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An Automated Approach to Examining Conversational Dynamics between People with Dementia and Their Carers

Overview of attention for article published in PLOS ONE, December 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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116 Mendeley
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Title
An Automated Approach to Examining Conversational Dynamics between People with Dementia and Their Carers
Published in
PLOS ONE, December 2015
DOI 10.1371/journal.pone.0144327
Pubmed ID
Authors

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

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 time-efficient 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 116 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 19%
Student > Ph. D. Student 19 16%
Student > Doctoral Student 15 13%
Researcher 10 9%
Student > Bachelor 8 7%
Other 21 18%
Unknown 21 18%
Readers by discipline Count As %
Psychology 30 26%
Nursing and Health Professions 26 22%
Medicine and Dentistry 11 9%
Social Sciences 9 8%
Linguistics 5 4%
Other 11 9%
Unknown 24 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 June 2019.
All research outputs
#5,066,931
of 24,187,594 outputs
Outputs from PLOS ONE
#75,981
of 208,062 outputs
Outputs of similar age
#82,053
of 397,517 outputs
Outputs of similar age from PLOS ONE
#1,251
of 4,883 outputs
Altmetric has tracked 24,187,594 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 208,062 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 397,517 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 4,883 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.