Growing the Evidence Base for Telemedicine Using Qualitative Research Methodologies Suparna Qanungo, PhD Assistant Professor, College of Nursing Co-Director Telehealth Research Program Medical University of South Carolina

Telehealth Use in Research

Qualitative vs. Quantitative Research ASPECT QUALITATIVE QUANTITATIVE Focus of research Quality (nature, essence) Quantity (how much, how many) Philosophical Roots Phenomenology, symbolic interaction Positivism, logical empiricism Common Purpose Understanding, interpretation, discover ideas, hypothesis generating Prediction, control, confirmation, causal explanation, hypothesis testing Approach Observe and interpret Measure and test Design Characteristics Flexible, free form, evolving, emergent Predetermined, structured Setting Natural, familiar Artificial, unfamiliar Sample Small, non-random, theoretical Large, random, representative, generalizability Researcher independence Researcher is intimately involved, “Emic” (insider perspective) Researcher uninvolved observer, “Etic” (outsider perspective) View of reality Subjective Objective Data collection Researcher as primary instrument, interviews, observation Inanimate instruments (scales, tests, surveys, questionnaires) Mode of analysis Inductive (by researchers) Deductive (by statistical methods) Findings Comprehensive, holistic Precise, narrow, reductionist Based on Merriam, 1988 and Sandelowski, 1986

Qualitative Research An inquiry process that addresses a social or human problem, analyzes words, reports detailed views of informants and is conducted in a natural setting (Creswell, 1998)

Qualitative Research Managing Life with Spinal Cord Injury (Experience, Environment) Research involving health workers visiting homes and communities (Experience, Environment) Community integration for wheelchair bound individuals

Data Collection Techniques and Sources Observations (e.g. photovoice) Documents Artifacts Interviews Focus groups Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

KI Interviews: how hard can THAT be? Mainstay of qualitative research Conduct the interview in a place and at a time which is most comfortable and convenient for the participant Unstructured conversation with a purpose Outcome of the interview is an understanding (e.g. experience, perceptions, barriers, facilitators) for those who are part of it Features audiotaping and verbatim transcription of data, and use of an interview guide Researcher must: Learn the roles of the informants Understand the culture Must have mutual trust and respect with the interviewee Must be fully engaged Communicate clearly and focused observation Understand the language Anything, phones etc. should be turned off. Fully engaged. Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

Focus groups… Should be done IF the data are appropriate for collection in a group Ideal group size is 6-10 members Should be observed for group dynamics Should be developed based on some a priori grouping Require at least 2 researchers: one to ask questions, and one to monitor equipment and observe group interactions Have to watch for “groupthink” You have to shut down overpowering people and if someone who do not speak, get them to speak Two people needed: one to conduct and other to observe interaction. If more than 2, better Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

So how do we get participants? Think about where/how they live; you can only do this if you are very well acquainted with your population Flyer distribution Community Gatekeepers Snowballing (word of mouth) Snowballing: word of mouth, give out flyers to give people who might need other people Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

Qualitative Process Key Informant Interviews (KII) Focus Groups (FG) Individual Group Ask, Listen, Interact, Record Audio Recording (Digital) Video/ Photos Field Notes Transcribe/Translate Software Human 1 hr KII/FG >6-10 hrs transcription time Data Analysis (Nvivo/Dedoose) Themes, sub-themes, barriers, facilitators Snowballing: word of mouth, give out flyers to give people who might need other people

Data Analysis Step 1. Get familiar with your data (listen to your recordings, read notes and transcripts or summaries again) Step 2. Identify codes and themes (look for regularities in data and identify segments that fit) Step 3. Coding your data (match content to coding scheme) Step 4. Organize your codes and themes (cutting out data extracts and putting them together under each code) Snowballing: word of mouth, give out flyers to give people who might need other people Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

Data Analysis For scientific findings, you have to analyze the data and not just say out the quotes and interviews.

Data Analysis Research on telehealth rehab training using gaming interventions Snowballing: word of mouth, give out flyers to give people who might need other people Some contents in this slide is courtesy Dr. Julie Barosso, Chair, College of Nursing, MUSC

Telehealth Use in Research at MUSC Mealtime Interventions for Caregivers/Dementia Patients at Respite Care Centers HIV and substance use prevention program in Latina adolescents Telehealth research for prenatal care Patient navigation to Enhance palliative cancer care services in rural India Peer Navigator interventions for individuals with spinal cord injury Nurse-guided community based outreach for stroke recovery in African-Americans Interventions to provide relief to patients with chronic leg venous ulcers

Telehealth Use in Research

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