Evidence map›Paper›PMID 41341281›Full record

Article... Workshop on Cognitive Modeling and Computational Linguistics. Workshop on Cognitive Modeling and Computational Linguistics2025

"Is There Anything Else?": Examining Administrator Influence on Linguistic Features from the Cookie Theft Picture Description Cognitive Test.

Changye Li, Zhecheng Sheng, Trevor Cohen, Serguei Pakhomov

Abstract read
In one paragraph

Article in ... Workshop on Cognitive Modeling and Computational Linguistics. Workshop on Cognitive Modeling and Computational Linguistics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Changye LiUniversity of Washington.
Zhecheng ShengUniversity of Minnesota.
Trevor CohenUniversity of Washington.
Serguei PakhomovUniversity of Minnesota.

Funding

DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLPR01LM014056 · NLM · UNIVERSITY OF WASHINGTON · PI COHEN, TREVOR, PAKHOMOV, SERGUEI VS · 2022 to 2025
$1.7M
Computerized assessment of linguistic indicators of lucidity in Alzheimer's Disease dementiaR21AG069792 · NIA · UNIVERSITY OF MINNESOTA · PI MICHALOWSKI, MARTIN, PAKHOMOV, SERGUEI VS · 2020 to 2021
$671k
NIA NIH HHS R21 AG069792NLM NIH HHS R01 LM014056
6 · The paper itself

Abstract

Alzheimer's Disease (AD) dementia is a progressive neurodegenerative disease that negatively impacts patients' cognitive ability. Previous studies have demonstrated that changes in naturalistic language samples can be useful for early screening of AD dementia. However, the nature of language deficits often requires test administrators to use various speech elicitation techniques during spontaneous language assessments to obtain enough propositional utterances from dementia patients. This could lead to the "observer's effect" on the downstream analysis that has not been fully investigated. Our study seeks to quantify the influence of test administrators on linguistic features in dementia assessment with two English corpora the "Cookie Theft" picture description datasets collected at different locations and test administrators show different levels of administrator involvement. Our results show that the level of test administrator involvement significantly impacts observed linguistic features in patient speech. These results suggest that many of significant linguistic features in the downstream classification task may be partially attributable to differences in the test administration practices rather than solely to participants' cognitive status. The variations in test administrator behavior can lead to systematic biases in linguistic data, potentially confounding research outcomes and clinical assessments. Our study suggests that there is a need for a more standardized test administration protocol in the development of responsible clinical speech analytics frameworks.

Identifiers

PMID41341281
PMCPMC12671980

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Registered trials

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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.