24 Facts About Thematic analysis

Thematic analysis is one of the most common forms of analysis within qualitative research.

Thematic analysis is often understood as a method or technique in contrast to most other qualitative analytic approaches - such as grounded theory, discourse analysis, narrative analysis and interpretative phenomenological analysis - which can be described as methodologies or theoretically informed frameworks for research.

Thematic analysis is best thought of as an umbrella term for a variety of different approaches, rather than a singular method.

Different versions of thematic analysis are underpinned by different philosophical and conceptual assumptions and are divergent in terms of procedure.

Thematic analysis is used in qualitative research and focuses on examining themes or patterns of meaning within data.

Thematic analysis goes beyond simply counting phrases or words in a text and explores explicit and implicit meanings within the data.

In some thematic analysis approaches coding follows theme development and is a deductive process of allocating data to pre-identified themes, in other approaches - notably Braun and Clarke's reflexive approach - coding precedes theme development and themes are built from codes.

One of the hallmarks of thematic analysis is its flexibility - flexibility with regards to framing theory, research questions and research design.

Thematic analysis can be used to explore questions about participants' lived experiences, perspectives, behaviour and practices, the factors and social processes that influence and shape particular phenomena, the explicit and implicit norms and 'rules' governing particular practices, as well as the social construction of meaning and the representation of social objects in particular texts and contexts.

Thematic analysis can be used to analyse most types of qualitative data including qualitative data collected from interviews, focus groups, surveys, solicited diaries, visual methods, observation and field research, action research, memory work, vignettes, story completion and secondary sources.

Thematic analysis can be used to analyse both small and large data-sets.

Thematic analysis is often used in mixed-method designs - the theoretical flexibility of TA makes it a more straightforward choice than approaches with specific embedded theoretical assumptions.

Thematic analysis is sometimes claimed to be compatible with phenomenology in that it can focus on participants' subjective experiences and sense-making; there is a long tradition of using thematic analysis in phenomenological research.

Thematic analysis is sometimes erroneously assumed to be only compatible with phenomenology or experiential approaches to qualitative research.

For some thematic analysis proponents, including Braun and Clarke, themes are conceptualised as patterns of shared meaning across data items, underpinned or united by a central concept, which are important to the understanding of a phenomenon and are relevant to the research question.

Some coding reliability and code book proponents provide guidance for determining sample size in advance of data Thematic analysis - focusing on the concept of saturation or information redundancy.

The initial phase in reflexive thematic analysis is common to most approaches - that of data familiarisation.

Second step in reflexive thematic analysis is tagging items of interest in the data with a label.

Thematic analysis allows for categories or themes to emerge from the data like the following: repeating ideas; indigenous terms, metaphors and analogies; shifts in topic; and similarities and differences of participants' linguistic expression.

Researchers must then conduct and write a detailed Thematic analysis to identify the story of each theme and its significance.

The goal of this phase is to write the thematic analysis to convey the complicated story of the data in a manner that convinces the reader of the validity and merit of your analysis.

However, there is rarely only one ideal or suitable method so other criteria for selecting methods of Thematic analysis are often used - the researcher's theoretical commitments and their familiarity with particular methods.

Thematic analysis provides a flexible method of data analysis and allows for researchers with various methodological backgrounds to engage in this type of analysis.

Thematic analysis has several advantages and disadvantages, it is up to the researchers to decide if this method of analysis is suitable for their research design.