Qualitative Data Analysis

Module 8: Data Analysis in Qualitative Studies Qualitative Data Analysis Qualitative data analysis is used when researchers generate non-numerical data The goal of qualitative data analysis should stem from the research question or study purpose  Is the goal to increase clarity in defining a construct?  Is the goal to develop themes to characterize participants’ responses and experiences?  Is the goal to develop theory to explain an aspect of personal, social or physical realties?? Qualitative data analysis is immediate, ongoing, and spiral Immediate:  Data analysis begins as part of the development of the research  Meaning-making begins at the start of the investigation Ongoing  Researcher reflexivity should be continuous  Data analysis doesn’t take place at one moment  Researchers engage in data analysis throughout the entire research process Spiral  Data analysis is not fixed linear approach  Researchers flow through the data analysis process in analytic circles, often returning to earlier steps in the analysis as new insights are created  These analytic circles create a “spiral” form the beginning of data generation through to final account of findings  The data analysis spiral  Data collection and data analysis are concurrent and ongoing processes  Data analysis is an ongoing process of meaning making  Analysis conducted concurrently with gathering data  Involves continual reflection and making interpretations  Data analysis “steps” area guide, but not necessarily discrete  Researchers can move between steps, return to earlier steps, etc. to build on Researchers need to decide if they will utilize inductive or deductive processes (or a combination of both) “inductive analysis means that the patterns, themes and categories of analysis come from the data; they emerge out of the data rather than being imposed on them prior to data collection and analysis” Deductive analysis means that themes are provided in advance of data analysis and the researcher makes the data fit themes in a pre-existing framework Researcher as Key Instrument Researcher collects the data him/herself  Personal contact  Personal experience and engagement  Actively engaging in the life of the participant Requires a commitment to extensive time in the field  Gaining entry, gaining access, building rapport All part of the research process filtered through the lens of the researcher  Researcher’s personal experiences, characteristics, pre-existing knowledge, etc. inform the research question Researcher Reflexivity Researcher cannot be separated from the research Qualitative researchers “position themselves” by reflecting on their biases, values, experiences and background to consider how these may shape the research Reflexivity consists of two parts:  Reflecting on one’s experiences with the phenomenon being explored  Considering how one’s experiences shape the interpretation Steps in Qualitative Data Analysis Step 1: organize and prepare the data  Transcribe interviews  Type field notes  Scan images  Create files Step 2: read or look at all the data  Read and memo  Read and re-read text… do NOT jump to step 3 too quickly!!  Gain a general sense of the data and reflect on overall meaning  Immersion in entire database; get overall sense of information as a whole before breaking it into parts  Make margin notes  General thoughts, short phrases, ideas, key concepts Step 3: start coding all the data  Systematically organize and reduce the data into meaningful segments/chunks/ categories/ and assign names for segments  Often includes in vivo terms  Some methods for coding might include using sticky notes highlighters, electronic comments, spreadsheets, visual grouping Step 4: generate description or themes  Researchers look for organizing frameworks that tell the story of their data in a way that best informs their research question  Common categories might be grouped (from step 3), isolated data points might be discarded, unique elements might be highlighted  Types and numbers of themes can vary widely  Descriptions might be particularly important to allow the reader direct entry into the research  Researchers need to tell the story that best represents the data Step 5: decide how the findings will be represented  Many ways to represent findings of a qualitative study  Journal articles  Common in academia  Require peer-view  Many researchers are trained to write  Journal articles can be limiting!  Page limits  Might miss the intended audience  A written outcome might not correspond with the research Step 6: interpret the findings  Making an interpretation by making sense of the data and going beyond the themes to the larger meaning  What was learned? What is the larger story? What is the essence? How do the themes interrelate? Couched within or in contrast to literature?  Multiple interpretations of findings are okay, expected, and valued  Recall: researcher as key instrument  Strive for perspectival subjectivity The Qualitative Data Analysis: The Role of the Researcher Qualitative researchers are an integral part of the research process The researcher’s values, history and characteristics are inescapable elements of the research that shape their interpretation Qualitative Data Analysis Additional helpful hints  Slow down  Consider looking for commonalities and differences an a way to “get to know your data”  Remember that you only have a “piece”, not the whole  Be aware of challenges  Multiple researchers  Dominant voices?  Different assumptions and perspectives  There are systematic ways to analyze qualitative data, but we need to remember to rely on our brains and not just specific techniques