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📌Common Methods of Data Analysis used in Qualitative Research:

1. Thematic Analysis

📌Description: Identifying, analyzing, and reporting patterns (themes) within data.

📌Steps:

📍Familiarization with data

📍Generating initial codes

📍Searching for themes

📍Reviewing themes

📍Defining and naming themes

📍Writing the report

📍Use case: Widely used across many disciplines; suitable for interview and focus group data.

2. Content Analysis

📍Description: Systematic coding and categorizing to explore large volumes of textual information.

📍Types: Can be conventional, directed, or summative.

📍Use case: To quantify qualitative data, identify frequency of certain words or concepts.

3. Grounded Theory

📍Description: Developing a theory grounded in data systematically gathered and analyzed.

📍Process: Uses open coding, axial coding, and selective coding.

📍Use case: When the goal is to develop a new theory or model from the ground up.

4. Narrative Analysis

📍Description: Analyzing stories and personal accounts to understand how people make sense of events.

📍Use case: Biographical studies, life histories, and identity research.

5. Discourse Analysis

📍Description: Examining language use, communication, and the way knowledge and meaning are constructed.

📍Focus: Language, context, and social interaction.

📍Use case: Media texts, political speeches, institutional discourse.

6. Phenomenological Analysis

📍Description: Exploring how individuals perceive and make sense of their experiences.

📍Use case: Research focused on lived experiences

7. Framework Analysis

📍Description: Systematic method involving summarizing data in a matrix to identify patterns.

📍Use case: Common in policy research and public health.

8. Case Study Analysis

📍Description: In-depth examination of a single case or multiple cases over time.

📍Use case: Education, health, organizational studies.

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ChatGPT in thematic analysis: Can AI become a research assistant in qualitative research? Full PDF at https://doi.org/10.1007/s11135-025-02165-z

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