Peer Support in Online Discussions of Male Infertility: A Natural Language Processing Study of Reddit
Khatun, M.; Patel, N.; Loid, M.; Destouni, A.; Lingasamy, P.; S, S. L.; Peters, M.; Sharma, R.; Salumets, A.; Modhukur, V.
Show abstract
Infertility generates profound psychological and social distress for both women and men, yet mens communicative experiences remain comparatively underexamined. Male infertility (MI) is often shaped by stigma, norms of masculinity, and limited opportunities for emotional disclosure, constraining help-seeking in offline settings. This study investigates how men use anonymous online peer-support spaces to discuss MI by analyzing discussions from the r/maleinfertility subreddit on Reddit. Using natural language processing techniques, we examined 10,769 posts and 80,381 comments published between 2013 and 2025. Analyses assessed sentiment and emotional expression, topic structure, hyperlink networks, and discussions related to diagnostic testing, treatment decision-making, and donor sperm use. Topic modeling revealed a functional differentiation between posts and comments. Original posts primarily focused on clinical sense-making, including interpretation of semen analyses, hormonal testing, and assisted reproduction options. In contrast, comments emphasized emotional validation, experiential knowledge-sharing, and normalization of alternative family-building pathways. Emotional expression varied by discussion topic, with heightened fear and sadness in conversations involving genetic testing, surgical sperm retrieval, and donor sperm. Hyperlink analysis indicated frequent engagement with peer-reviewed medical information, reflecting active evidence-seeking alongside peer exchange. Taken together, findings suggest that anonymous online communities function as critical infrastructures of support for men experiencing infertility, enabling forms of disclosure and vulnerability often constrained in offline contexts. These spaces facilitate interpretation of medical information, collective coping, and decision-making regarding treatment and donor options. The study highlights the role of digital anonymity in mitigating stigma and expanding communicative possibilities for men navigating infertility alongside clinical care.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Innovative AI models for clinical decision-making: predicting blastocyst formation and quality from time-lapse embryo images up to embryonic day 3 92%
- From Web to RheumaLpack: Creating a Linguistic Corpus for Exploitation and Knowledge Discovery in Rheumatology 90%
- SymScore: Machine Learning Accuracy Meets Transparency in a Symbolic Regression-Based Clinical Score Generator 89%
Similar papers in this journal
- Inferring Gender from First Names: Comparing the Accuracy of Genderize, Gender API, and the gender R Package on Authors of Diverse Nationality 92%
- Diversity and inclusion: A hidden additional benefit of Open Data 92%
- Defining Destigmatizing Design Guidelines for Use in Sexual Health-Related Digital Technologies: A Delphi Study 91%
Similar papers in this journal
- Early medical abortion using telemedicine – acceptability to patients 92%
- Why women choose abortion through telemedicine outside the formal health sector in Germany? A mixed-methods study 92%
- Demand for Self-Managed Online Telemedicine Abortion in Eight European Countries During the COVID-19 Pandemic: A Regression Discontinuity Analysis 91%
Similar papers in this journal
- Multimodal Recruitment for an Internet-Based Pilot Study of Ovulation and Menstruation (OM) Health 95%
- “Is this Herpes or Syphilis?”: Latent Dirichlet Allocation Analysis of Sexually Transmitted Disease-Related Reddit Posts During the COVID-19 Pandemic 92%
- Tracking private WhatsApp discourse about COVID-19: A longitudinal infodemiology study in Singapore 92%
Similar papers in this journal
- Digital intervention mylovia improves sexual functioning in women with sexual dysfunction in randomized controlled trial 92%
- Assessment of Menstrual Health Status and Evolution through Mobile Apps for Fertility Awareness 91%
- Digital Health Tools for the Passive Monitoring of Depression: A Systematic Review of Methods 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.