536 The Professional Counselor | Volume 10, Issue 4 length of time in the CES program; year graduated; if they were pregnant or adopted children and the number of children/their ages while in the program; and if they were mentored by faculty, peer, or both. The first author conducted the 12 interviews through V-SEE, a Stanford-created, telehealth videoconferencing application that supports online collaboration. It allowed the participants and research interviewer to interact synchronously via audio and video. Interview length ranged from 60–75 minutes as participants described their mentoring experiences. The interview settings were descriptively “in the field,” as they were interviewed in their offices, cars, and homes. Three had their babies/toddlers with them during the home interviews. Participants described their university type, cohort structure, and employment status. The first author asked each participant open-ended questions using a semistructured interview format developed from our review of the literature on mentoring, motherhood, and issues concerning doctoral student mothers. The questions included: (a) “What factors, if any, influenced your decision to be mentored?” (b) “Can you describe your mentoring experience in detail?” (c) “Can you speak to your work–study–life balance while being mentored?” (d) “Can you speak of your academic progress and/or professional development while being mentored?” (e) “Describe the characteristics or traits of a mentor that are important for doctoral student mothers,” and (f) “What, if anything, could a counselor education department do to promote successful mentoring experiences for doctoral student mothers?” With qualitative inquiry, the goal is to include enough participants to adequately understand the phenomenon in question (Hays & Singh, 2012). Wanting to capture a fresh perspective from these doctoral students who were mentored, many while becoming mothers for the first time, all 12 interviews were retained, yielding in-depth descriptions of their experiences. Pseudonyms were assigned to participants prior to data analysis to protect their identities. Data Analysis Phenomenological data analysis is concerned with examining participants’ experiences to understand the depth and meaning of those lived experiences (Hays & Singh, 2012; Moustakas, 1994). Delving into large amounts of transcription data, the goal is to develop a composite description or essence of the experience that represents the group as a whole (Moustakas, 1994). The first author began the inductive method of analysis by engaging in horizontalization, the process of identifying non-repetitive, nonoverlapping statements from the first three interview transcripts (Hays & Singh, 2012; Moustakas, 1994). Next, the first author clustered these statements in units of meaning or themes and then wrote textual descriptions of “what” the participants experienced, including verbatim examples from the transcripts (Creswell, 2013; Moustakas, 1994). The first and second investigators met weekly to discuss and rework these themes. From there, they wrote a structural description, “how” the experience happened in the context of the setting or circumstances and who was involved (Creswell, 2013; Moustakas, 1994). The first author used these themes to analyze the rest of the transcripts with care given to reanalyzing previous interviews as new themes or subthemes emerged. The teammet to finalize the central themes and subthemes that emerged collectively from the participants’ reflections, contextualizing them into a holistic understanding of the essence of the mentoring experience (Hays & Singh, 2012). Validation strategies included recognizing and controlling for research bias through bracketing, capturing participants’ viewpoints through substantial engagement, and triangulation through crosschecking codes and themes and by using thick participant descriptions (Denzin & Lincoln, 2011; Lincoln & Guba, 1985). Using basic member checking, participants reviewed their transcripts for accuracy, with two making clarifying comments (Creswell, 2013; Hays & Singh, 2012). The first and second authors met weekly to process reflection notes to bracket any biases and discuss themes to allow triangulation of data (Creswell, 2013; Hays & Singh, 2012). The two other members of the team reviewed the themes/subthemes matched with descriptive statements for cross-checking purposes