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Integrating cognitive, linguistic and acoustic features to identify individuals with cognitive impairment: a proof-of-concept study
Chan, M. M. Y.; Robinson, G. A.. medRxiv (preprint), 2026-08-27
Topic: Risk, prevention and care in population studies
Early identification of cognitive impairment remains challenging in settings where comprehensive cognitive and clinical assessments are not available. Acoustic and linguistic features in naturalistic speech may serve as useful behavioural markers of cognitive impairment, but the value of integrating these measures with cognitive assessment remains unclear. We tested whether combining acoustic and linguistic features from one-minute speech samples with multi-domain cognitive assessment (spanning attention, language, memory and executive functions) improves classification of cognitively unimpaired individuals from those with amnestic mild cognitive impairment or early-stage Alzheimers Disease. Across multiple machine learning models, combining cognitive, acoustic and linguistic features yielded significantly better classification performance than models using cognitive or speech features alone (area under the curve = 0.96-0.98, both comparisons p < .05). This proof-of-concept study reveals that integrating speech-based measures with cognitive testing may improve identification of cognitive impairment, supporting the development of accessible and scalable multimodal screening tools for primary care.
Key findings
- Across multiple machine learning models, combining cognitive, acoustic and linguistic features yielded significantly better classification performance than models using cognitive or speech features alone (area under the curve = 0.96-0.98, both comparisons p < .05).
Why it matters
In this proof-of-concept study, combining cognitive, acoustic and linguistic features classified cognitively unimpaired people from those with amnestic mild cognitive impairment or early Alzheimer's disease better than either alone. It supports development of screening tools, not treatment, cure or prevention.
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Study details
- Evidence strengthLow
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 20 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on impact for its field and year, so that was left out: it earned 19 of the 94 points we could judge it on, which is 20 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (medRxiv (preprint)) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 0 / 7 | Cited 0 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.0 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 0 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Gail A. Robinson: h-index 30 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | The University of Queensland: institution h-index 1,516 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Points | 19 / 94 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 19 of the 94 points we could judge it on is 20 out of 100. |
| Total | 20 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Chan, M. M. Y., & Robinson, G. A. (2026). Integrating cognitive, linguistic and acoustic features to identify individuals with cognitive impairment: a proof-of-concept study. medRxiv (preprint). https://doi.org/10.64898/2026.08.25.26361344
Vancouver
Chan MMY, Robinson GA. Integrating cognitive, linguistic and acoustic features to identify individuals with cognitive impairment: a proof-of-concept study. medRxiv (preprint). 2026. doi:10.64898/2026.08.25.26361344.
BibTeX
@article{chan2026-81f7031c,
author = {Chan, M. M. Y. and Robinson, G. A.},
title = {{Integrating cognitive, linguistic and acoustic features to identify individuals with cognitive impairment: a proof-of-concept study}},
journal = {medRxiv (preprint)},
year = {2026},
doi = {10.64898/2026.08.25.26361344},
url = {https://doi.org/10.64898/2026.08.25.26361344}
}
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