Key data points
- Across 5,733 individual test findings, comprehension friction, content that testers could technically access but couldn’t understand, was flagged more often than any other category, at 29.4%, ahead of “content not found” (21.6%) and accessibility-specific friction (19.4%).
- The most common WCAG criteria underlying comprehension findings are 3.3.2 (Labels or Instructions) and 3.1.3 (Unusual Words), tied at 99 occurrences each, followed by 2.4.6 (Headings and Labels, 66) and 3.1.5 (Reading Level, 62).
- Comprehension friction is not confined to any one disability group: it is the single most-cited friction category for testers with limited English proficiency (181 findings), and the second most-cited for blind testers (163) and low-vision testers (104), cohorts more commonly associated with access barriers than language barriers.
- When findings are synthesized into higher-level patterns rather than counted individually, accessibility-specific issues account for a larger share (35.9%) than comprehension (29.1%), because accessibility complaints from the same tester tend to consolidate into a smaller number of large, high-severity patterns, while comprehension issues are more numerous but more scattered.
- Accessibility-tagged patterns are rated high or severe severity 74.3% of the time, compared to 37.7% for comprehension-tagged patterns, meaning comprehension issues are reported more often, but accessibility issues are more likely to be serious when they occur.
Two different failure modes, both labelled “accessibility” by most teams
Most product teams treat “accessibility” as a single category: does the product work with assistive technology. This dataset (5,733 individual findings across 15 independently tested products) separates that into two measurably different failure modes. One is access: can the tester’s assistive technology or interaction method operate the interface at all. The other is comprehension: once the content is reached, does the tester actually understand what it says. These are tracked as separate friction types in this data, and the comprehension category is, by simple count, the largest single failure mode measured, ahead of pure access failures.
Comprehension is a plain-language problem more than a translation problem
Looking at which WCAG criteria are actually tagged against comprehension-labelled findings clarifies what’s failing:
| WCAG criterion | Description | Occurrences in comprehension findings |
|---|---|---|
| 3.3.2 | Labels or Instructions | 99 |
| 3.1.3 | Unusual Words | 99 |
| 2.4.6 | Headings and Labels | 66 |
| 1.3.1 | Info and Relationships | 65 |
| 3.1.5 | Reading Level | 62 |
| 3.1.4 | Abbreviations | 34 |
| 3.3.1 / 3.3.3 | Error Identification / Suggestion | 18 each |
Unusual Words (3.1.3) and Reading Level (3.1.5) together account for a substantial share of comprehension findings, and both concern plain-language writing: unexplained jargon, technical terminology, and sentence complexity above what the content actually requires. This is a content design and UX writing problem, not primarily a translation, captioning, or code-level accessibility problem, and it shows up across content that is already technically “accessible” by conformance standards.
Comprehension friction cuts across cohorts that don’t share a language or sensory barrier
The cohort breakdown for comprehension findings is the clearest evidence that this isn’t a niche language-access issue: limited-English-proficiency testers generate the most comprehension findings (181), unsurprising, but blind testers (163) and low-vision testers (104) are the second and third largest sources, followed closely by deaf testers (101), over-65 testers (90), and neurodivergent testers (86). These six cohorts share almost nothing in terms of assistive technology or sensory need, yet all six generate substantial comprehension friction. The common thread is not disability type; it’s that unclear labelling, undefined jargon, and dense sentence structure create friction for any tester, regardless of how they’re accessing the content.
Why the ranking flips at the pattern-synthesis level
A close look at this dataset’s two levels of analysis explains an apparent contradiction that’s worth being transparent about. At the level of individual, unsynthesized findings, comprehension is the largest category (29.4% vs. 19.4% for accessibility). But once findings are synthesized into consolidated patterns (grouping multiple individual observations from the same root cause into one pattern-level insight), accessibility overtakes comprehension (35.9% vs. 29.1%). The explanation is consistent with how accessibility failures tend to behave: a single structural access barrier (for example, a control with no accessible name) often generates many individual findings from the same tester across a session, which consolidate into one large, high-severity pattern. Comprehension issues are more evenly distributed (many separate wording, labelling, and structure problems scattered across different parts of a product), so they generate more individual findings but fewer giant consolidated patterns. Both views are accurate; they answer different questions. If the question is “what do testers run into most often,” comprehension leads. If the question is “what’s driving the largest, most severe consolidated problem areas,” accessibility leads.
What this means for content and product teams
The practical implication is that a plain-language pass is not a “nice to have” layered on top of accessibility work: in this dataset, it addresses the single most frequently occurring friction category, ahead of pure access failures, and it benefits cohorts far beyond the audience most content teams assume they’re writing for. Two specific, low-effort interventions map directly onto the largest comprehension sub-categories: defining or removing unusual/technical terms on first use (addressing 3.1.3, tied for the top comprehension-linked criterion) and auditing form labels and instructions for specificity (addressing 3.3.2, the other top criterion): together these two fixes touch roughly 43% of all comprehension findings with a WCAG tag in this dataset.
Frequently asked questions
What is the most common type of usability friction found in real testing, comprehension or accessibility?
It depends on the level of analysis. Counting individual findings directly, comprehension friction is the largest category at 29.4%, ahead of accessibility-specific friction at 19.4%. Counting consolidated, synthesized patterns, accessibility edges ahead at 35.9% versus 29.1% for comprehension, because accessibility issues tend to generate fewer but larger, more severe consolidated patterns.
Which WCAG criteria are most associated with comprehension failures rather than access failures?
Labels or Instructions (3.3.2) and Unusual Words (3.1.3) are tied as the most common, each appearing in 99 comprehension-tagged findings in this dataset, followed by Headings and Labels (2.4.6) and Reading Level (3.1.5).
Is content comprehension only a problem for non-native speakers?
No. While limited-English-proficiency testers generated the most comprehension findings in this dataset, blind testers were the second-largest source (163 findings) and low-vision testers were third (104), followed by deaf, over-65, and neurodivergent testers: comprehension friction affects cohorts with no shared language or sensory barrier.
About this analysis
Figures in this article are drawn from an anonymised aggregation of 15 independent usability testing projects conducted by See Me Please between late 2025 and mid-2026. Friction-type tagging, cohort assignment, and WCAG mapping were applied during test synthesis by trained reviewers based on task-based sessions. Individual-level figures reflect unsynthesized test findings; pattern-level figures reflect the same findings after consolidation into higher-level insights. All client and participant identities have been removed.
