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de Felice, Giulio [Author]; Giuliani, Alessandro [Author]; Gelo, Omar Carlo Gioacchino [Author]; Mergenthaler, Erhard [Author]; De Smet, Melissa M. [Author]; Meganck, Reitske [Author]; Paoloni, Giulia [Author]; Andreassi, Silvia [Author]; Schiepek, Guenter K. [Author]; Scozzari, Andrea [Author]; Orsucci, Franco F. [Author]

What differentiates poor- and good-outcome psychotherapy? A statistical-mechanics-inspired approach to psychotherapy research, part two: network analyses

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  • Media type: E-Article
  • Title: What differentiates poor- and good-outcome psychotherapy? A statistical-mechanics-inspired approach to psychotherapy research, part two: network analyses
  • Contributor: de Felice, Giulio [Author]; Giuliani, Alessandro [Author]; Gelo, Omar Carlo Gioacchino [Author]; Mergenthaler, Erhard [Author]; De Smet, Melissa M. [Author]; Meganck, Reitske [Author]; Paoloni, Giulia [Author]; Andreassi, Silvia [Author]; Schiepek, Guenter K. [Author]; Scozzari, Andrea [Author]; Orsucci, Franco F. [Author]
  • Published: Universität Ulm, 2022-03-07T15:29:46Z
  • Language: English
  • DOI: https://doi.org/10.18725/OPARU-42068
  • Keywords: Psychotherapie ; Nichtlineare Dynamik ; non-linear dynamics ; Vorhersagetheorie ; Psychotherapy ; Statistical mechanics ; Prediction (Psychology) ; complex systems ; Human behavior ; DDC 150 / Psychology ; DDC 510 / Mathematics ; process of change
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  • Description: 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 R2 = 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 ...
  • Access State: Open Access
  • Rights information: Attribution (CC BY)