Knowledge Bank

Background Self diagnosis is changing the way we approach healthcare. This phenomenon has gained prominence on social media as users share personal mental health experiences. While online self-disclosure is not new, the rise of self diagnosis and identification with mental illnesses via social media has become increasingly prevalent. This trend is fueled by the growth of online communities, though existing scholarship on the topic remains limited. Although accessible online resources can empower individuals, questions have arisen about the credibility of the information shared, as well as the diagnostic criteria presented.

Methods Using a phenomenological approach, this qualitative study (n=4) elucidates the relationship between social media use and self-diagnosed conditions among assigned female at birth (AFAB) individuals (aged 18-24), gaining a clearer understanding of this population’s lived experiences. Phenomenology was chosen as the research method because of the need to explore the subjective experiences of self diagnosis in depth. Participants identified as self diagnosed and were recruited via social media, taking part in semi-structured interviews.

Results Analysis identified the importance of (1) online support for vulnerable populations, (2) empowerment through knowledge and labels, and (3) issues within the healthcare system. Participants from marginalized communities reported feeling empowered by diagnostic labels and that online communities provided a safer space for questioning and exploring their identities, compared to in-person communities. Many individuals seeking self diagnosis may do so due to mistrust of the medical system or lack of access to professional care.

Implications Findings offer insights into the phenomenon of online self diagnosis among young AFAB individuals, as well as the potential effects on healthcare and mental health practices. There is a continued need for research as the literature. While scholarship on this topic is continuing to grow, the psychological and social impacts of online self diagnosis remain largely unknown. Results also inform future clinical approaches and highlight the need for improved healthcare access.