1. Qualitative Research Designs Naturalistic Inquiry May 29
Scholarly Inquiry II
Qualitative Research Designs
Naturalistic Inquiry
May 29

2. Lectures July 12---Qualitative Analysis Due Day I 5-29 Day 2 5-31
overview
Research designs
Day
Sampling and Data Collection
Sign up for topic
Day
Data Analysis
Bring draft of questions
Day 4 6/12
In-class work day
Secure question approval
Day /14
Work day
Day 6 6/19
Midterm
July 12---Qualitative Analysis Due

3. Naturalistic (qualitative) Research Please refer to the Qualitative Research and Design Sampling handout
All designs seek to describe, understand or interpret daily phenomenon within the context in which they occur

4. Purpose of Naturalistic (Qualitative) Research Please refer to the Qualitative Research and Design Sampling handout
The purpose of qualitative research varies from developing descriptive knowledge to evolving full-fledged theories about observed or experienced phenomena.
Preferred when no adequate theory exists to explain a human phenomenon or when the investigator believes that existing theory and explanations are not accurate, true, or complete
Designs enable new insights and understanding to be revealed without the imposition of preconceived concepts, constructs, and principals

5. Qualitative (naturalistic) Designs
Endogenous
Participatory Action
Critical theory
Phenomenological
Heuristic
Ethnography
Narrative
Object reading
Life history
Case study
Grounded theory
Meta analysis
Content analysis
Ethnography
Narrative
Case study
Grounded theory
Content analysis
Phenomenological

6. Ethnography
Ethnography - The study of cultural patterns and perspectives of participants in their natural settings in order to describe, analyze, and interpret the culture of a group, over time, in terms of the group’s shared beliefs, behaviors, and language.
Key characteristics:
Carried out in a natural setting, extended immersion
Intimate, face-to-face interaction
Accurate reflection of participants’ perspectives and behaviors

7. Narrative
Narrative- Study of how humans experience the world around them through the telling of their “storied lives”. Seen more in OT literature than in other disciplines.
Narrative Analysis vs. Analysis of Narrative
Narrative Analysis is the process of collecting description of events through observations and interviews and synthesizing them into a narrative. Analysis of Narrative is the process of collecting stories and analyzing them for common themes.
Examples:
Autobiographies
Biographies
Narrative Interviews
Life Stories
Ethno biographies

8. Case Study
Case Study- Researchers focus on a unit of study called a “bounded system”. Outcomes are more concrete and allow readers to compare and contrast the case to their own life. Case study is the name of the approach and also the name of the product of the approach.
Key Characteristics:
Particularistic – focused on a particular situation or event.
Descriptive – the end result is a “thick description” of the many variables and their interactions.
Heuristic – the case study “illuminates the reader’s understanding of the phenomenon under study” beyond the reader’s original knowledge. heuristic – a simple way of arriving at a solution, so the case study illustrates how to treat someone with this disorder

9. Grounded theory
Grounded Theory- collecting, coding, and analyzing data with the goal of developing a theory based on observations
Key Characteristics:
Theory grows out of ongoing constant comparative analysis of data
Process of gathering data, coding, and analyzing and then assigning it to a category until the data becomes repetitive

10. Content analysis
Content Analysis- examining records of communication for commonalities: themes, biases, patterns. Often used in mixed method designs, combines quantitative elements (counting occurrences) with a qualitative analysis (interpreting what one person said and comparing that to what others said to come up with a synthesis of similarities and differences).

11. Phenomenography
Phenomenology- Describes the meaning of experiences of a phenomenon (or topic or concept) for several individuals. The researcher reduces the experiences to a central meaning or the “essence” of the experience.
Key Characteristics
Participants are people who have experienced the phenomenon being studied.
Interviews with up to 10 people.
Long interview protocol.
Data is in the form of interview transcriptions (usually typed up verbatim from interviews)

12. Planning a Phenomenological Study
Research question
Informant
Sample
Inclusion/exclusion
Brainstorm
Develop questions
Create a plan for interview
Trustworthiness
Data analysis

13. Thursday
Be prepared to sign up
Group
topic

14. Qualitative Research Designs Naturalistic Inquiry May 31
Scholarly Inquiry II
Qualitative Research Designs
Naturalistic Inquiry
May 31

15. Qualitative Sampling
Definition - The process of selecting a small number of individuals in such a way that the individuals will be good key informants:
Sampling is almost always purposive.
Researcher relies on experience and insight when selecting a sample

16. Types of Qualitative Sampling (CHRIS)
Criterion- participants who meet some criteria, Residents at the Buckhalter who are African American, Males with Parkinson’s who live alone
Homogeneous- Participants are very similar in experience, perspective and outlook (likely to give similar responses) Example: Women in the Tea Party
Random Purposive- When you get more participants than you need, randomly select from the pool of people who meet your criteria
Intensity - participants that represent different levels of research topic (good and poor students, experienced OTRs and inexperienced OTRs)
Snowball- when it is difficult to find participants (often due to a sensitive issue like drug use or AIDS) you ask someone who meets your criteria to find people they know who also meet your criteria

17. Choosing a good informant
Ability to be reflective and thoughtful
Ability to communicate effectively orally, in writing, or both
Ability to be comfortable with the researcher’s presence at the research site
Exposure to or special knowledge of the phenomena under study

18. What is a graduate students attitudes towards chocolate?
Sampling---
Criterion sampling---students must be currently enrolled in a graduate program.
Homogeneous---participants must be enrolled in an allied health graduate program
Random purposive---random selection (when ample participants)
Intensity---participants must have been enrolled in graduate program for at least 12 months
Snowball

19. Data Collection Observation
Interviews: Unstructured, structured, focus groups, interviews
Questionnaires: written collection of self-report questions to be answered by a selected group of research participants (can collect large amounts of data in short period of time, but responses can only be on the form provided)
Examining Records- naturally occurring in many settings , for example: archival documents, personal journals, maps, video or audiotape, artifacts (Egyptian tomb or product of an OT task group like a client’s collage)

20. “Validity & Reliability” in Qualitative Research (Trustworthiness)
Internal validity- truth or authenticity and credibility (author must explain the complexities of the research and address problems that are not easily explained)
External validity- Transferability (must have enough detail so the reader can identify with the setting or ‘see’ the context
Reliability- Consistency and dependability (address the stability of the data collected)
Objectivity- Confirmability- extent to which others can corroborate the findings, use audit trail
Internal validity—
To what extint are biases and personal perspectives of the investigator identified and considered in the data analysis and interpretation
What actions have the investigators taken to enhance the credibility of the investigation
Transferbility we are are not concerned with the ability to generalizability or external validity in the traditional sence. We are concerned with richness and depth leads to the ability to transfer not generalize meaning

21. Strategies for Trustworthiness
Prolong participation at the study site (data saturation) – this helps overcome distortions.
Peer debriefing – test your growing insights with other professionals.
Collect documents, artifacts or other “raw” data items – as background confirmation.
Audit trail – clear description & documentation of thought process used to interpret data (to allow external reviewers to verify the processes of data collection, analysis and interpretation)
Triangulation – collect data in multiple ways example: observation, journaling, questionnaire
Member checks – test the overall report with participants before final publication.

22. Strategies for Dependability
Examine the results of an inquiry and determine whether the data would be collected consistently if the same techniques were used again
Remember that the goal is NOT generalizability
What is the experience of individuals inlisting in the armed forces?
much different immediately following 911

23. Review Topics

24. Qualitative Research Designs Naturalistic Inquiry June 7
Scholarly Inquiry II
Qualitative Research Designs
Naturalistic Inquiry
June 7

25. Data Analysis
Requires the researcher to make sense of all of the data from multiple sources.
Analysis involves answering the question: “What’s in there?”
Requires dependable and accurate summation.
There are multiple ways to analyze qualitative data that will yield a “correct” outcome.

26. Felice D. Billups, EdD., NERA Webinar Presentation
FOUR BASIC STEPS
All qualitative data analysis involves the same four essential steps:
1. Raw data management
2. Data reduction
3. Data interpretation
4. Data representation – ‘telling the story’,
‘making sense of the data for others’
Felice D. Billups, EdD., NERA Webinar Presentation

27. Steps to Data Analysis
Reading/Memoing – read the transcripts, field notes, etc. and take notes, highlight, underline, etc.
Describing – create a detailed picture of the participants, setting, and phenomenon of study from your data.
Classifying – break down the data into small units or chunks, then collect similar ideas or concepts into categories.
Data reduction
Get a sense of the data holistically, read several times (immersion)
Classify and categorize repeatedly, allowing for deeper immersion
Write notes in the margins (memoing)
Preliminary classification schemes emerge, categorize raw data into groupings (chunking)
Repeat data reduction
The process of reducing data from chunks into clusters and codes to make meaning of that data:
Chunks of data that are similar begin to lead to initial clusters and coding
Clusters – assigning chunks of similarly labeled data into clusters and assigning preliminary codes
Codes – refining, developing code books, labeling codes, creating codes through 2-3 cycles

28. Stratagies
Coding – while reading the data, labeling similar passages of text with a code
Coding is the process of combing the data for themes, ideas and categories and then marking similar passages of text with a code label so that they can easily be retrieved at a later stage for further comparison and analysis.
Identifying themes – organize the “big picture”. Do patterns emerge?

29. Data Analysis
Data Interpretation- goal is to find meaning in the data, must answer these four questions:
What is important in the data?
Why is it important?
What can be learned for the analysis and interpretation?
So what?