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. 2023 Mar 9;32(2):426-438.
doi: 10.1044/2022_AJSLP-22-00281. Epub 2023 Feb 15.

DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses

Alyssa M Lanzi  1   2 , Anna K Saylor  1 , Davida Fromm  3 , Houjun Liu  4 , Brian MacWhinney  3 , Matthew L Cohen  1   2   5
Affiliations

DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses

Alyssa M Lanzi et al. Am J Speech Lang Pathol. .

Abstract

Purpose: Dementia from Alzheimer's disease (AD) is characterized primarily by a significant decline in memory abilities; however, language abilities are also commonly affected and may precede the decline of other cognitive abilities. To study the progression of language, there is a need for open-access databases that can be used to build algorithms to produce translational models sensitive enough to detect early declines in language abilities. DementiaBank is an open-access repository of transcribed video/audio data from communicative interactions from people with dementia, mild cognitive impairment (MCI), and controls. The aims of this tutorial are to (a) describe the newly established standardized DementiaBank discourse protocol, (b) describe the Delaware corpus data, and (c) provide examples of automated linguistic analyses that can be conducted with the Delaware corpus data and describe additional DementiaBank resources.

Method: The DementiaBank discourse protocol elicits four types of discourse: picture description, story narrative, procedural, and personal narrative. The Delaware corpus currently includes data from 20 neurotypical adults and 33 adults with MCI from possible AD who completed the DementiaBank discourse protocol and a cognitive-linguistic battery. Language samples were video- and audio-recorded, transcribed, coded, and uploaded to DementiaBank. The protocol materials and transcription programs can be accessed for free via the DementiaBank website.

Results: Illustrative analyses show the potential of the Delaware corpus data to help understand discourse metrics at the individual and group levels. In addition, they highlight analyses that could be used across TalkBank's other clinical banks (e.g., AphasiaBank). Information is also included on manual and automatic speech recognition transcription methods.

Conclusions: DementiaBank is a shared online database that can facilitate research efforts to address the gaps in knowledge about language changes associated with MCI and dementia from AD. Identifying early language markers could lead to improved assessment and treatment approaches for adults at risk for dementia.

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Figures

Figure 1.
Figure 1.
EVAL-D dialog box.
Figure 2.
Figure 2.
Segment of EVAL-D spreadsheet output.
See this image and copyright information in PMC

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