AphasiaBank Main Concept Analysis

This page provides links to information about main concept analysis.

Selected articles on main concept analysis:

Main Concepts

Here are links to main concepts for tasks from the AphasiaBank Discourse Protocol. These include instructions for scoring presence, accuracy and completeness.


Procedures vary. Examples include:

Main Concept Analysis Training Materials -- Richardson & Dalton

The materials here were compiled by Jessica Richardson, Ph.D. and Sarah Grace Dalton, Ph.D., who continue to update these materials regularly. The materials contain:

Automatic Coding and Scoring

1. Using CLAN. It is efficient to use Coder Mode to enter main concepts into a CHAT transcript. You can download this mc.cut file, put it in the folder with the CHAT files you want to code, and then enter the codes into the transcript by following the steps explained in the Coder Mode section of the CLAN manual or viewing the Coder Mode screencast here. This mc.cut file will allow you to code up to 34 main concepts and mark them as AC (Accurate Complete), AI (Accurate Incomplete), IC (Inaccurate Complete), or II (Inaccurate Incomplete). Utterances with no main concept can be coded as NA. If a main concept spans multiple utterances, code it once on the final utterance.

Once the CHAT file has the MC codes on the coder tier, run this CLAN command -- codes filename.cha (or *.cha for all CHAT files in the folder) -- and you'll get a list of all MCs in the sample, the code assigned to each MC, the total number of MCs used in the sample, the total number of each code (AC, AI, IC, II, NA), and a composite score based on the Richardson and Dalton (2015) scoring.

2. Using a web-app. Scoring can be done automatically with this web-app --
https://rb-cavanaugh.shinyapps.io/mainConcept/. Using simple orthographic transcription of the language sample (Broken Window, Refused Umbrella, Cat Rescue, Cinderella, Sandwich), the app provides a summary page with total scores and percentiles based on average norms relative to healthy controls and other individuals with aphasia. It also allows users to download a spreadsheet of their data and a PDF report. Finally, the app includes a training manual with practice transcripts, readings/resources, anda training workshop.

The app was developed by Rob Cavanaugh, Sarah Grace Dalton, and Jessica Richardson with grant support from NIH/NIDCD (Cavanaugh, F31 DC019853-01). Citation for this software and link for source code: Cavanaugh, R., Dalton, S. G., & Richardson, J. (2021). mainConcept: An open-source web-app for scoring main concept analysis. R package version https://github.com/aphasia-apps/mainConcept . Comments, feedback, and bug-reports can be made on the github page.