Overview
This lecture explains thematic analysis as a qualitative research method, including its definition, approaches, strengths, weaknesses, and when it’s best applied.
What is Thematic Analysis?
- Thematic Analysis (TA) is a qualitative method for identifying patterns, themes, and meanings in language-based data.
- TA can analyze data from interviews, open-ended surveys, or social media posts (both primary and secondary sources).
- The main goal is to extract key themes aligned with the research aims and questions.
Approaches to Thematic Analysis
- Inductive TA: Codes and themes emerge from the data itself without pre-set categories, allowing flexibility and adjustment.
- Deductive TA: Uses predefined codes (a priori), often based on theory or prior research; codes are fixed and outlined in a codebook.
- Coding Reliability TA: In deductive TA, multiple researchers use the same codebook to ensure consistency and reliability.
Strengths of Thematic Analysis
- Simple process for developing codes and themes, suitable for beginners.
- Flexible and applicable to a wide range of topics, participant numbers, and data types.
- Useful for research aimed at uncovering patterns in thoughts, beliefs, and opinions.
Weaknesses of Thematic Analysis
- Results can be vague or imprecise due to TA’s flexibility and broad application.
- May lack detail or miss subtle nuances and contradictions in the data.
- Less suitable for research requiring high sensitivity to context or precise, nuanced understanding.
When to Use Thematic Analysis
- Best for projects aiming to identify similarities and patterns within large or diverse data sets.
- Appropriate when the research seeks to understand shared meanings, attitudes, or beliefs.
Key Terms & Definitions
- Thematic Analysis (TA) — a method for finding themes or patterns within qualitative data.
- Inductive Approach — developing codes and themes from the data itself.
- Deductive Approach — applying codes developed prior to data analysis, often from theory.
- A Priori Codes — codes created before data analysis, usually based on existing frameworks.
- Codebook — a document outlining the definitions and scope of each code used.
- Coding Reliability TA — a process to increase reliability by having multiple researchers apply the same codebook.
Action Items / Next Steps
- Review your research aims and questions to assess if thematic analysis fits your project.
- Explore other qualitative analysis methods for comparison.
- If unfamiliar, study qualitative coding and writing research questions.