Accessible data visualization for university students screening positive on the adult ADHD self-report scale

Abstract Digital information is increasingly delivered through visual interfaces, yet these interfaces are rarely designed with neurodiverse cognitive profiles in mind. This study evaluated how different data visualization formats influence information processing, perceived cognitive demand, user preference, and supplementary physiological indicators among university students who screened positive or negative on the Adult ADHD Self-Report Scale (ASRS v1.1). A controlled experimental study was conducted with 70 participants (40 ASRS-negative and 30 ASRS-positive), who completed information-processing tasks using eight visualization formats: Plain Text, Highlighted Text, Bar Charts, Bar Charts with Images, Pictographs, Simplified Infographics, Detailed Infographics, and AI-modified Text. Performance was assessed using the Inverse Efficiency Score (IES), while heart rate and peripheral oxygen saturation (SpO $$_2$$ ) were recorded as supplementary physiological measures. Data were analyzed using Two-Way Mixed ANOVA, Linear Mixed-Effects Models, MANOVA, Bonferroni-adjusted post hoc comparisons, and Bayesian analyses. The results demonstrated a significant interaction between participant group and visualization format ( $$p<0.001$$ , partial $$\eta ^2=0.104$$ ), indicating that visualization effectiveness differed between students screening positive and negative on the ASRS. Plain Text, Highlighted Text, and Bar Charts with Images generally supported comparatively better behavioral performance across groups, whereas Detailed Infographics and AI-modified Text were associated with substantially poorer performance among ASRS-positive participants (Hedges’ $$g=-1.775$$ and $$-1.162$$ , respectively). Contrary to common assumptions, text highlighting did not consistently improve performance across groups, suggesting that attentional cues may not be universally beneficial. Evidence of divergence between subjective preference and objective performance was observed for selected visualization formats, indicating that user preference alone may not reliably predict behavioral effectiveness. Physiological measurements exhibited relatively limited variation across experimental conditions and are therefore interpreted as supplementary rather than primary indicators. These findings provide empirically derived recommendations for designing more accessible digital learning materials for university students who screen positive on the ASRS while highlighting the importance of evaluating visualization effectiveness using objective behavioral measures alongside subjective user feedback.