Doing qualitative research: study design, sampling, data collection Elizabeth Boyd, PhD EPI 240 January 15, 2008.

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Doing qualitative research: study design, sampling, data collection Elizabeth Boyd, PhD EPI 240 January 15, 2008

Recap: Using qualitative methods To interpret, illuminate, illustrate To understand why or how To describe previously unstudied processes or situations To learn about subjects who are few or hard to reach To brainstorm ideas

Research questions - what do you want to understand? Meaning Context Unanticipated phenomena Process Explanations Opinions Attitudes Understandings Actions

Formulating research questions Pub bias example Your examples Common problems: Too broad Impossible to find answers or ‘how to operationalize’ Really asking a quantitative question

Data collection Based on what you want to know: Where do you go to find out? Site selection Who do you ask/observe? ‘Sample’ What do you ask/do? Data

Choosing your site Justification: why is this site the best for answering your research questions? Naturalistic? Ethnography; video Public vs. private settings Neutral? Interviews; focus groups

Choosing your site Implications Ethical Role as researcher-caregiver Logistic How to gain access? How to gather data?

‘Sampling’ Who will you include in your study and why? Everyone (ethnography) Sample -- need sampling strategy Random Convenience Purposeful  Typical  Hetereogenous  Extreme cases/comparisons

Data collection Once you have identified your site and participants, practical matters include: Timing -- when to go/how long to stay? Fitting in Establishing relationships -- Who? How? How much? Equipment: Recording devices Hand notes Video/digital Impact on participants Cost/transportability/impact

Quality in qualitative research Two ‘phases’ -- data collection and write-up Overall: quality = credibility Credibility is achieved through depth, clarity, nuance

Rich and sufficient data Enough background to understand and portray full range of persons, processes, settings Detailed description of range of views & actions -- multiple perspectives Beyond superficial Analytic categories -- complexity Comparisons -- generative or general? Saturation -- stop seeing new cases/instances

Bottom Line Regardless of the type of data you are working with, Ground ALL observations, analyses in the particular details of your data

Managing your data … You’ve interviewed 10 (or 20, or 30, or 100) people, now what? Transcription Coding Analysis

Transcription Written representation of the interview Types of transcription: “Cleansed” transcript “Just the words” “Jeffersonian” transcript

The “cleansed” transcript Dr. E: I’m deputy editor of Annals of Internal Medicine. I was associate editor from 1978 to 1999, and I was deputy editor from 1999 to My sub-specialty is pulmonary disease which I practice every day at the University of Pennsylvania. Most of the editors at Annals do practice, though not as extensively as I do. …

“Just the words” IR:So today is March seventh. I’m at Annals of Internal Medicine and I’ll be interviewing Dr. P.E. And for the record can you state your name and position? DrE: It’s P.E. I’m deputy editor of Annals of Internal Medicine. IR: Okay. And how long have you been working at Annals? DrE: Since It’s a long time. I was associate editor from 1978 to 1999 and I’ve been deputy editor from 1999 to 2003.

“Jeffersonian” transcript IR: So: today is March seventh, I’m at Annals of Internal Medicine and I’ll be interviewing doctor Pete Ernest. (0.4) A::nd um for the record can you state your name and position? IE: It’s Pete Ernest, I’m deputy editor of Annals of Internal Medicine. IR: Okay. And how long have you been working at Annals? (0.4) IE: Since nineteen seventy eight. It’s a lo::ng time. I was uh:: associate editor from nineteen seventy eight t nineteen ninety ni:ne, …

Which transcription method to use? Speed versus detail and accuracy versus cost What are you most interested in learning -- Content? Narrative? Interaction?/Context?

Assignment If necessary, refine your research questions Describe your sample and data collection protocol Describe how you will prepare your data for analysis Be sure to defend your choices!