An automated approach to examining conversational dynamics between people with dementia and their carers

Christina Atay, Erin R. Conway, Daniel Angus, Janet Wiles, Rosemary Baker, Helen J. Chenery

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)
81 Downloads (Pure)

Abstract

The progressive neuropathology involved in dementia frequently causes a gradual decline in communication skills. Communication partners who are unaware of the specific communication problems faced by people with dementia (PWD) can inadvertently challenge their conversation partner, leading to distress and a reduced flow of information between speakers. Previous research has produced an extensive literature base recommending strategies to facilitate conversational engagement in dementia. However, empirical evidence for the beneficial effects of these strategies on conversational dynamics is sparse. This study uses a timeefficient computational discourse analysis tool called Discursis to examine the link between specific communication behaviours and content-based conversational engagement in 20 conversations between PWD living in residential aged-care facilities and care staff members. Conversations analysed here were baseline conversations recorded before staff members underwent communication training. Care staff members spontaneously exhibited a wide range of facilitative and non-facilitative communication behaviours, which were coded for analysis of conversation dynamics within these baseline conversations. A hybrid approach combining manual coding and automated Discursis metric analysis provides two sets of novel insights. Firstly, this study revealed nine communication behaviours that, if used by the care staff member in a given turn, significantly increased the appearance of subsequent content- based engagement in the conversation by PWD. Secondly, the current findings reveal alignment between human- and computer-generated labelling of communication behaviour for 8 out of the total 22 behaviours under investigation. The approach demonstrated in this study provides an empirical procedure for the detailed evaluation of content-based conversational engagement associated with specific communication behaviours.

Original languageEnglish
Article numbere0144327
JournalPLoS One
Volume10
Issue number12
DOIs
Publication statusPublished - 1 Dec 2015

Fingerprint

dementia
animal communication
Caregivers
Dementia
Communication
communication (human)
communication skills
neuropathology
distress
Interpersonal Relations
Labeling
Research

Cite this

Atay, C., Conway, E. R., Angus, D., Wiles, J., Baker, R., & Chenery, H. J. (2015). An automated approach to examining conversational dynamics between people with dementia and their carers. PLoS One, 10(12), [e0144327]. https://doi.org/10.1371/journal.pone.0144327
Atay, Christina ; Conway, Erin R. ; Angus, Daniel ; Wiles, Janet ; Baker, Rosemary ; Chenery, Helen J. / An automated approach to examining conversational dynamics between people with dementia and their carers. In: PLoS One. 2015 ; Vol. 10, No. 12.
@article{a3fa84d94c634fa19eeba14dde4c5b3a,
title = "An automated approach to examining conversational dynamics between people with dementia and their carers",
abstract = "The progressive neuropathology involved in dementia frequently causes a gradual decline in communication skills. Communication partners who are unaware of the specific communication problems faced by people with dementia (PWD) can inadvertently challenge their conversation partner, leading to distress and a reduced flow of information between speakers. Previous research has produced an extensive literature base recommending strategies to facilitate conversational engagement in dementia. However, empirical evidence for the beneficial effects of these strategies on conversational dynamics is sparse. This study uses a timeefficient computational discourse analysis tool called Discursis to examine the link between specific communication behaviours and content-based conversational engagement in 20 conversations between PWD living in residential aged-care facilities and care staff members. Conversations analysed here were baseline conversations recorded before staff members underwent communication training. Care staff members spontaneously exhibited a wide range of facilitative and non-facilitative communication behaviours, which were coded for analysis of conversation dynamics within these baseline conversations. A hybrid approach combining manual coding and automated Discursis metric analysis provides two sets of novel insights. Firstly, this study revealed nine communication behaviours that, if used by the care staff member in a given turn, significantly increased the appearance of subsequent content- based engagement in the conversation by PWD. Secondly, the current findings reveal alignment between human- and computer-generated labelling of communication behaviour for 8 out of the total 22 behaviours under investigation. The approach demonstrated in this study provides an empirical procedure for the detailed evaluation of content-based conversational engagement associated with specific communication behaviours.",
author = "Christina Atay and Conway, {Erin R.} and Daniel Angus and Janet Wiles and Rosemary Baker and Chenery, {Helen J.}",
year = "2015",
month = "12",
day = "1",
doi = "10.1371/journal.pone.0144327",
language = "English",
volume = "10",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "12",

}

An automated approach to examining conversational dynamics between people with dementia and their carers. / Atay, Christina; Conway, Erin R.; Angus, Daniel; Wiles, Janet; Baker, Rosemary; Chenery, Helen J.

In: PLoS One, Vol. 10, No. 12, e0144327, 01.12.2015.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - An automated approach to examining conversational dynamics between people with dementia and their carers

AU - Atay, Christina

AU - Conway, Erin R.

AU - Angus, Daniel

AU - Wiles, Janet

AU - Baker, Rosemary

AU - Chenery, Helen J.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - The progressive neuropathology involved in dementia frequently causes a gradual decline in communication skills. Communication partners who are unaware of the specific communication problems faced by people with dementia (PWD) can inadvertently challenge their conversation partner, leading to distress and a reduced flow of information between speakers. Previous research has produced an extensive literature base recommending strategies to facilitate conversational engagement in dementia. However, empirical evidence for the beneficial effects of these strategies on conversational dynamics is sparse. This study uses a timeefficient computational discourse analysis tool called Discursis to examine the link between specific communication behaviours and content-based conversational engagement in 20 conversations between PWD living in residential aged-care facilities and care staff members. Conversations analysed here were baseline conversations recorded before staff members underwent communication training. Care staff members spontaneously exhibited a wide range of facilitative and non-facilitative communication behaviours, which were coded for analysis of conversation dynamics within these baseline conversations. A hybrid approach combining manual coding and automated Discursis metric analysis provides two sets of novel insights. Firstly, this study revealed nine communication behaviours that, if used by the care staff member in a given turn, significantly increased the appearance of subsequent content- based engagement in the conversation by PWD. Secondly, the current findings reveal alignment between human- and computer-generated labelling of communication behaviour for 8 out of the total 22 behaviours under investigation. The approach demonstrated in this study provides an empirical procedure for the detailed evaluation of content-based conversational engagement associated with specific communication behaviours.

AB - The progressive neuropathology involved in dementia frequently causes a gradual decline in communication skills. Communication partners who are unaware of the specific communication problems faced by people with dementia (PWD) can inadvertently challenge their conversation partner, leading to distress and a reduced flow of information between speakers. Previous research has produced an extensive literature base recommending strategies to facilitate conversational engagement in dementia. However, empirical evidence for the beneficial effects of these strategies on conversational dynamics is sparse. This study uses a timeefficient computational discourse analysis tool called Discursis to examine the link between specific communication behaviours and content-based conversational engagement in 20 conversations between PWD living in residential aged-care facilities and care staff members. Conversations analysed here were baseline conversations recorded before staff members underwent communication training. Care staff members spontaneously exhibited a wide range of facilitative and non-facilitative communication behaviours, which were coded for analysis of conversation dynamics within these baseline conversations. A hybrid approach combining manual coding and automated Discursis metric analysis provides two sets of novel insights. Firstly, this study revealed nine communication behaviours that, if used by the care staff member in a given turn, significantly increased the appearance of subsequent content- based engagement in the conversation by PWD. Secondly, the current findings reveal alignment between human- and computer-generated labelling of communication behaviour for 8 out of the total 22 behaviours under investigation. The approach demonstrated in this study provides an empirical procedure for the detailed evaluation of content-based conversational engagement associated with specific communication behaviours.

UR - http://www.scopus.com/inward/record.url?scp=84955464572&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0144327

DO - 10.1371/journal.pone.0144327

M3 - Article

VL - 10

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 12

M1 - e0144327

ER -