Introduction

Thematic analysis is one of the most widespread and flexible methods in qualitative research. It is used to identify, organize, and interpret recurring patterns of meaning within data. This method is not bound to a specific theoretical framework but can be employed by researchers coming from different epistemological standpoints. Its flexibility makes it particularly useful for novice researchers, as it provides fundamental skills that can later be applied to more specialized analytic approaches.

Purpose of Thematic Analysis

The primary aim of thematic analysis is the systematic recording and categorization of patterns of meaning—referred to as themes—that emerge from interviews, observations, or other research material. Through this process, the researcher does not simply uncover pre-existing themes, but actively co-constructs meaning in continuous interaction with the data. The goal is to produce an interpretation that answers the research questions and highlights participants’ experiences on a collective level. At the same time, a key methodological challenge arises: to what extent do the “common themes” identified by the researcher truly reflect shared experiences, or are they heterogeneous opinions merged arbitrarily? This makes reflexivity, attentiveness, and theoretical sensitivity indispensable for the researcher, in order to avoid simplistic or misleading generalizations.

Methodological Steps

The process of thematic analysis involves sequential steps that allow the researcher to systematically organize the interpretation of the data.

Transcription of the interview

The first step involves transforming recorded interviews into written text. Transcription is not a purely technical process but already a first stage of interpretation, since the researcher decides what to record and how to represent it. Accuracy in the rendering of spoken language is crucial, while it is recommended to use simple notation systems that also capture paralinguistic features, such as pauses, laughter, or emphatic intonation.

Familiarization with the data and identification of extracts

Next comes a careful reading of the material and the selection of extracts that are directly relevant to the research questions. This process reduces the complexity of the data and enables the researcher to focus on more manageable sections of text, which can then be compared to identify common meanings or variations. In this way, the transition is facilitated from the totality of the data to specific, targeted parts that provide answers to the research questions.

Coding

The following stage is coding, where the researcher assigns conceptual labels to segments of the data. Codes can be descriptive, reflecting the explicit content, or interpretive, uncovering underlying meanings. Importantly, the researcher can make use of pre-existing theoretical categories, which should not be restrictive but serve as sensitizing tools that broaden the researcher’s perspective and help identify significant aspects of meaning. Thus, coding is not a mere categorization exercise, but a creative process of interpretation.

From codes to themes

Once codes have been generated, the next stage is to construct themes. Themes represent broader and more abstract categories that result from organizing, comparing, and synthesizing codes. They constitute recurring patterns of meaning that are essential for understanding the phenomenon under study. At this stage, creativity and theoretical depth are required, as themes are not simply discovered but actively constructed by the researcher through analysis.

Reporting the findings

The final stage is the presentation of findings. Each theme is described and analyzed in detail, always in relation to the research questions. Different dimensions, nuances, and even contradictions that characterize each theme are highlighted to capture the complexity of the phenomenon. Reporting goes beyond a descriptive account: it interprets the data and links the findings back to the study’s theoretical framework.

Conclusions

Thematic analysis is one of the most significant and accessible methods of qualitative data analysis. It offers a flexible yet systematic framework for identifying and organizing patterns of meaning. It is not a mechanical procedure but requires creativity, insight, and theoretical preparation. For novice researchers, thematic analysis functions as a starting point that allows them to practice understanding and processing qualitative data. For more experienced researchers, it serves as a reliable tool that combines clarity with depth. Overall, thematic analysis is a method that respects the complexity of participants’ experiences, organizes the data into thematic structures, and produces rich interpretations that address research questions. Its use must be guided by the purpose of the study, the available data, and the researcher’s epistemological stance, in order to maximize its effectiveness.