Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions.

Introduction: Machine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. This study aimed to develop ML algorithms to predict the upper tertile group of various anxiety symptoms based on multimodal data from virtual reality (VR) therapy sessions for social anxiety disorder (SAD) patients and to evaluate their predictive performance across each data type.

Methods: This study included 32 SAD-diagnosed individuals, and finalized a dataset of 132 samples from 25 participants.

Factor structures and psychometric properties of three brief versions of the difficulties in emotion regulation scale in the Korean population.

Background: This study examined the latent factor structures and psychometric properties of three brief versions of the Difficulties in Emotion Regulation Scale (DERS)-DERS-SF, DERS-18, and DERS-16-across large-scale samples of the Korean population.

Methods: Participants from two independent community samples (N = 862 and N = 1,242) completed an online self-report survey, including brief versions of the DERS and associated measures. Confirmatory factor analyses were employed to examine the latent factor structures of the brief versions of the DERS with comparable models.

Correction: Digital Phenotypes for Early Detection of Internet Gaming Disorder in Adolescent Students: Explorative Data-Driven Study.

[This corrects the article DOI: 10.2196/50259.].

App-Based Interventions for Moderate to Severe Depression: A Systematic Review and Meta-Analysis.

Importance: Mobile mental health applications (apps) for moderate to severe depression are proliferating, likely owing to their capacity to overcome the limitations of conventional psychotherapy, but research on the potential moderators of treatment efficacy is lacking.

Objective: To examine the treatment efficacy associated with mobile app interventions for moderate to severe depression and identify the potential moderators associated with better treatment outcomes.

Data Sources: PubMed, Embase, and PsycINFO were searched from their inception to January 22, 2023.

Prediction of Specific Anxiety Symptoms and Virtual Reality Sickness Using In Situ Autonomic Physiological Signals During Virtual Reality Treatment in Patients With Social Anxiety Disorder: Mixed Methods Study.

Background: Social anxiety disorder (SAD) is the fear of social situations where a person anticipates being evaluated negatively. Changes in autonomic response patterns are related to the expression of anxiety symptoms. Virtual reality (VR) sickness can inhibit VR experiences.

A robust multivariate structure of interindividual covariation between psychosocial characteristics and arousal responses to visual narratives.

People experience the same event but do not feel the same way. Such individual differences in emotion response are believed to be far greater than those in any other mental functions. Thus, to understand what makes people individuals, it is important to identify the systematic structures of individual differences in emotion response and elucidate how such structures relate to what aspects of psychological characteristics.

The Effects of Virtual Reality Treatment on Prefrontal Cortex Activity in Patients With Social Anxiety Disorder: Participatory and Interactive Virtual Reality Treatment Study.

Background: Attempts to use virtual reality (VR) as a treatment for various psychiatric disorders have been made recently, and many researchers have identified the effects of VR in psychiatric disorders. Studies have reported that VR therapy is effective in social anxiety disorder (SAD). However, there is no prior study on the neural correlates of VR therapy in patients with SAD.

Virtual Reality-Based Psychotherapy in Social Anxiety Disorder: fMRI Study Using a Self-Referential Task.

Background: Although it has been well demonstrated that the efficacy of virtual reality therapy for social anxiety disorder is comparable to that of traditional cognitive behavioral therapy, little is known about the effect of virtual reality on pathological self-referential processes in individuals with social anxiety disorder.

Objective: We aimed to determine changes in self-referential processing and their neural mechanisms following virtual reality treatment.

Methods: We recruited participants with and without a primary diagnosis of social anxiety disorder to undergo clinical assessments (Social Phobia Scale and Post-Event Rumination Scale) and functional magnetic resonance imaging (fMRI) scans.

Attenuated Resting-State Functional Anticorrelation between Attention and Executive Control Networks in Schizotypal Personality Disorder.

Exploring the disruptions to intrinsic resting-state networks (RSNs) in schizophrenia-spectrum disorders yields a better understanding of the disease-specific pathophysiology. However, our knowledge of the neurobiological underpinnings of schizotypal personality disorders mostly relies on research on schizotypy or schizophrenia. This study aimed to investigate the RSN abnormalities of schizotypal personality disorder (SPD) and their clinical implications.

Effectiveness of a Participatory and Interactive Virtual Reality Intervention in Patients With Social Anxiety Disorder: Longitudinal Questionnaire Study.

Background: Social anxiety disorder (SAD) is characterized by excessive fear of negative evaluation and humiliation in social interactions and situations. Virtual reality (VR) treatment is a promising intervention option for SAD.

Objective: The purpose of this study was to create a participatory and interactive VR intervention for SAD.

Intrinsic functional connectivity of blue and red brains: neurobiological evidence of different stress resilience between political attitudes.

Conservatives are more sensitive to threatening/anxious situations in perceptual and cognitive levels, experiencing emotional responses and stress, while liberals are more responsive to but tolerant of ambiguous and uncertain information. Interestingly, conservatives have greater psychological well-being and are more satisfied with their lives than liberals despite their psychological vulnerability to stress caused by threat and anxiety sensitivities. We investigated whether conservatives have greater resilience and self-regulation capacity, which are suggested to be psychological buffers that enhance psychological well-being, than liberals and moderates.

Development and validation of the Korean version of the Reading the Mind in the Eyes Test.

The Reading the Mind in the Eyes Test (RMET) is one of the most widely used instruments for assessing the ability to recognize emotion. To examine the psychometric properties of the Korean version of the RMET and to explore the possible implications of poor performance on this task, 200 adults aged 19-32 years completed the RMET and the Korean version of the 20-item Toronto Alexithymia Scale (TAS-20K), the cognitive empathy domain of the Korean version of the Interpersonal Reactivity Index (IRI-C), and the Buss-Durkee Hostility Inventory-Aggression (BDHI-A). In the present study, confirmatory factor analyses confirmed that the hypothesized three-factor solution based on three different emotional valences of the items (positive, negative, or neutral) had a good fit to the data.

Disguised Emotion in Alexithymia: Subjective Difficulties in Emotion Processing and Increased Empathic Distress.

Despite decades of speculation, many causal aspects that contribute to the heterogeneity of alexithymia still must be clarified. This study examined the extent of the alexithymia phenotype and its contribution to social function in the general population. In total, 200 participants (females = 111) completed the Toronto Alexithymia Scale-20 (TAS-20), multiple self-reporting questionnaires measuring emotion intelligence, empathy, hostility and impulsivity, and the Reading the Mind in the Eyes Test (RMET).

Multi-group analysis using generalized additive kernel canonical correlation analysis.

Multivariate analysis has been widely used and one of the popular multivariate analysis methods is canonical correlation analysis (CCA). CCA finds the linear combination in each group that maximizes the Pearson correlation. CCA has been extended to a kernel CCA for nonlinear relationships and generalized CCA that can consider more than two groups.

Neural bases of the clinical and neurocognitive differences between earlyand late-onset obsessive–compulsive disorder.

Background: Using biological evidence to define subtypes within the heterogeneous population with obsessive–compulsive disorder (OCD) is important for improving treatment response. Based on age at onset, OCD can be clustered into 2 groups, each of which is more homogeneous with respect to clinical and cognitive phenotype. However, the neural bases for these phenotypic differences need to be established to construct evidence-based homogeneous groups.