About The Research
Research Overview
This research sought to answer one question: How can UX design improve user comprehension and trust in digital terms and privacy agreements? It investigated a critical gap in digital consent design where users often accept terms and privacy agreements without reading or understanding them. While most UX improvements focus on making interfaces easier or simpler to use, this study examined whether design changes actually improve user comprehension and trust in the process.
The OpenConsent Framework emerged from empirical research testing three different consent interface designs with real users, measuring both their understanding and their trust. What I discovered challenged conventional UX assumptions and revealed unexpected tensions between comprehension and trust.
In summary, the Framework represents an evidence-based approach to one of digital design's most persistent challenges: how to help users truly understand what they're agreeing to.
The Study
Method:
Mixed-methods approach combining quantitative metrics with qualitative insights
Participants:
10 adult digital users with diverse backgrounds and digital literacy levels
Data Collection Period:
October to November 2025
Three Designs Tested:
Total Consent: Traditional, comprehensive single-page design presenting all information at once
Tiered Consent: Progressive disclosure with layered information architecture
Selective Consent: Granular control allowing users to accept/reject individual terms
What Was Measured:
Comprehension accuracy (via post-interaction quizzes)
Trust levels (7-point Likert scale)
Task completion patterns
User confidence and decision-making
Qualitative feedback on clarity and control
Ethical Foundation:
Full ethics approval obtained from Falmouth University; all participants provided informed consent and interacted with fictional (non-consequential) consent scenarios.
Key Findings
The Comprehension-Trust Paradox:
The research revealed a striking paradox that challenges simplistic approaches to consent design. Total Consent (the most traditional design of the three) scored the highest comprehension (3.55 out of 5) and the lowest trust (3.1 out of 7). Selective Consent (UX-improved design) on the other hand scored the lowest comprehension (2.43 out of 5) and the highest trust (4.8 out of 7).
This finding suggests that making consent interfaces more user-friendly may increase trust while potentially reducing actual understanding. Users felt more in control with granular options, but this complexity fragmented their attention and reduced their grasp of what they were actually consenting to.
The Comprehension-Control Paradox:
More choice doesn't necessarily mean better understanding. The research found that:
Unified information flows (Total Consent) supported better mental model formation
Progressive disclosure and selective options risked hiding critical information
Cognitive simplicity sometimes outperforms UX sophistication for comprehension
Universal Button Confusion:
Across all three designs, participants struggled with button labels and action clarity. This wasn't a design-specific problem, it was a fundamental usability issue affecting consent interfaces universally, pointing to the need for explicit, unambiguous action design.
From Research to Framework
The OpenConsent Framework translates these empirical insights into 10 evidence-based design principles. Rather than prescribing a single "best" interface design, the framework acknowledges the inherent tensions in consent design and provides principles that help designers navigate the complexity.
Each principle is grounded in the research findings. For example:
Progressive Complexity emerged from understanding that simplicity aids comprehension, but users need access to detail.
Explicit Risk Communication addresses users' inability to assess implications in abstract legal language.
Transparent Data Practices responds to the trust-comprehension gap by front-loading critical information.
The framework prioritizes genuine user comprehension over superficial user experience improvements, recognizing that informed consent requires actual understanding, not just a pleasant interface.
Methodology
Design Framework:
Double Diamond (Discover, Define, Develop, Deliver)
Research Approach:
The study followed academic research standards with a structured methodology:
Literature Review: Analysis of existing consent practices, regulatory frameworks, and UX research
Prototype Development: High-fidelity prototypes created in Figma representing three distinct design approaches (Total, Tiered, and Selective)
User Testing: Moderated sessions with think-aloud protocols and observation
Data Collection: Quantitative metrics (comprehension scores, trust ratings, completion times) + qualitative insights (interviews, observations)
Analysis: Thematic analysis of qualitative data; descriptive statistics for quantitative measures
Tools Used: Figma (prototyping), Google Forms (comprehension testing), Google Sheets (data analysis), Google Meet (remote sessions)
Research Limitations
This research provides valuable insights while acknowledging important limitations:
Fictional Scenarios: Participants interacted with non-consequential consent flows. Real-world scenarios where users have genuine stakes (e.g., wanting to use an app they need) may produce different behaviors.
Sample Size: With 10 participants, findings are indicative rather than statistically generalizable. The research prioritizes depth of insight over statistical power.
Short-term Testing: The study measured immediate comprehension and trust, not long-term behavioral change or retention of consent information.
Context Constraints: Testing occurred in controlled settings with dedicated attention. Real-world consent happens amid distractions, time pressure, and competing priorities.
These limitations don't diminish the value of the findings, they contextualize them and point toward valuable directions for future research.
Future Research Directions
This research opens several promising avenues for further investigation:
Longitudinal Studies: How do comprehension and trust evolve over time and repeated interactions?
Real-world Implementation: Testing these principles in live consent flows with actual consequences
Cross-cultural Research: How do different cultural contexts affect consent comprehension and trust?
Cognitive Load Studies: Deeper investigation into the mental models users form during consent interactions
AI-Assisted Comprehension: Exploring how tools like an OpenConsent Tool (comprehension aid with summarization and Q&A) may affect understanding and trust of digital consent experiences.
Academic Foundation
This research was conducted as part of the MA User Experience Design program at Falmouth University (2024-2025).
Research Title: Designing for Informed Consent: A UX Approach to Improving Comprehension of Digital Terms and Privacy Agreements
Researcher: Isaac Quainoo (isaacquainoo.com)
Supervisors: Chengcheng Qu and Liz Coulter-Smith
Ethics Approval: Falmouth University Ethics Review Board