8.3.10

(2026 Exams) Thematic Analysis (A2 only)

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Thematic Analysis

Qualitative data is analysed using either content or thematic analysis. Thematic analysis looks at the overall themes of the data.

Data - themes

Data - themes

  • This method is used quite often for analysing qualitative data.
  • This form of analysis involves the scientist looking over their data to familiarise themselves.
  • This allows them to establish the key themes within the data - themes they can define and name.
  • From there, they can write a report.
Hypotheses

Hypotheses

  • But themes can be subjective according to the interpretation of the researcher conducting the analysis.
  • Finally, hypotheses can be formulated from this data.
  • The hypotheses, even though they could still be subjective, are based on the themes of the data.
Example - __Delaney et al. (2011)__

Example - Delaney et al. (2011)

  • An example of thematic analysis is the Delaney et al. (2011) study on the experiences of unemployment in Ireland.
  • Because the vast majority of this data was collected through interviews, thematic analysis was applied.
  • The researchers defined 15 overarching themes such as gender differences in experiences of unemployment, health issues associated with unemployment and identity challenges.

Evaluation of Thematic Analysis

Qualitative data is analysed using either content or thematic analysis. Thematic analysis looks at the overall themes of the data.

Strengths

Strengths

  • Unlike content analysis, the level of detail is maintained.
  • Objectivity is possible.
    • This is done through triangulation, which involves comparing other sources of data (like previous interviews) to verify the conclusions drawn.
Strengths cont.

Strengths cont.

  • By formulating hypotheses grounded in the data, new understandings are established.
    • For example, the Delaney et al. study found that many interviewees wanted to return to work but felt hopeless and assumed that unemployment would continue.
Weaknesses

Weaknesses

  • It can be difficult at first to establish the themes and categories.
  • Subjectivity can come into play when deciding how certain statements fit into these categories.
  • It can be time-consuming to comb through a vast amount of text.
Weaknesses cont.

Weaknesses cont.

  • Obviously, by summarising data, some of the text will be left out - it is challenging to decide which data to leave out.
  • Overall, subjectivity and researcher bias can affect the validity of the results.
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