How and What We Learn from Interviews, Focus Groups, and Participant Observation
NRSA Trainees Research Conference Slide Presentation (Text Version)
By Daniel Dohan, Ph.D
On June 5, 2004, Daniel Dohan, Ph.D, made a presentation at the 10th Annual National Research Service Award (NRSA) Trainees Research Conference. This is the text version of his slide presentation. Select to access the PowerPoint® slides (70 KB).
Slide 1
Using and Interpreting Qualitative Data: How and What We Learn from Interviews, Focus Groups, and Participant Observation
Daniel Dohan, Ph.D.
Institute for Health Policy Studies &
Dept. of Anthropology, History, & Social Medicine
University of California, San Francisco
Slide 2
Research Background
- Poverty, culture, and healthcare.
- Projects and methods:
- The Price of Poverty: Solo p-o.
- Cancer & culture: Solo p-o and iv's; team focus groups.
- Welfare & substance abuse: Team iv's.
- Poverty & stigma: Team p-o and iv's.
Slide 3
Overview
- Qualitative and quantitative approaches.
- Producing qualitative data.
- Analyzing & publishing qualitative results.
Slide 4
All Researchers Face Four Fundamental Tasks
- Selecting subjects to study.
- Interacting with subjects to gather data.
- Avoiding arbitrary findings.
- Convincing others of what you found.
- Quant & qual approach tasks differently:
- Quantitative: four R's.
- Qualitative: four P's.
Slide 5
Different Approaches to Research:.4 "R's" versus 4 "P's"
Research Task |
4 R's
(Quantitative) |
4 P's
(Qualitative) |
How do I select research subjects? |
Representativeness |
Purposefulness |
How do I work with subjects to get data? |
(non-)Reactivity |
Participation |
How do I avoid arbitrary findings? |
Reliability |
Process |
How do I convince others of my findings? |
Replicability |
Particularity |
Slide 6
Tasks by Research Activity
Research Task |
Research Activity |
How do I select research subjects? |
Data Collection |
How do I work with subjects to get data? |
How do I avoid arbitrary findings? |
Data Analysis |
How do I convince others of my findings? |
Slide 7
Quantitative and Qualitative Research Activities
(Data Collection row is highlighted)
Research Activity |
Quantitative Approaches |
Qualitative Approaches |
Data Collection |
- Representativeness: Random samples of pre-determined groups.
- Reactivity: Fixed data collection instruments.
|
- Purposefulness: Sites and subjects sampled according to needs.
- Participation: Flexible data collection strategies.
|
Data Analysis |
- Reliability: Hypothesis testing via statistical inference.
- Replicability: Standard reporting formats (tables, etc.).
|
- Process: Iterative coding and memoing to refine results.
- Particularity: Narrative reports of findings in context.
|
Slide 8
Quantitative and Qualitative Research Activities
(Data Analysis row is highlighted)
Research Activity |
Quantitative Approaches |
Qualitative Approaches |
Data Collection |
- Representativeness: Random samples of pre-determined groups.
- Reactivity: Fixed data collection instruments.
|
- Purposefulness: Sites and subjects sampled according to needs.
- Participation: Flexible data collection strategies.
|
Data Analysis |
- Reliability: Hypothesis testing via statistical inference.
- Replicability: Standard reporting formats (tables, etc.).
|
- Process: Iterative coding and memoing to refine results.
- Particularity: Narrative reports of findings in context.
|
Slide 9
"R's" or "P's"? Depends on Your Question
R's:
- Population is well defined, accessible, and appreciates non-reactivity.
- Available measures are appropriate and support hypothesis testing.
P's:
- Population is unclear, inaccessible, or uncomfortable with research institutions.
- Available measures are unavailable, problematic, or undesirable.
Slide 10
Collecting Qualitative Data
- Talk to people:
- Individual interviews, focus groups.
- Interact with people:
- Participant-observation (p-o).
- Read what people write:
- Scholarly publications (literature reviews).
- Private archives (historical analyses).
- Popular publications (content analyses).
Slide 11
Qualitative Data Production: Interviews, Focus Groups, P-O
HI Interviews <=> Focus Groups <=> P-O LOW
- Control over production:
- Specificity of data for research question.
- Scalability of production:
- Amount of data that can be collected.
- Intrusiveness of production:
- Range of addressable questions.
Slide 12
Analytic Principles
- Analyze cases:
- Retain holism, contingency, complexity.
- Balance analysis and data.
- Analyze iteratively:
- Let new data inform ongoing analysis.
- Revise analytical categories as needed.
- Pursue new questions that emerge during write-up.
Slide 13
Analytic Principles
- Coding data:
- Mark, corral, and reduce data.
- Start with codes a priori or allow to develop.
- Codes evolve with time and experience.
- Analyzing data and codes:
- Mimic quantitative by counting, correlating.
- Reduce data and focus analysis.
- Proliferate codes to see layers of meaning.
Slide 14
Computer Assistance
- Does not alter analysis process.
- Usually not a shortcut or timesaver.
- Programs fit different data & needs.
Slide 15
Computer Software
- Atlas-ti: large datasets, unstructured coding, mimic paper code & sort.
- NUDIST: large datasets, structured coding, mimic quant analysis.
- NVivo: less data, unstructured coding, find patterns/relationships in codes.
- Folio Views: huge datasets, focused coding, search & sort.
Slide 16
Publishing
- Journals approach to qualitative findings:
- CMP, SSM: collect/analyze data, send it in.
- AJPH, HSR, JNCI: qualitative is exception.
- Targeting the "exceptional" journals:
- Supplement quantitative approach.
- Mimic quantitative approach.
- Answer question quantitative approach can't.
Current as of September 2004
Internet Citation:
Using and Interpreting Qualitative Data: How and What We Learn from Interviews, Focus Groups, and Participant Observation. Text Version of a Slide Presentation at a National Research Service Award (NRSA) Trainees Research Conference. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/fund/training/dohantxt.htm