📄 health informatics

eHEALS-Br: An Automated Platform for Digital Health Literacy Assessment and Personalized Feedback

This paper presents eHEALS-Br, a secure web-based platform that automates the administration and scoring of the Brazilian eHealth Literacy Scale to provide real-time, personalized feedback, demonstrating high reliability in a pilot study and offering a scalable tool for both population research and individualized clinical health literacy assessment in Brazil.

Original authors: Cotta Fontainha, T., Werneck, V. M., Cappelli, C.

Published 2026-01-24

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CC BY 4.0

Original authors: Cotta Fontainha, T., Werneck, V. M., Cappelli, C.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine you have a toolbox for checking how good someone is at using the internet to find health advice. For years, this toolbox (called eHEALS) was a paper checklist that doctors or researchers had to hand out, read out loud, and grade by hand. It was like trying to measure the temperature of a room with a thermometer that only works if you hold it perfectly still for ten minutes.

This paper introduces eHEALS.com.br, a new, automated version of that toolbox designed specifically for Brazil. Think of it as upgrading from a manual, paper-based map to a GPS app that not only tells you where you are but also gives you a personalized "tour guide" on how to get better at navigating.

Here is a breakdown of what the paper actually did and found, using simple analogies:

1. The Problem: The "Paper Map" Was Too Slow

The authors looked at existing tools for measuring "digital health literacy" (how well people can find and understand health info online). They found three main problems with the old ways of doing things:

No Automation: Most tools were just paper forms. You couldn't just click a link and get an instant result.
No Comparison: If you filled out a paper form, you didn't know how you compared to your neighbor or the rest of the country.
One-Size-Fits-All: The tools didn't really fit the specific culture or language needs of Brazil's huge and diverse population.

2. The Solution: The "Smart GPS"

The team built a website (eHEALS.com.br) that acts like a smart, automated GPS for health literacy.

How it works: Instead of a paper form, users log in, answer 8 simple questions on their phone or computer, and the system instantly calculates their score.
The "Tour Guide": Based on the score, the system immediately gives the user a personalized message. It's like a fitness app telling you, "Great job! You're a pro at finding info," or "Hey, you might want to double-check your sources next time."
The Ranking: It also lets users see where they stand compared to others (anonymously), which acts like a friendly nudge to keep learning.

3. The Test Drive: The "Pilot Flight"

To see if this new "GPS" actually worked, the authors took it for a test drive with a small group of 12 people in Rio de Janeiro.

The Method: They used a "snowball" method. They asked three health professionals to send the link to their friends, who sent it to their friends, and so on. It's like a game of telephone, but everyone is passing along a link to a health quiz.
The Results:
- Reliability: The test showed the system was extremely consistent. If you asked the same questions, it gave the same reliable results every time. The authors gave it a score of 0.929 on a scale where anything above 0.90 is considered "excellent" (like a straight-A student).
- User Experience: The participants found the site easy to use, clear, and safe. They felt the questions were easy to understand.

4. What the Paper Actually Claims (and What It Doesn't)

It is important to stick to what the authors actually said:

They proved it works: They showed that you can turn the paper version of this test into a website and have it work reliably.
They proved it's consistent: The math behind the scoring holds up.
They proved it's user-friendly: People could use it without getting confused.

What they did NOT claim:

They did not claim that using this website cured anyone's illness.
They did not claim that this tool is ready for every single hospital in Brazil right now.
They did not claim that the small group of 12 people represents the whole country. They explicitly stated that bigger, wider tests are needed in the future to confirm it works everywhere.

The Bottom Line

Think of this paper as the "blueprint and prototype" phase. The authors built a digital machine that can automatically measure how good Brazilians are at finding health info online. They tested it on a small scale, and the machine worked perfectly, giving excellent, consistent scores and helpful feedback. It's a successful proof-of-concept that says, "We can automate this, and it works well," paving the way for bigger tests in the future.

Technical Summary: eHEALS.com.br – Automating Digital Health Literacy Assessment and Personalized Feedback in Brazil

Problem Statement
The paper addresses the limitations of existing digital health literacy assessment tools, specifically the Brazilian version of the eHealth Literacy Scale (eHEALS-Br). While the original eHEALS instrument is a validated standard for measuring an individual's ability to seek, find, understand, and appraise health information from electronic sources, its traditional application is manual. The authors identify three critical gaps in the current landscape:

Lack of Automation: Existing studies rely on traditional, non-automated application methods, lacking temporal control and integration with Information Systems.
Absence of Comparative Mechanisms: Current tools do not offer systems for ranking or comparing participant scores, limiting the ability to provide contextualized feedback.
Inclusion Barriers: Standard instruments often fail to incorporate specific adaptations for the sociocultural diversity and digital inclusion needs of the Brazilian population, such as simplified language and accessible design.

Methodology
The study proposes and validates a web-based platform, eHEALS.com.br, designed to automate the administration, scoring, and feedback of the eHEALS-Br.

System Architecture: The platform utilizes a modern tech stack comprising a React and TypeScript frontend for a responsive, accessible interface, and a Node.js and MongoDB backend for data management. It is hosted on a secure Virtual Private Server (VPS) with SSL certificates to ensure data privacy.
Instrument Adaptation: The system retains the eight validated items of the eHEALS-Br but transforms them into an interactive digital quiz. It incorporates multimedia content (GIFs, visual guides), plain language principles, and accessibility features compliant with WCAG 2.1 (e.g., audio controls, mobile optimization).
Scoring and Feedback: The system employs a cumulative scoring algorithm (8 to 40 points) based on a 5-point Likert scale. It classifies users into five distinct literacy levels (ranging from "8–15" to "36–40") and generates personalized, automated feedback for each level. The feedback ranges from motivational guidance for lower scores to recognition of critical thinking skills for higher scores.
Study Design: A pilot study was conducted using snowball sampling with 12 participants in Rio de Janeiro between March 17 and 25, 2025. Data collection occurred via the eHEALS.com.br platform and Google Forms. The study included a systematic literature review (PRISMA methodology) to map existing instruments and identify gaps.
Reliability Analysis: Internal consistency was measured using Cronbach's alpha ( $\alpha$ ) for both the automated platform responses and the supplementary Google Forms questionnaire.

Key Contributions

Automated Platform Development: The creation of eHEALS.com.br, the first system to automate the eHEALS-Br with real-time scoring and personalized feedback tailored to the Brazilian context.
Comparative Ranking: The introduction of a mechanism that allows participants to understand their performance relative to a group, a feature absent in previous manual applications.
Accessibility Integration: The application of Plain Language principles and WCAG 2.1 guidelines to make the assessment accessible to users with varying educational levels and digital skills.
Psychometric Validation: The demonstration that the automated version maintains the psychometric properties of the original instrument, achieving high internal consistency.

Results

Reliability: The automated eHEALS-Br scale demonstrated excellent internal consistency with a Cronbach's alpha of 0.929 (95% CI [0.847 - 0.976]).
Supplementary Questionnaire: The additional dimensions collected via Google Forms showed good reliability overall ( $\alpha = 0.891$ $α = 0.891$ ). However, sub-dimension analysis revealed variability:
- Evaluation (usability, clarity, security): $\alpha = 0.836$
- Capacity (skills and confidence): $\alpha = 0.833$
- Agreement (usefulness): $\alpha = 0.505$
- Frequency (usage patterns): $\alpha = 0.351$
Feasibility: The pilot study confirmed the feasibility of the automated workflow, from unique link access to the delivery of personalized feedback, with no technical failures reported during the data collection period.

Significance and Claims
The authors claim that the study demonstrates the feasibility of automating the eHEALS-Br, supporting its use in both population studies and individualized clinical settings. The platform is presented as a strategic tool that:

Expands Applicability: By automating the process, the tool can scale from small research groups to large-scale public health monitoring.
Enhances Accessibility: It democratizes access to health literacy assessment by overcoming barriers related to manual administration and complex language.
Aligns with Global Goals: The project is explicitly linked to the United Nations Sustainable Development Goals (SDGs), specifically ODS 3 (Health and Well-being), ODS 4 (Quality Education), and ODS 9 (Industry, Innovation, and Infrastructure).

The paper concludes modestly, noting that while the automated tool is robust, the lower reliability in the "Agreement" and "Frequency" dimensions suggests a need for item reformulation in future iterations. The authors recommend broader, multi-regional validations across Brazil's diverse social contexts to ensure the tool's equity and reliability before widespread clinical deployment. The work is positioned as a Master's dissertation contribution that bridges theoretical research and practical implementation in Brazil's digital health landscape.

1. The Problem: The "Paper Map" Was Too Slow

2. The Solution: The "Smart GPS"

3. The Test Drive: The "Pilot Flight"

4. What the Paper Actually Claims (and What It Doesn't)

The Bottom Line

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