Social Anxiety Disorder Severity Research Articles

Epigenetic signatures of social anxiety, panic disorders and stress experiences: Insights from genome-wide DNA methylation risk scores

Social anxiety disorder (SAD) and panic disorder (PD) are prevalent anxiety disorders characterized by a complex interplay of genetic and environmental factors. Both disorders share overlapping features and often coexist, despite displaying distinct characteristics. Childhood life adversity, overall stressful life events, and genetic factors contribute to the development of these disorders. DNA methylation, an epigenetic modification, has been implicated in the pathogenesis of these diseases. In this study, we investigated whether whole-genome DNA methylation risk scores (MRSs) for SAD risk, severity of social anxiety, childhood life adversity, PD risk, and overall stressful life events were associated with SAD or PD case‒control status. Preliminary epigenome-wide association studies (EWASs) for SAD risk, severity of social anxiety, and childhood life adversity were conducted in 66 SAD individuals and 77 healthy controls (HCs). Similarly, EWASs for PD risk and overall stressful life events were performed in 182 PD individuals and 81 HCs. MRSs were calculated from these EWASs. MRSs derived from the EWASs of SAD risk and severity of social anxiety were greater in PD patients than in HCs. Additionally, MRSs derived from the EWASs of overall stressful life events, particularly in PD individuals, were lower in SAD individuals than in HCs. In contrast, MRSs for childhood life adversity or PD risk were not significantly associated with PD or SAD case‒control status. These findings highlight the epigenetic features shared in both disorders and the distinctive epigenetic features related to social avoidance in SAD patients, helping to elucidate the epigenetic basis of these disorders.

Guided and unguided internet-delivered psychodynamic therapy for social anxiety disorder: A randomized controlled trial

Social Anxiety Disorder (SAD) is highly prevalent and debilitating disorder. Treatments exist but are not accessible and/or helpful for all patients, indicating a need for accessible treatment alternatives. The aim of the present trial was to evaluate internet-delivered psychodynamic therapy (IPDT) with and without therapist guidance, compared to a waitlist control condition, in the treatment of adults with SAD. In this randomized, clinical trial, we tested whether IPDT was superior to a waitlist control, and whether IPDT with therapeutic guidance was superior to unguided IPDT. Participants were recruited nationwide in Sweden. Eligible participants were ≥ 18 years old and scoring ≥ 60 on the Liebowitz Social Anxiety Scale self-report (LSAS-SR) whilst not fulfilling any of the exclusion criteria. Included participants were randomly assigned to IPDT with guidance (n = 60), IPDT without guidance (n = 61), or waitlist (n = 60). The IPDT intervention comprised eight self-help modules based on affect-focused dynamic therapy, delivered over 8 weeks on a secure online platform. The primary outcome was SAD symptoms severity measured weekly by the LSAS-SR. Primary analyses were calculated on an intention-to-treat sample including all participants randomly assigned. Secondary outcomes were depressive symptoms, generalized anxiety, quality of life, emotion regulation and defensive functioning. At post-treatment, both active treatments were superior to the waitlist condition with guided treatment exhibiting larger between group effects than unguided treatment (d = 1.07 95% CI [0.72, 1.43], p < .001 and d = 0.61, 95% CI [0.25, 0.98], p = .0018) on the LSAS-SR respectively. Guided IPDT lead to larger improvements than unguided IPDT (d = 0.46, 95% CI [0.11, 0.80], p < .01). At post-treatment, guided IPDT was superior to waitlist on all secondary outcome measures. Unguided IPDT was superior to waitlist on depressive symptoms and general anxiety, but not on emotion regulation, self-compassion or quality of life. Guided IPDT was superior to unguided PDT on depressive symptoms, with a trend towards superiority on a measure of generalized anxiety. At six and twelve month follow-up there were no significant differences between guided and unguided IPDT. In conclusion, IPDT shows promising effects in the treatment of SAD, with larger benefits from guided IPDT compared to non-guided, at least at post-treatment. This finding increases the range of accessible and effective treatment alternatives for adults suffering from SAD. The study was prospectively registered at ClinicalTrials (NCT05015166).

Unveiling Social Anxiety: Analyzing Acoustic and Linguistic Traits in Impromptu Speech within a Controlled Study

Early detection and treatment of Social Anxiety Disorder (SAD) is crucial. However, current diagnostic methods have several drawbacks, including being time-consuming for clinical interviews, susceptible to emotional bias for self-reports, and inconclusive for physiological measures. Our research focuses on a digital approach using acoustic and linguistic features extracted from participants’ “speech” for diagnosing SAD. Our methodology involves identifying correlations between extracted features and SAD severity, selecting the effective features, and comparing classical machine learning and deep learning methods for predicting SAD. Our results demonstrate that both acoustic and linguistic features outperform deep learning approaches when considered individually. Logistic Regression proves effective for acoustic features, while Random Forest excels with linguistic features, achieving the highest accuracy of 85.71%. Our findings pave the way for non-intrusive SAD diagnosing that can be used conveniently anywhere, facilitating early detection.

Multiclassification of the symptom severity of social anxiety disorder using digital phenotypes and feature representation learning

Objective Social anxiety disorder (SAD) is characterized by heightened sensitivity to social interactions or settings, which disrupts daily activities and social relationships. This study aimed to explore the feasibility of utilizing digital phenotypes for predicting the severity of these symptoms and to elucidate how the main predictive digital phenotypes differed depending on the symptom severity. Method We collected 511 behavioral and physiological data over 7 to 13 weeks from 27 SAD and 31 healthy individuals using smartphones and smartbands, from which we extracted 76 digital phenotype features. To reduce data dimensionality, we employed an autoencoder, an unsupervised machine learning model that transformed these features into low-dimensional latent representations. Symptom severity was assessed with three social anxiety-specific and nine additional psychological scales. For each symptom, we developed individual classifiers to predict the severity and applied integrated gradients to identify critical predictive features. Results Classifiers targeting social anxiety symptoms outperformed baseline accuracy, achieving mean accuracy and F1 scores of 87% (with both metrics in the range 84–90%). For secondary psychological symptoms, classifiers demonstrated mean accuracy and F1 scores of 85%. Application of integrated gradients revealed key digital phenotypes with substantial influence on the predictive models, differentiated by symptom types and levels of severity. Conclusions Leveraging digital phenotypes through feature representation learning could effectively classify symptom severities in SAD. It identifies distinct digital phenotypes associated with the cognitive, emotional, and behavioral dimensions of SAD, thereby advancing the understanding of SAD. These findings underscore the potential utility of digital phenotypes in informing clinical management.

Social anxiety mediates workplace incivility and work engagement

The average working person spends between 35 and 60 h a week in the workplace, making it an influential place for mental well-being and a place for socioeconomic contribution. Workplace incivility can diminish positive mental health outcomes and negatively impact work engagement through increased social anxiety. To investigate this, 118 working adults in Singapore aged between 19 to 67 years old were recruited for a survey consisting of demographic questions, the Workplace Incivility Scale, the Brief DSM-5 Social Anxiety Disorder Severity Scale, and the Utrecht Work Engagement Scale-9 between November 2022 to April 2023. Correlational, regression, and mediation analysis showed workplace incivility scale scores to significantly predict social anxiety after controlling for covariates. This supports our hypothesis that employees exposed to workplace incivility would have higher social anxiety levels mediating work engagement after controlling for age and gender. The findings here show workplace incivility as a possible intervention target for social anxiety, in order to reduce negative impact on work engagement to improve employee experience and retention for organizations.

Long-Term Outcomes and Cost-Effectiveness of an Internet-Based Self-Help Intervention for Social Anxiety Disorder in University Students: Results of a Randomized Controlled Trial

Social anxiety disorder (SAD) is widespread among university students and is associated with high costs for the society. While unguided internet- and mobile-based interventions (IMIs) may have short-term effects in reducing SAD symptoms, evidence for their long-term efficacy and cost-effectiveness is still limited. The aim of this study is to examine the 6-month outcomes of an IMI for university students with SAD. Participants were recruited via mass mails sent to enrolled students and included if they were at least 18 years old, met the diagnostic criteria of SAD in a structured clinical interview for DSM-IV axis I disorders (SCID-I), and provided written informed consent. In a prospective study designed as a two-armed randomized-controlled trial, 200 students (mean age 26.7 years) diagnosed with SAD were randomly assigned to an IMI or a waitlist control (WLC) condition. The IMI consisted of nine weekly sessions based on the cognitive-behavioral treatment model for social phobia by Clark and Wells. The primary outcome was SAD symptom severity assessed via the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS). A health economic evaluation from a societal and healthcare perspective examined the costs related to the symptom-free status and quality-adjusted life years (QALYs) gained. Statistically significant differences in SAD symptom severity previously found at posttreatment favoring the IMI were maintained at a 6-month follow-up [SIAS (Cohen’s d = 0.59 ; 95% CI, 0.30, 0.87) and SPS (Cohen’s d = 0.83 ; 95% CI, 0.54, 1.1)]. From a societal perspective, at a willingness to pay (WTP) of €0, the intervention was found to have a 92% and 93% probability of cost-effectiveness compared with the WLC per symptom-free status and QALY gained, respectively. From a healthcare perspective, the likelihood of cost-effectiveness of the intervention was 97% per symptom-free status at a WTP of €1000 (US$1326) and 96% per QALY gained at a WTP of €6000 (US$7956). This IMI is effective in treating university students with SAD and has an acceptable likelihood of cost-effectiveness compared with WLC from a societal perspective. This intervention can be integrated into university healthcare to reach students with SAD as it is scalable, shows a high probability of cost-effectiveness, and overcomes known treatment barriers. This trial is registered with DRKS00011424.

6 A review of neuropsychological measures of executive functioning in the Japanese and Japanese-American population

Objective:There are approximately 1.5 million Japanese and Japanese Americans in the United States, with the Japanese population increasing steadily over the past two decades. Given the growing number of the Japanese population, it is likely that a clinical neuropsychologist may encounter a Japanese patient, particularly for neurocognitive disorder evaluations given the aging population. Literature has reported that cross-cultural bias in neuropsychological testing and cultural factors affect individuals’ test performance. In order to conduct and interpret neuropsychological assessments for this population, it is important to use normative data and consider the impact of various factors such as acculturation, language, and generation in the U.S. Availability of normative cognitive test data for Japanese-Americans is limited. Tests with most extensive use, adaptation, validation, and norming were identified. Many clinically used measures of executive functioning (EF) have been translated into Japanese and studied in multiple clinical populations. We present information on tests in this domain given their appropriateness for use in cross-linguistic and cross-cultural evaluations.Participants and Methods:Available studies of neuropsychological tests measuring EF that have been translated and normed in the Japanese and/or Japanese-American patient population are reported. Review of the literature was conducted by authors of Japanese descent familiar with neuropsychological assessment and Japanese and Japanese-American culture. We prioritized studies published in both English and Japanese and those that included commonly utilized tests in the U.S, allowing for maximum accessibility and utility for Western-based neuropsychologists. Additionally, inclusion priority was given to studies published in English which report the clinical diagnoses, age range, and gender characteristics of the sample population. The Wisconsin card sorting test (WCST) and Trail Making Test (TMT) were reviewed.Results:The WCST and the TMT, with its variant, was the most normed EF cognitive test currently available. The Keio version Japanese-Trail Making Test (J-TMT) and a simplified version of the Trail Making Test (S-TMT) has been utilized in Japan, however norms are still lacking. Of the available studies, the S-TMT and J-TMT were found to be moderately correlated with the TMT. The Keio version WCST (KWCST) (Kao et al., 2012) was correlated to education level (Abe et al., 2004), appropriately differentiating severity of social anxiety disorder (Fujii et al., 2013), patients with schizophrenia (Banno et al., 2012), and cognitive impairment in Parkinson’s disease (Yoshii et al., 2019).Conclusions:Information regarding translated and normed tests are presented to assist clinical neuropsychologists provide competent services to Japanese-Americans. The J-TMT and the S-TMT may be clinically useful as an evaluation of attention for the Japanese population. The KWCST has also been found to be an appropriate tool for this population. However, publicly available norms for these assessments are still sparse, and there is very limited information about administration of these tests by English-speaking neuropsychologists with the use of interpreters. Further work is needed to increase access to and awareness of linguistically and culturally appropriate versions of clinical measures to better serve the Japanese and Japanese-American population.

Effectiveness of Acceptance Commitment Therapy in Social Anxiety Disorder: Application of a Longitudinal Method to Evaluate the Mediating Role of Acceptance, Cognitive Fusion, and Values.

The aim of the present study was to examine the effectiveness of acceptance and commitment therapy (ACT) on symptom severity, fear of negative evaluation, quality of life (QoL), and the mediating role of acceptance, cognitive fusion, and value among patients with social anxiety disorder (SAD). Thirty patients diagnosed with SAD were randomized in the intervention (n=15) or waiting list groups (n=15). The social phobia and Anxiety inventory (SPAI), brief fear of negative evaluation scale (BFNE), World Health Organization quality of life (WHOQoL) scale, social anxiety-acceptance and action questionnaire (SA-AAQ), cognitive fusion questionnaire (CFQ), and valued living questionnaire (VLQ) were administered before, immediately after, and at a one-month follow-up. Repeated measurement design was used in the intervention group to investigate the changes of mediation and outcomes variables in the pre-test, during treatment, and post-test. Twenty-four patients completed the study. Data were analyzed using one-way analysis of covariance (ANCOVA), multivariate analysis of covariance (MANCOVA), and repeated measurements. There were significant differences between the intervention and waiting list groups in the severity of symptoms (P=0.001), fear of negative evaluation (P=0.002), and QoL (P=0.03), as well as in terms of specific measures of SA-AAQ (P=0.001), cognitive fusion (P=0.001), an important section of VLQ (P=0.001). Repeated measurement results showed that acceptance and action of social anxiety and cognitive fusion had a mediating role in the severity of social anxiety, fear of negative evaluation, and QoL. The results indicated the effectiveness of ACT for SAD and highlighted the mediator role of social anxiety, acceptance and action, and cognitive fusion in the severity of SAD. This study evaluated effectiveness of acceptance commitment therapy(ACT) on social anxiety disorders (SAD).This study evaluated mechanisms of change of ACT in SAD.ACT has effectiveness for SAD.Acceptance and action and cognitive fusion have mediator role in SAD. Social anxiety disorder (SAD) is one of the most psychiatric disorders. Although CBT has been effective for SAD, most patients continue to demonstrate residual symptoms and impairment after treatment. Over the past several years, a third-wave behavioral therapy has been developed within behavioral and cognitive approaches. Some researchers suggest a new generation of psychotherapists termed acceptance and commitment therapy (ACT) that has many evidence in SAD. However, studies have not examined the mechanism of change of ACT in SAD using methods and proper instruments.in the present study ACT have effectiveness for SAD. In addition to, acceptance and action and cognitive fusion have mediator role in SAD.

Prevalence and correlates of cannabis use among individuals with DSM-5 social anxiety disorder: Findings from a nationally representative sample

Cannabis use disorder (CUD) and frequency of use are highly related to social anxiety disorder (SAD). With updates to diagnostic criteria of psychiatric disorders and recent changes in cannabis laws, the present study sought to explore the relationships between cannabis use, CUD, and social anxiety in a large nationally representative sample of individuals with lifetime (N = 1255) and past-year SAD (N = 980). Notably, we found that at the symptom level, at least weekly cannabis use was significantly related to fear or avoidance of social situations interfering with relationships in both samples. Weekly + cannabis use and CUD were significantly associated with lifetime SAD symptom severity, but only weekly + cannabis use was related to SAD severity in the past-year sample. We also found that weekly + cannabis use but not CUD was related to greater odds of seeking treatment for SAD and suicide attempt history. Overall, these data provide an updated examination of cannabis use and SAD using DSM-5 criteria and a large nationally representative sample and also highlight the importance of weekly + cannabis use as a marker of severity and suicide risk in individuals with SAD.

Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures.

The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the severity of SAD into different grading (severe, moderate, mild, and control) by using the patterns of brain information flow with their corresponding graphical networks. We quantified the directed information flow using partial directed coherence (PDC) and the topological networks by graph theory measures at four frequency bands (delta, theta, alpha, and beta). The PDC assesses the causal interactions between neuronal units of the brain network. Besides, the graph theory of the complex network identifies the topological structure of the network. Resting-state electroencephalogram (EEG) data were recorded for 66 patients with different severities of SAD (22 severe, 22 moderate, and 22 mild) and 22 demographically matched healthy controls (HC). PDC results have found significant differences between SAD groups and HCs in theta and alpha frequency bands (p < 0.05). Severe and moderate SAD groups have shown greater enhanced information flow than mild and HC groups in all frequency bands. Furthermore, the PDC and graph theory features have been used to discriminate three classes of SAD from HCs using several machine learning classifiers. In comparison to the features obtained by PDC, graph theory network features combined with PDC have achieved maximum classification performance with accuracy (92.78%), sensitivity (95.25%), and specificity (94.12%) using Support Vector Machine (SVM). Based on the results, it can be concluded that the combination of graph theory features and PDC values may be considered an effective tool for SAD identification. Our outcomes may provide new insights into developing biomarkers for SAD diagnosis based on topological brain networks and machine learning algorithms.

Examining the Latent Dimensions of Social Anxiety Disorder.

While the body of literature has investigated the latent dimensions of Social Anxiety Disorder (SAD), only few have directly anchored in the DSM-5 SAD symptoms. Similarly, a continuing issue on measuring mental health disorders pertains to whether a symptom's frequency, intensity, or both, are appropriate and sufficient indicators of severity. To address this gap, the present study developed and validated a DSM-5-based measurement tool, the Social Anxiety Symptom Severity Inventory (SASSI), which assesses both the intensity (intensity of disturbance) and frequency (frequency of occurrence) of SAD symptoms. In study 1 (n = 6458, college students), the results revealed a two-factor structure using exploratory structural equation modeling. In study 2 (n = 425, left-behind emerging adults), confirmatory factor analysis, measurement invariance testing, and latent class analysis were used. Findings demonstrated the importance of using both frequency and intensity of symptoms in assessing SAD severity. Moreover, a five-class solution best fitted the sample. Studies 1 and 2 demonstrated the good psychometric properties of SASSI and filled an important gap among available measures in assessing SAD severity through symptom frequency and intensity.

The Severity of Social Anxiety Disorder among Nursing Students at the University of Tabuk

Background: Social Anxiety Disorder (SAD) or known as social phobia is an excessive fear of interacting withpeople and a fear of being evaluated negatively by others. The person has extreme concerns about being exposedto possible scanning and social fears or performance situations in which embarrassment may occur.Objective: This study aimed to measure the severity of social anxiety disorder and its associated factors amongnursing students.Methods: This is a descriptive, cross-sectional study. The participants were 138 nursing students of the Universityof Tabuk. Data were collected using a SPIN self-administered questionnaire.Results: The findings revealed that the prevalence of SAD among the nursing students was very severe (2.2%),severe (6.5%), moderate (13.0%), mild (18.1%), and no social phobia at 60.2%. This showed no significantrelationship between the severity of SAD across the demographic profile (P=&gt;0.05).Conclusion: About 40% of nursing students suffered from mild to severe social anxiety disorder which may affecttheir academic performance. Nursing leaders should conduct awareness programs and educational activities tolessen SAD among nursing students.

Complexity Analysis of EEG in Patients With Social Anxiety Disorder Using Fuzzy Entropy and Machine Learning Techniques

The diagnosis of social anxiety disorder (SAD) is of great consequence not only due to its impacts on the individual and society but also the expenditures to the national health systems. There is yet a deficiency of objective neurophysiological information to assist the present clinical SAD diagnosis. The main objective of this study is to analyze the electroencephalogram (EEG) complexity of 88 SAD subjects, subdivided into 4 balanced groups (22 severe, 22 moderate, 22 mild, and 22 healthy controls (HCs) using Fuzzy Entropy measure (FE) and machine learning algorithms. In addition, this study aimed at designing a computer-aided diagnosis system to identify the severity of SAD (severe, moderate, mild, and HC) in different EEG frequency bands (delta, theta, alpha, and beta). The experimental results showed that among the HC and the three considered levels of SAD, SAD patients in fast-waves exhibited significantly less FE values in resting-state compared with HCs (p <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\leq0.05$ </tex-math></inline-formula> ). The EEG complexity analysis showed a discriminatory neuronal activity over the frontoparietal and occipital regions between SAD patients and HCs. Additionally, the FE values measured in the resting-state were positively correlated with Social Interaction Anxiety Scale (SIAS) scores in fast-waves (beta and alpha), indicating that the regional FE measures are putative biomarkers in assessing the clinical symptoms of SAD. Also, the classification results demonstrated that the proposed method outperformed the state of the art methods with an accuracy of 86.93 %, sensitivity of 92.46%, and specificity of 95.32% with the Naive Bayes (NB) classifier. This study emphasizes the viability of quantitative FE measures and the specific combinations involving the chosen classifiers could be considered as an alternative biomarker for future clinical SAD recognition.

Descended Social Anxiety Disorder and Craving in Women Heroin Dependence Through Exercise Alerts Plasma Oxytocin Levels.

Purpose: This study explored the association between peripheral blood oxytocin (OT) and social anxiety disorder (SAD) and cue-induced cravings in female heroin addicts. The effect of exercise on alleviation of SAD and OT levels was also explored.Methods: A total of 72 females with heroin dependence were assigned to three groups based on SAD severity. The three groups were Non-SAD control, SAD control, and SAD exercise groups. Subjects in the SAD exercise group underwent aerobic exercise and resistance training for 8 weeks (60 min/day, 5 days/week). Enzyme-linked immunosorbent assay analysis and Liebowitz Social Anxiety Scale (LSAS) scores were used to determine plasma OT concentration and SAD, respectively. Cue-induced craving was assessed using Visual Analog Scale (VAS) and Desires for Drug Questionnaire (DDQ). Mixed-effect analysis of variance and Pearson correlation analysis were used to explore the effect and correlation between different parameters.Results: OT levels in the SAD exercise group were significantly high after exercise (p < 0.01). LSAS, VAS, and DDQ (“Desire and Intention” and “Negative reinforcement”) scores in the SAD exercise group were significantly lower after exercise (p < 0.01). Plasma OT level was negatively correlated with LSAS score (r = −0.534, p < 0.001), VAS score (r = −0.609, p < 0.001), “Desire and Intention” score (r = −0.555, p < 0.001), and “Negative reinforcement” score (r = −0.332, p < 0.01) and positively correlated with the “control” score (r = 0.258, p < 0.05). LSAS was positively correlated with VAS score (r = 0.588, p < 0.001) and “Desire and Intention” score (r = 0.282, p < 0.05).Conclusions: The findings of the present study indicate that plasma OT is a potential peripheral biomarker for prediction of the severity of social anxiety in female heroin withdrawal patients. Aerobic exercise combined with resistance training plus incremental load for 8 weeks can increase plasma OT levels and significantly reduce severity of SAD and cue-induced cravings in female heroin addicts.

Pilot randomized trial of self-guided virtual reality exposure therapy for social anxiety disorder

BackgroundVirtual reality exposure therapy (VRE) has shown promising efficacy for the treatment of social anxiety disorder (SAD) and related comorbidities. However, most trials conducted to date were therapist-led, and little is known about the efficacy of self-guided VRE. Therefore, this randomized controlled trial (RCT) aimed to determine the efficacy of a self-directed VRE for SAD. MethodForty-four community-dwelling or undergraduate adults diagnosed with SAD based on the Mini International Neuropsychiatric Interview were randomly assigned to VRE designed to last four sessions or more (n = 26) or waitlist (WL; n = 18). Self-reported SAD severity (Social Phobia Diagnostic Questionnaire and Social Interaction Anxiety Scale), job interview anxiety (Measure of Anxiety in Selection Interviews), trait worry (Penn State Worry Questionnaire), and depression symptoms (Patient Health Questionnaire-9) were administered at baseline, post-treatment, 3-month-follow-up (3MFU), and 6-month-follow-up (6MFU). Piecewise multilevel modeling analyses were conducted to manage clustering in the data. ResultsVRE vs. WL resulted in greater reductions in SAD symptom severity, job interview fear, and trait worry, with moderate-to-large effect sizes (Hedge's g = −0.54 to −1.11) from pre-to-post treatment. Although significant between-group differences did not emerge for change in depression, VRE led to change in depression, whereas waitlist did not. These gains were also maintained at 3MFU and 6MFU. Further, facets of presence increased during the course of VRE (g = 0.36–0.45), whereas cybersickness decreased (g = −0.43). DiscussionBrief, self-guided VRE might ameliorate SAD and comorbid worry, for young-to-middle-aged adults with SAD. Other theoretical and practical implications were also discussed.

Empathy in Social Anxiety Disorder: The Association with Attention Deficit Hyperactivity Disorder

Objectives: Our main hypothesis in this study was that patients with social anxiety disorder (SAD) and comorbid attention deficit hyperactivity disorder (ADHD) had lower empathy levels than those without ADHD. Also, after controlling for the severity of SAD and depression, we hypothesized that ADHD symptoms contributed to lower levels of empathy in SAD patients. Methods: 72 patients (46 females, 32 males) with SAD between the ages of 18–65 years were divided into two groups as those with (n = 32) and those without ADHD (n = 40). Participants were evaluated using the Liebowitz Social Anxiety Scale (LSAS), Turgay’s Adult Attention-Deficit/Hyperactivity Disorder, Beck Depression Inventory (BDI), and Empathy Quotient. In this study, Mann Whitney-U test, Spearman correlation test, logistic and multiple regression analysis were used. Results: Education level (U = 371.5, p = .002) and empathy scores (U = 259.5, p < .0001) of SAD patients with ADHD were significantly lower than those without ADHD. BDI (U = 206.5, p < .0001), LSAS total (U = 454.5, p = .036), fear (U = 457.0, p = .038), and avoidance scores (U = 453.0, p = .034) were higher in SAD patients with ADHD than those without ADHD. Low levels of empathy (B = - 0.119, Exp(B) = 0.895, p = .014) and high severity of current depression (B = 0.119, Exp(B) = 1.127, p = .001) were significantly associated with comorbidity between SAD and ADHD. ADHD-inattention (β = −0.369, Exp(B) = −0.541, p = .004), and depression (β = −0.262, Exp(B) = −0.212, p = .036) negatively predicted empathy levels. Conclusions: Our findings may provide some evidence for the contribution of ADHD-inattention and depression to poor empathy in SAD patients. Therefore, it is recommended that symptoms of ADHD-inattention and depression should be carefully evaluated in SAD patients with low empathy.

Analysis of Default Mode Network in Social Anxiety Disorder: EEG Resting-State Effective Connectivity Study.

Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neuroscientists could not quantify the fast dynamic connectivity of causal information networks in SAD. In this study, SAD-related changes in brain connections within the default mode network (DMN) were investigated using eight electroencephalographic (EEG) regions of interest. Partial directed coherence (PDC) was used to assess the causal influences of DMN regions on each other and indicate the changes in the DMN effective network related to SAD severity. The DMN is a large-scale brain network basically composed of the mesial prefrontal cortex (mPFC), posterior cingulate cortex (PCC)/precuneus, and lateral parietal cortex (LPC). The EEG data were collected from 88 subjects (22 control, 22 mild, 22 moderate, 22 severe) and used to estimate the effective connectivity between DMN regions at different frequency bands: delta (1–3 Hz), theta (4–8 Hz), alpha (8–12 Hz), low beta (13–21 Hz), and high beta (22–30 Hz). Among the healthy control (HC) and the three considered levels of severity of SAD, the results indicated a higher level of causal interactions for the mild and moderate SAD groups than for the severe and HC groups. Between the control and the severe SAD groups, the results indicated a higher level of causal connections for the control throughout all the DMN regions. We found significant increases in the mean PDC in the delta (p = 0.009) and alpha (p = 0.001) bands between the SAD groups. Among the DMN regions, the precuneus exhibited a higher level of causal influence than other regions. Therefore, it was suggested to be a major source hub that contributes to the mental exploration and emotional content of SAD. In contrast to the severe group, HC exhibited higher resting-state connectivity at the mPFC, providing evidence for mPFC dysfunction in the severe SAD group. Furthermore, the total Social Interaction Anxiety Scale (SIAS) was positively correlated with the mean values of the PDC of the severe SAD group, r (22) = 0.576, p = 0.006 and negatively correlated with those of the HC group, r (22) = −0.689, p = 0.001. The reported results may facilitate greater comprehension of the underlying potential SAD neural biomarkers and can be used to characterize possible targets for further medication.

Social Anxiety and Obsessive-Compulsive Disorder Are Common Among Persons With Multiple Sclerosis at King Abdulaziz Medical City, Riyadh.

BackgroundMultiple sclerosis (MS) is associated with a physical disability and disturbed psychosocial functioning in young people. Many psychological and psychiatric comorbidities have been reported in MS.ObjectiveTo determine the frequency of social anxiety disorder (SAD) and obsessive-compulsive disorder (OCD) among MS patients and their relation to MS severity.MethodsA cross-sectional survey was conducted in an adult MS cohort. Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and Social Phobia Inventory (SPIN) were used to determine the presence and severity of OCD and SAD. The Statistical Package for the Social Sciences (SPSS) version 22 (IBM Corp., Armonk, NY) was used for statistical analysis. The Mann-Whitney U test and logistic regression were used to assess the association of the two diseases with the severity of MS.ResultsA total of 145 persons with MS (pwMS) were studied. The mean age was 33.5 (±8.5) years; the mean duration of MS was 7.2 (± 5.1) years. The majority (74.1%) were women; 57.3% were married; 63% had a college education; 50% belonged to the higher middle-class socioeconomic strata. Relapsing-remitting multiple sclerosis was the most common type of MS (92.2%). The mean Expanded Disability Status Scale (EDSS) score was 2.24 (±2.19). SAD was reported by 26.9%, and OCD was reported by 31% of the cohort. PwMS with walking difficulty but not wheelchair-bound had a statistically significant increased risk of SAD (p = 0.036). There was no direct association between MS-related disability and OCD. However, pwMS with SAD were more likely to have concomitant OCD (t=4.68, p-value <0.001, 95% CI: 0.47-1.16). Increasing disability was associated with higher chances of developing social anxiety and, in turn, OCD (t=3.39, p-value <0.001, 95% CI: 0.66-2.52).ConclusionsSocial anxiety and obsessive-compulsive disorders were present in nearly one-third of pwMS. Impaired walking but not wheelchair dependence was associated with social anxiety. PwMS with SAD were more likely to have obsessive-compulsive disorder.

Smartphone-Detected Ambient Speech and Self-Reported Measures of Anxiety and Depression: Exploratory Observational Study.

BackgroundThe ability to objectively measure the severity of depression and anxiety disorders in a passive manner could have a profound impact on the way in which these disorders are diagnosed, assessed, and treated. Existing studies have demonstrated links between both depression and anxiety and the linguistic properties of words that people use to communicate. Smartphones offer the ability to passively and continuously detect spoken words to monitor and analyze the linguistic properties of speech produced by the speaker and other sources of ambient speech in their environment. The linguistic properties of automatically detected and recognized speech may be used to build objective severity measures of depression and anxiety.ObjectiveThe aim of this study was to determine if the linguistic properties of words passively detected from environmental audio recorded using a participant’s smartphone can be used to find correlates of symptom severity of social anxiety disorder, generalized anxiety disorder, depression, and general impairment.MethodsAn Android app was designed to collect periodic audiorecordings of participants’ environments and to detect English words using automatic speech recognition. Participants were recruited into a 2-week observational study. The app was installed on the participants’ personal smartphones to record and analyze audio. The participants also completed self-report severity measures of social anxiety disorder, generalized anxiety disorder, depression, and functional impairment. Words detected from audiorecordings were categorized, and correlations were measured between words counts in each category and the 4 self-report measures to determine if any categories could serve as correlates of social anxiety disorder, generalized anxiety disorder, depression, or general impairment.ResultsThe participants were 112 adults who resided in Canada from a nonclinical population; 86 participants yielded sufficient data for analysis. Correlations between word counts in 67 word categories and each of the 4 self-report measures revealed a strong relationship between the usage rates of death-related words and depressive symptoms (r=0.41, P<.001). There were also interesting correlations between rates of word usage in the categories of reward-related words with depression (r=–0.22, P=.04) and generalized anxiety (r=–0.29, P=.007), and vision-related words with social anxiety (r=0.31, P=.003).ConclusionsIn this study, words automatically recognized from environmental audio were shown to contain a number of potential associations with severity of depression and anxiety. This work suggests that sparsely sampled audio could provide relevant insight into individuals’ mental health.

Psychometric properties of the Ryerson Social Anxiety Scales in individuals with social anxiety disorder

ABSTRACT Background Although numerous self-report measures of social anxiety exist, most instruments assess symptom severity by examining the range of social situations that provoke anxiety, rather than the distress and impairment associated with social anxiety. The Ryerson Social Anxiety Scales (RSAS; Lenton-Brym, A. P., Rogojanski, J., Hood, H. K., Vorstenbosch, V., McCabe, R. E., & Antony, M. M. (2020). Development and validation of the Ryerson Social Anxiety Scales (RSAS). Anxiety, Stress, & Coping, 33(6), 642–660), a measure assessing breadth of social anxiety inducing situations and severity of associated distress and impairment, was recently developed to fill this gap. The present study is the first to investigate the psychometric properties of the RSAS in a clinical sample. Method/Design Participants included 110 individuals with a principal diagnosis of social anxiety disorder (SAD). A subsample of participants (n = 23) completed cognitive–behavioural group treatment (CBGT) for SAD. Results The RSAS demonstrated excellent internal consistency. Examination of the correlations between the RSAS and other conceptually related and distinct measures supported the convergent and discriminant validity of the RSAS. The RSAS was also sensitive to changes in severity of social anxiety following CBGT. Conclusion The RSAS is a reliable and valid instrument for assessing the severity of SAD.