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Thematic analysis is the most common form of analysis in qualitative research. It emphasizes pinpointing, examining, and recording patterns (or "themes") within data. Themes are patterns across data sets that are important to the description of a phenomenon and are associated to a specific research question. The themes become the categories for analysis. Thematic analysis is performed through the process of coding in six phases to create established, meaningful patterns. These phases are: familiarization with data, generating initial codes, searching for themes among codes, reviewing themes, defining and naming themes, and producing the final report. ==What is thematic analysis?== Thematic analysis is used in qualitative research and focuses on examining themes within data.〔 This method emphasizes organization and rich description of the data set. Thematic analysis goes beyond simply counting phrases or words in a text and moves on to identifying implicit and explicit ideas within the data. Coding is the primary process for developing themes within the raw data by recognizing important moments in the data and encoding it prior to interpretation. The interpretation of these codes can include comparing theme frequencies, identifying theme co-occurrence, and graphically displaying relationships between different themes.〔 Most researchers consider thematic analysis to be a very useful method in capturing the intricacies of meaning within a data set.〔 There is a wide range as to what a "data set" entails (see qualitative data). Texts can range from a single-word response to an open-ended question or as complex as a body of thousands of pages. As a consequence, data analysis strategies will likely vary according to size. Most qualitative researchers analyze transcribed in-depth interviews that can be 2-hours in length, resulting in nearly 40 pages of transcribed data per respondent. Also, it should be taken into consideration that complexity in a study can vary according to different data types. Thematic analysis takes the concept of supporting assertions with data from grounded theory. This work is designed to construct theories that are grounded in the data themselves. This is reflective in thematic analysis because the process consists of reading transcripts, identifying possible themes, comparing and contrasting themes, and building theoretical models. Thematic analysis is also related to phenomenology in that it focuses on the human experience subjectively.〔 This approach emphasizes the participants' perceptions, feelings and experiences as the paramount object of study. Rooted in humanistic psychology, phenomenology notes giving voice to the "other" as a key component in qualitative research in general. This allows the respondents to discuss the topic in their own words, free of constraints from fixed-response questions found in quantitative studies. Like most research methods, this process of data analysis can occur in two primary ways—inductively or deductively. In an inductive approach, the themes identified are strongly linked to the data because assumptions are data-driven.〔 This means that the process of coding occurs without trying to fit the data into a pre-existing model or frame. It is important to note that throughout this inductive process, it is not possible for the researchers to free themselves from their theoretical epistemological responsibilities. Deductive approaches, on the other hand, are theory-driven. This form of analysis tends to be less descriptive overall because analysis is limited to the preconceived frames. The result tends to focus on one or two specific aspects of the data that were determined prior to data analysis. The choice between these two approaches generally depends on the researchers' epistemologies (see epistemology). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「thematic analysis」の詳細全文を読む スポンサード リンク
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