Difference between revisions of "Blackburn-etal2016"
ElliottHoey (talk | contribs) (Created page with "{{BibEntry |BibType=ARTICLE |Author(s)=Daniel Blackburn; Chris Elsey; Kirsty Harkness; Sarah Wakefield; Annalena Venneri; Paul Drew; Markus Reuber |Title=Conversation analysis...") |
(No difference)
|
Revision as of 22:18, 11 December 2016
| Blackburn-etal2016 | |
|---|---|
| BibType | ARTICLE |
| Key | Blackburn-etal2016 |
| Author(s) | Daniel Blackburn, Chris Elsey, Kirsty Harkness, Sarah Wakefield, Annalena Venneri, Paul Drew, Markus Reuber |
| Title | Conversation analysis in the memory clinic |
| Editor(s) | |
| Tag(s) | EMCA, Memory, Seizure, Applied, Medical, Diagnosis |
| Publisher | |
| Year | 2016 |
| Language | |
| City | |
| Month | |
| Journal | Journal of Neurology, Neurosurgery & Psychiatry |
| Volume | 87 |
| Number | 1 |
| Pages | |
| URL | Link |
| DOI | 10.1136/jnnp-2016-315106.55 |
| ISBN | |
| Organization | |
| Institution | |
| School | |
| Type | |
| Edition | |
| Series | |
| Howpublished | |
| Book title | |
| Chapter | |
Abstract
Introduction Conversation Analysis (CA) can help with the differential diagnosis of seizure disorders. We investigated if CA could be used in the memory clinic to distinguish neurodegenerative (NDD) from functional memory disorders (FMD).
Methods We recruited consecutive, patients newly referred to the Neurology-led memory Clinic. Consultations were video & audio recorded. All participants underwent detailed Neuropsychology testing and MRI.
Results 111 patients of 178 approached were recruited (20 ND, 24 FMD, 87 other). We identified profiles of 14 interactional features that can distinguish NDD from FMD consultations based on encounters with 15 patients with NDD and 15 with FMD. Features of NDD included an inability to answer compound questions fully, inability to give detailed examples of memory failures, shorter length of turn and reduced complexity of replies. Prospective analysis of an additional 10 encounters proved that Conversation Analysts could use these features to predict the diagnoses of FMD and ND with high sensitivity and specificity.
Conclusions Simple differences in the communication behaviour of patients can help to distinguish between ND and FMD, suggesting that a targeted observation of interactional features could improve screening for ND in primary or secondary or care settings.
Notes
