According to Gram Research analysis of a 2026 study, researchers without programming skills can build working digital health prototypes with the no-code platform CIAS-EU. In a 16-person workshop, 15 participants finished a prototype in one session, and the platform scored 70.8 on a usability scale where 68 is average.
Building digital health tools, such as apps that support nutrition or mental health, usually requires programming skills that many researchers lack. According to Gram Research analysis of a 2026 study, a no-code platform called CIAS-EU may help close that gap. In a 3.5-hour workshop at a German public health conference, 16 health researchers learned the platform through a live demonstration and hands-on practice. Fifteen of them built a working prototype during the session. Participants rated the platform’s ease of use as good but not excellent. They found the interface intuitive but reported difficulty with branching logic and hidden advanced features. The findings suggest that brief training can get beginners started, though becoming skilled takes more time and better guidance.
Key Statistics
A 2026 study of 16 health researchers found that 15 of them built a working digital health prototype with the no-code platform CIAS-EU during a single 90-minute hands-on session.
In a 2026 usability study of the CIAS-EU platform, participants gave an average System Usability Scale score of 70.8 out of 100, above the commonly used benchmark of 68.
A 2026 evaluation reported that the usability scores of 16 CIAS-EU users ranged widely, from 32.5 to 95.0, with a standard deviation of 16.2.
The Quick Take
- What they studied: Can researchers with no coding background use a drag-and-drop tool to build digital health programs after a short introduction, and how easy do they find it to use?
- Who participated: Sixteen health researchers from varied backgrounds attended a workshop at a 2025 German public health congress. Sixteen of 18 invited attendees, an 88.9% response rate, completed the feedback surveys. Most had little or no programming experience.
- Key finding: The platform earned an average usability score of 70.8 on a 0 to 100 scale, where 68 is the commonly used benchmark for average usability. Fifteen of 16 participants finished a working prototype during a single session. Scores varied widely, from 32.5 to 95.0.
- What it means for you: If you work in health and want to test a simple digital tool without learning to code, this platform appears to be a realistic starting point. Expect a learning curve, and plan for more practice before building anything complex or ready for the public.
The Research Details
The researchers wanted to know whether a no-code platform called CIAS-EU, which lets people build health programs by dragging and connecting visual blocks instead of writing code, is easy enough for beginners to use. They tested it at a conference workshop. The session had two parts: a 75-minute live demonstration by the developers, followed by a 90-minute hands-on period in which participants built their own intervention prototypes.
After the workshop, participants completed the System Usability Scale, a widely used 10-question survey that produces a score from 0 to 100. They also answered open-ended questions about what they liked and what was hard. Together, these two measures gave the team both a number and a description of the experience.
The design is a single-session evaluation, not a long-term trial. It shows how people react to the tool right after brief training, but it does not show whether they keep using it or whether the programs they build actually work for patients.
Digital health tools can reach people at home, but building them has traditionally required specialized software skills. A no-code platform could let the researchers who understand health problems create tools themselves. Measuring usability right after a hands-on session captures a first impression that matters for whether people will try the platform again.
Using a standard usability survey also makes the results easier to compare with other software. Pairing the score with written comments explains why people scored the platform as they did, which helps developers decide what to fix first.
The study used a recognized, validated usability questionnaire, and the response rate of 88.9% is high for a voluntary survey. Participants came from varied backgrounds, which adds some diversity to the feedback.
However, the group was small, with only 16 people, so the scores could shift considerably with a different group. The participants also chose to attend a workshop, so they may have been more motivated than typical researchers. The study was published as a research article in a German-language journal focused on health care evidence and training. It has not yet been replicated by independent teams.
What the Results Show
The average usability score was 70.8 out of 100, with a standard deviation of 16.2. The standard deviation measures how spread out the individual scores were. A spread that large means some people found the tool very easy while others struggled. Scores ranged from 32.5 to 95.0. Because 68 is commonly treated as the average benchmark for this survey, the score is above average, although the authors describe it as good rather than excellent.
The most encouraging result was practical. Fifteen of the 16 participants completed at least one working prototype during the 90-minute hands-on session. These prototypes covered topics such as mental health, nutrition, disease management, and health literacy. That suggests that a short introduction is enough for people with no programming background to produce something functional.
Participants praised the interface for being intuitive and said it made them feel they could develop tools on their own. Their comments also pointed to trouble areas. Many found it hard to understand how the platform was organized, to set up branching paths, meaning the choices a program makes based on a user’s answer, and to find advanced features on their own.
The comments suggest that the biggest barrier is not the drag-and-drop design itself but the time needed to understand how the pieces fit together. Participants who grasped the underlying logic could move quickly, while others needed help with conditional steps. The authors conclude that clearer documentation and a better layout for advanced options would likely improve the experience.
The authors also note that finishing a prototype in one session is not the same as mastering the tool. Building a program that is accurate, safe, and useful for real patients requires further skill and practice.
Earlier work on no-code and low-code health tools has generally found that visual builders can lower the barrier for non-programmers, but that usability depends heavily on documentation and training. This study adds a focused look at a specific open-source platform with a short workshop format. Its findings are consistent with the broader view that quick starts are possible while deep expertise takes longer to develop.
The most important limitation is the small group of 16 people. Results from so few participants cannot be generalized to all health researchers or to people outside academia, such as community health workers or clinicians. The participants were also volunteers at a conference, which may have attracted people already interested in digital tools.
The study measured how easy the platform felt right after a single training session. It did not track whether participants kept using it, built more complex programs, or completed a finished intervention that was tested on real people. The study also relied on self-reported impressions rather than objective measures of performance.
The Bottom Line
Based on this early evidence, researchers with no programming experience may be able to build simple digital health prototypes with CIAS-EU after a brief introduction. Confidence in this finding is moderate, because it comes from a single small workshop. Confidence that the platform is ready for large-scale use is lower. Researchers should plan for hands-on practice, read the documentation carefully, and consider getting support from someone experienced with branching logic before deploying anything to patients.
Health researchers, public health staff, educators, and graduate students who want to design digital health tools without hiring a developer should pay attention. Experienced software developers and people looking for a consumer app or personal health tracker will find little here that applies directly to them. Anyone planning to use a tool built this way with real patients should consult a qualified professional first.
Participants built simple prototypes within a single 90-minute session. Reaching the level of skill needed for a reliable, tested program will likely take weeks or months of regular practice. The study did not measure long-term progress, so the exact timeline for independent, confident use remains unknown.
Frequently Asked Questions
Can you build a digital health app without knowing how to code?
Researchers without programming experience can build simple digital health prototypes using no-code platforms. A 2026 study found that 15 of 16 participants built a working prototype with CIAS-EU after a single 90-minute hands-on session, though fuller mastery requires more practice.
What is CIAS-EU and who is it for?
CIAS-EU is an open-source, no-code platform that lets users create digital health interventions through visual drag-and-drop tools. It is designed for health researchers who lack programming skills. Its usability scored 70.8 out of 100 in a 2026 study of 16 participants.
How easy is the CIAS-EU platform to use?
Usability is above average but not excellent. In a 2026 study, the platform scored 70.8 on the System Usability Scale, where 68 is the common benchmark. Users praised its intuitive interface but found branching logic and advanced features difficult to learn.
What do beginners find hardest when using no-code health app builders?
In a 2026 study of CIAS-EU, beginners struggled most with understanding the platform’s structural logic, setting up branching paths, and discovering advanced features. Clearer documentation and more guided practice were identified as likely ways to make these tasks easier.
Want to Apply This Research?
- If you are building or testing a health program, track how many steps you complete without help, how long each prototype takes to finish, and how many times you need to consult the documentation. Recording these numbers each week gives a measurable sense of whether the tool is becoming easier to use.
- Set aside two or three short practice sessions in your first month. Start with a simple one-question program, then add one branching path at a time. Review the platform’s documentation before each session so that advanced features become familiar gradually.
- Repeat a short usability check every few months, such as the 10-question System Usability Scale, to see whether your confidence and results are improving. Keep notes on problems you run into, and share them with the developers or your user community. Over time, these records can show whether the platform is becoming more suitable for your work.
This article summarizes an early-stage usability study of a software platform with 16 participants, and it does not show that any health program built with this tool improves health. Anyone planning to create or use digital health tools for patients should consult qualified health and technology professionals and follow applicable ethical and data protection rules. This content is for general information and does not replace professional advice.
This research translation is published by Gram Research, the science division of Gram, an AI-powered nutrition tracking app.