Real-World Implementation of EndoConnect in Brazilian Primary Care: Formative Study of Usability, Engagement, and Equity in Digital Endometriosis Care

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AI-generated summary by claude@2026-06, 2026-06-09

This study found that the EndoConnect digital health platform showed high usability, acceptability, and user engagement in Brazilian primary care, with exploratory signals of improved symptoms and knowledge, especially among rural and less educated participants.

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AI-generated deep summary by claude@2026-06, 2026-06-11 · read from full text

This formative applied methodological study developed and deployed EndoConnect Alpha, an offline-capable progressive web app for digital endometriosis care in Brazil’s SUS primary care units in Ceará, enrolling 45 women aged 18–45 with suspected/confirmed endometriosis and 15 primary care professionals across 10 units (with 60% rural participation). Over 8 weeks (Jan 2024–Nov 2025), the authors assessed usability (System Usability Scale), acceptability (Technology Acceptance Model), and engagement (Firebase Analytics), along with pre/post pelvic pain VAS, knowledge (EKES-15), anxiety (GAD-7), adherence, and referral rates, and reported mean usability as excellent (SUS 88.9 ± 9.8) with 79% trail completion. They found significant improvements including reduced pelvic pain (−23%, P=.02), increased adherence (+17%, P=.01) and knowledge (+21%, P<.001), reduced anxiety (−14%, P=.04), and increased referral rate (+15%, P=.04), with the largest benefits in rural and underserved subgroup categories; a stated limitation is that the work is formative with no clinical trial framework. The paper is centrally about endometriosis — it evaluates real-world feasibility, usability, engagement, equity impacts, and an ethical AI governance framework for a digital endometriosis care tool in SUS primary care.

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Abstract

BACKGROUND: Endometriosis is a chronic gynecological condition affecting approximately 10% of women of reproductive age worldwide and is associated with chronic pelvic pain, infertility, and reduced quality of life. In Brazil's Unified Health System (Sistema Único de Saúde [SUS]), diagnostic delays frequently range from 7 to 10 years and disproportionately affect socially vulnerable populations, including rural, low-income, Black, and Indigenous women. Digital health interventions have been proposed as scalable solutions; however, most available applications are developed in high-income settings and do not align with the structural and operational realities of low- and middle-income countries (LMICs). OBJECTIVE: This study aimed to evaluate feasibility, usability, acceptability, and user engagement associated with the real-world implementation of EndoConnect Alpha in primary health care settings, and to explore preliminary patterns of change in symptom burden, knowledge, and care navigation. METHODS: A single-arm, prospective, formative implementation study was conducted in 10 primary health care units in Ceará, Brazil. A convenience sample of 60 participants, including women with suspected or confirmed endometriosis and primary care professionals, used the platform over an 8-week period under real-world conditions. Usability (assessed using the System Usability Scale), acceptability (assessed using the Technology Acceptance Model), engagement metrics, and exploratory outcomes were assessed. All analyses were exploratory, with no control group and no causal inference. RESULTS: High usability and acceptability were observed, with strong user engagement, including a 79% completion rate of educational modules and consistent platform use. Observed decreases in pelvic pain and anxiety were identified, alongside increases in disease-related knowledge, self-reported therapy adherence, and reported gynecological referrals. A positive association between usability and acceptability was also observed. These findings should be interpreted as exploratory signals given the study design. Descriptive subgroup analyses suggested more pronounced trends among rural participants and those with a lower education level. CONCLUSIONS: The real-world implementation of EndoConnect Alpha demonstrated high feasibility, usability, and acceptability within a public primary care setting in a middle-income country. Observed trends suggest potential benefits, particularly among underserved populations; however, causal inference cannot be established. These findings support further controlled evaluation and highlight the relevance of equity-oriented digital health strategies tailored to LMIC contexts.
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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 Request queued. Please wait while the file is being generated. It may take some time. Copyright © The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.

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Outcome instruments

VAS-pain

Condition tags

endometriosischronic_pelvic_paininfertility

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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europepmc
last seen: 2026-08-03T06:10:56.557307+00:00
pubmed
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