Chapters 15 & 16 Notes
Characteristics of Qualitative Data Analysis
Qualitative analysis is characterized by a lack of universal rules, meaning there is no single prescribed way to perform the analysis correctly.
Researchers must deal with large amounts of narrative data, which requires intensive labor and significant time investment.
The process demands a high degree of creativity from the researcher.
A primary challenge is condensing rich, voluminous data into concise and readable reports.
Qualitative Data Management and Organization
Developing a Coding Scheme: Researchers must create a systematic method for labeling segments of data.
Coding Qualitative Data: The actual process of applying the developed scheme to the narrative information.
Organizing the Data: This involves structuring the coded information for easier analysis.
Manual Methods: Historically, data was organized using conceptual files.
Computerized Methods: Modern analysis often utilizes Computer-Aided Qualitative Data Analysis Software (CAQDAS), such as Nvivo and other similar programs.
Illustrative Data Extract and Coding Example
The Narrative (Case Study): "One of the most traumatic birth experiences happened a few year ago but I still remember it as though it were yesterday. A grand multipara came to labor and delivery in labor. This was her pregnancy. The doctor, who I don't really get along with, treated her like a piece of dirt. He delivered the baby with no complications. He immediately put the baby in the warmer without letting the mom see or hold her baby. He then proceeded to put his hand inside of her practically halfway up his arm to start pulling her placenta out! She was yelling 'something's not right, it's never hurt like this before!' I walked away from the bed but went back to be with her because she was still screaming. I felt like I was watching a rape! I felt so helpless. He's one of those doctors that for whatever reason seems to get away with anything. I talked to my case manager about it and how upset I was. Nothing was ever done. I felt so powerless. I really feel that I failed my patient. She was counting on me to keep her safe. I let her down. To this day I still think about it and what I could have done differently. I should have protected my patient and advocated for her, but I didn't."
Associated Codes: From this specific narrative, several codes were extracted:
Felt helpless.
Felt powerless.
Feel like I failed my patient.
What could have been done differently?
I let my patient down.
General Analytic Overview and Content Analysis
Thematic Identification: The goal is to identify themes or broad categories.
Definition of a Theme: An abstract entity that brings meaning and identity to a current experience.
Pattern Searching: Researchers search for patterns among themes and variations within the data.
Aids to Analysis: Development of charting devices and timelines is common.
Use of Metaphors: Researchers may employ metaphors to evoke a visual analogy for the findings.
Integration: The final step is to weave thematic pieces into an integrated whole.
Qualitative Content Analysis Process:
Analyze narrative data content to identify prominent themes and patterns.
Break down the data into smaller, manageable units.
Code and name units based on their specific content.
Group coded material based on shared content.
The general flow moves from starting with data, grouping into themes, and developing codes from the data and themes.
Analytic Traditions and Research Designs
Ethnographic Analysis:
Domain Analysis: Identification of broad categories representing units of cultural knowledge; focuses on cultural meanings of terms and symbols (objects and events).
Taxonomic Analysis: Deciding on the number of domains to be included in the final analysis.
Componential Analysis: Examining multiple relationships among terms within domains to find similarities and differences among cultural terms.
Thematic Analysis: Uncovering underlying cultural themes.
Phenomenological Analysis (Three Broad Schools):
Duquesne School: Focused on descriptive phenomenology based on Husserl’s philosophy. Key figures include Colaizzi, Giorgi, and Van Kaam.
Utrecht School: Combines descriptive and interpretive phenomenology. Associated with Van Manen.
Heideggerian Hermeneutics: Purely interpretive phenomenology. Associated with Benner.
Grounded Theory Analysis:
Constant Comparison Analysis: A technique involving the comparison of elements (e.g., segments of an interview) within one data source against those in other data sources.
Comparison of Alternative Grounded Theory Approaches
Glaser (Emergent Theory/Discovery):
Initial Data Analysis: Breaking down and conceptualizing data with comparisons so patterns emerge.
Types of Coding: Open, selective, and theoretical.
Connections between Categories: Use of coding families plus theoretical codes from different disciplines.
Corbin and Strauss (Conceptual Description/Verification):
Initial Data Analysis: Breaking down and conceptualizing data, which includes taking apart a single sentence, observation, or incident.
Types of Coding: Open and axial.
Connections between Categories: Paradigm (conditions, actions-interactions, and consequences or outcomes) and the conditional/consequential matrix.
Charmaz (Interpretive Theory Constructed):
Initial Data Analysis: Creating a link between collecting data and developing emergent theory; defining what is occurring in data and analyzing its meaning.
Types of Coding: Initial and focused.
Connections between Categories: Analytic strategies are emergent rather than a procedural application; includes categories, subcategories, and links.
Guidelines for Critically Appraising Qualitative Analyses (Box )
Was the data analysis approach appropriate for the research design or tradition?
Was the coding scheme described? If so, does the scheme appear logical and complete?
Did the report adequately describe the process by which the actual analysis was performed? Did the report indicate whose approach to data analysis was used (e.g., Glaser, Corbin and Strauss, or Charmaz)?
What major themes or processes emerged? Were relevant excerpts provided, and do the themes capture the meaning of the narratives? Is the analysis parsimonious (could themes be collapsed into broader conceptualizations)?
Was a conceptual map, model, or diagram effectively displayed?
Was the context of the phenomenon adequately described to give a clear picture of the social or emotional world of participants?
Did the analysis yield a meaningful and insightful picture, or is the result trivial and obvious?
Trustworthiness and Integrity in Qualitative Research
Debates About Rigor and Validity: There are significant controversies regarding quality. Key disputes center on whether terms like "validity" and "rigor" are appropriate for qualitative work.
Diverse Perspectives: Some researchers reject these terms entirely; others believe they are appropriate, while many have searched for parallel goals or new terminology.
Terminology Proliferation: There is no common vocabulary. Terms include Goodness, Truth value, Integrity, Trustworthiness, Validity, and Rigor.
Lincoln and Guba’s Framework
Widely considered the "gold standard" in qualitative research.
Key Goal: Trustworthiness, which concerns the "truth value" of data, analysis, and interpretation.
Five Criteria of Trustworthiness:
Credibility: Concerns confidence in the truth of the data and interpretations. It involves carrying out the study to enhance believability and demonstrating that credibility to readers. This is the analog to internal validity and is arguably the most important criterion.
Dependability: Refers to the stability of data over time and over different conditions. It is the analog to reliability.
Confirmability: Refers to objectivity—establishing that data represent participant information and not researcher imagination. It is the potential for congruence between two or more independent people regarding data accuracy. This is the analog to objectivity.
Transferability: The extent to which findings can be transferred to other settings or groups. It is the analog to generalizability or external validity.
Authenticity: The extent to which researchers faithfully show a range of different realities and convey the tone/feeling of participants' lives. There is no quantitative analog for this criterion.
Strategies to Enhance Qualitative Quality
During Data Collection:
Prolonged Engagement: Investing sufficient time to achieve in-depth understanding.
Persistent Observation: Intensive focus on the salience of the data being gathered.
Reflexivity Strategies: Attending to the researcher’s own effect on the data.
Recording: Comprehensive and vivid recording of information.
Audit Trail: Systematic collection of documentation, materials, and a decision trail specifying decision rules.
Member Checking: Providing feedback to participants about interpretations and obtaining their reactions (a controversial procedure; some see it as essential, others as inappropriate).
Triangulation (Using multiple referents to draw conclusions about truth):
Data Triangulation: Using multiple data sources (e.g., Time triangulation, Space triangulation).
Method Triangulation: Using multiple methods of data collection for the same phenomenon (e.g., self-report, documents, and observation).
Strategies for Coding, Analysis, and Presentation
Search for Disconfirming Evidence: Using purposive or theoretical sampling to find cases that challenge existing interpretations.
Negative Case Analysis: Specifically searching for cases that discredit earlier hypotheses.
Peer Review and Debriefing: Sessions with peers to elicit critical feedback on the research process.
Inquiry Audit: A formal scrutiny of data and supporting documents by an external reviewer.
Thick and Contextualized Description: Providing a vivid portrayal of participants, the context, and the phenomenon.
Researcher Credibility: Sharing the researcher’s experience, credentials, and motivations to enhance reader confidence.
Guidelines for Critically Appraising Quality and Integrity (Box )
Did the report discuss efforts to enhance or evaluate the quality of the data and inquiry? Was the description clear?
Which specific techniques were used to enhance trustworthiness and integrity? Which were not used? Would additional strategies have helped?
Did the researcher represent multiple realities? Do findings seem authentic?
What can be concluded about the study's validity, integrity, rigor, or trustworthiness given the efforts made?
Did the report discuss study limitations and their effects on credibility or interpretation?
Were implications for clinical practice or future research discussed and grounded in study evidence?