RESUMO
Statistical mechanics is the field of physics focusing on the prediction of the behavior of a given system by means of statistical properties of ensembles of its microscopic elements. The authors examined the possibility of applying such an approach to psychotherapy research with the aim of investigating (a) the possibility of predicting good and poor outcomes of psychotherapy on the sole basis of the correlation pattern among their descriptors and (b) the analogies and differences between the processes of good- and poor-outcome cases. This work extends the results reported in a previous paper and is based on higher-order statistics stemming from a complex network approach. Four good-outcome and four poor-outcome brief psychotherapies were recorded, and transcripts of the sessions were coded according to Mergenthaler's Therapeutic Cycle Model (TCM), i.e., in terms of abstract language, positive emotional language, and negative emotional language. The relative frequencies of the three vocabularies in each word-block of 150 words were investigated and compared in order to understand similarities and peculiarities between poor-outcome and good-outcome cases. Network analyses were performed by means of a cluster analysis over the sequence of TCM categories. The network analyses revealed that the linguistic patterns of the four good-outcome and four poor-outcome cases were grounded on a very similar dynamic process substantially dependent on the relative frequency of the states in which the transition started and ended ("random-walk-like behavior", adjusted R 2 = 0.729, p < 0.001). Furthermore, the psychotherapy processes revealed statistically significant changes in the relative occurrence of visited states between the beginning and the end of therapy, thus pointing to the non-stationarity of the analyzed processes. The present study showed not only how to quantitatively describe psychotherapy as a network, but also found out the main principles on which its evolution is based. The mind, from a linguistic perspective, seems to work-through psychotherapy sessions by passing from the most adjacent states and the most occurring ones. This finding can represent a fertile ground to rethink pivotal clinical concepts such as the timing of an interpretation or a comment, the clinical issue to address within a given session, and the general task of a psychotherapist: from someone who delivers a given technique toward a consultant promoting the flexibility of the clinical field and, thus, of the patient's mind.
RESUMO
A systematic single case study with a mixed quantitative and qualitative methodology was conducted to investigate the nonlinear dynamics of change in play profiles of a child in psychodynamic play therapy. The first aim of the study was to cluster the different features of play characteristics (i.e., descriptive, cognitive, affective, and social characteristics of play, and the defensive strategies used in play) in order to construct the different play profiles of this child, and secondly to assess the transitions between profiles over the course of treatment. It was expected that there would be an increase in critical fluctuations during the transitions between the profiles and an increase in the variability of play profiles. Results showed that the child's play characteristics clustered into eight states and three attractors. The Markov Transition Matrix showed how play profiles evolved over time. Entropy analyses comparing the first and the second half of therapy showed an increase in variability. Qualitative analyses indicated the importance of expression of the child's underlying fear, and its integration with overt anger in the generation of the new play profiles. The results indicate an increase in variability, and a destabilization of old play profiles that were used towards generating new play profiles.
