The Professional Counselor - Journal Volume 13, Issue 1

The Professional Counselor | Volume 13, Issue 1 31 and accurate information about OCD shared. It is important to note that at the time of data analysis, the current edition of the Diagnostic and Statistical Manual of Mental Disorders was the DSM-5 (APA, 2013). The DSM-5-TR (APA, 2022) was released in 2022; however, there were no updates to the OCD diagnostic criteria in the text revision. The research team identified more codes during the review of the data, and we altered codes to be more specific to the data, including daily routine, checking OCD, and feeling misunderstood. During the segmentation phase of the coding process, the research team divided the data into individual units, or segments, based on a thematic criterion. More specifically, we divided the larger chunks of data (i.e., the entirety of what was said in a TikTok) into individual units (i.e., sentences) based on the aforementioned codes. Next, we went through a pilot round of coding using the predetermined codes on approximately 50% of the data. We evaluated and made changes to the coding frame as necessary, developing more specific codes to best represent the data. From there, we proceeded to the main analysis phase, in which the research team coded all data according to our final coding framework and determined themes and subthemes based on the coded data. Each team member individually determined themes, and then the team members met to compare, discuss, and alter the themes until we reached consensus on the themes and subthemes that best represented the data. Of the total sample, 48 videos comprise the two final categories. Increasing Trustworthiness The research team for the content analysis consisted of the first two authors of this article, Erin E. Woods and Alexandra Gantt-Howrey, who are cisgender heterosexual (cishet) White women and are mental health counselors familiar with OCD. To increase trustworthiness, Woods and Gantt-Howrey practiced weekly reflexive journaling to become more aware of and bracket our biases throughout the data analysis, with the recognition that bias cannot be completely bracketed (Creswell, 2003). As part of the reflexive journaling process, we recognized and considered various sociocultural factors at play in our own lives, including our existence as cishet White women in the United States. Moreover, we identified various biases and expectations we held, including expectations of seeing OCD used as a non-clinical descriptor, previous knowledge related to OCD misdiagnosis and misunderstanding, and the belief that OCD should be used only in reference to the actual disorder. In an attempt to bracket these biases throughout the data analysis process, we engaged in frequent dialogue with one another to consider and evaluate assumptions that arose during the data analysis. Finally, to increase trustworthiness, the third author, Amber L. Pope, a licensed mental health counselor and counselor educator who identifies as a cishet White woman, acted as an auditor and reviewed the final themes and subthemes according to the data (Creswell, 2003). More specifically, Pope reviewed the data as well as the themes and subthemes developed by Woods and Gantt-Howrey. Pope then offered feedback on the results (e.g., use of theme names to accurately represent the data), and Woods and Gantt-Howrey integrated Pope’s feedback into the final results presented below. Results This investigation explored how women communicate about OCD on TikTok. Two themes and three subthemes emerged from the data: 1) minimizes OCD symptoms and 1a) uses OCD as a synonym for cleanliness and organization; 2) accurately depicts OCD symptoms, 2a) corrects misunderstanding, and 2b) shares obsessive fears. A clear dichotomy was found: Many TikTok videos depicted women using OCD as an inaccurate descriptor, perpetuating stigma surrounding the diagnosis, while others shared factually based information in alignment with the DSM-5 description of OCD, often representing their own experiences with OCD. Below, our findings are illustrated with rich descriptions from the data.

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