The Use of Qualitative Data Analysis Software (NVivo): Early Career Experiences of Young Adults with ADHD

European Sociological Association Research Network 20 Con
Barbara Mather
Presentation Date: 
Thursday, September 1, 2016
Event or Conference: 
Qualitative Research Summit/Qualitative Methods Conference, Krakow, Poland
Presentation Type: 
Paper Presentation
Boyer's Domain: 
Presentation Location: 
United States
Associated Awards: 
Sept 2016 Faculty Honorarium Award
Abstract: 
The tasks of analyzing, thematically coding, and synthesizing volumes of data collected—or in this case, hundreds of pages of transcribed interview results—are streamlined and more rapidly performed when data analysis software is utilized. The ease in which to recode data in multiple iterations allowed the researcher to discover additional important information about her participants not directly related to the research question of: What are some of the challenging work experiences as described by young adults with ADHD in a structured work environment? In this qualitative research study, the challenges that young adults (ages 22-28) with ADHD experience in the workplace across the USA were analyzed and then categorized into four distinct types of workplace challenges. Recoding & further analysis using NVivo led to an additional finding not directly related to the research question: that is, the effect of self-awareness in young adults with ADHD & how self-awareness can mitigate or influence one’s workplace behaviors towards these challenging work experiences. Noteworthy in this research was the finding that the young adults with ADHD who demonstrated the highest levels of self-awareness either participated in the past, or are currently engaged in, counseling or therapy of some form. Prior research findings suggest that individuals with ADHD typically suffer from much lower self-awareness as compared to those without ADHD. The researcher will emphasize the opportunities provided by use of qualitative data analysis technology and software when applied to qualitative research projects that generate significant volumes of data to be analyzed. The ability to perform iterative thematic content analyses is significantly enhanced and supports a more rigorous and thorough ability to analyze content using qualitative data analysis software.