Chapter Summary
Key Takeaways
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Qualitative analysis is complex and diverse – No single approach fits all; methods vary widely (e.g., grounded theory, ethnography, content analysis).
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Ethics and cultural humility are foundational – Respect participant contributions, recognize cultural differences, and remain aware of power dynamics in analysis.
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Informed consent must include analysis plans – Participants should know how their data will be used and what the final product may look like.
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Reflexive journaling builds trustworthiness – Document your assumptions, feelings, and influences throughout the study to promote transparency.
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Memoing supports deeper insight – Write interpretive notes during coding to capture patterns, themes, and emerging questions.
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Audit trails ensure rigor and transparency – Keep detailed records of coding decisions, theme development, and analytic steps for verification.
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Coding is central to qualitative analysis – It’s a recursive, systematic process of identifying meaning in data using open and focused coding.
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Use codebooks to stay organized – Define codes clearly and consistently to maintain reliability, especially when working with others.
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Qualitative analysis is recursive, not linear – Expect to move back and forth across stages (e.g., data collection, coding, theme development).
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Analytic memos go beyond coding – Help transition from categorizing data to interpreting and theorizing based on your findings.
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CAQDAS tools (e.g., NVivo, ATLAS.ti) – Help manage, code, and analyze large qualitative datasets, though interpretation remains the researcher’s responsibility.
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Content analysis focuses on communication – Used to study media, ads, photos, etc., to find recurring themes and meanings.
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Steps in content analysis: (1) Select content, (2) Collect and store data, (3) Analyze for patterns, (4) Write up findings.
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Qualitative analysis involves multiple review rounds – Begin open-ended, refine focus over time, and return to data to confirm or challenge interpretations.
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Patterns may emerge through coding and counting – While qualitative, content analysis sometimes uses basic counts to support thematic interpretation.
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Begin analysis early – Don’t wait until after data collection is finished; thinking and interpreting can (and should) happen concurrently.