Qualitative Data Analysis Notes

Qualitative Data Analysis in Sport, Exercise, and Health

Learning Outcomes

  • Understand the key principles of qualitative analysis

    • Importance of grasping foundational concepts in qualitative research.

  • Identify the prominent forms of data analysis in qualitative research within the fields of Sport, Exercise, and Health (SHE)

    • Exploration of various methodologies adopted in qualitative analysis in SHE.

  • Explain key processes associated with reflexive thematic analysis

    • Insight into the stages and considerations involved in reflexive thematic analysis.

Emergent Research Design

  • Adapted from Maykut and Morehouse (1994)

    • Describes a dynamic framework for qualitative research.

  • Early ongoing inductive analysis

    • The process begins at the onset of data collection, allowing themes to emerge naturally from the data.

  • Focus of inquiry

    • Establish a specific area of interest to guide the research.

  • Purposive sample

    • Selection of participants based on specific criteria relevant to the research objectives.

  • Reflective researcher

    • Emphasizes the researcher’s role in interpreting data.

  • Rich in-depth data

    • Aim for comprehensive qualitative data that allows for nuanced understanding.

  • Qualitative methods in natural settings

    • Emphasizes the importance of context in qualitative research.

Purpose of Analyzing Qualitative Data

  • Quote from Schwandt (2011, p.6): "If data could speak for themselves [itself], analysis would not be necessary."

    • This highlights the necessity of the researcher’s role in interpreting data.

  • Key Points:

    • Data cannot self-interpret; needed to unveil underlying meanings.

    • Critical questions for the researcher:

    • What does this all mean?

    • How does this help us understand the phenomenon under study?

    • Why is this important?

The Analysis Process

  • Steps in qualitative data analysis:

    • Collect data: Gathering information related to the research question.

    • Process data: Converting raw data into analyzable content.

    • Early (and ongoing) inductive analysis: Analysis starts concurrently with data collection.

    • Decide on amendments (if any): Adapt the research approach in response to findings.

    • A reflexive or subjective researcher: Importance of researcher’s perspective in analysis.

    • Saturation Point: Point where additional data does not yield new insights.

    • Overarching analysis: Final synthesis of themes and findings.

Processing Your Qualitative Data

  • Transform data into a meaningful and workable format:

    • Transcription: Including accuracy checking and anonymisation of data.

    • Word processing: Formatting and organizing data for analysis.

    • Scanning: Digitizing paper documents for electronic analysis.

Early and Ongoing Inductive Data Analysis

  • Initiates during data collection:

    • Data processed immediately ensures richness and relevancy.

    • Research journal: Maintain notes on initial thoughts and themes.

    • Initial analysis post-data collection:

    • Identify commonalities or differences within data.

    • Explore connections between cases or prior datasets.

    • Emergence of themes and formulating new research questions.

    • Summative analysis: Final comprehensive view at the end of collection phase.

Data Analysis Methods

  • Main qualitative analysis methods to be employed include:

    • (Reflexive) Thematic analysis

    • Narrative analysis (thematic, structural, performative)

    • Discourse analysis

    • Visual analysis

    • Computer-assisted analysis

    • Hierarchical content analysis

    • Grounded theory analysis

    • Interpretative phenomenological analysis (as indicated in Sparkes & Smith, 2014, chapter 5).

Reflexive Thematic Analysis (RTA)

  • Definition and Importance:

    • What is Thematic Analysis (TA)?

    • A method that organizes and describes qualitative data, identifying, analyzing, interpreting, and reporting patterns (themes).

    • Quote: Braun and Clarke (2006): "An accessible and robust method for newcomers to qualitative analysis."

  • What is Reflexive Thematic Analysis (RTA)?

    • An approach that emphasizes a subjective, aware, and questioning researcher.

    • Reflexivity: Critical reflection on the researcher’s role and methodology.

    • Positions RTA firmly within the qualitative research paradigm (Braun and Clarke, 2022, p.5).

Why Choose (Reflexive) Thematic Analysis?

  • Highlighting advantages:

    • Flexibility and versatility as a method.

    • Aids in understanding similarities and differences across datasets.

    • Summarizes key findings effectively within research projects.

    • Accessible results for public understanding.

    • Addresses criticisms of traditional qualitative methodologies.

The Analysis Process in RTA

  • Sequential Steps:

    • Collect data: Gather qualitative information relevant to study objectives.

    • Process data: Convert and organize data for analysis.

    • Inductive analysis: Early and ongoing assessments leading to initial insights.

    • Amendments: Revisions to methodology based on preliminary insights.

    • Reflexive stance: Maintain awareness of researcher bias throughout.

    • Saturation Point: Ensure comprehensive data coverage before concluding.

    • Overarching analysis: Final analysis synthesizing findings into coherent themes.

Reflexive Stance in Research

  • Acknowledge researcher positioning:

    • Impact of personal “biographical baggage,” past experiences, and participant knowledge.

    • Enhancements to the research process through rigorous reflexivity.

  • Methods to promote reflexivity:

    • Embrace interpretivism alongside ontological relativism and constructionist epistemology.

    • Engage in participant verification or co-construction of knowledge.

    • Revisit aims and objectives while analyzing.

    • Discuss codes/themes with a supervisor for critical feedback.

Reflexive Questions during Data Collection

  • Key considerations for researchers:

    • Are the questions leading or loaded?

    • Are the questions open and well-worded?

    • Are probes directing responses towards personal biases?

    • Is the researcher’s body language neutral?

    • Are participant responses authentic and comprehensive?

Reflexive Processing of Qualitative Data

  • Continuous assessment:

    • Examine interview questions for potential bias.

    • Gather reflexive insights from each data collection.

    • Document necessary changes for future data collection activities.

Early and Inductive Analysis within RTA

  • Characteristics:

    • Begins concurrently with data collection (notetaking).

    • Immediate data processing initiates coding process.

    • Reflexively identify commonalities, candidate themes, and new research questions.

    • Analyze links between specific examples, societal issues, and existing theories.

    • Adjust focus and tools based on insights as needed.

Cautions Against Traditional Thematic Analysis Approaches

  • Note: Do NOT use Braun and Clarke’s (2006) Six Phase Approach for thematic analysis.

    • Phase 1: Immersion

    • Phase 2: Generating initial codes

    • Phase 3: Searching for and identifying themes

    • Phase 4: Reviewing themes

    • Phase 5: Defining and naming themes

    • Phase 6: Writing the report

Braun and Clarke’s (2022) Six Phase Approach to Reflexive Thematic Analysis

  • Phase 1: Dataset familiarization

    • (Re)reading transcripts and audio, noting analytic ideas.

  • Phase 2: Data coding

    • Revisit open coding and research notes; compile meaningful codes.

  • Phase 3: Generating initial themes

    • Compile transcripts to identify and cluster quotes exemplifying codes.

  • Phase 4: Developing and reviewing themes

    • Assess candidate themes aligned with research questions and evidence adequacy.

  • Phase 5: Refining, defining, and naming themes

    • Ensure clarity, understandability, and theoretical basis of themes.

  • Phase 6: Writing up

    • Formulate a narrative of findings, incorporating evidence and theoretical context.

Challenges and Criticisms of Reflexive Thematic Analysis

  • Acknowledge non-linear nature of thematic analysis.

    • Phases may overlap or require revisiting.

  • Risks include:

    • Losing nuances and contradictions in theme identification.

    • Gaining insights into 'whats' without addressing 'hows' unless critically focused.

    • Insufficient understanding of storytelling dynamics can diminish analysis quality.

Key Reading for Qualitative Analysis

  • Title: THEMATICS ANALYSIS: A PRACTICAL GUIDE

    • Authors: Virginia Braun & Victoria Clarke.

Other Data Analysis Methods

  • Overview of various alternative qualitative methods:

    • Narrative analysis, discourse analysis, visual analysis, and grounded theory analysis among others.

Narrative Analysis

  • An umbrella term for qualitative methods focused on storytelling data (Riessman, 2008).

    • Caution against fragmenting or over-coding narratives.

  • Explores the 'whats' (content) and 'hows' (structure and performance) of narratives.

Types of Narrative Analysis

  • Purpose-based categories:

    • Thematic narrative analysis (whats)

    • Structural narrative analysis (hows)

    • Performative narrative analysis (hows of interactions).

Frank’s (1995) Narratives of Illness and Injury

  • Categories:

    • Restitution narratives: Optimistic recovery.

    • Quest narratives: Change in self-identity through adversity.

    • Chaos narratives: Despair without hope for the future.

What is Discourse Analysis?

  • A category analyzing symbolic interactions, focusing on texts and language (Bloor and Bloor, 2007).

    • Emphasizes discursive formations identified through patterns in communication (Foucault, 1972, p.39).

  • Concerned with power dynamics in social institutions.

    • Applied broadly across textual contexts including social media and traditional media formats.

Text Production and Consumption

  • Fairclough's (2010) three-dimensional model for analyzing discourse:

    • Text: Description of analyzed materials.

    • Discourse practice: Processing of texts.

    • Sociocultural practice: Explanation of broader contexts influencing discourse.

Ethical Considerations in Research Representation

  • The crisis of representation called attention to how researchers depict others.

  • Quote from Richardson (2000, p.923): "Writing… is a way… of discovery and analysis."

    • Highlights varied researcher/participant voice dynamics.

Data Representation in Qualitative Research

  • Variety of innovative (re)presentation formats to share findings:

    • Realist tales, confessional tales, autoethnography, and poetic representations.

Challenges in Qualitative Research Legitimization

  • Key concerns:

    • Reliability: Replicability of research.

    • Validity: Consistency of findings across different studies.

Alternative Judgement Criteria for Qualitative Work

  • As proposed by Tracy (2010) and Barone & Eisner (2012):

    • Worthy topic, incisiveness, rich rigor, concision, sincerity, coherence, credibility, generativity, resonance, social significance, meaningful contribution.

Conclusion on Qualitative Research Methods in SHE

  • Emphasizes the journey from process to product in understanding qualitative research in Sport, Exercise, and Health.

  • Authors: Andrew C. Sparkes and Brett Smith

    • Key reading material for additional insights in qualitative methodologies.