THE ROLE OF INNOVATIVE TECHNOLOGIES, SOCIAL MEDIA ALGORITHMS, AND EHEALTH LITERACY IN SHAPING HEALTH-SEEKING BEHAVIOR AMONG ADOLESCENTS AND YOUNG ADULTS WITH POLYCYSTIC OVARY SYNDROME (PCOS): A SYSTEMATIC REVIEW

Karolina Julia Hak; Karolina Magda Leszczyńska; Maciej Tomasz Wieczorek; Alicja Maria Mitan; Aleksandra Maria Tomaszewska; Kamila Teresa Kańska; Karolina Krawczyk; Jeremi Leon Jasiński; Anna Krzysztofik; Weronika Napierała

doi:10.31435/ijitss.1(49).2026.5190

Authors

Karolina Julia Hak Independent Public Provincial Integrated Hospital in Szczecin, Szczecin, Poland https://orcid.org/0009-0009-7641-0237
Karolina Magda Leszczyńska Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0000-6427-7269
Maciej Tomasz Wieczorek Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0007-4058-7650
Alicja Maria Mitan Fryderyk Chopin University Clinical Hospital in Rzeszów, Rzeszów, Poland https://orcid.org/0009-0004-5617-5034
Aleksandra Maria Tomaszewska University Clinical Hospital of Bialystok, Białystok, Poland https://orcid.org/0009-0000-4684-0492
Kamila Teresa Kańska Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0005-2702-7013
Karolina Krawczyk Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0005-1191-5788
Jeremi Leon Jasiński Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0004-1690-5936
Anna Krzysztofik Pomeranian Medical University, Szczecin, Poland https://orcid.org/0009-0002-3130-1917
Weronika Napierała Jerzy Popiełuszko Hospital of Bielany, Warsaw, Poland https://orcid.org/0009-0005-1411-4046

DOI:

https://doi.org/10.31435/ijitss.1(49).2026.5190

Keywords:

Polycystic Ovary Syndrome, Digital Health, Social Media Algorithms, Misinformation, Machine Learning, Cyberchondria, eHealth Literacy, Health-Seeking Behavior, Big Data Infodemiology, Patient Empowerment

Abstract

Background: Polycystic Ovary Syndrome (PCOS) is a highly prevalent, complex endocrine and metabolic disorder that profoundly alters the physiological and psychological landscape of adolescent development. Driven by systemic clinical dissatisfaction, chronic invalidation, and a lack of tailored institutional support, the modern patient experience has rapidly transitioned from traditional, clinic-based management to hyper-connected digital self-management.

Objective: This systematic review aims to comprehensively explore how innovative digital technologies—specifically algorithmic social media platforms (TikTok, Instagram, YouTube, X), the Internet of Things (IoT), and machine-learning-analyzed discussion forums (Reddit)—shape the health-seeking behaviors and medical decision-making of women diagnosed with PCOS. Furthermore, it evaluates the critical mediating role of electronic health (eHealth) literacy.

Methodology: A systematic synthesis was conducted in strict accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Electronic databases (PubMed/MEDLINE, Google Scholar, Scopus) were systematically searched for peer-reviewed studies published between 2012 and 2026. The synthesis integrated qualitative sociological interviews, mixed-methods intervention studies, natural language processing (NLP) sentiment analyses, and big data infodemiology (total n=23).

Results: The synthesis reveals a critical, high-stakes dichotomy. While digital platforms and IoT applications are essential for identity reconstruction ("sense-making") and peer support, they are simultaneously potent vectors for unregulated health misinformation. Visual algorithms heavily promote unverified, "root-cause" supplements and restrictive diets, overshadowing evidence-based medicine. The reliance on digital crowdsourcing for interpreting laboratory results introduces unprecedented friction into the patient-physician dynamic. However, emerging evidence indicates that targeted, evidence-based Digital Health Interventions (DHIs) and higher baseline eHealth literacy significantly mitigate these risks, leading to improved clinical and psychological outcomes.

Conclusion: The integration of digital health literacy into routine endocrine and gynecological care is no longer optional. Healthcare providers must recognize social media as a primary, foundational diagnostic ecosystem. Addressing this requires active clinical mediation, the co-development of evidence-based digital interventions, and profound clinical empathy to help patients navigate algorithmic noise safely.

References

Afaq, M., Vashisht, K., Al-Dhoon, A., et al. (2025). Impact of #PCOSweightloss: A global X hashtag analysis study of weight loss narratives in the PCOS community. Digital Health. https://doi.org/10.1177/20552076251314100

Arabkermani, M., et al. (2025). Mobile apps designed for patients with polycystic ovary syndrome: Content analysis using the Mobile App Rating Scale. Journal of Medical Internet Research. https://doi.org/10.2196/71118

Atigan, A., & Atigan, A. (2023). Polycystic ovary syndrome and exercise: Evaluation of YouTube videos. Cureus. https://doi.org/10.7759/cureus.35093

Azziz, R., Carmina, E., Chen, Z., Dunaif, A., et al. (2016). Polycystic ovary syndrome. Nature Reviews Disease Primers, 2(1), 1–18. https://doi.org/10.1038/nrdp.2016.57

Darcy, R., Almgren-Bell, A., et al. (2026). Supplement use and weight loss for polycystic ovary syndrome: How much weight should we give the information we see on TikTok? American Journal of Obstetrics and Gynecology, 234(2), e21–e27. https://doi.org/10.1016/j.ajog.2025.09.052

Emanuel, R. H. K., Docherty, P. D., Lunt, H., & Campbell, R. E. (2023a). Comparing literature- and subreddit-derived laboratory values in polycystic ovary syndrome (PCOS): Validation of clinical data posted on PCOS Reddit forums. JMIR Formative Research. https://doi.org/10.2196/44810

Emanuel, R. H. K., Docherty, P. D., Lunt, H., & Campbell, R. E. (2023b). What do users in a polycystic ovary syndrome (PCOS) forum think about the treatments they tried: Analysing treatment sentiment using machine learning. Journal of Medical Internet Research, 25. https://doi.org/10.1007/s13246-025-01539-9

Gomula, J., Warner, M., & Blandford, A. (2024). Women’s use of online health and social media resources to make sense of their polycystic ovary syndrome (PCOS) diagnosis: A qualitative study. BMC Women’s Health, 24(1), 157. https://doi.org/10.1186/s12905-024-02993-5

Graca, S., Alloh, F., Lagojda, L., et al. (2024). Polycystic ovary syndrome and the Internet of Things: A scoping review. Healthcare. https://doi.org/10.3390/healthcare12161671

Hofmann, K., Decrinis, C., Bitterlich, N., et al. (2023). Body image and mental health in women with polycystic ovary syndrome-a cross-sectional study. European Journal of Endocrinology, 194(2), 233–240. https://doi.org/10.1007/s00404-024-07913-4

Horvath, A., Chaffin, K., Ahmad, S., et al. (2024). The discourse surrounding polycystic ovary syndrome on TikTok: A social media analysis. Journal of Adolescent Health. https://doi.org/10.3390/healthcare12222253

Hoyos, L. R., Putra, M., Armstrong, A. A., et al. (2020). Measures of patient dissatisfaction with health care in polycystic ovary syndrome: Retrospective analysis. Journal of Medical Internet Research. https://doi.org/10.2196/16541

Ismayilova, M., & Yaya, S. (2022). “I’m usually being my own doctor”: Women’s experiences of managing polycystic ovary syndrome in Canada. International Health. https://doi.org/10.1093/inthealth/ihac028

Kara, S. S., Keleş, E., & Bağlar, İ. (2023). Relationship between electronic health literacy and quality of life in women with PCOS: A web-based cross-sectional study. Scie. https://doi.org/10.14744/scie.2025.76500

Mousiolis, A., Michala, L., & Antsaklis, A. (2012). Polycystic ovary syndrome: Double click and right check. What do patients learn from the internet about PCOS? Journal of Gynecological Endocrinology. https://doi.org/10.1016/j.ejogrb.2012.03.028

Percy, C., Turner, A., & Orr, C. (2024). Developing a novel web-based self-management support intervention for polycystic ovary syndrome: Mixed methods study with patients and health care professionals. JMIR Formative Research. https://doi.org/10.2196/52427

Riemma, G., Carotenuto, R. M., Casolari, C., et al. (2025). Assessing quality, reliability and accuracy of polycystic ovary syndrome-related content on TikTok: A video-based cross-sectional analysis. International Journal of Gynecology & Obstetrics. https://doi.org/10.1002/ijgo.70007

Rohden, F., & Corrêa, A. S. (2024). On the borderlines of health, beauty, and enhancement: An analysis of polycystic ovary syndrome. Ciência & Saúde Coletiva. https://doi.org/10.1590/1413-81232024292.05122023

Sanchez, N. (2015). Polycystic ovary syndrome, absent from national surveillance and present online: Implications for mental and behavioral health. https://hdl.handle.net/2027.42/113329

Sucu, S. T., Gayretli, T. K., Küçükkayıkçı, A. S., et al. (2024). Cyberchondria levels in adolescent patients with polycystic ovary syndrome in the digital age. Journal of Pediatric and Adolescent Gynecology. https://doi.org/10.1016/j.jpag.2024.08.006

Teede, H. J., Tay, C. T., Laven, J. J., et al. (2023). Recommendations from the 2023 international evidence-based guideline for the assessment and management of polycystic ovary syndrome. European Journal of Endocrinology. https://doi.org/10.1210/clinem/dgad463

Wright, P. J., Burts, C., Harmon, C., & Corbett, C. F. (2025). Availability and use of digital technology among women with polycystic ovary syndrome: Scoping review. JMIR Formative Research. https://doi.org/10.2196/68469

Zhao, et al. (2026). The effectiveness of digital health interventions on anthropometric and healthy behavior in women with polycystic ovarian syndrome: A systematic review. Frontiers in Endocrinology. https://doi.org/10.3389/fendo.2026.1676915