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.
Highlights
The objective, systematic study of communication has been an essential element of psychotherapy process research for over seven decades [1]
The software was designed for use with the Motivational Interviewing Skill Code (MISC 2.5) [30], a sequential-coding system for psychotherapy sessions that was derived from the Sequential Code for Observing Process Exchanges (SCOPE) [31]
Results ranged from q = 20.40 to q = 0.69, with a mean of 0.11 (SD = .33). (See Table S1 for an overview.) These results suggest that coding with Coding Treatment Interactions (CACTI) can produce comparable interrater reliabilities to those acquired via previous methods
Summary
The objective, systematic study of communication has been an essential element of psychotherapy process research for over seven decades [1]. This approach to studying the interactions between clients and clinicians within treatment sessions spread rapidly with the introduction of inexpensive analog audio recording equipment [2], a technology that permitted the preservation and study of these interactions. By preserving the temporal sequence of behaviors, the sequential approach permits the analysis of mutual influence between client and clinician, which can help to identify and test hypothesized mechanisms of action of psychotherapies and potentially improve treatment delivery and outcomes [12,13]. Sequential analyses may range in complexity from classic lag-sequential techniques [7] to hidden Markov models [14]
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