Currently accepted at: JMIR Formative Research
Date Submitted: Dec 12, 2025
Open Peer Review Period: Dec 15, 2025 - Feb 4, 2026
Date Accepted: Apr 4, 2026
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/89464
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Real-World Pilot of EndoConnect: A Digital Health Platform for Endometriosis Education, Symptom Management, and Ethical AI-Assisted Triage in Brazilian Primary Care – A Formative Study and Proposal of the NAM-Endora Framework for Bias Mitigation and Health Equity in LMICs
ABSTRACT
Background:
Endometriosis affects ≈10% of reproductive-age women worldwide (≈190 million) and is marked by debilitating chronic pain and infertility. In Brazil’s public health system (SUS), diagnostic delays average 7–10 years, disproportionately affecting low-income, rural, Black, and Indigenous women.
Objective:
This formative study aimed to (1) develop and deploy EndoConnect Alpha—an offline-capable progressive web app integrating evidence-based education, symptom tracking, moderated community support, and privacy-by-design AI-assisted tele-ultrasound triage—in SUS primary care units in Ceará, Brazil; (2) evaluate usability, acceptability, engagement, and preliminary clinical-psychosocial impact; and (3) propose the NAM-Endora Framework for ethical AI governance in low- and middle-income countries (LMICs).
Methods:
Applied methodological study with quantitative cross-sectional formative design (January 2024–November 2025). After expert validation and software registration (INPI BR5120250005556-0), 60 participants (45 women aged 18–45 years with suspected/confirmed endometriosis and 15 primary care professionals) were recruited from 10 SUS units (60% rural). Usability (System Usability Scale), acceptability (Technology Acceptance Model), engagement (Firebase Analytics), and pre/post outcomes (pain VAS, EKES-15 knowledge, GAD-7 anxiety, adherence, referral rate) were assessed over 8 weeks. Ethics approval: CAAE 82094924.8.0000.5049.
Results:
Mean SUS score 88.9 ± 9.8 (excellent); TAM 91.4%. Trail completion 79%; mean daily use 17.2 minutes. Significant improvements: pelvic pain −23% (P=.02), adherence +17% (P=.01), knowledge +21% (P<.001), anxiety −14% (P=.04), referrals +15% (P=.04). Largest benefits observed in rural, low-education, Black/Brown/Indigenous subgroups. The NAM-Endora Framework is proposed as the first LMIC-tailored ethical AI governance model.
Conclusions:
EndoConnect Alpha is feasible and equity-enhancing in SUS primary care. The NAM-Endora Framework provides a novel, replicable model for responsible AI deployment in LMICs, with potential to reduce the global burden of endometriosis. Clinical Trial: Not applicable
Citation
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Copyright
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