Quantifying the Effects of Word Length, Frequency, and Predictability on Dyslexia
This work addresses reading difficulties for dyslexic individuals by identifying key lexical features that exacerbate costs, offering insights for interventions and models, though it is incremental in building on existing dyslexia theories.
The study quantified how word length, frequency, and predictability affect reading times in dyslexic versus typical readers, finding that dyslexic readers show stronger sensitivities, especially to predictability, and that manipulating these features reduced the reading gap by about one third.
We ask where, and under what conditions, dyslexic reading costs arise in a large-scale naturalistic reading dataset. Using eye-tracking aligned to word-level features (word length, frequency, and predictability), we model how each feature influences dyslexic time costs. We find that all three features robustly change reading times in both typical and dyslexic readers, and that dyslexic readers show stronger sensitivities to each, especially predictability. Counterfactual manipulations of these features substantially narrow the dyslexic-control gap by about one third, with predictability showing the strongest effect, followed by length and frequency. These patterns align with dyslexia theories that posit heightened demands on linguistic working memory and phonological encoding, and they motivate further work on lexical complexity and parafoveal preview benefits to explain the remaining gap. In short, we quantify when extra dyslexic costs arise, how large they are, and offer actionable guidance for interventions and computational models for dyslexics.