The stigmatization of women's health concerns and the disparity in healthcare resources between men and women pose significant challenges to healthcare inclusivity from a societal standpoint. These challenges also carry significant implications in the realm of digital health. FemTech, a rapidly evolving digital health solution focused on improving women's wellness, presents a hopeful avenue to address female’s underrepresented status in healthcare and for inclusive health interventions to bridge disparities. However, there's a limited understanding of how FemTech reflects to females’ needs by specific design and how it distinguishes itself from general digital health solutions.
This study employed a computational grounded theory approach, utilizing the LDA topic modeling analysis on user reviews of FemTech applications (FemTech apps), to underscore affordances in FemTech apps from the actual users' perspectives. We narrowed our focus to the primary category of FemTech apps: ""Fertility & Pregnancy Mobile"". This not only provided a deeper understanding of user feedback and expectations but also ensured a consistent and ample dataset for the LDA analysis. In total, 21,489 reviews from 193 apps were analyzed.
When the topic number was set to 40, we achieved optimal topic distribution performance. From the generated topics, we identified three primary affordances of FemTech apps: instrumental, experiential, and empowerment affordances. This research deepens the theoretical understanding of FemTech's unique characteristics and offers valuable insights for practical design and FemTech industry’s development.