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Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment
Robin J, Xu M, Kaufman LD, Simpson W.. Frontiers in digital health, 2021-10-27
Topic: Brain imaging, connectivity and assessment
Detecting early signs of cognitive decline is crucial for early detection and treatment of Alzheimer's Disease. Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing. Recent findings have highlighted changes to speech and language patterns that occur in Alzheimer's Disease, and may be detectable prior to diagnosis. Automated tools to assess speech have been developed that can be used on a smartphone or tablet, from one's home, in under 10 min. In this study, we present the results of a study of older adults who completed a digital speech assessment task over a 6-month period. Participants were grouped according to those who scored above ( N = 18) or below ( N = 18) the recommended threshold for detecting cognitive impairment on the Montreal Cognitive Assessment (MoCA) and those with diagnoses of mild cognitive impairment (MCI) or early Alzheimer's Disease (AD) ( N = 14). Older adults who scored above the MoCA threshold had better performance on speech composites reflecting language coherence, information richness, syntactic complexity, and word finding abilities. Those with MCI and AD showed more rapid decline in the coherence of language from baseline to 6-month follow-up, suggesting that this score may be useful both for detecting cognitive decline and monitoring change over time. This study demonstrates that automated speech assessments have potential as sensitive tools to detect early signs of cognitive impairment and monitor progression over time.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Robin, J., Xu, M., Kaufman, L. D., & Simpson, W. (2021). Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment. Frontiers in digital health. https://doi.org/10.3389/fdgth.2021.749758
Vancouver
Robin J, Xu M, Kaufman LD, Simpson W. Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment. Frontiers in digital health. 2021. doi:10.3389/fdgth.2021.749758. PMID: 34778869.
BibTeX
@article{robin2021-34778869,
author = {Robin, J. and Xu, M. and Kaufman, L. D. and Simpson, W.},
title = {{Using Digital Speech Assessments to Detect Early Signs of Cognitive Impairment}},
journal = {Frontiers in digital health},
year = {2021},
doi = {10.3389/fdgth.2021.749758},
pmid = {34778869},
url = {https://doi.org/10.3389/fdgth.2021.749758}
}
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Key findings
- Most of the current screening tools for Alzheimer's Disease represent a significant burden, requiring invasive procedures, or intensive and costly clinical testing.
- In this study, we present the results of a study of older adults who completed a digital speech assessment task over a 6-month period.
- Those with MCI and AD showed more rapid decline in the coherence of language from baseline to 6-month follow-up, suggesting that this score may be useful both for detecting cognitive decline and monitoring change over time.
Study details
- Participants18
- Evidence strengthLow
How this study scored 50/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 29 of the 58 points we could judge it on, which is 50 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in digital health) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| 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 | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2021 — within 6 year(s) of the newest study here |
| Sample size | 1 / 4 | 18 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| 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 | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 34778869) |
| Free to read | 2 / 2 | Free to read |
| Points | 29 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 29 of the 58 points we could judge it on is 50 out of 100. |
| Total | 50 / 100 | — |
What each of these 20 components measures, and what this score is not →
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