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CACTI: Free, Open-Source Software for the Sequential Coding of Behavioral Interactions

Overview of attention for article published in PLOS ONE, July 2012
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Title
CACTI: Free, Open-Source Software for the Sequential Coding of Behavioral Interactions
Published in
PLOS ONE, July 2012
DOI 10.1371/journal.pone.0039740
Pubmed ID
Authors

Lisa H. Glynn, Kevin A. Hallgren, Jon M. Houck, Theresa B. Moyers

Abstract

The sequential analysis of client and clinician speech in psychotherapy sessions can help to identify and characterize potential mechanisms of treatment and behavior change. Previous studies required coding systems that were time-consuming, expensive, and error-prone. Existing software can be expensive and inflexible, and furthermore, no single package allows for pre-parsing, sequential coding, and assignment of global ratings. We developed a free, open-source, and adaptable program to meet these needs: The CASAA Application for Coding Treatment Interactions (CACTI). Without transcripts, CACTI facilitates the real-time sequential coding of behavioral interactions using WAV-format audio files. Most elements of the interface are user-modifiable through a simple XML file, and can be further adapted using Java through the terms of the GNU Public License. Coding with this software yields interrater reliabilities comparable to previous methods, but at greatly reduced time and expense. CACTI is a flexible research tool that can simplify psychotherapy process research, and has the potential to contribute to the improvement of treatment content and delivery.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 33%
Researcher 9 17%
Student > Master 4 7%
Student > Doctoral Student 3 6%
Student > Postgraduate 3 6%
Other 9 17%
Unknown 8 15%
Readers by discipline Count As %
Psychology 17 31%
Computer Science 7 13%
Social Sciences 5 9%
Agricultural and Biological Sciences 3 6%
Medicine and Dentistry 3 6%
Other 6 11%
Unknown 13 24%