Thematic Approach

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1 Thematic Approach Name Student’s Number Course Title and Number Professor’s Name Institution Date
2 Thematic Approach Thematic analysis is a strategy of providing insight, organizing, and identifying themes (patterns of the meaning) in a given dataset. Braun & Clarke (2022) claim that when an individual focuses on the meaning embedded in a dataset, thematic analysis helps the person recognize and make sense of shared or collective experiences and meanings. Thematic analysis is a method of identifying what information is commonly written or talked about and deriving meaning from these commonalities. This approach is also commonly used in qualitative studies to determine the key themes in these articles. Kiger & Varpioadds (2020) add that the thematic approach to a survey allows a researcher to analyze qualitative data by researching across a dataset to recognize and examine repeated patterns. For instance, if a researcher is studying the impact of a particular lifestyle behaviour on the health outcomes of an individual while using the thematic analysis approach, they will first collect a variety of articles on the topic and study them closely to identify the common themes in the papers before making conclusions about the subject. There are six main steps to be followed when using the thematic analysis approach in examining a given dataset. Bryne (2022) states that the first step a researcher takes when using the thematic approach is familiarizing themselves with the data. This step consists of reading the whole dataset comprehensively to become familiar with the information. This step is essential since it helps a researcher identify the correct data pertinent to the research questions. One of the most practical ways a researcher can grasp the information is through manual transcription. The researcher makes preliminary notes on the topic they are studying, which would be crucial during the interpretation of the data phase of using this data analysis approach.
3 The second step is generating initial codes. Bryne (2022) argues that codes are the basic building blocks that the researcher would use to derive themes from the dataset. Coding is conducted to produce shorthand and succinct interpretive or descriptive labels for data which might be relevant to the research questions. However, researchers need to work systematically on the whole dataset by examining each data item and noting the aspects that appear to be informative and exciting in developing themes. This phase is followed by the third step, which entails generating themes. Once the data items have been coded, a researcher needs to shift their attention from interpreting individual data items in a given dataset to interpreting the aggregated meaning of the dataset. The fourth step while utilizing the thematic analysis approach is reviewing the themes. Nowell (2017) explains that this step consists of refining the set of themes that have been identified in phase three. Nonetheless, it is not surprising to discover that some potential themes might not be used to derive meaningful interpretation or might not offer the information essential to addressing the study questions. Ideally, the main objective of this stage is to yield a refined thematic table or map which illustrates the most crucial aspects of the dataset which are relevant to addressing the research questions (Bryne, 2022). This phase is followed by the fifth step, naming and defining the theme. In this stage, researchers present a comprehensive examination of the thematic context. Every distinct sub-theme and main theme is supposed to be stated according to the given set of data and the relevant study questions. The last step of using the thematic analysis approach is producing the final report (Maguire & Delahunt, 2017). This final stage, which marks the end of the thematic analysis, involves the researcher making the appropriate analysis about the topic they were researching. A researcher studies the issue, the research questions and the themes that have been redefined using
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4 this analysis approach to make the correct conclusion about a given topic. However, it is vital to ensure that the themes are connected in a meaningful and logical manner and that they can build a convincing narrative of the dataset. Thematic analysis is widely utilized as a qualitative approach in examining one-on-one semi-structured interviews. George (2022) defines semi-structured interviews as methods of collecting data that depend on asking the study questions sample with a predetermined thematic framework. Besides, this data collection method is usually qualitative in nature. Judger (2016) explains that the thematic approach is widely utilized in analyzing most interviews. This analysis approach is effective in examining one-on-one semi-structured interviews since it helps produce insightful analyses which answer the semi-structured interview questions. Primarily when an interviewer wants to study a particular topic, they construct predetermined questions, which in this case, act as the research questions and use them during the interview to understand the issue they are researching. Once the answers from the discussions have been collected, the interviewer goes through them to identify the themes in the respondents' answers. The researcher would then study these themes to make the appropriate conclusion about the subject. The thematic analysis approach of analyzing data is beneficial because it offers a highly flexible method which could be modified accordingly to satisfy the requests of several studies, offering a detailed and rich yet multifaceted account of information (Nowell et al., 2017). Additionally, since the thematic analysis approach does not demand the all-inclusive technological and theoretical information of other qualitative procedures, it provides a more manageable type of analysis, especially for the researchers that are new in their research careers. Ideally, researchers unfamiliar with qualitative approaches might discover that thematic analysis is easy to grasp and understand since it consists of a few procedures and prescriptions.
5 Another significant benefit of using the thematic analysis is that it is an effective tool for studying the viewpoints of several research respondents, highlighting differences and similarities, and deriving unexpected understandings. Nowell et al. (2017) state that thematic analysis is beneficial in summarizing the main characteristics of a massive dataset since it prompts a researcher to employ a well-structured method in treating data. This is essential in helping the researcher produce an organized and clear final report. According to Barkley (2021), thematic analysis is vital and advantageous because it is effective when studying a large amount of data. It is always challenging to analyze extensive data in most qualitative studies. It is often easy for a researcher to become distracted from their crucial research objectives. Therefore, the thematic analysis approach helps a researcher deal with large amounts of data because it divides the data into several relevant datasets. In conclusion, the thematic analysis is an effective qualitative study analysis tool since it helps a researcher identify the significant themes in a given dataset which are essential in making the required conclusions. As mentioned in the preceding paragraphs, this approach is divided into six essential steps which help a researcher recognize commonalities in a particular dataset. Therefore, it is applicable in studying and analyzing large datasets, which could be challenging if other approaches were used. This aper has also mentioned different advantages which are associated with using the thematic approach in analyzing a given set of data.
6 References Barkley, A. (2021). What is Thematic Analysis? Advantages and Disadvantages. https://www.theacademicpapers.co.uk/blog/2021/10/02/what-is-thematic-analysis- advantages-and-disadvantages/#Advantages_of_Thematic_Analysis Braun, V., & Clarke, V. (2022). Thematic analysis . American Psychological Association. Byrne, D. (2022). A worked example of Braun and Clarke’s approach to reflexive thematic analysis. Quality & quantity , 56 (3), 1391-1412. George, T. (2022). Semi-Structured Interview | Definition, Guide & Examples. https://www.scribbr.com/methodology/semi-structured-interview/ Judger, N. (2016). The thematic analysis of interview data: An approach used to examine the influence of the market on a curricular provision in Mongolian higher education institutions. Hillary place papers, 3rd edition, University of Leeds . Kiger, M. E., & Varpio, L. (2020). Thematic analysis of qualitative data: AMEE Guide No. 131. Medical teacher , 42 (8), 846-854 Maguire, M., & Delahunt, B. (2017). Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. All Ireland Journal of Higher Education , 9 (3). Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International journal of qualitative methods , 16 (1), 1609406917733847.
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