Too Many Tabs Open? Using Everyday Computer Data to Support Focus for adults with ADHD

Adults with ADHD often struggle to maintain focus in digital environments, where multiple tabs and applications compete for attention. Although attention can be measured in clinical settings, there is a need for practical tools that operate in everyday contexts. This proof-of-concept study investigates whether simple patterns of computer use-such as tab switching frequency, idle time, and relevance of activity to the intended task-can be used to estimate attention in real time. A machine learning model trained on these features achieved a cross-validated R² of 0.77 within a small, simulated dataset-suggesting potential for this approach in predicting moment-to-moment attention. This approach has potential to inform more adaptive, accessible tools to support focus and self-regulation for adults with ADHD. As a preliminary proof-of-concept, these findings require validation in the real-world, ecologically valid settings with larger and more diverse samples.