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 = 0.729, < 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.
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http://dx.doi.org/10.3389/fpsyg.2020.00788 | DOI Listing |
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Qinghai Provincial Key Laboratory of Tibetan Medicine Research and CAS Key Laboratory of Tibetan Medicine Research, Northwest Institute of Plateau Biology, Chinese Academy of Science, Xining, 810008, P.R. China.
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Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Woodstock Rd, Oxford, Oxfordshire, OX2 6GG, UK.
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Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, No. 74, Linjiang Road, Chongqing, 400010, China.
Angiotensin receptor-neprilysin inhibitor (ARNI) and angiotensin II receptor blockers (ARB) are antihypertension medications that improve cardiac remodeling and protect the heart. However, at the early stage of hypertension, it is still unclear how these two drugs affect the transcriptomic profile of multiple organs in hypertensive rats and the transcriptomic differences between them. We performed RNA sequencing to define the RNA expressing profiles of the eight tissues (atrium, ventricle, aorta, kidney, brain, lung, white fat, and brown fat) in spontaneously hypertensive rats (SHRs) and SHRs treated with ARNI or ARB.
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