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Detecting Apathy in Older Adults with Cognitive Disorders Using Automatic Speech Analysis
König A, Linz N, Zeghari R, Klinge X, Tröger J, Alexandersson J, Robert P.. Journal of Alzheimer's disease : JAD, 2019-01-01
Topic: Risk, prevention and care in population studies
Background Apathy is present in several psychiatric and neurological conditions and has been found to have a severe negative effect on disease progression. In older people, it can be a predictor of increased dementia risk. Current assessment methods lack objectivity and sensitivity, thus new diagnostic tools and broad-scale screening technologies are needed. Objective This study is the first of its kind aiming to investigate whether automatic speech analysis could be used for characterization and detection of apathy. Methods A group of apathetic and non-apathetic patients (n = 60) with mild to moderate neurocognitive disorder were recorded while performing two short narrative speech tasks. Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, examined between the groups and compared to baseline assessments. Machine learning experiments were carried out to validate the diagnostic power of extracted markers. Results Correlations between apathy sub-scales and features revealed a relation between temporal aspects of speech and the subdomains of reduction in interest and initiative, as well as between prosody features and the affective domain. Group differences were found to vary for males and females, depending on the task. Differences in temporal aspects of speech were found to be the most consistent difference between apathetic and non-apathetic patients. Machine learning models trained on speech features achieved top performances of AUC = 0.88 for males and AUC = 0.77 for females. Conclusions These findings reinforce the usability of speech as a reliable biomarker in the detection and assessment of apathy.
Key findings
- Paralinguistic markers relating to prosodic, formant, source, and temporal qualities of speech were automatically extracted, examined between the groups and compared to baseline assessments.
- Results Correlations between apathy sub-scales and features revealed a relation between temporal aspects of speech and the subdomains of reduction in interest and initiative, as well as between prosody features and the affective domain.
- Conclusions These findings reinforce the usability of speech as a reliable biomarker in the detection and assessment of apathy.
Why it matters
In 60 patients with mild to moderate neurocognitive disorder, automatic speech analysis found links between speech features and apathy. It is a detection study and reports no treatment, cure, or prevention.
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Study details
- Participants60
- Effect sizeAUC = 0.88; AUC = 0.77
- Evidence strengthLow
How this study scored 48/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of Alzheimer's disease : JAD) |
| Journal's citation record | 2 / 4 | Journal of Alzheimer s Disease: journal h-index 218 (OpenAlex, 2026-10-29) |
| 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 | 2 / 5 | 2019 — within 10 year(s) of the newest study here |
| Sample size | 1 / 4 | 60 participants |
| Effect reported | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| 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 | 4 / 7 | Cited 57 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 6.3 citations a year over 9 year(s) since 2019 |
| Impact for its field and year | 3 / 6 | Cited 5.3× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 2 / 4 | Cited 18 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Philippe Henri Robert: h-index 61 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Université Côte d'Azur: institution h-index 696 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 31127764) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 48 / 100 | — |
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Read the original
- DOI: 10.3233/jad-181033
- PubMed: 31127764
- Original source →
- Free full text: Journal of Alzheimer s Disease →
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. The record names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
König, A., Linz, N., Zeghari, R., Klinge, X., Tröger, J., Alexandersson, J., et al. (2019). Detecting Apathy in Older Adults with Cognitive Disorders Using Automatic Speech Analysis. Journal of Alzheimer's disease : JAD. https://doi.org/10.3233/jad-181033
Vancouver
König A, Linz N, Zeghari R, Klinge X, Tröger J, Alexandersson J, et al. Detecting Apathy in Older Adults with Cognitive Disorders Using Automatic Speech Analysis. Journal of Alzheimer's disease : JAD. 2019. doi:10.3233/jad-181033. PMID: 31127764.
BibTeX
@article{konig2019-31127764,
author = {König, A. and Linz, N. and Zeghari, R. and Klinge, X. and Tröger, J. and Alexandersson, J. and Robert, P.},
title = {{Detecting Apathy in Older Adults with Cognitive Disorders Using Automatic Speech Analysis}},
journal = {Journal of Alzheimer's disease : JAD},
year = {2019},
doi = {10.3233/jad-181033},
pmid = {31127764},
url = {https://doi.org/10.3233/jad-181033}
}
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