Providing remote psychotherapy using technology is a growing practice, especially since the outbreak of the COVID-19 pandemic. Even if in numerous studies video conferencing psychotherapy (VCP) was found to be clinically effective, some doubts continue to exist about how the psychotherapeutic alliance works in the online setting, and the characteristics of the empathic process are still poorly understood. This is an exploratory study aimed at analyzing the degree of empathy between the psychotherapist and client pair, and the degree of support perceived by the client who shall be referred to as the patient interchangeably in this study, comparing the sessions in person with those online, during the current pandemic, in order to discriminate the impact of empathy in the digital setting. The sample analyzed was composed of 23 patients with different severity of pathology engaged in online and in-person therapeutic sessions with five psychotherapists of different theoretical leanings. The scores of the support and empathy scale, obtained by both members of the psychotherapeutic couple in the two settings, were analyzed and compared. The test used belongs to an Italian adaptation of the Empathic Understanding (EU) of the Relationship Inventory. What emerged from comparing the scores was interesting: Unlike the psychotherapists, the patients perceived their therapists as significantly more empathic and supportive in the remote setting. These are rather important data, because the literature documents that client empathic perception measures represent a more accurate measure of the empathic relationship and, in general, can predict a good treatment outcome. Although these results need further investigation, they represent an important contribution in filling the scientific gap in the understanding of digital empathy. Also, this study provides new insights for future research on the characteristics and impact empathy has on the practice of remote psychotherapy.

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.

Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence) and character dimensions (cooperativeness and self directedness). In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called “multilayer perceptron,” was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89%) to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a greater influence than the character traits in the borderline personality disorder e disease. In conclusion, the results seem to indicate that to borderline personality disorder development, contribute both psychic factors, such as temperament and character traits, and environmental factors, such as traumatic events capable of producing dissociative symptoms. These factors interact in a nonlinear way in producing maladaptive behaviors typical of this disorder.

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.

The study describes the relationship between personality traits and executive functions within a circularly based paradigm.

Dissociative phenomena are common among psychiatric patients; the presence of these symptoms can worsen the prognosis, increasing the severity of their clinical conditions and exposing them to increased risk of suicidal behavior. Personality disorders as long duration stressful experiences may support the development of dissociative phenomena. In 933 psychiatric outpatients consecutively recruited, presence of dissociative phenomena was identified with the Dissociative Experience Scale (DES). Dissociative phenomena were significantly more severe in the group of people with mental disorders and/or personality disorders. All psychopathologic traits detected with the symptom checklist-90-revised had a significant correlation with the total score on the DES. Using total DES score as the dependent variable, a linear regression model was constructed. Mental and personality disorders which were associated with greater severity of dissociative phenomena on analysis of variance were included as predictors; scores from the nine scales of symptom checklist-90-revised, significantly correlated to total DES score, were used as covariates. The model consisted of seven explanatory variables (four factors and three covariates) explaining 82% of variance. The four significant factors were the presence of borderline and narcissistic personality disorder, substance abuse disorders and psychotic disorders. Significant covariates were psychopathologic traits of anger, psychoticism and obsessiveness. This study, confirming Janet’s theory, explains that, mental disorders and psychopathologic experiences of patients can configure the chronic stress condition that produces functional damage to the adaptive executive system. The symptoms of dissociative depersonalization/derealization and dissociative amnesia can be explained, in large part, through their current and previous psychopathologic experiences.