Qualitative Research Flashcards
Nature of reality for a positivist (quantitative) vs constructivist (qualitative)
Positivist - a regular reality is “out there” and can be explained
Constructivist - reality is multiple and subjective, constructed by the individual
Relationships for positivist (quantitative) vs constructivist (qualitative)
Positivist - researcher is independent
Constructivist - researcher interacts and co-creates findings with participants
Values for positivist (quantitative) vs constructivist (qualitative)
Positivist - objective, values and biases are limited
Constructivist - subjectivity is valued
Methods for data collection for positivist (quantitative) vs constructivist (qualitative)
Positivist - deductive, quantifiable and generalizable
Constructivist - inductive, narratives, in-depth understanding of certain groups
What is qualitative research?
An approach that seeks to elucidate an in-depth understanding or exploration of a phenomenon of interest
Relying on non-numerical data points (eg. narratives, observations, reflections, and photos) to explain processes or patterns of human behaviours that may otherwise be difficult to quantify
What is the purpose of qualitative research?
- Develop in-depth understanding and/or connections between constructs/concepts (eg. to build or explain a theory)
- Explore unique experiences of a certain phenomenon or circumstances
- Understand how a particular intervention has influenced or impacted an individual
Qualitative study designs - descriptive
A common technique in nursing and healthcare to describe,
explore, understand, summarize a phenomenon of interest
Advantages: Flexible, simple, and be applied in many contexts
Disadvantages: Lack scientific rigor / qualitative position
Qualitative study designs - phenomenology
Describing lived experiences → but what are lived experiences?
Schutz (1960) → lived experience is how an individual perceives or experience the world of everyday life through his or her interactions with objects, persons, and events
Purpose: Using interviews to understand an individual’s lived experience (e.g., living with COVID-19)
Qualitative study designs - ethnography
A work that describes culture → researchers spend an extended duration immersed within the culture
* Living with the participants
* Observing their behaviours within their natural environment
* Documenting using photos, observations (field notes), and interviews
Purpose: To define and/or study culture (e.g., understanding caste system)
Qualitative study designs - grounded theory
Understanding social processes with a goal of developing a theory
* Theory explains mechanisms (What? Why? How?)
* Symbolic interactionist approach → people behave and interact → they interpret or give meaning to certain symbols (e.g., dressing, communication)
* Purpose: Use interviews to understand these processes → make sense of how they interact (if they do), and what happens after
Qualitative study designs - participatory action research
A form of social research (group-based) that involves people in a process of change:
- Researchers
- Members of the community /
organization of interest
Example: Understand a community’s world view → what are the circumstances that led to this situation?
Allow community members to feel empowered, less threatened and increase ownership of the problem and results
What are the common sampling strategies in qualitative research?
Non-probability:
Convenience sampling
Purposive sampling
Snowball sampling
What is convenience sampling?
Selecting participants based on convenience (e.g., within existing network)
- Example: Evaluate effects of resilience programs
- Benefits: Readily available, easy to access and collect, and cost effective
- Drawbacks: Sampling bias, may not contribute meaningfully to your qualitative study
What is purposive sampling?
Selecting participants based on certain characteristics (e.g., disease, exposure, received certain training)
- Example: Explore participants’ perception of resilience training
- Benefits: Meaningful contribution to the phenomenon of interest, in-depth understanding
- Drawbacks: Difficult to find participants
What is snowball sampling?
Initial participants will help identify or recruit future participants (e.g., cases that are not easy to locate)
- Example: Exploring patients with HIV’s perception of resilience
- Benefits: Meaningful contribution to the phenomenon of interest, in-depth understanding
- Drawbacks: Difficult and slow recruitment, reliance on initial network
Rationale behind the sample size of qualitative studies
Qualitative studies often look at ‘depth’ of data and has a relatively small sample size when compared to quantitative
Determine the sample size for qualitative studies
Strategy 1: Previous similar studies
- Provide an approximate number → ethics application or study protocol
Strategy 2: Obtaining data saturation or information redundancy
- No new codes or ideas are emerging from the data → may not be necessary to continue data collection
- Can confirm saturation → adding 1-2 more interviews
Qualitative data collection methods - interviews
Most common data collection tool to gather in-depth data
- Structured, semi-structured or unstructured interview guides
- Conducted face-to-face (either physically or virtually)
- Can be done individually or in groups (Focus group discussions)
- Advantages: Able to clarify ideas, identify non-verbal cues (e.g., emotions)
- Disadvantages: Time consuming, manpower intensive (transcribing), scheduling, challenging for new interviewers
Qualitative data collection methods - instant messagin
Interviews that are done either synchronously or asynchronously via communicative tools such as Skype, Telegram
- Advantages: Easy to schedule, no need for transcription, can maintain anonymity
- Disadvantages: Unable to obtain non-verbal cue
Qualitative data collection methods - surveys
Open-ended questions either physically or virtually
- Advantages: Inexpensive and relatively easier to administer
- Disadvantages: Unable to clarify with the participants, or get quality data
Qualitative data collection methods - field notes
Researcher records their emotions, participants’ non-verbal expressions or situations that they observe to complement other research data (e.g., interview)
Qualitative data collection methods - photos
Using photos or images
- Advantages: Allow participants to express their perceptions about topics that may be
difficult to verbalize (e.g., depicting heaven)
- Disadvantages: Participants may not do sufficient preparatory work (take photos) or may send you copyright images
Qualitative data collection methods - observations
Researcher spends time in the environment of interest to observe and record their findings
Qualitative data collection methods - open source
Forums, chatrooms
Sensitivity of the topic in qualitative research
Conforming to societal norms?
E.g., Talking about suicide, death and dying can be challenging
- E.g., Topics relating to sexual orientation may be uncomfortable within
Singapore
- Possible strategies: Purposive sampling and snowball sampling to identify
suitable participants, using instant messaging may be helpful
Participant involvement in qualitative research
Individual or group? Schedule?
E.g., Participants feel safe enough to provide their responses within a group
E.g., Nurses often have shift work, they may not be able to commit to a
common group timing
- Possible strategies: Using individual virtual interviews may be helpful to
collecting their responses
Types of data in qualitative research
Interviews? Observations?
Does interviewing lead to socially desirable responses?
* E.g., Do nurses count the respiratory rate when taking vital signs?
* Potential strategies: Covert observations, or instant messaging techniques
may allow participants to be more forthcoming
Feasibility in qualitative research
What is available? Is it possible? Time frame?
- E.g., I want to interview people who vape, but vaping is illegal in Singapore
- E.g., I want to interview all PhD nursing students around the world
- Potential strategies: Use instant messaging, or open-ended survey
questions can be helpful
Data analysis in qualitative research - overview
preparation -> preliminary coding -> developing codebook -> code all transcripts -> group all codes -> synthesise and create new coherent story
Data analysis - inductive coding = data driven
- “Bottom-up approach”
- Codes and themes are
developed based on
the findings - Advantages:
Generate new insights - Disadvantages:
Reliance on researcher
→ biasness or
subjectivity - Example: Thematic
analysis
Data analysis - deductive coding = analyst driven
- ”Top-down approach”
- A pre-set framework
or theory is used to
guide the analysis - Advantages: Easier
to adopt for a new
analyst - Disadvantages: Omit
or ignore emerging
insights of relevance - Examples: Content
analysis or framework
analysis
Data analysis in qualitative research - thematic analysis steps
Step 1
* Reviewing all transcripts for verbatim accuracy
* Immersing in data by reading all transcripts
Step 2
* Generating initial codes (highlighting in different colours)
* Developing a code book
Step 3
* Grouping codes with similar meanings
* Searching for potential themes and subthemes
Step 4 and 5
* Reviewing and naming
themes and subthemes
Step 6
* Producing the report using
both visual and narratives -> subheaders for themes and including quotations
Data analysis in qualitative research - framework analysis
Deductive analysis method
* Using a pre-determined theoretical framework or conceptual
framework to guide the data analysis
* Example: Exploring participants’ perception of a resilience
program
Research questions
* What were the participants’
experiences of the RISE program?
* What were the contextual factors?
* How did the RISE program impact
participants’ resilience?
Why framework analysis?
* Guided approach to draw out
specific information to support
the refinement of an intervention
* Understand the impacts of the
intervention
Data analysis in qualitative research - content analysis
Example: You want to explore participants’ perception of the various
features in the resilience training
Unit of analysis: Individual interview transcripts
Categories: Features of the resilience program
Trustworthiness strategies in qualitative research
(the criterion - the test)
truth value - credibility
applicability - transferability
consistency - dependability
neutrality - confirmability
Explain:
Trustworthiness strategy - credibility
Confidence in the truth of the findings
* Ensure an accurate description or interpretations of human experience that individuals with similar experiences would recognize these descriptions
Eg:
* Prolonged engagement
* Member checking
* Interview technique
* Reflexivity journal
* More than one data analyst
Explain:
Trustworthiness strategy - transferability
Extent to which a reader
can transfer the findings to
another similar situation or
context
Eg:
* Thick description of
the sample, setting,
and context
Explain:
Trustworthiness strategy - dependability
Stability of the findings
across time
* Ensure that research can be
audited; variations can be
traced back to identifiable
sources
Eg:
* Dense description of
research methods
* Triangulation
* Peer examination
* Audit trail of
decision-making
process
Explain:
Trustworthiness strategy - confirmability
Stability of the findings
across contexts and
population
* Neutrality of the data as
opposed to the researcher
Eg:
* Triangulation
* Reflexivity
* Peer debriefing
What are the common guidelines for qualitative research?
Consolidated criteria for Reporting Qualitative research checklist (COREQ)
Enhancing Transparency in Reporting the synthesis of Qualitative research checklist (ENTREQ)
