The Professional Counselor | Volume 10, Issue 4 569 Data Analysis The overarching purpose of the data analysis process is to bring structure and order into understanding the data for the purpose of addressing the research questions (Patton, 2015). In phenomenological research, there are many paradigms and differing worldviews on data analysis, including the issue of whether it is most suitable to analyze participant narratives through an ideographical approach or amass the data into qualitative themes (Moules et al., 2015). Accumulation of data with an analysis of themes was selected as the phenomenological data analysis approach. The results of the study were analyzed through Creswell’s (2014) approach to phenomenological analysis. Throughout the analysis, the research team bracketed their presuppositions and assumptions. The purpose of bracketing was to allow the voices of the participants, not the researchers, to dominate the analysis. Following the interviews, the recordings were transcribed (using pseudonyms), and the transcriptions were reviewed for accuracy. The analyses of both the interviews and the reflections were conducted using NVivo12 (QSR International). The interview analysis was a three-part process that included open coding, thematic analysis, and thematic integration (Rossman & Rallis, 1998). The process began with reading and rereading the transcripts to deduce a list of core meanings for each transcript. This work was conducted by the lead author and verified by independent analysis of the second author. Once core meanings of individual transcripts were agreed upon, the meanings were cross-analyzed for repetition and clustered into themes and subthemes by the first and second authors working independently of one another. Team consensus was reached, and the data were then organized into a codebook. Data saturation was accomplished when it was determined that no new themes were emerging. The themes were then reviewed in relation to one another to clarify overlapping areas and collapse subthemes into broader themes. Direct quotes were extracted to support both textural and structural descriptions. After the analysis of the interview data, student reflections were analyzed using the codebook derived from the interview data. An “inconsistent” codebook category was created to code data inconsistent with the data found in the interviews. An “other coding” category was created to code data that reflected new concepts or themes not apparent in the interview data. Reflexivity An important aspect of considering trustworthiness in phenomenological research is addressing bias (Creswell, 2013). The research team consisted of two White female researchers and one Hispanic and American Indian female researcher. One was a tenured full professor with extensive CES experience. Another had conducted research related to dispositional assessment. The third member of the research team had no specific background or personal experiences with gatekeeping. The team members had a wide range of experience in program evaluation and qualitative research. The shared assumptions of the research team were that understanding gatekeeping was an important professional obligation and that doctoral students with career aspirations of entering counselor education needed a solid foundation in gatekeeping. Trustworthiness The process of establishing trustworthiness began with an understanding that the findings represented only one of many interpretations of the data (Corbin & Strauss, 2008). Early in the process, we consulted with a qualitative research expert who confirmed the analysis process (D. Barone, personal communication, December 2, 2018). Peer debriefing was used throughout the process (Creswell, 2014). The debriefing process included the research team presenting tentative findings at one regional and one national counselor education conference, a process that fostered research team deliberation on the interpretation of the data.