HealthPsyc4 Flashcards
Qualitative & Quantitative comparisons
- Binocular vision
- Balancing strengths and weaknesses
- Teamwork- utilising qual. and quant. in research
- Value of mixed method approach- not one team or the other
Research paradigms: Qualitative
Interpretivism • Researcher & social world interact • Characteristied by interpretivist theory of knowledge • Facts & values not distinct • Affected by researcher values & perspectives • Not possible to do objective, value-free research
Research paradigms: Quantitative
Positivism
• World unaffected by the researcher
• Facts and values distinct, possible to do objective, value free research that is generalisable
• Natural science method (hypothesis testing, causal
explanations appropriate to understand social phenomena)
Qualitative General framework/ objectives
Explore phenomena (describe, gain insight)
Quantitative General framework/ objectives
Confirm hypotheses about phenomena (quantify, predict)
Qualitative Data Format
Words, pictures, objects
Quantitative Data Format
Numerical data
Qualitative Question format
Open-ended
Quantitative Question format
Closed
Qualitative flexibility in design
Flexible, iterative
Quantitative flexibility in design
Fixed design from beginning
to end
Qualitative Sampling
Sampled to reflect diversity of the population (purposive), to access hidden groups (snowball) or to test emergent hypotheses (theoretical)
Quantitative Sampling
Probability sampling to be
statistically representative of
the population
Qualitative data collection & analysis
Dynamic process>
Interactive & responsive to
emergent topics
Analysis Content> analysis
Identify themes, relationships
between themes and underlying
explanations
Quantitative data collection & analysis
Static process>
Questions pre-formulated &
standardised
Statistical analysis>
Identify relationships
between variables and the
strength of relationships
When to use qualitative research
When there is not much to go on:
• Little known about the topic, limited theory to guide topic
• E.g. We don’t know much about family involvement in cancer consultations
• When you want a particular perspective on the topic:
• The perspective of a specific person/group, or a more holistic perspective
• E.g. More specifically, we need to know about how health professionals perceive family involvement
• When you want to explain quantitative results:
• E.g. Why do people prefer one intervention to another?
• E.g. Why does gender influence compliance?
• When you want to identify relevant questionnaire items
• E.g. Why did you decide to receive the HPV vaccine?
Common features of qualitative research
- Uses INDUCTIVE reasoning
- using observations to formulate an idea or theory
- exploring new phenomena
- Starting with observations»_space;» theory
- Doesn’t typically use DEDUCTIVE reasoning
- using a known idea/theory and applying it to a different situation
- usually begin with hypotheses and focus on causalities
- Starting with theory»_space;» confirmation
• Has high VALIDITY
• measuring what we are supposed to measure
• e.g. describe your perception of the experience of
chemotherapy in your own words
• Has low RELIABILITY
• inconsistent response given same conditions
• e.g. describing the same experience of chemotherapy in a different way on two separate occasions
Methods: Data collection
- Interviews
- Open ended questionnaires
- Observation
- Participant / non-participant
- Overt / covert observation
- Document analysis (written/audio/video)
- Oral histories
Methods: Interview types
• Structured interview
• Set questions, set order, usually with a limited range of
responses
• Semi-structured interview
• Open-ended questions, with prompts to gain further insight
• In-depth interview
• One or two issues covered in detail
• Questions follow what the interviewee says
• Focus groups
• A form of group interview that capitalizes on communication between group participants
Methods: Sampling
- Small samples
* Seeking to gain rich insights, not generalise findings
Purposive Sampling
- Participants recruited according to pre-selected criteria relevant to research question
- Participants have the required experience or knowledge that researchers seek
Convenience Sampling
- Participation invited because individuals are conveniently (opportunistically) available- access, location, time and willingness
- Relatively fast and easy
Theoretical Sampling
• Used in grounded theory studies
• Research starts from homogenous (small) and moves to a more
heterogeneous (larger) sample
• Occurs sequentially and alongside data analysis
• Previously analysed data guides what data needs to be collected next
Snowballing Sampling
• Recruiting one or a few people and then relying on these people
to put the researcher in touch with others.
• Useful where the sample are marginalised/stigmatised individuals and to find and recruit ‘hidden populations’
Methods: Data Analysis
• Data usually presented in written form (observations,
transcribed audio-taped interviews)
• Data is transcribed, coded, categorised
• Code and categorise
• Present themes/patterns from data
• Concept of ‘saturation’ of data
• Phase of analysis in which the researcher has continued sampling and analysing data until no new data/themes appear
Problems with qualitative research
• Ensuring rigour
• Use appropriate methods to maximise validity and reliability
• Results may be influenced by personal bias &
idiosyncrasies
• Generalising beyond the sample
• Aims to capture the range of views, not representative views
• Time consuming
• Smaller samples based on theoretical saturation are achievable
Rigorous sampling
- Purposive sampling to maximise likelihood of capturing all views
- Recruit a range of participants for key variables likely to influence views
- e.g. range of ages, gender, socio-economic status
- Practical considerations also important (e.g. snowball sampling for ‘hidden’ populations)
- New variables may emerge in analyses and prompt additional sampling of different groups
- Sampling continues until no new themes are identified in three consecutive interviews- ‘saturation’
Rigorous data collection
- Interview / focus groups:
- Audio or video-taped
- Transcribed in full
- Participant confidentiality assured
- Interviewer:
- Suitably trained in qualitative methods
- Accepted by participants as trustworthy
- Familiar with the context
Managing personal bias & idiosyncrasies
Investigators own personal bias and idiosyncrasies can influence the qualitative research process» need to be reflexive
• Reflexivity - awareness of the way own beliefs/attitudes affect the research process and outcomes
• One technique— use of a journal throughout research process which reflects researcher’s thoughts, feelings, questions, frustrations.
• Researcher may become aware of biases/assumptions
» may alter the way they collect data or approach analysis
Rigorous coding
• Development and application of coding frame (with
themes/concepts) can improve rigour
• Immersion in the data (e.g. read transcripts multiple times)
• Multiple researchers should code some of the same transcripts and compare results to improve the coding frame
• Apply final coding frame systematically to all the data by annotating the transcripts with codes
Rigorous analysis
Agreement between the researchers on the categorisation of data
can be calculated
• Map the relationships between themes to explain findings
• Make sure the themes/concepts are supported by the data rather
than based on your assumptions
• There are qualitative data programs that can help!
• Nvivo (www.qsrinternational.com)
• Excel- Framework analysis
Rigorous validity checking: Triangulation
• Compare same issue from different sources, methods, points (e.g.
researcher notes, interview transcripts, audio-tapes)
Rigorous validity checking: Provide evidence for themes/concepts
• Use participants’ own language to demonstrate the source of the theme or concept (e.g. illustrative quotes)
Rigorous validity checking: Participant feedback/validation/verification
- Member checking
* Ask participants to review your interpretation of their data
Choosing a qualitative approach
Many different qualitative approaches- differ in theoretical underpinnings and practical considerations
• Share many similarities- often more than one approach that could reasonably be employed to explore a topic
• Depends on many factors:
• Research topic area
• Research aims/question
• Researcher experience/training
• Intended audience
• Practical considerations (e.g. number of participants, time, budget)
Common qualitative approaches: Grounded Theory
• Strong tradition grounded theory in health research
Aims
• to collect and analyse qualitative data to
• describe components of a phenomenon
• the relationships between them
• generate a theory of the phenomena that is ‘grounded’ in the data
Methods
• Complex iterative process, no distinct end point
• Coding: identifying/describing codes, relating codes to one another
• Memoing: Recording thoughts/ideas as they evolve
• Diagrams: Make sense of the data with respect to the emerging theory
Common qualitative approaches: Interpretive Phenomenological Analysis (IPA)
Aims
• To gain a detailed examination of the participant’s lifeworld, personal experience/perceptions of an event
• To gain understanding of the lived experience through its meaning to individuals
• Methods
• Data collection: open questions, look for meaning of the experience for that person, check interpretation with the person
• Data analysis: Goal is to describe phenomena and improve understanding; Might not have obvious ‘conclusions’
Common qualitative approaches: Ethnography
• Aims
• Seeks to understand human behaviour and individuals’ experiences within
a group culture
• What is the experience of a breast cancer support group participant?
• Methods
• Most common approach is participant observation (e.g. field research)
• Ethnographer becomes immersed in the culture and records extensive field notes
Thematic analysis
- Useful approach for doing applied qualitative research in health
- Method for identifying, analysing, and reporting patterns (themes) within data.
- Highly flexible- not bound to a particular theoretical approach
- Progresses from description of data»_space;> interpretation of the significance of patterns and their broader meanings and implications
- Authors provide step-by-step guide to thematic analysis
Framework method
• Ritchie and Spencer (2002)
• Analytic approach which sits within the broad family of thematic
analysis
• Tool for supporting thematic analysis because it provides a
systematic model for managing and mapping data
• 7 key steps
Framework method- Key steps: Stage 1: Transcription
- Good quality audio recording
- Verbatim transcription of the interview
- Process of transcription is a good opportunity to become immersed in the data - strongly encouraged for new researchers.
Framework method- Key steps: Stage 2: Familiarisation with the interview
- Becoming familiar with interview using audio recording/transcript and any reflective notes is a vital stage of interpretation
- Helpful to re-listen to audio recording
- Can make contextual notes on the transcript
Framework method- Key steps: Stage 3: Coding
• Researcher carefully reads the transcript line-by-line applying a
label (code) that describes what they have interpreted as important
• Codes can refer to:
• Substantive things (behaviours, incidents)
• Values (beliefs, attitudes)
• Emotions (fear, frustration, admiration)
• Coding aims to classify the data so it can be compared systematically with other parts of the dataset
• Independent coding of multiple team members important
Framework method- Key steps: Stage 4: Developing a working analytical framework
- After coding a few transcripts, team members should meet to compare codes and agree on a set of codes to apply to all transcripts
- Codes can be grouped together into categories/subthemes/themes (tree)
- Forms a “working analytical framework”- likely to undergo several iterations
Framework method- Key steps: Stage 5: Applying the analytical framework
- Working analytical framework then applied by indexing transcripts using themes/categories/codes
- Can use specialist software, tracked changes (comments) in Microsoft word, or pencil/paper
Framework method- Key steps: Stage 6: Charting data into the framework matrix
• Qualitative data are voluminous
• Being able to manage/summarise data is a vital aspect of analysis
• Spreadsheet used to generate a matrix and data are charted
• Rows (cases), columns (codes) and ‘cells’ of summarised data
• Provide a structure into which the researcher can systematically reduce the
data, in order to analyse it by case and by code
• Should include illustrative quotations
Framework method- Key steps: Stage 7: Interpreting the data
Analysis of the framework within and across themes and participants
to identify overarching themes and relationships
• Characteristics of and differences between the data are identified
• Typologies
• Theoretical concepts
• Mapping connections between categories
Framework method- Strategies ensuring rigour
Specific strategies to ensure methodological rigour
• Immersion: Steps 1 and 2 focus on researcher immersion with the data
• Team-based coding: Advocates for several researchers to engage in coding and for all team members to read summaries to offer perspectives during analysis
• Close attention to participant experiences: Through chartingresearchers pay close attention to describing the data using participant’s own expressions, before moving onto interpretation
- Systematic, thorough analysis: Systematic procedures makes analysis easy to follow
- Inclusion of contextual data: Flexible enough that non-interview data (e.g. field notes taken during interview or reflexive considerations) can be included in matrix
- Audit-trail: Framework method ensures there is a clear audit trail from original raw data to final themes, including illustrative quotes.
Framework method- Pitfalls
- Temptation to quantify: Systematic approach, matrix format, spreadsheet-look»> can be appealing to those trained quantitatively- increases temptation to quantify the qualitative data (e.g. “13/20 participants said …”)
- Resource intensive: Framework method is time consuming and resource-intensive
- High training needs: High training component to successfully use Framework Method
