Reading with Diversity in Mind: Pupillometry and Typography Towards Inclusive Design for ADHD Readers
Borano Llana, Alisa Baron, Haihan Yu, Maedeh Hosseinpour, Yusra Suhail, Sean Chin, Kushas Khadka, Shaun Wallace · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26) · doi:10.1145/3772363.3799383
Summary
Llana and colleagues at the University of Rhode Island examine how typographic choices interact with ADHD when reading digital text. The motivation is practical: digital reading is now the default for most education and work, and small typographic decisions (font family, size, spacing) materially shape comprehension, speed, and cognitive effort - yet ADHD readers are an under-studied population in readability research. The authors ran a controlled in-lab study with an EyeLink Portable Duo eye tracker recording fixations, saccades, and pupil dilation while 21 participants (6 with ADHD, screened with the Adult ADHD Self-Report Scale ASRS-v1.1) read four eighth-grade-level passages, each randomly assigned one of four Roboto variants (Default sans-serif, Mono, Serif, Slab) and one of three sizes (14/16/18 px), followed by five-question multiple-choice comprehension quizzes. As a methodological contribution they also released ReadGen, an open-source tool that generates consistent text images for SR Research's Experiment Builder so pupillometry data are not contaminated by viewing-angle artifacts. Quantitative analysis used Pearson correlations linking pupil size to reading speed, mixed-effects linear models for ADHD effects on speed, and a Poisson regression for saccade counts. They followed the lab study with five semi-structured interviews of ADHD participants on what helps or hurts focus during digital reading.
Key findings
Reading speed correlated negatively with mean pupil dilation (r=-0.376, p<.001) across all participants - faster reading meant smaller pupils, consistent with lower cognitive effort - and 61.9%% of participants showed an ~8.5%% gradual decrease in pupil size over the session, suggesting effort drops with sustained reading. The clearest typographic effect was a familiar speed-comprehension trade-off: Roboto Default produced the fastest reading (~10%% above mean) but the lowest accuracy (~27%%), while Roboto Serif was the slowest but most accurate (~34%%). Font size effects on comprehension were small. The ADHD-specific findings are the headline. Mixed-effects models found ADHD participants read significantly faster than non-ADHD participants (p=.029), and Poisson regression showed they made roughly 22%% fewer saccades (IRR=0.78, beta=-0.245, p=.013), suggesting broader, less detailed visual scanning. The two groups also responded to typography differently: ADHD readers were fastest with the default sans-serif Roboto at smaller sizes (14-16 px), while non-ADHD readers were fastest with Roboto Serif at 18 px. Qualitative interviews reinforced the design implications: ADHD participants reported that ads, notifications, AI summaries, visual clutter, and continuous scrolling derail reading; 80%% wanted user-controlled font, size, brightness, and background; all preferred dark or warm color palettes; 67%% favored interfaces that emulate physical books with chunked text, consistent formatting, and annotation.
Relevance
For accessibility practitioners and reading-tool designers, this paper is useful on three fronts. First, it provides direct evidence that ADHD readers are not just non-ADHD readers with worse focus - their visual scanning, preferred font, and preferred size are systematically different, which means fixed defaults optimized for the general population may actively underserve them. Second, the speed-comprehension trade-off across font variants reframes 'good for ADHD' as a choice between throughput and accuracy that should be user-controlled, not pre-selected by designers. Third, the qualitative themes (distraction-free chrome, customization controls for font/size/contrast, chunked text, dark/warm color modes, no auto-injected AI summaries) form a concrete design checklist for any product targeting reading by people with ADHD. The pupillometry-as-cognitive-effort signal is also methodologically useful for evaluating future readability tools beyond self-report. Caveats are significant: only 6 ADHD participants, all university-affiliated and 90%% with a bachelor's or higher, short laboratory passages rather than long-form reading, and the study cannot disentangle ADHD-specific scanning strategies from individual variation. The authors frame the paper as a prequel - the right next steps are larger samples, longer passages, and ablations of which interface customizations actually help.
Tags: readability · typography · ADHD · eye tracking · pupillometry · cognitive accessibility · reading