Evidence map›Paper›PMID 40666441›Full record

ArticleFrontiers in psychiatry2025

Audio and linguistic prediction of objective and subjective cognition in older adults: what is the role of different prompts?

Varsha D Badal, Caitlyn Tran, Haze Brown, Danielle K Glorioso, Rebecca Daly, Anthony J A Molina, Alison A Moore, Erhan Bilal, Ellen E Lee, Colin A Depp

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Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Varsha D BadalDepartment of Psychiatry, University of California San Diego, San Diego, CA, United States.
Caitlyn TranUniversity of California San Diego, San Diego, CA, United States.
Haze BrownUniversity of California San Diego, San Diego, CA, United States.
Danielle K GloriosoDepartment of Psychiatry, University of California San Diego, San Diego, CA, United States.
Rebecca DalyDepartment of Psychiatry, University of California San Diego, San Diego, CA, United States.
Anthony J A MolinaStein Institute for Research on Aging, University of California San Diego, San Diego, CA, United States.
Alison A MooreStein Institute for Research on Aging, University of California San Diego, San Diego, CA, United States.
Erhan BilalInternational Business Machines Corporation (IBM) Research, Yorktown, NY, United States.
Ellen E LeeDepartment of Psychiatry, University of California San Diego, San Diego, CA, United States.
Colin A DeppDepartment of Psychiatry, University of California San Diego, San Diego, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Psycho-linguistic and audio data derived from speech may be useful in screening and monitoring cognitive aging. However, there are gaps in understanding the predictive value of different prompts (e.g., open ended or structured) and the relationship of features to subjective versus objective cognition. Objective: To advance understanding of method variation in speech-analysis based psychometry, we evaluated targeted prompts for classification of impaired cognition and cognitive complaints. Method: A sample of 49 older participants (mean age: 76.9, SD: 8.5) completed short interview questions and cognitive assessments. Acoustic and Linguistic Inquiry through Word Counting i.e., LIWC (verbal content-based) features were derived from answers to open ended questions about aging (AG) and the Cookie Theft task (CT). Outcomes were objective cognitive ability measured using Telephone Interview for Cognitive Status (TICS-m), and subjective cognition using Cognitive Failures Questionnaire (CFQ). Results: A combined feature set including acoustic and LIWC (verbal content) yielded excellent classification results for both CFQ and TICS-m. The F1, precision and recall for CFQ elevation was 0.83, 0.85 and 0.82, and for TICS-m cutoff was 0.92, 0.92 and 0.92 respectively (using single learners). Features derived from CT task were of greater relevance to TICS-m classification, while the features from the AG task were of greater relevance to the CFQ classification. Conclusion: Acoustic and psycholinguistic features are relevant to assessment of cognition and subjective cognitive complaints, with combined features performing best. However, subjective and objective cognitions were predicted to differing extents by the different tasks, and the feature sets.

Indexed as

acousticAlzheimer’scognitive impairmentdementiamachine learningNLPpsycholinguistic

Identifiers

PMID40666441
PMCPMC12259555

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.