Methods of Analyzing Qualitative Data Notes

Qualitative and quantitative research follows a structured trajectory to ensure rigor and validity:

Domain and Topic Selection: Choosing a specific area of interest (e.g., workplace stress or child development).
Formulating Research Questions: Defining specific, answerable questions that guide the study. In qualitative research, these are often open-ended and exploratory.
Theoretical Framework: Identifying the lens through which data will be viewed (e.g., Social Constructivism or Positivism).
Ethical Study Design: Ensuring the protection of participants through informed consent, confidentiality, and the right to withdraw. Ethical approval from institutional boards is mandatory.
Data Collection: Utilizing tools such as semi-structured interviews, focus groups, observational logs, or surveys.
Data Analysis: Applying specific methodologies (e.g., coding in RTA or constant comparison in GT) to organize raw data.
Interpretation and Contextualization: Making sense of findings in relation to existing literature and the specific social/historical context.
Communication: Reporting results using standardized formats like APA style to ensure clarity and professional dissemination.

Qualitative methods vary in their epistemological and ontological underpinnings:

Reflexive Thematic Analysis (RTA): Emphasizes the researcher's subjectivity as a resource; focuses on identifying patterns of shared meaning.
Interpretative Phenomenological Analysis (IPA): Committed to an idiographic level of analysis (individual cases); explores the personal, lived experience.
Grounded Theory (GT): Aims to generate a theory that is 'grounded' in the data itself through an iterative process.
Discourse Analysis (DA): Investigates how language functions as a social practice to create or maintain specific versions of reality.
Narrative Analysis: Focuses on the 'story' as the unit of analysis, examining how individuals construct identity through sequential accounts.

Hypothesis Testing: Driven by deductive logic (H0 and H1). Example (H_1): Increasing job control reduces workplace stress.
Measurement: Uses standardized instruments (e.g., Job Stress Survey) to convert concepts into numerical data.
Statistical Analysis: Employs techniques like regression analysis to identify predictors of a dependent variable (Y) based on independent variables (X_n).
Generalizability: Aims for findings that can be applied to a wider population through representative sampling.

Phenomenological Focus: Prioritizes how individuals make sense of their world; seeks 'depth' through rich, descriptive data.
Inductive Logic: Theory is often built from the bottom-up based on observed patterns.
Researcher Reflexivity: Acknowledges that the researcher's own background and values influence the analysis process.
Contextual Meaning: Recognizes that human behavior and experience cannot be separated from the environment in which they occur.

Simultaneous Data Collection and Analysis: Unlike linear research, GT involves analyzing data as it is collected to inform the next steps.
Theoretical Sampling: The process of choosing new participants or data sources specifically to refine and challenge the emerging categories.
Constant Comparison: Every piece of new data is compared against existing codes and categories to ensure the theory remains grounded.
Memo-Writing: The researcher keeps notes on their own analytic process, thoughts, and emerging ideas throughout the study.
Theoretical Saturation: The point at which no new information or insights are being gained from additional data collection.
Hierarchy of GT:
1. Codes: Initial labels for segments of data.
2. Concepts: Grouping similar codes together.
3. Categories: Broad themes that represent clusters of concepts.
4. Theory: The final explanatory framework.

Social Action: DA views language as a tool that does things—it justifies, persuades, excludes, or empowers.
Micro-Discourse: Focuses on the fine-grained structure of talk and turn-taking.
Macro-Discourse: Focuses on broader institutional frameworks and power relations (e.g., medical discourse, political rhetoric).
Identity Construction: Explores how labels influence social roles. For example, the shift from "chairman" to "chairperson" reflects a change in social values regarding gender inclusivity.
The 'Hero' Narrative: In the context of COVID-19, labeling nurses as 'heroes' can serve to justify high-risk workloads while placing a moral burden on individuals to maintain that identity.

Idiography: Focuses on the particular rather than the universal; often uses small, homogenous sample sizes.
The Double Hermeneutic: A two-stage interpretation process where the participant is trying to make sense of their world, and the researcher is trying to make sense of the participant trying to make sense of their world.
Reflexive Thematic Analysis (RTA) Phases:
1. Familiarization with the data.
2. Generating initial codes.
3. Generating initial themes.
4. Reviewing potential themes.
5. Defining and naming themes.
6. Producing the report.