Reflexive Thematic Analysis Vs Thematic Analysis – Importance

There are different analysis techniques. Each analysis technique has its pros and cons. Similarly, the way to conduct each analysis is specified. From a broader perspective, you can categorize analysis techniques in two different ways. The first one is reflexive thematic analysis, while the second one is thematic analysis. As per the importance of these analysis techniques, this article aims to discuss about reflexive thematic analysis and thematic analysis.

Importance Of Reflexive Thematic Analysis 

The reflexive thematic analysis is the one which allows you to come up with research outcomes that are obtained from a particular theoretical framework. The selection of reflexive thematic analysis is made based on the type of research and the commitment to the research approach. The importance of this analysis is measured through a flexible interpretative approach, which works well for qualitative data analysis. Also, whenever your research work demands the use of patterns and themes, you can find reflexive analysis as a good option. Whether it’s the identification of data patterns or analysis of data themes, the role of reflexive analysis is vital.

Researchers take this analysis helping because of the impartial process. In this way, it becomes easy to have significant details reflected from the respondents of the research. In this analysis, you are supposed to look at assumptions repeatedly and acknowledge them. This approach helps you get the desired shape of the research and its end results.

Importance Of Thematic Analysis 

Qualitative data is a subjective form of data. The analysis of qualitative data gives you a detailed discussion of the selected issue. You can use qualitative data for quantitative analysis as well. For this, you have to code your data and then make it quantitative. Thematic analysis is used to work on qualitative data. It is supposed to find results based on collected data. Also, it works well to interpret some details out of qualitative data. Before using this analysis technique, it is necessary to know about its purpose and main points. After having descriptive data, you have to critically evaluate the main theme of the study.

A designed theme is the thing that helps you well in solving the problem. At the time of using this analysis, you have to be focused. It is necessary to come up with a logical interpretation of data. Another important thing about this analysis technique is linked with its reasoning approach. As this analysis prefers qualitative data, so the reasoning approaches in always inductive.

Make A Discussion for Reflexive Thematic Analysis vs Thematic Analysis.

Following are the differences that can help you learn reflexive thematic analysis and thematic analysis:

Study Type 

You can find the difference in study type between the selected analysis types. In thematic analysis, you can target different aspects of education. It includes the project as well as the location. In simple words, you can say it covers location-based study. Also, it works well for project-based education. At the same time, reflexive analysis is not location-based.

Insights Of Problem 

Reflexive analysis plays a vital role in getting insights into a research problem, but you have to be careful that the problem is associated with health research. In simple words, the study domain is specified in the reflexive analysis. On the other hand, thematic analysis is considered a good way to get insights into a particular problem. It works well for hot issues and current themes, and you can narrow down the main theme of any study. So, it is an effective way to learn different aspects of a particular topic.

Comprehension of Analysis 

The reflexive analysis may not be so simple for all novel researchers. With a large sample size, it helps you with assembled and organized end results of a study. In contrast, the procedure of thematic analysis is easy to comprehend. You do not have to spend a long time in training. It is easy to understand, so you can go for this analysis as a novel researcher. Also, when you are running short on time, you can go for a thematic approach to get effective results.

Way To Conduct Analysis

For reflexive analysis, you have to ensure the steps as mentioned below:

• First of all, you need to go for data familiarization. It helps you get the depth of the content and give an idea about data patterns.
• The second step is supposed to be a generation of codes. This step is meant to organize data. Do not forget to pay high attention because a mistake at this stage can cause a problem in rest of the procedure.
• The second last step is about theme generation by sorting codes. The best approach is to get the meaning of each code and then build relationships between them.
• The last step is about the final review. In this step, you need to review all previous steps to clarify if the generated theme is good to go.

On the other hand, thematic analysis demands for following steps:

• The whole process of thematic study starts with data collection. You can collect data through relevant articles and other study material. It can be a case study, journal or research paper. You have to be very careful about the authentication of the site and researcher from where you are supposed to collect data.
• After data collection, you have to start data analysis. The thematic analysis identifies the main theme of selected study.
• Code the main theme of study in subcategories. The data coding makes your end results effective and valid.
• Review the main theme of study.
• Finally, analyze the theme and its codes. If you find some issue in any of the two discussed procedures, you can avail the option of masters dissertation help. 

Final Thoughts 

By understanding the above-mentioned points, you can grasp the importance of each analysis type. Also, you will get the difference between reflexive thematic analysis and thematic analysis. Many novel researchers take them as different names for the same analysis, but in reality, both are two complete different things.