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Recent research indicates that temporary deteriorations of variables monitored continuously in the course of the therapeutic relationship are important characteristics of psychotherapeutic change. These so-called rupture-repair episodes were assessed by different authors using different mathematical methods.
The study deals with the criteria for identifying rupture-repair episodes that have been established in previous studies. It proposes modifications of these criteria which prospectively could make it possible to identify rupture-repair episodes more precisely and consistently. The authors developed an alternative criterion. This criterion is able to include crisis patterns which had not been considered before, as well as to characterize the length of the crises. As a sample application, the different criteria were applied to continuously measured assessments of the therapeutic interaction in psychodynamic therapy courses (ten shorter processes and one long-term therapy).
The analysis revealed that the number of the identified rupture-repair episodes differed depending on the criterion that was used. Considerably more crises were identified with the newly developed criterion. The authors developed a classification of crisis patterns. They distinguished five patterns of crises and their resolution in therapy processes and ascertained the frequency of distribution. The most frequent pattern was the simple V-shape. The second most common pattern was a decline over more than one session with a sudden repair. The longest downward trend comprised a period of six sessions.
The findings of the study give insight into basic mechanisms of change within the therapeutic relationship. A phenomenological discussion of how a crisis is defined is useful to create a methodological approach to the operationalization of crises, to differentiate specific characteristics and to specifically link these characteristics to the outcome in future studies. The methodological deliberations might be applyable to different research areas where the analysis of fluctuations in a variable of interest over time is relevant.