Everyday Language and Cognitive Functioning in Late Life.

Abstract

Objectives: Language deterioration is a marker of cognitive decline in late life. An emerging literature has examined features of language associated with executive functioning and working memory when older adults are cognitively healthy. This study aims to identify linguistic features that predict cognitive functioning in a sample of cognitively healthy individuals.

Method: Participants from the Daily Experiences and Well-being Study (DEWS) (aged 65-89, N = 260) completed a battery of standard cognitive tests. They wore an Android device containing the Electronically Activated Recorder (EAR) app, which recorded ambient sound 30 seconds every 7 minutes for 5 to 6 days (N= 26,339 sound files with participant speech). Linguistic Inquiry and (LIWC) software generated linguistic features from transcriptions of recorded speech. Machine learning models (random forest classifier) were trained with the linguistic features (n = 29) to predict cognitive functioning.

Results: Principal component analysis (PCA) revealed that the cognitive domains fit a single factor. The random forest classifier achieved robust model performance (accuracy = 0.72, precision = 0.74, recall = 0.91, F1-score = 0.81, and AUC = 0.73). Linguistic features most strongly associated with cognitive functioning included: first-person singular pronouns (with worse cognitive functioning), articles, words indicating differentiation, first-person plural pronouns, and words per sentence (with better cognitive functioning).

Discussion: Findings suggest that language processes are evident across multiple domains of cognitive functioning when older adults remain within a cognitively healthy range. Use of complex language may indicate optimal cognitive functioning, a topic worthy of future investigation.