Automated Proposition Density Analysis for Discourse in Aphasia

J Speech Lang Hear Res. 2016 Oct 1;59(5):1123-1132. doi: 10.1044/2016_JSLHR-L-15-0401.

Abstract

Purpose: This study evaluates how proposition density can differentiate between persons with aphasia (PWA) and individuals in a control group, as well as among subtypes of aphasia, on the basis of procedural discourse and personal narratives collected from large samples of participants.

Method: Participants were 195 PWA and 168 individuals in a control group from the AphasiaBank database. PWA represented 6 aphasia types on the basis of the Western Aphasia Battery-Revised (Kertesz, 2006). Narrative samples were stroke stories for PWA and illness or injury stories for individuals in the control group. Procedural samples were from the peanut-butter-and-jelly-sandwich task. Language samples were transcribed using Codes for the Human Analysis of Transcripts (MacWhinney, 2000) and analyzed using Computerized Language Analysis (MacWhinney, 2000), which automatically computes proposition density (PD) using rules developed for automatic PD measurement by the Computerized Propositional Idea Density Rater program (Brown, Snodgrass, & Covington, 2007; Covington, 2007).

Results: Participants in the control group scored significantly higher than PWA on both tasks. PD scores were significantly different among the aphasia types for both tasks. Pairwise comparisons for both discourse tasks revealed that PD scores for the Broca's group were significantly lower than those for all groups except Transcortical Motor. No significant quadratic or linear association between PD and severity was found.

Conclusion: Proposition density is differentially sensitive to aphasia type and most clearly differentiates individuals with Broca's aphasia from the other groups.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Aphasia / diagnosis*
  • Diagnosis, Computer-Assisted*
  • Female
  • Humans
  • Language Tests
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Narration*
  • Pattern Recognition, Automated*
  • Speech*