical for drawing meaningful insights from the data and articulating the significance of the findings in the broader context of the research field.

An analysis of secondary data should be useful to addressing your research questions. Photo by Blaz Photo.