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Accepted for/Published in: JMIR Aging

Date Submitted: Nov 17, 2023
Open Peer Review Period: Nov 17, 2023 - Jan 25, 2024
Date Accepted: Jun 5, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study

Badal VD, Reinen JM, Twamley EW, Lee EE, Fellows RP, Bilal E, Depp CA

Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study

JMIR Aging 2024;7:e54655

DOI: 10.2196/54655

PMID: 39283659

PMCID: 11443203

Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults

  • Varsha D. Badal; 
  • Jenna M. Reinen; 
  • Elizabeth W. Twamley; 
  • Ellen E. Lee; 
  • Robert P. Fellows; 
  • Erhan Bilal; 
  • Colin A. Depp

ABSTRACT

Background:

About one third of older adults aged 65 years and older often have mild cognitive impairment (MCI) or dementia. Acoustic and psycho-linguistic features derived from conversation may be of great diagnostic value because speech involves verbal memory, cognitive and neuromuscular processes. The relative decline in these processes, however, may not be linear and remains understudied.

Objective:

The relationship between cognitive health and speech or natural language has been gathering increasing attention in the emerging field of computational psychiatry. To date, the majority of research has been cross-sectional, relying mostly on data from structured interactions and restricted to textual versus acoustic analyses.

Methods:

In a sample of 71 older (mean age=83.3 years, SD=7.0 years) community-dwelling adults who completed qualitative interviews and cognitive testing, we investigated the performance of both acoustic and psycholinguistic features associated with cognitive deficits contemporaneously and at 1-2 years follow up (mean follow-up time = 512.3 days, SD=84.5 days).

Results:

Combined acoustic and psycholinguistic features achieve high performance (F1-scores 0.73-0.86) and sensitivity (up to 0.90) in estimating cognitive deficits across multiple domains. Performance remained high when acoustic and psycholinguistic features were used to predict follow-up cognitive performance. The psycholinguistic features that were most successful at classifying high cognitive impairment reflected vocabulary richness, quantity of speech produced, and the fragmentation of speech, whereas the analogous top ranked acoustic features reflected breathing and non-verbal vocalizations such as giggle or laughter.

Conclusions:

These results suggest that both acoustic and psycholinguistic features extracted from qualitative interviews may be reliable markers of cognitive deficits in late life.


 Citation

Please cite as:

Badal VD, Reinen JM, Twamley EW, Lee EE, Fellows RP, Bilal E, Depp CA

Investigating Acoustic and Psycholinguistic Predictors of Cognitive Impairment in Older Adults: Modeling Study

JMIR Aging 2024;7:e54655

DOI: 10.2196/54655

PMID: 39283659

PMCID: 11443203

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