The aim of this study was to evaluate the degree of insight and resistance in a sample of obsessive-compulsive patients, and the predictive value of poor insight with respect to response to treatment with serotonin reuptake inhibitors (SRIs). Ninety-three patients fulfilling DSM-IV criteria for obsessive-compulsive disorder were evaluated. Seventy patients were treated with an SRI in a 24-week open-label trial. Sixteen percent of the patients did not recognize obsessions and compulsions as unreasonable or senseless. Fifty-two percent of the patients did not try to resist, 72% had little or no control over obsessions, and 64% were not able to exercise an effective control over compulsions. Patients with poor insight had a greater severity of obsessive-compulsive symptoms, a higher rate of schizophrenia spectrum disorders in their first-degree relatives and a higher frequency of a history of psychiatric disorders during childhood. Fifty-two percent of the patients with normal insight responded to SRIs, whereas none of the patients with poor insight were found to be responders. These results suggest the utility of the assessment of insight and resistance in obsessive-compulsive patients, also for the prediction of response to treatment with SRIs.

This study aims to review the evidence for the reciprocal relationship between envy and social comparison (SC) on social networking sites (SNSs) and depression. We searched PsychINFO, PubMed, and Web of Science from January 2012 to November 2022, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A total of 9 articles met our inclusion criteria. In all articles reviewed, a simple correlation was found between SC on SNSs, envy, and depression. Three cross-sectional studies successfully tested a model with envy as a mediator between SNSs and depression. The moderating role of additional variables such as self-efficacy, neuroticism, SC orientation, marital quality, and friendship type was also evident. The only two studies that were suitable to determine direction found that depression acted as a predictor rather than an outcome of SC and envy, and therefore depression might be a relevant risk factor for the negative emotional consequences of SNSs use.

Personality disorders (PDs) are one of the major problems for the organization of public health systems. Deepening the link between personality traits and psychopathological drifts, it seems increasingly essential for the often dramatic repercussions that PDs have on social contexts. Some of these disorders, such as borderline PD, antisocial PD, in their most tragic expression, are the basis of problems related to crime, sexual violence, abuse, and mistreatment of minors. Many authors propose a dimensional classification of personality pathology, which has received empirical support from numerous studies over the last 20 years based on more robust theoretical principles than those applied to current nosography. The present study investigates the nature of the research carried out in the last years on the personality in the clinical field exploring the contents of current research on personality relapses, evaluating, on the one hand, the emerging areas of greatest interest and others, those that they stopped generating sufficient motivations in scholars. This study evaluates text patterns regarding how the terms “personality” and “mental health” are used in titles and abstracts published in PubMed in the last 5 years. We use a topic analysis: Latent Dirichlet Allocation that expresses every report as a probabilistic distribution of latent topics that are represented as a probabilistic distribution of words. A total of 7,572 abstracts (from 2012 to 2017) were retrieved from PubMed for the query on “mental health” and “personality.” The study found 30 topics organized in eight hierarchical clusters that describe the type of current research carried out on personality and its clinical relapse. The hierarchical clusters latent themes were the following: social dimensions, clinical aspects, biological issues, clinical history of PD, internalization and externalization symptoms, impulsive behaviors, comorbidities, criminal behaviors. The results indicate that the concept of personality is associated with a wide range of conditions. The study of personality and mental health still proceeds, mainly, according to a practical-clinical approach; too little moves, however, according to an innovative research approach, but the work shows the common commitment of scholars to a new way of dealing with the study of personality.

Background: Although different personality traits have often been associated with different levels of mental activity and cognitive functioning, no previous studies have evaluated the association in a sample that mirrors a nationally-representative sample of elderly individuals.Objective: To evaluate the association between personality traits and neurocognitive functioning among individuals 51 years and older using the Cognition and Aging in the USA (CogUSA) database.Methods: We analyzed the association between personality traits and neurocognitive scores derived from Waves I and II of the study. Neurocognitive functions were modeled as an outcome variable using the Big Five Personality Traits as predictors.Results: All personality traits were associated with higher education except Conscientiousness. Older age was associated with higher levels of the Agreeableness and Openness traits. Extraversion, Conscientiousness and Openness were positively associated with increased neurocognitive function and self-rated present memory. Extraversion and Openness also had a positive association with long-term retrieval. Agreeableness was negatively associated with several neurocognitive functions, while Neuroticism was negatively associated with memory and cognitive effort.Conclusion: Extraversion, Conscientiousness and Openness personality traits are associated with good cognitive health. Individuals scoring high in Neuroticism and Agreeableness might benefit from tailored cognitive interventions to prevent age-related cognitive decline.

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.