Rural communities face significant barriers to early identification and prevention of dementia and related neurological conditions. Limited access to specialty care, transportation challenges, and healthcare workforce shortages can delay detection of cognitive-communication decline and reduce opportunities for early intervention.

This project evaluated whether speech and language data are associated with cognitive performance and whether these data can be collected through a mobile, community-based brain health screening model. Using ADNI Cohort 4 storytelling data, we examined lexical, discourse, acoustic, and voice features in relation to cognitive outcomes. Findings showed that several speech and language variables, including delayed story recall, speech duration, syntactic cohesion, and acoustic features, were associated with cognitive performance.

The BRAIN-FIT pilot brought brief, noninvasive brain health screening and individualized education into trusted rural community settings. In Year 1, BRAIN-FIT reached 163 participants across 18 community events. Evaluation results supported the acceptability, relevance, and feasibility of the model.

These findings suggest that speech and language measures may be useful, scalable indicators of cognitive health and that mobile community-based screening may be a way to provide noninvasive screenings such as speech and language to improve access to dementia risk prevention and early detection in rural populations.