Clinical supervision is essential for trainees, preventing burnout and ensuring the effectiveness of their interventions. AI technologies offer increasing possibilities for developing clinical practices, with supervision being particularly suited for automation. The aim of this study is to evaluate the feasibility of using ChatGPT-4 as a supervisory tool in psychotherapy training. To achieve this, a clinical case was presented to three distinct groups (untrained AI, pre-trained AI, and qualified human supervisor), and their feedback was evaluated by Gestalt psychotherapy trainees using a Likert scale rating of satisfaction. Statistical analysis, using the statistical package SPSS version 25 and applying principal component analysis (PCA) and one-way analysis of variance (ANOVA), demonstrated significant differences in favor of pre-trained AI feedback. PCA highlighted four components of the questionnaire: relational and emotional (C1), didactic and technical quality (C2), treatment support and development (C3), and professional orientation and adaptability (C4). The ratings of satisfaction obtained from the three kinds of supervisory feedback were compared using ANOVA. The feedback generated by the pre-trained AI (f2) was rated significantly higher than the other two (untrained AI feedback (f1) and human feedback (f3)) in C4; in C1, the superiority of f2 over f1 but not over f3 appears significant. These results suggest that AI, when appropriately calibrated, may be an appreciable tool for complementing the effectiveness of clinical supervision, offering an innovative blended supervision methodology, in particular in the area of career guidance.

Background: The study of complex systems, such as the psychotherapeutic encounter, transcends the mechanistic and reductionist methods for describing linear processes and needs suitable approaches to describe probabilistic and scarcely predictable phenomena. Objective: The present study undertakes a scoping review of research on the computational methods in psychotherapy to gather new developments in this field and to better understand the phenomena occurring in psychotherapeutic interactions as well as in human interaction more generally. Design: Online databases were used to identify papers published 2011–2022, from which we selected 18 publications from different resources, selected according to criteria established in advance and described in the text. A flow chart and a summary table of the articles consulted have been created. Results: The majority of publications (44.4%) reported combined computational and experimental approaches, so we grouped the studies according to the types of computational methods used. All but one of the studies collected measured data. All the studies confirmed the usefulness of predictive and learning models in the study of complex variables such as those belonging to psychological, psychopathological and psychotherapeutic processes. Conclusions: Research on computational methods will benefit from a careful selection of reference methods and standards. Therefore, this review represents an attempt to systematise the empirical literature on the applications of computational methods in psychotherapy research in order to offer clinicians an overview of the usefulness of these methods and the possibilities of their use in the various fields of application, highlighting their clinical implications, and ultimately attempting to identify potential opportunities for further research.

During the last period of lockdown because of the Covid-19 pandemic influence, a lot of mental health professionals were able to continue working online, assisting their patients from home too. Even if there are still some doubts about videoconferencing psychotherapy (VCP), a lot of studies indicate that VCP can be feasible and clinically effective, in fact the online therapy is becoming increasingly popular, reducing distances even during the current pandemic. The aim of this study is to analyze the degree of satisfaction after using VCP in a sample of psychotherapists freely recruited through the publication on social media of a specially created questionnaire. The collected data were analyzed by performing descriptive statistics to show the qualitative and quantitative composition of the sample examined. A tree classification model was created to predict the liking of the remote therapeutic intervention based on the sociodemographic characteristics, previous experiences and aspects of psychotherapeutic orientation of the therapists recruited in the study. Through a decision tree that explains which variables are related to positive responses, the following characteristics were found to predict the degree of satisfaction of the psychotherapists in using the VCP: belonging to a specific age group; having previously used VCP; and belonging to a specific psychotherapeutic orientation. According to the results, the first two important characteristics of the psychotherapists to influence the satisfaction in their use of VCP (belonging to the specific age group 45–65 and having previously used VCP) are probably a matter that can be linked to the degree of professional maturity and experience. The innovation of this research is to highlights the real impact of the distance therapy on the main therapeutic models, concluding that to have a certain level of proficiency, according the own orientation, in the use of the VCP may influence the level of satisfaction of the psychotherapists.

A situational individual’s mental state contains the dynamic interaction between explicit, conscious cognitive processes and implicit automatisms that develop outside of consciousness. The influence of implicit and unaware processes, often underestimated, manifests itself in the speed with which we process information, in immediate emotional responses, and in the emergence of intentions even before they are accessible to awareness. The brain activity that precedes a decision manifests itself several milliseconds before the subject reports the conscious intention to act. This phenomenon highlights how awareness emerges after the decision-making process. The Quantum Cognition model proposes an alternative theoretical framework to classical logic to explain complex cognitive phenomena such as ambivalence, overlapping intentions, and sudden changes in perspective. The aim of this paper is to propose the QC model as a powerful formal strategy for describing the mind as a dynamic, probabilistic, and context-sensitive system.

Although there is no agreement between the various theoretical models of psychotherapy as to the nature of the psychic processes that are the object of therapeutic intervention, many theories regard cognition and consciousness as multimodal phenomena. In them, perceptual, motor, proprioceptive and enterceptive processes are active in a synchronic and coherent manner, under the control of a brain area that acts as ‘director’. In the current state of knowledge, the brain structure that produces this multimodal synchronisation appears to be the thalamus. The chapter discusses the implications and consequences of the processes described in Gestalt psychotherapy. This psychotherapeutic approach focuses the process of gestalt formation that is generated by proprioceptive, interoceptive and exteroceptive integration as the centre of clinical intervention. This integrative process in traditional Gestalt theory is referred to as field, a concept that integrates the aspects of Kurt Lewin’s theory and fits well with the current approach of affective neuroscience.