Qualitative data analysis Flashcards
Name four ways that you can create an audit trail in qualitative research (1 mark each). An additional mark is available for each item
where you provide a brief description and/or example.
Meticulous record keeping: Research journal/log, document every aspect
Analytical transparency: codebook/ coding scheme
Verification strategies: member checking- return to research participants with preliminary findings or interpretations- can confirm understanding or adjust your analysis
Reflexibility: Maintain a separate journal to explore you positionality, including your background, assumptions and potential biases and reflect on them.
Provide a brief description or denition of a theme in qualitative data analysis (2 marks). Additional marks are available when you
demonstrate your understanding of the definition by using your own words rather than using a copy and paste approach only.
In qualitative analysis, a theme is a broad, overarching idea, concept, or pattern that emerges from your data. Here’s a breakdown of what that means:
Pattern across data: Themes represent repeated or recurring concepts, experiences, emotions, or behaviors expressed throughout your collected data (e.g., interview transcripts, field notes, documents).
Broader than a code: While codes are specific labels for smaller segments of data, themes encompass multiple codes, capturing a larger meaning. For example, codes like “frustration,” “lack of control,” and “uncertainty” might coalesce into the theme of “powerlessness.”
Interpretive element: Identifying themes involves a degree of interpretation by the researcher. You’re making connections, identifying relationships, and bringing together the data in meaningful ways that go beyond simple surface-level descriptions.
Answers the “Why?” and “How?” Themes help you delve deeper into the data to explain why people feel or behave the way they do, and how their experiences are interconnected.
Match the statements describing approaches to qualitative analysis with the correct definition This approach to analysis is ‘bottom-up’
Grounded
Match the statements describing approaches to qualitative analysis with the correct definition This approach to analysis is entirely led by the data
Grounded
Match the statements describing approaches to qualitative analysis with the correct definition This approach to analysis is ‘top-down’
Directed
Match the statements describing approaches to qualitative analysis with the correct definition This approach to analysis is led by pre-analytic
theory
Directed
Match the statements describing approaches to qualitative analysis with the correct definition Grounded or directed approaches are never mixed
together
False
Grounded theory is..
exploratory research that aims to describe a phenomenon
Grounded theory data collection..
often uses unstructured interviews
In grounded theory the completed analysis
is compared to other literature and theories
In grounded theory the codes and themes
arise from the data and the researcher’s interpretation of that data
Is this Directed analysis, grounded theory analysis or inbetween?
Conrming or extending existing theory
Uses a model e.g. Bronfebrenner’s Ecological Model
Uses themes from existing literature at the start of
the analysis
Directed
Is this Directed analysis, grounded theory analysis or inbetween?
Themes arise from the data only
Knowledge of the eld can inuence the analysis
Compare the analysis with existing theories at the
END of analysis
Grounded
Is this Directed analysis, grounded theory analysis or inbetween?
A mix of pre-determined and emerging themes
Inbetween
In qualitative research what is the advantage of using the participants own words?
Richness and Authenticity:
Nuances of Experience: Participants’ own words capture subtleties in their emotions, thoughts, beliefs, and experiences that pre-designed surveys or researcher-phrased questions might miss.
Uniqueness of Voice: Preserving participants’ language allows their distinctive perspectives, turns of phrase, and emphasis to shine through, adding texture to the data.
Preserving Context: Direct quotations embed participants’ statements within the flow of the interview or conversation, revealing the context that influences their meaning.
2. Depth of Understanding:
Grounding Interpretations: Using participants’ words grounds your analysis directly in the data, reducing the risk of imposing your own assumptions. This builds a strong foundation for your interpretations
**Exploring the “How” and “Why” **: Participants’ own explanations reveal their internal reasoning and motivations, helping to understand not just what they think, but why they think it.
3. Empowerment and Credibility:
Participant Voice: Prioritizing participants’ words acknowledges their centrality in the research process and shows respect for their experiences.
Trustworthiness: Using direct quotes strengthens the credibility of your findings by demonstrating that your analysis is rooted in the participants’ reality.
Provide three reasons why qualitative research is important in nursing.
Capturing Patient Experience: Qualitative methods go beyond clinical indicators, delving into the lived experiences of patients. Understanding their feelings, fears, motivations, and support needs allows for more patient-centered care.
Exploring Complex Phenomena: Healthcare isn’t just about physical ailments. Qualitative research helps nurses understand complex issues like decision-making processes for patients with chronic illness, the emotional impact of caregiving, and barriers to accessing healthcare in marginalized communities.
Understanding Cultural Context: Beliefs, values, and traditions shape health behaviors and responses to treatment. Qualitative research uncovers how cultural factors influence health outcomes, promoting culturally sensitive and effective nursing interventions.
Informing Evidence-Based Practice: While quantitative research is essential, it cannot always capture the nuances of human experience. Qualitative findings fill in the gaps, offering insights that can improve nursing guidelines, protocols, and interventions.
Illuminating Staff Perspectives: Understanding the challenges, motivations, and emotional toll experienced by nurses is crucial. Qualitative research can reveal factors affecting job satisfaction, nurse burnout, and the quality of care delivered, leading to improvements in the work environment.
Driving Policy Change: Qualitative findings can powerfully advocate for change in healthcare systems, policies, and resource allocation. Stories, in-depth experiences, and narratives from patients and nurses can influence decision-makers and promote more just and equitable healthcare delivery
Please give three benefits of a focus group as opposed to an individual semi-structured interview as a means to gather data in qualitative
research.
Synergy and Idea Generation: The interactive nature of focus groups encourages participants to build on each other’s ideas, leading to a greater depth and breadth of discussion. A comment from one participant might spark insights and deeper reflection from others that wouldn’t emerge in an individual interview.
Observation of Group Dynamics: Focus groups allow researchers to observe how participants interact, negotiate meaning, and potentially influence each other’s opinions. This provides valuable insights into social norms, power dynamics, and the way people’s beliefs are shaped within a group context.
Exploration of Sensitive Topics: In some cases, the group setting can offer a sense of support and reduce the pressure felt by an individual discussing sensitive topics. Seeing that others share similar experiences can be validating.
Efficiency: Focus groups allow researchers to gather data from multiple participants simultaneously, making them potentially more time-efficient than conducting several individual interviews.
Contrasting Viewpoints: Focus groups are particularly useful for exploring topics where there’s a diversity of opinions or experiences. The discussion can uncover contrasting viewpoints, which can help researchers understand the complexity of an issue more fully.
For four marks please explain what constitutes bias in qualitative research and out these can be overcome
- Researcher Bias
Problem: Personal background and assumptions may skew data collection and interpretation.
Solutions:
Reflexivity: Keep a journal to reflect on your values and biases.
Triangulation: Use varied data sources or multiple researchers for balanced analysis.
- Participant Bias
Problem: Participants may tailor responses to appear favorable or meet perceived expectations.
Solutions:
Build Rapport: Foster trust and stress the importance of honest responses.
Probing & Verification: Use follow-up questions and share findings for feedback (member checking).
- Sampling Bias
Problem: Non-representative samples limit generalizability.
Solutions:
Purposeful Sampling: Select participants based on relevant criteria.
Maximum Variation: Ensure diversity to capture a range of perspectives.
- Confirmation Bias
Problem: Favoring data that supports pre-existing beliefs.
Solutions:
Negative Case Analysis: Explore contradictory data.
Peer Debriefing: Review findings with others for objective insights.
If we were to do a qualitative study into life after a suicide attempt describe three ethical considerations that would need to be made?
Qualitative research delving into suicide presents unique ethical challenges requiring careful consideration. Here are six significant ethical problems:
Potential for Distress: Exploring suicide-related topics can evoke strong emotions, potentially triggering or exacerbating distress in vulnerable participants. This includes those with personal experience with suicide, as well as those currently experiencing suicidal ideation.
Risk of Harm: While the research goal is to prevent suicide, the process itself carries a potential risk of harm. Participants might re-experience trauma or have increased suicidal thoughts after discussing these sensitive subjects.
Competency and Consent: Assessing a participant’s capacity to provide informed consent can be especially challenging if they are experiencing emotional distress or cognitive difficulties. There’s a delicate balance between protecting those at risk and respecting their autonomy.
Confidentiality Breaches: Participants may disclose deeply personal information, and any breach of confidentiality could have devastating consequences. This is especially true in tight-knit communities or when researching individuals with a public profile.
Responsibility to Intervene: Researchers face an ethical dilemma: how to balance respecting a participant’s expressed intent to keep information private versus the duty to act if there’s an immediate risk of harm to themselves or others. Clear pre-established protocols are crucial.
Researcher Well-being: Exposure to emotionally challenging narratives can affect the researcher’s mental health, leading to vicarious trauma or burnout.
Qualitative methods are not well-suited for testing hypotheses. Briefly discuss this claim
Why Qualitative Research Isn’t Typically Used for Hypothesis Testing
Exploratory Nature: Qualitative research aims to explore phenomena, uncover insights, and build theories—not test existing ones.
Small, Purposeful Samples: Designed for depth over breadth, these samples limit generalizability, a key element of hypothesis testing.
Context and Nuance: Emphasizes individual experiences in specific contexts, making broad conclusions difficult.
Subjectivity: Involves interpretation by both researchers and participants, which contrasts with the objectivity typically sought in hypothesis testing.
But It’s Not Black and White
Hypothesis Generation: Qualitative insights often lay the groundwork for hypotheses tested later with quantitative methods.
Mixed Methods: Combining qualitative and quantitative approaches can enrich findings and allow for both exploration and testing.
Testing in Qualitative Traditions: Some methods (e.g., grounded theory) involve iterative hypothesis development and refinement.
Summary:
Qualitative research excels at exploring complexity and generating ideas but is generally less suited for rigorous hypothesis testing compared to quantitative methods.
